chore(mcp): migrate client integration to SDK v2

docs/configuration.md

@@ -348,19 +348,6 @@ Valid `apiType` values are exactly `auto`, `chat_completions`, and `responses`.
 
 </details>
 
-<a id="responses-state-and-compaction"></a>
-
-### Responses conversation state and compaction
-
-Providers that use the Responses API can keep reasoning context across a
-conversation, which helps with multi-step tasks. Supported providers can also
-compact long conversations automatically.
-
-nanobot preserves Responses conversation state automatically for OpenAI Responses, OpenAI Codex, Azure OpenAI, DeepSeek V4 Flash, and compatible GitHub Copilot models.
-Native compaction is also automatic when the provider supports it. The
-threshold is derived from the active model's context window and reserved output
-headroom; no provider configuration is required.
-
 <details>
 <summary><b>Azure OpenAI</b></summary>
 

docs/providers.md

@@ -229,9 +229,7 @@ Arbitrary custom provider names are OpenAI-compatible only; they do not use the
 }
 ```
 
-`providers.openai.apiType` may be set when you need to force a specific OpenAI API surface. Other providers reject `apiType`; leave it unset outside `providers.openai`. Replace the model with a model ID available to your OpenAI account. Direct OpenAI Responses, OpenAI Codex, Azure OpenAI Responses, and eligible GitHub Copilot models share [opaque Responses state retention](./configuration.md#responses-state-and-compaction); native compaction is enabled only where the backend supports it.
-
-DeepSeek is the model-level exception in the OpenAI-compatible provider: `deepseek-v4-flash` automatically uses DeepSeek's native Responses API, while `deepseek-v4-pro` remains on Chat Completions.
+`providers.openai.apiType` may be set when you need to force a specific OpenAI API surface. Other providers reject `apiType`; leave it unset outside `providers.openai`. Replace the model with a model ID available to your OpenAI account.
 
 ### Custom OpenAI-Compatible Endpoint
 
@@ -460,7 +458,7 @@ For GitHub Copilot:
 nanobot provider login github-copilot --set-main
 ```
 
-Each command authenticates the selected provider and makes its current default model active. OpenAI Codex and eligible GitHub Copilot models participate in [Responses state retention](./configuration.md#responses-state-and-compaction), while native compaction remains provider-capability-specific. OAuth providers are not valid automatic fallbacks. See [`troubleshooting.md`](./troubleshooting.md#provider-and-model-problems) for proxy, headless-login, model-name, and config-key errors.
+Each command authenticates the selected provider and makes its current default model active. OAuth providers are not valid automatic fallbacks. See [`troubleshooting.md`](./troubleshooting.md#provider-and-model-problems) for proxy, headless-login, model-name, and config-key errors.
 
 ## Provider Resolution
 

nanobot/agent/autocompact.py

@@ -31,19 +31,9 @@ class AutoCompact:
                     now: datetime | None = None) -> bool:
         if self._ttl <= 0 or not ts:
             return False
-        try:
-            if isinstance(ts, str):
-                ts = datetime.fromisoformat(ts)
-            current = now or datetime.now()
-            if getattr(ts, "tzinfo", None) is not None or current.tzinfo is not None:
-                idle_seconds = current.timestamp() - ts.timestamp()
-            else:
-                idle_seconds = (current - ts).total_seconds()
-        except (OSError, OverflowError, TypeError, ValueError):
-            # list_sessions() forwards raw persisted metadata; an unusable value
-            # must not escape the idle scan and stop the agent loop.
-            return False
-        return idle_seconds >= self._ttl * 60
+        if isinstance(ts, str):
+            ts = datetime.fromisoformat(ts)
+        return ((now or datetime.now()) - ts).total_seconds() >= self._ttl * 60
 
     def _has_compactable_idle_tail(self, key: str) -> bool:
         session = self.sessions.get_or_create(key)
@@ -134,21 +124,10 @@ class AutoCompact:
         if entry:
             return session, self._format_summary(entry[0], entry[1])
         # Cold path: summary persisted in session metadata (process restarted).
-        # Persisted metadata may outlive schema changes; a malformed summary must
-        # not abort turn preparation.
         meta = session.metadata.get("_last_summary")
         if isinstance(meta, dict):
-            summary_meta = cast(dict[str, object], meta)
-            text = summary_meta.get("text")
-            if isinstance(text, str) and text:
-                raw_last_active = summary_meta.get("last_active")
-                try:
-                    last_active = (
-                        datetime.fromisoformat(raw_last_active)
-                        if isinstance(raw_last_active, str)
-                        else session.updated_at
-                    )
-                except ValueError:
-                    last_active = session.updated_at
-                return session, self._format_summary(text, last_active)
+            return session, self._format_summary(
+                cast(str, meta["text"]),
+                datetime.fromisoformat(cast(str, meta["last_active"])),
+            )
         return session, None

nanobot/agent/context.py

@@ -217,18 +217,19 @@ class ContextBuilder:
         include_memory_recent_history: bool = True,
         session_key: str | None = None,
         unified_session: bool = False,
-        conversation_only: bool = False,
     ) -> list[dict[str, Any]]:
         """Build the complete message list for an LLM call."""
-        messages = list(history)
-        if not conversation_only:
-            root = workspace or self.workspace
-            active_skill_names = (
-                self.skills.get_explicitly_invoked_skills(current_message)
-                if current_role == "user"
-                else []
-            )
-            messages.insert(0, {
+        root = workspace or self.workspace
+        active_skill_names = (
+            self.skills.get_explicitly_invoked_skills(current_message)
+            if current_role == "user"
+            else []
+        )
+        user_content = self.build_user_content(current_message, image_paths=media)
+        blocks = list(runtime_context_blocks or ()) if current_role == "user" else []
+        merged, runtime_context_meta = append_runtime_context(user_content, blocks)
+        messages: list[dict[str, Any]] = [
+            {
                 "role": "system",
                 "content": self.build_system_prompt(
                     active_skill_names=active_skill_names,
@@ -239,47 +240,23 @@ class ContextBuilder:
                     session_key=session_key,
                     unified_session=unified_session,
                 ),
-            })
-        current = self.build_current_message(
-            current_message,
-            media=media,
-            current_role=current_role,
-            runtime_context_blocks=runtime_context_blocks,
-        )
-        if messages and messages[-1].get("role") == current_role:
+            },
+            *history,
+        ]
+        if messages[-1].get("role") == current_role:
             last = dict(messages[-1])
-            last["content"] = self._merge_message_content(
-                last.get("content"),
-                current.get("content"),
-            )
-            current_meta = current.get("_meta")
-            if current_role == "user" and isinstance(current_meta, dict):
+            last["content"] = self._merge_message_content(last.get("content"), merged)
+            if current_role == "user" and runtime_context_meta is not None:
                 internal_meta = dict(last.get("_meta") or {})
-                internal_meta.update(cast(dict[str, Any], current_meta))
+                internal_meta[RUNTIME_CONTEXT_MESSAGE_META] = runtime_context_meta
                 last["_meta"] = internal_meta
             messages[-1] = last
             return messages
-        messages.append(current)
-        return messages
-
-    def build_current_message(
-        self,
-        current_message: str,
-        *,
-        media: list[str] | None = None,
-        current_role: str = "user",
-        runtime_context_blocks: Sequence[RuntimeContextBlock] | None = None,
-    ) -> dict[str, Any]:
-        """Build only the fresh turn message without merging it into history."""
-        content = self.build_user_content(current_message, image_paths=media)
-        blocks = list(runtime_context_blocks or ()) if current_role == "user" else []
-        merged, runtime_context_meta = append_runtime_context(content, blocks)
         current: dict[str, Any] = {"role": current_role, "content": merged}
         if current_role == "user" and runtime_context_meta is not None:
-            current["_meta"] = {
-                RUNTIME_CONTEXT_MESSAGE_META: runtime_context_meta,
-            }
-        return current
+            current["_meta"] = {RUNTIME_CONTEXT_MESSAGE_META: runtime_context_meta}
+        messages.append(current)
+        return messages
 
     def build_user_content(
         self,

nanobot/agent/loop.py

@@ -9,7 +9,6 @@ import dataclasses
 import inspect
 import os
 import time
-import weakref
 from collections.abc import Coroutine, Iterable, Mapping
 from contextlib import AbstractContextManager, ExitStack, nullcontext, suppress
 from dataclasses import dataclass, field
@@ -49,7 +48,7 @@ from nanobot.bus.queue import MessageBus
 from nanobot.bus.runtime_events import RuntimeEventBus
 from nanobot.command import CommandContext, CommandRouter, register_builtin_commands
 from nanobot.config.schema import AgentDefaults, ModelPresetConfig
-from nanobot.providers.base import LLMProvider, ProviderConversationState
+from nanobot.providers.base import LLMProvider
 from nanobot.providers.factory import ProviderSnapshot
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_HISTORY_META,
@@ -106,7 +105,6 @@ if TYPE_CHECKING:
     from nanobot.triggers.local_store import LocalTriggerStore
 
 _T = TypeVar("_T")
-_SUBAGENT_PROVIDER_TASK_META = "subagent_provider_task_id"
 
 
 class TurnKind(Enum):
@@ -127,7 +125,6 @@ class TurnContext:
 
     history: list[dict[str, Any]] = field(default_factory=list)
     initial_messages: list[dict[str, Any]] = field(default_factory=list)
-    provider_state: ProviderConversationState | None = field(default=None, repr=False)
     request_context: RequestContext | None = None
     runtime_context_blocks: list[RuntimeContextBlock] = field(default_factory=list)
     attributes: dict[str, Any] = field(default_factory=dict)
@@ -245,8 +242,6 @@ class AgentLoop:
 
     _RUNTIME_CHECKPOINT_KEY = "runtime_checkpoint"
     _PENDING_USER_TURN_KEY = "pending_user_turn"
-    _PROVIDER_STATE_CHECKPOINT_VERSION_KEY = "provider_state_checkpoint_version"
-    _PROVIDER_STATE_CHECKPOINT_VERSION = "v1"
 
     def __init__(
         self,
@@ -399,9 +394,7 @@ class AgentLoop:
         self._runtime_context_providers: list[RuntimeContextProvider] = []
         self._active_tasks: dict[str, set[asyncio.Task[Any]]] = {}
         self._background_tasks: set[asyncio.Task[Any]] = set()
-        self._session_locks: weakref.WeakValueDictionary[str, asyncio.Lock] = (
-            weakref.WeakValueDictionary()
-        )
+        self._session_locks: dict[str, asyncio.Lock] = {}
         # Per-session pending queues for mid-turn message injection.
         # When a session has an active task, new messages for that session
         # are routed here instead of creating a new task.
@@ -723,7 +716,6 @@ class AgentLoop:
             include_memory_recent_history=not ctx.ephemeral,
             session_key=ctx.session.key,
             unified_session=self._unified_session,
-            conversation_only=ctx.session.transient is True,
         )
 
     def _request_context_for_turn(self, ctx: TurnContext) -> RequestContext:
@@ -751,12 +743,10 @@ class AgentLoop:
         self,
         ctx: TurnContext,
     ) -> list[RuntimeContextBlock]:
-        if ctx.require_session().transient is True:
-            return []
         assert ctx.request_context is not None
         return await self._resolve_runtime_context_for_request(
             ctx.request_context,
-            ctx.tools if ctx.tools is not None else self.tools,
+            ctx.tools or self.tools,
         )
 
     async def _resolve_runtime_context_for_request(
@@ -787,24 +777,18 @@ class AgentLoop:
         else:
             logger.warning("Command '{}' matched but dispatch returned None", raw)
 
-    async def cancel_active_turn(self, key: str) -> int:
-        """Cancel active work and discard queued follow-ups for *key*.
+    async def _cancel_active_tasks(self, key: str) -> int:
+        """Cancel and await all active tasks and subagents for *key*.
 
         Returns the total number of cancelled tasks + subagents.
         """
-        pending = self._pending_queues.pop(key, None)
-        queued = 0
-        if pending is not None:
-            while not pending.empty():
-                pending.get_nowait()
-                queued += 1
         tasks = tuple(self._active_tasks.pop(key, set()))
         cancelled = sum(1 for t in tasks if not t.done() and t.cancel())
         for t in tasks:
             with suppress(asyncio.CancelledError, Exception):
                 await t
         sub_cancelled = await self.subagents.cancel_by_session(key)
-        return queued + cancelled + sub_cancelled
+        return cancelled + sub_cancelled
 
     def _effective_session_key(self, msg: InboundMessage) -> str:
         """Return the session key used for task routing and mid-turn injections."""
@@ -870,7 +854,6 @@ class AgentLoop:
         turn_scopes: list[AbstractContextManager[Any]] | None = None,
         tools: ToolRegistry | None = None,
         request_context: RequestContext | None = None,
-        provider_state: ProviderConversationState | None = None,
     ) -> tuple[str | None, list[str], list[dict[str, Any]], str, bool]:
         """Run the agent iteration loop.
 
@@ -886,18 +869,7 @@ class AgentLoop:
         async def _checkpoint(payload: dict[str, Any]) -> None:
             if session is None:
                 return
-            public_payload = dict(payload)
-            private_state = public_payload.pop("provider_state", None)
-            public_payload.pop(self._PROVIDER_STATE_CHECKPOINT_VERSION_KEY, None)
-            if "provider_state" in payload and (
-                private_state is None
-                or isinstance(private_state, ProviderConversationState)
-            ):
-                session.provider_state = private_state
-                public_payload[self._PROVIDER_STATE_CHECKPOINT_VERSION_KEY] = (
-                    self._PROVIDER_STATE_CHECKPOINT_VERSION
-                )
-            self._set_runtime_checkpoint(session, public_payload)
+            self._set_runtime_checkpoint(session, payload)
 
         async def _drain_pending(*, limit: int = _MAX_INJECTIONS_PER_TURN) -> list[dict[str, Any]]:
             """Drain follow-up messages from the pending queue.
@@ -931,10 +903,7 @@ class AgentLoop:
                     if isinstance(metadata_value, dict)
                     else {}
                 )
-                if (
-                    pending_msg.channel != "system"
-                    and not (session is not None and session.transient is True)
-                ):
+                if pending_msg.channel != "system":
                     scope = self.workspace_scopes.for_turn(
                         channel=pending_msg.channel,
                         message_metadata=metadata,
@@ -1014,7 +983,7 @@ class AgentLoop:
             message_metadata=metadata,
             session_metadata=session.metadata if session is not None else None,
         )
-        effective_tools = tools if tools is not None else self.tools
+        effective_tools = tools or self.tools
         request_ctx = request_context or RequestContext(
             channel=channel,
             chat_id=chat_id,
@@ -1098,7 +1067,6 @@ class AgentLoop:
                     session_metadata=session_metadata,
                     message_metadata=metadata,
                 ),
-                provider_state=provider_state,
             ))
         finally:
             turn_scope_stack.close()
@@ -1106,8 +1074,6 @@ class AgentLoop:
             reset_request_context(request_token)
             reset_file_states(file_state_token)
         self._last_usage = result.usage
-        if session is not None and not ephemeral:
-            session.provider_state = result.provider_state
         if result.stop_reason == "max_iterations":
             logger.warning("Max iterations ({}) reached", self.max_iterations)
             should_stream = turn_continuation.should_stream_budget_response(
@@ -1172,11 +1138,6 @@ class AgentLoop:
                 effective_key = self._effective_session_key(msg)
                 if await agent_context.handle_runtime_control(self, msg, self.tools):
                     continue
-                if (
-                    msg.transient_session
-                    and not self.sessions.is_transient_active(effective_key)
-                ):
-                    continue
                 if self.commands.is_priority(raw):
                     await self._dispatch_command_inline(
                         msg, effective_key, raw,
@@ -1245,7 +1206,7 @@ class AgentLoop:
         session_key = self._effective_session_key(msg)
         if session_key != msg.session_key:
             msg = dataclasses.replace(msg, session_key_override=session_key)
-        lock = self._get_session_lock(session_key)
+        lock = self._session_locks.setdefault(session_key, asyncio.Lock())
         gate = self._concurrency_gate or nullcontext()
 
         delivery = self.turn_delivery_factory.unrouted(msg, session_key)
@@ -1288,8 +1249,6 @@ class AgentLoop:
                             session_key,
                             exc_info=True,
                         )
-                    if msg.transient_session:
-                        raise
                     # Preserve partial context from the interrupted turn so
                     # the user does not lose tool results and assistant
                     # messages accumulated before /stop.  The checkpoint was
@@ -1592,16 +1551,13 @@ class AgentLoop:
         if ctx.session is None:
             ctx.session = self.sessions.get_or_create(ctx.session_key)
         session = ctx.session
-        if session.transient is True:
-            ctx.ephemeral = True
-            ctx.tools = ToolRegistry()
         self._remember_unified_session_route(
             session,
             msg,
             is_user_turn=ctx.original_user_text is not None,
         )
         await ctx.delivery.started()
-        if ctx.kind is TurnKind.USER and not session.transient:
+        if ctx.kind is TurnKind.USER:
             self.workspace_scopes.persist_message_scope(session, msg)
 
         if self._restore_runtime_checkpoint(session):
@@ -1611,8 +1567,6 @@ class AgentLoop:
 
     async def _compact_session(self, ctx: TurnContext) -> None:
         session = ctx.require_session()
-        if session.transient is True:
-            return
         ctx.session, pending = self.auto_compact.prepare_session(
             session,
             ctx.session_key,
@@ -1703,24 +1657,14 @@ class AgentLoop:
             "extend_to_user": is_subagent,
         }
         ctx.history = session.get_history(**_hist_kwargs)
-        stored_state = session.provider_state
-        subagent_followup_persisted = False
         if is_subagent:
             # Keep the durable internal delivery as an assistant record, but
             # present this completion to the model as fresh follow-up input.
             # Providers without assistant-prefill support drop trailing
             # assistant messages, so using the persisted record as the current
             # prompt would hide an independently dispatched subagent result.
-            subagent_followup_persisted = self._persist_subagent_followup(
-                session,
-                ctx.msg,
-            )
-            if subagent_followup_persisted:
+            if self._persist_subagent_followup(session, ctx.msg):
                 logger.debug("Subagent result persisted for session {}", ctx.session_key)
-                # Establish a durable, replay-safe baseline before any fallible
-                # provider compatibility or prompt assembly work. A compatible
-                # staged state replaces this in a second atomic save below.
-                session.provider_state = None
                 self.sessions.save(session)
             ctx.input_persisted_early = True
         ctx.delivery.record_runtime(runtime)
@@ -1728,65 +1672,13 @@ class AgentLoop:
         ctx.request_context = self._request_context_for_turn(ctx)
         if ctx.kind is TurnKind.USER:
             ctx.runtime_context_blocks = await self._resolve_runtime_context_for_turn(ctx)
-        staged_provider_state = False
-        if stored_state is not None and runtime.provider.can_resume_conversation_state(
-            stored_state,
-            runtime.model,
-        ):
-            current_provider_message = self.context.build_current_message(
-                ctx.msg.content,
-                media=ctx.msg.media if ctx.kind is TurnKind.USER and ctx.msg.media else None,
-                runtime_context_blocks=ctx.runtime_context_blocks,
-            )
-            task_id = ctx.msg.metadata.get("subagent_task_id") if is_subagent else None
-            already_staged = False
-            if isinstance(task_id, str) and task_id:
-                internal_meta = current_provider_message.get("_meta")
-                current_provider_message["_meta"] = {
-                    **(
-                        cast(dict[str, Any], internal_meta)
-                        if isinstance(internal_meta, dict)
-                        else {}
-                    ),
-                    _SUBAGENT_PROVIDER_TASK_META: task_id,
-                }
-                already_staged = any(
-                    isinstance(message.get("_meta"), dict)
-                    and cast(dict[str, Any], message["_meta"]).get(
-                        _SUBAGENT_PROVIDER_TASK_META
-                    )
-                    == task_id
-                    for message in stored_state.pending_messages
-                )
-            ctx.provider_state = (
-                stored_state
-                if already_staged
-                else stored_state.with_pending_messages([
-                    *stored_state.pending_messages,
-                    current_provider_message,
-                ])
-            )
-            if (
-                not ctx.ephemeral
-                and (ctx.kind is TurnKind.USER or subagent_followup_persisted)
-            ):
-                session.provider_state = ctx.provider_state
-                staged_provider_state = True
-        elif stored_state is not None:
-            session.provider_state = None
+        ctx.initial_messages = self._build_initial_messages(ctx)
         if ctx.kind is TurnKind.USER:
             ctx.input_persisted_early = self._persist_user_message_early(
                 ctx.msg,
                 session,
                 runtime_context_blocks=ctx.runtime_context_blocks,
             )
-            if staged_provider_state and not ctx.input_persisted_early:
-                session.provider_state = stored_state
-        elif subagent_followup_persisted and staged_provider_state:
-            # Upgrade the replay-safe baseline to the resumable state before
-            # prompt assembly and the first model checkpoint.
-            self.sessions.save(session)
-        ctx.initial_messages = self._build_initial_messages(ctx)
 
         if ctx.on_progress is None:
             ctx.on_progress = ctx.delivery.progress_callback()
@@ -1820,7 +1712,6 @@ class AgentLoop:
             turn_scopes=ctx.turn_scopes,
             tools=ctx.tools,
             request_context=ctx.request_context,
-            provider_state=ctx.provider_state,
         )
         final_content, _, all_msgs, stop_reason, had_injections = result
         ctx.final_content = final_content
@@ -2158,36 +2049,7 @@ class AgentLoop:
             ):
                 overlap = size
                 break
-        appended_messages = restored_messages[overlap:]
-        session.messages.extend(appended_messages)
-        assistant_message_data = (
-            cast(dict[str, Any], assistant_message)
-            if isinstance(assistant_message, dict)
-            else None
-        )
-        provider_state_is_synchronized = (
-            checkpoint_data.get(self._PROVIDER_STATE_CHECKPOINT_VERSION_KEY)
-            == self._PROVIDER_STATE_CHECKPOINT_VERSION
-        )
-        phase = checkpoint_data.get("phase")
-        exact_final_response = (
-            phase == "final_response"
-            and assistant_message_data is not None
-            and assistant_message_data.get("role") == "assistant"
-            and not bool(checkpoint_data.get("completed_tool_results"))
-            and not bool(checkpoint_data.get("pending_tool_calls"))
-        )
-        exact_completed_tools = (
-            phase == "tools_completed"
-            and assistant_message_data is not None
-            and assistant_message_data.get("role") == "assistant"
-            and not bool(checkpoint_data.get("pending_tool_calls"))
-        )
-        if not (
-            provider_state_is_synchronized
-            and (exact_final_response or exact_completed_tools)
-        ):
-            session.provider_state = None
+        session.messages.extend(restored_messages[overlap:])
 
         self._clear_pending_user_turn(session)
         self._clear_runtime_checkpoint(session)
@@ -2208,7 +2070,6 @@ class AgentLoop:
                     "timestamp": datetime.now().isoformat(),
                 }
             )
-            session.provider_state = None
             session.updated_at = datetime.now()
 
         self._clear_pending_user_turn(session)
@@ -2247,7 +2108,7 @@ class AgentLoop:
             content=content, media=media or [], metadata=metadata,
         )
         # Share the dispatch lock so direct calls serialize with bus turns.
-        lock = self._get_session_lock(session_key)
+        lock = self._session_locks.setdefault(session_key, asyncio.Lock())
         try:
             async with lock:
                 kwargs: dict[str, Any] = {
@@ -2278,11 +2139,3 @@ class AgentLoop:
         finally:
             await self.runtime_event_publisher.run_status_changed(msg, session_key, "idle")
             self.runtime_event_publisher.clear_turn(session_key)
-
-    def _get_session_lock(self, session_key: str) -> asyncio.Lock:
-        """Return the shared lock while allowing idle session entries to expire."""
-        lock = self._session_locks.get(session_key)
-        if lock is None:
-            lock = asyncio.Lock()
-            self._session_locks[session_key] = lock
-        return lock

nanobot/agent/memory.py

@@ -713,10 +713,11 @@ class MemoryStore:
                 if tools_used
                 else ""
             )
-            raw_timestamp = message.get("timestamp")
-            timestamp = str(raw_timestamp) if raw_timestamp is not None else "?"
-            role = str(message.get("role") or "unknown")
-            lines.append(f"[{timestamp[:16]}] {role.upper()}{tools}: {content}")
+            timestamp = cast(str, message.get("timestamp", "?"))
+            role = cast(str, message["role"])
+            lines.append(
+                f"[{timestamp[:16]}] {role.upper()}{tools}: {content}"
+            )
         return "\n".join(lines)
 
     def raw_archive(
@@ -930,7 +931,6 @@ class Consolidator:
             session_key=session.key,
         )
         session.last_consolidated = end_idx
-        session.provider_state = None
         self.sessions.save(session)
         return summary
 
@@ -1136,7 +1136,6 @@ class Consolidator:
                 if summary:
                     last_summary = summary
                 session.last_consolidated = end_idx
-                session.provider_state = None
                 self.sessions.save(session)
                 if not summary:
                     # LLM is degraded — stop hammering it this call;
@@ -1206,7 +1205,6 @@ class Consolidator:
 
             # Preserve history and advance only the replay boundary.
             session.last_consolidated = len(session.messages) - len(visible_suffix)
-            session.provider_state = None
             self.sessions.save(session)
 
             logger.info(

nanobot/agent/runner.py

@@ -19,17 +19,7 @@ from nanobot.agent.context_governance import (
 )
 from nanobot.agent.hook import AgentHook, AgentHookContext, AgentRunHookContext
 from nanobot.agent.tools.registry import ToolRegistry, is_tool_error_result
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-    ToolCallRequest,
-)
-from nanobot.providers.conversation_state import (
-    ProviderConversationStateController,
-    allows_conversation_message_merge,
-)
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_MESSAGE_META,
     detach_runtime_context,
@@ -114,7 +104,6 @@ class AgentRunSpec:
     goal_active_predicate: Callable[[], bool] | None = None
     goal_continue_message: GoalContinueMessage | None = None
     finalize_on_max_iterations: bool = True
-    provider_state: ProviderConversationState | None = None
 
 
 @dataclass(slots=True)
@@ -131,7 +120,6 @@ class AgentRunResult:
     had_injections: bool = False
     # Terminal tail to emit when the preceding final-content prefix was already streamed.
     pending_stream_content: str | None = None
-    provider_state: ProviderConversationState | None = field(default=None, repr=False)
 
 
 class AgentRunner:
@@ -173,7 +161,6 @@ class AgentRunner:
                 and messages[-1].get("role") == "user"
                 and not is_hidden_history_message(injection)
                 and not is_hidden_history_message(messages[-1])
-                and allows_conversation_message_merge(messages[-1])
             ):
                 merged = dict(messages[-1])
                 left_meta = merged.get("_meta")
@@ -244,7 +231,6 @@ class AgentRunner:
         assistant_message: dict[str, Any] | None,
         injection_cycles: int,
         *,
-        conversation_state: ProviderConversationStateController | None = None,
         phase: str = "after error",
         iteration: int | None = None,
         allow_goal_continue: bool = False,
@@ -272,21 +258,16 @@ class AgentRunner:
         if assistant_message is not None:
             messages.append(assistant_message)
             if iteration is not None:
-                checkpoint: dict[str, Any] = {
-                    "phase": "final_response",
-                    "iteration": iteration,
-                    "model": spec.runtime.model,
-                    "assistant_message": assistant_message,
-                    "completed_tool_results": [],
-                    "pending_tool_calls": [],
-                }
-                if conversation_state is not None:
-                    checkpoint["provider_state"] = conversation_state.checkpoint(
-                        messages
-                    )
                 await self._emit_checkpoint(
                     spec,
-                    checkpoint,
+                    {
+                        "phase": "final_response",
+                        "iteration": iteration,
+                        "model": spec.runtime.model,
+                        "assistant_message": assistant_message,
+                        "completed_tool_results": [],
+                        "pending_tool_calls": [],
+                    },
                 )
         self._append_injected_messages(messages, injections)
         if real_injection:
@@ -439,12 +420,6 @@ class AgentRunner:
         injection_cycles = 0
         compacted_tool_call_ids: set[str] = set()
         pending_stream_content: str | None = None
-        conversation_state = ProviderConversationStateController(
-            provider=spec.runtime.provider,
-            model=spec.runtime.model,
-            messages=messages,
-            state=spec.provider_state,
-        )
         governance_config = ContextGovernanceConfig(
             provider=spec.runtime.provider,
             model=spec.runtime.model,
@@ -475,20 +450,7 @@ class AgentRunner:
                 session_key=spec.session_key,
             )
             await hook.before_iteration(context)
-            provider_context = conversation_state.prepare_request(
-                messages,
-                context_window_tokens=spec.runtime.context_window_tokens,
-                model_messages=messages_for_model,
-            )
-            response = await self._request_model(
-                spec,
-                messages_for_model,
-                hook,
-                context,
-                conversation_state=conversation_state,
-                provider_context=provider_context,
-            )
-            conversation_state.observe_response(response, messages)
+            response = await self._request_model(spec, messages_for_model, hook, context)
             context.response = response
             context.tool_calls = list(response.tool_calls)
 
@@ -518,10 +480,6 @@ class AgentRunner:
                     reasoning_content=response.reasoning_content,
                     thinking_blocks=response.thinking_blocks,
                 )
-                assistant_message = conversation_state.project_response_message(
-                    assistant_message,
-                    response,
-                )
                 messages.append(assistant_message)
                 await self._emit_checkpoint(
                     spec,
@@ -586,15 +544,6 @@ class AgentRunner:
                         length_recovery_parts.clear()
                         continue
                     break
-                checkpoint_model_messages = (
-                    self.context_governor.prepare_for_model(
-                        governance_config,
-                        messages,
-                        compacted_tool_call_ids,
-                    )
-                    if response.provider_state is not None
-                    else None
-                )
                 await self._emit_checkpoint(
                     spec,
                     {
@@ -604,10 +553,6 @@ class AgentRunner:
                         "assistant_message": assistant_message,
                         "completed_tool_results": completed_tool_results,
                         "pending_tool_calls": [],
-                        "provider_state": conversation_state.checkpoint(
-                            messages,
-                            model_messages=checkpoint_model_messages,
-                        ),
                     },
                 )
                 empty_content_retries = 0
@@ -630,11 +575,7 @@ class AgentRunner:
                 )
 
             clean = hook.finalize_content(context, response.content)
-            if (
-                response.finish_reason
-                not in {"error", "length", "refusal", "content_filter"}
-                and is_blank_text(clean)
-            ):
+            if response.finish_reason != "error" and is_blank_text(clean):
                 empty_content_retries += 1
                 if empty_content_retries < _MAX_EMPTY_RETRIES:
                     logger.warning(
@@ -657,12 +598,7 @@ class AgentRunner:
                 if hook.wants_streaming():
                     await hook.on_stream_end(context, resuming=False)
                 retry_messages = self._finalization_retry_messages(messages_for_model)
-                response = await self._request_finalization_retry(
-                    spec,
-                    messages_for_model,
-                    transcript=messages,
-                    conversation_state=conversation_state,
-                )
+                response = await self._request_finalization_retry(spec, messages_for_model)
                 retry_usage = self._usage_or_estimate(spec, retry_messages, response)
                 self._accumulate_usage(usage, retry_usage)
                 raw_usage = self._merge_usage(raw_usage, retry_usage)
@@ -672,7 +608,7 @@ class AgentRunner:
                 original_content = response.content
                 clean = hook.finalize_content(context, response.content)
 
-            if response.finish_reason == "length":
+            if response.finish_reason == "length" and not is_blank_text(clean):
                 if len(length_recovery_parts) < _MAX_LENGTH_RECOVERIES:
                     length_recovery_parts.append(
                         _restore_outer_whitespace(clean or "", original_content)
@@ -687,13 +623,10 @@ class AgentRunner:
                     if hook.wants_streaming():
                         context.stream_continues_current_message = True
                         await hook.on_stream_end(context, resuming=True)
-                    messages.append(conversation_state.project_response_message(
-                        build_assistant_message(
-                            clean,
-                            reasoning_content=response.reasoning_content,
-                            thinking_blocks=response.thinking_blocks,
-                        ),
-                        response,
+                    messages.append(build_assistant_message(
+                        clean,
+                        reasoning_content=response.reasoning_content,
+                        thinking_blocks=response.thinking_blocks,
                     ))
                     messages.append(build_length_recovery_message(clean or ""))
                     await hook.after_iteration(context)
@@ -723,22 +656,15 @@ class AgentRunner:
                     reasoning_content=response.reasoning_content,
                     thinking_blocks=response.thinking_blocks,
                 )
-                assistant_message = conversation_state.project_response_message(
-                    assistant_message,
-                    response,
-                )
 
             # Check for mid-turn injections BEFORE signaling stream end.
             # If injections are found we keep the stream alive (resuming=True)
             # so streaming channels don't prematurely finalize the card.
             should_continue, injection_cycles = await self._try_drain_injections(
                 spec, messages, assistant_message, injection_cycles,
-                conversation_state=conversation_state,
                 phase="after final response",
                 iteration=iteration,
-                allow_goal_continue=(
-                    response.finish_reason not in {"refusal", "content_filter"}
-                ),
+                allow_goal_continue=True,
             )
             if should_continue:
                 had_injections = True
@@ -791,17 +717,11 @@ class AgentRunner:
                     continue
                 break
 
-            messages.append(
-                assistant_message
-                or conversation_state.project_response_message(
-                    build_assistant_message(
-                        clean,
-                        reasoning_content=response.reasoning_content,
-                        thinking_blocks=response.thinking_blocks,
-                    ),
-                    response,
-                )
-            )
+            messages.append(assistant_message or build_assistant_message(
+                clean,
+                reasoning_content=response.reasoning_content,
+                thinking_blocks=response.thinking_blocks,
+            ))
             await self._emit_checkpoint(
                 spec,
                 {
@@ -811,7 +731,6 @@ class AgentRunner:
                     "assistant_message": messages[-1],
                     "completed_tool_results": [],
                     "pending_tool_calls": [],
-                    "provider_state": conversation_state.checkpoint(messages),
                 },
             )
             if length_recovery_parts:
@@ -845,7 +764,6 @@ class AgentRunner:
                     hook,
                     messages,
                     usage,
-                    conversation_state,
                 )
             if terminal_content is None:
                 terminal_content = self._max_iterations_fallback(spec)
@@ -869,7 +787,6 @@ class AgentRunner:
             tool_events=tool_events,
             had_injections=had_injections,
             pending_stream_content=pending_stream_content,
-            provider_state=conversation_state.finish(messages),
         )
 
     def _build_request_kwargs(
@@ -900,8 +817,6 @@ class AgentRunner:
         context: AgentHookContext,
         *,
         malformed_retry: bool = False,
-        conversation_state: ProviderConversationStateController,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         timeout_s: float | None = spec.llm_timeout_s
         if timeout_s is None:
@@ -971,7 +886,6 @@ class AgentRunner:
 
             coro = spec.runtime.provider.chat_stream_with_retry(
                 **kwargs,
-                provider_context=provider_context,
                 on_content_delta=_stream,
                 on_thinking_delta=_thinking,
                 on_tool_call_delta=_provider_tool_event,
@@ -1006,15 +920,11 @@ class AgentRunner:
 
             coro = spec.runtime.provider.chat_stream_with_retry(
                 **kwargs,
-                provider_context=provider_context,
                 on_content_delta=_stream_progress,
                 on_tool_call_delta=_provider_tool_event,
             )
         else:
-            coro = spec.runtime.provider.chat_with_retry(
-                **kwargs,
-                provider_context=provider_context,
-            )
+            coro = spec.runtime.provider.chat_with_retry(**kwargs)
 
         # Streaming requests also have provider-level idle timeouts
         # (NANOBOT_STREAM_IDLE_TIMEOUT_S), but a stream that keeps producing
@@ -1076,10 +986,6 @@ class AgentRunner:
             return await self._request_model(
                 spec, retry_messages, hook, context,
                 malformed_retry=True,
-                conversation_state=conversation_state,
-                provider_context=conversation_state.independent_request_context(
-                    context_window_tokens=spec.runtime.context_window_tokens,
-                ),
             )
         if (
             all_dropped
@@ -1092,13 +998,7 @@ class AgentRunner:
             fallback_messages = self._malformed_tool_call_retry_messages(
                 messages, response.content,
             )
-            return await self._request_no_tools(
-                spec,
-                fallback_messages,
-                provider_context=conversation_state.independent_request_context(
-                    context_window_tokens=spec.runtime.context_window_tokens,
-                ),
-            )
+            return await self._request_no_tools(spec, fallback_messages)
         return response
 
     @staticmethod
@@ -1131,10 +1031,6 @@ class AgentRunner:
             original_finish_reason,
         )
         response.tool_calls = valid
-        # The opaque candidate still contains every raw function_call item.
-        # Advancing it after dropping even one call would replay an unmatched
-        # call without a corresponding tool output on the next request.
-        response.provider_state = None
         if not valid:
             response.finish_reason = "stop"
         return (dropped, not valid, original_finish_reason)
@@ -1164,27 +1060,9 @@ class AgentRunner:
         self,
         spec: AgentRunSpec,
         messages: list[dict[str, Any]],
-        *,
-        transcript: list[dict[str, Any]],
-        conversation_state: ProviderConversationStateController,
     ) -> LLMResponse:
         retry_messages = self._finalization_retry_messages(messages)
-        provider_context = conversation_state.prepare_request(
-            transcript,
-            context_window_tokens=spec.runtime.context_window_tokens,
-            supplemental_messages=[retry_messages[-1]],
-        )
-        response = await self._request_no_tools(
-            spec,
-            retry_messages,
-            provider_context=provider_context,
-        )
-        conversation_state.observe_response(
-            response,
-            transcript,
-            adopt_candidate_state=False,
-        )
-        return response
+        return await self._request_no_tools(spec, retry_messages)
 
     @staticmethod
     def _finalization_retry_messages(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
@@ -1198,17 +1076,10 @@ class AgentRunner:
         hook: AgentHook,
         messages: list[dict[str, Any]],
         usage: dict[str, int],
-        conversation_state: ProviderConversationStateController,
     ) -> str | None:
         retry_messages = self._budget_exhausted_finalization_messages(messages)
         try:
-            response = await self._request_no_tools(
-                spec,
-                retry_messages,
-                provider_context=conversation_state.independent_request_context(
-                    context_window_tokens=spec.runtime.context_window_tokens,
-                ),
-            )
+            response = await self._request_no_tools(spec, retry_messages)
         except Exception:
             logger.exception(
                 "Budget-exhausted finalization failed for {}; using fallback",
@@ -1244,18 +1115,9 @@ class AgentRunner:
         self,
         spec: AgentRunSpec,
         messages: list[dict[str, Any]],
-        *,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
-        kwargs = self._build_request_kwargs(
-            spec,
-            messages,
-            tools=None,
-        )
-        return await spec.runtime.provider.chat_with_retry(
-            **kwargs,
-            provider_context=provider_context,
-        )
+        kwargs = self._build_request_kwargs(spec, messages, tools=None)
+        return await spec.runtime.provider.chat_with_retry(**kwargs)
 
     @staticmethod
     def _budget_exhausted_finalization_messages(

nanobot/agent/tools/exec_session.py

@@ -5,7 +5,6 @@ from __future__ import annotations
 import asyncio
 import time
 import uuid
-from collections import deque
 from contextlib import suppress
 from dataclasses import dataclass
 from typing import Any
@@ -52,66 +51,6 @@ class ExecSessionInfo:
     owner_session_key: str | None = None
 
 
-class _BoundedOutputBuffer:
-    """Keep the first and most recent characters within a fixed budget."""
-
-    def __init__(self, max_chars: int) -> None:
-        self.max_chars = max_chars
-        self._content = ""
-        self._tail: deque[str] = deque()
-        self._tail_chars = 0
-        self._total_chars = 0
-        self._truncated = False
-
-    @property
-    def has_output(self) -> bool:
-        return self._total_chars > 0
-
-    @property
-    def retained_chars(self) -> int:
-        return len(self._content) + self._tail_chars
-
-    def append(self, text: str) -> None:
-        if not text:
-            return
-        self._total_chars += len(text)
-        if not self._truncated:
-            combined = self._content + text
-            if len(combined) <= self.max_chars:
-                self._content = combined
-                return
-            head_chars = self.max_chars // 2
-            tail_chars = self.max_chars - head_chars
-            self._content = combined[:head_chars]
-            self._tail.append(combined[-tail_chars:])
-            self._tail_chars = tail_chars
-            self._truncated = True
-            return
-
-        tail_chars = self.max_chars - len(self._content)
-        self._tail.append(text)
-        self._tail_chars += len(text)
-        while self._tail_chars > tail_chars:
-            excess = self._tail_chars - tail_chars
-            first = self._tail[0]
-            if len(first) <= excess:
-                self._tail.popleft()
-                self._tail_chars -= len(first)
-            else:
-                self._tail[0] = first[excess:]
-                self._tail_chars -= excess
-
-    def drain(self) -> tuple[str, int]:
-        output = self._content + "".join(self._tail)
-        truncated_chars = self._total_chars - len(output)
-        self._content = ""
-        self._tail.clear()
-        self._tail_chars = 0
-        self._total_chars = 0
-        self._truncated = False
-        return output, truncated_chars
-
-
 class _ExecSession:
     def __init__(
         self,
@@ -134,27 +73,30 @@ class _ExecSession:
         # timeout None/0 means no limit; an infinite deadline is never reached.
         self.deadline = time.monotonic() + timeout if timeout else float("inf")
         self.last_access = time.monotonic()
-        self._stdout = _BoundedOutputBuffer(MAX_OUTPUT_CHARS)
-        self._stderr = _BoundedOutputBuffer(MAX_OUTPUT_CHARS)
+        self._chunks: list[str] = []
         self._lock = asyncio.Lock()
         self._timed_out = False
-        self._stdout_task = asyncio.create_task(self._read_stream(process.stdout, self._stdout))
-        self._stderr_task = asyncio.create_task(self._read_stream(process.stderr, self._stderr))
+        self._stdout_task = asyncio.create_task(self._read_stream(process.stdout, ""))
+        self._stderr_task = asyncio.create_task(self._read_stream(process.stderr, "STDERR:\n"))
 
     async def _read_stream(
         self,
         stream: asyncio.StreamReader | None,
-        buffer: _BoundedOutputBuffer,
+        prefix: str,
     ) -> None:
         if stream is None:
             return
+        first = True
         while True:
             chunk = await stream.read(4096)
             if not chunk:
                 break
             text = chunk.decode("utf-8", errors="replace")
+            if prefix and first:
+                text = prefix + text
+                first = False
             async with self._lock:
-                buffer.append(text)
+                self._chunks.append(text)
 
     async def write(self, chars: str) -> str | None:
         if self.process.returncode is not None:
@@ -215,14 +157,10 @@ class _ExecSession:
             await self._wait_for_buffered_output()
 
         async with self._lock:
-            stdout, stdout_truncated = self._stdout.drain()
-            stderr, stderr_truncated = self._stderr.drain()
+            output = "".join(self._chunks)
+            self._chunks.clear()
 
-        output_parts = [stdout] if stdout else []
-        if stderr:
-            output_parts.append(f"STDERR:\n{stderr}")
-        output = "\n".join(output_parts)
-        output, response_truncated = _truncate_output(output, max_output_chars)
+        output, truncated = _truncate_output(output, max_output_chars)
         return _SessionPoll(
             output=output,
             done=self.process.returncode is not None,
@@ -231,7 +169,7 @@ class _ExecSession:
             timed_out=self._timed_out,
             terminated=terminated,
             stdin_closed=stdin_closed,
-            truncated_chars=stdout_truncated + stderr_truncated + response_truncated,
+            truncated_chars=truncated,
         )
 
     async def kill(self) -> None:
@@ -257,7 +195,7 @@ class _ExecSession:
         deadline = time.monotonic() + OUTPUT_DRAIN_GRACE_S
         while time.monotonic() < deadline:
             async with self._lock:
-                if self._stdout.has_output or self._stderr.has_output:
+                if self._chunks:
                     return
             await asyncio.sleep(0.01)
 
@@ -465,16 +403,20 @@ def clamp_session_int(value: int | None, default: int, minimum: int, maximum: in
 def _truncate_output(output: str, max_output_chars: int) -> tuple[str, int]:
     if len(output) <= max_output_chars:
         return output, 0
-    head_chars = max_output_chars // 2
-    tail_chars = max_output_chars - head_chars
+    half = max_output_chars // 2
     omitted = len(output) - max_output_chars
-    return output[:head_chars] + output[-tail_chars:], omitted
+    return (
+        output[:half]
+        + f"\n\n... ({omitted:,} chars truncated) ...\n\n"
+        + output[-half:],
+        omitted,
+    )
 
 
 def format_session_poll(session_id: str, poll: _SessionPoll) -> str:
     parts = [poll.output] if poll.output else []
     if poll.truncated_chars:
-        parts.append(f"({poll.truncated_chars:,} chars truncated from output)")
+        parts.append(f"(output truncated by {poll.truncated_chars:,} chars)")
     if poll.timed_out:
         parts.append("Error: Command timed out; session was terminated.")
     if poll.terminated and not poll.timed_out:
@@ -645,9 +587,7 @@ class WriteStdinTool(Tool):
         max_output_chars: int,
     ) -> str:
         deadline = time.monotonic() + (wait_timeout_ms / 1000)
-        aggregate = _BoundedOutputBuffer(max_output_chars)
-        upstream_truncated = 0
-        search_overlap = ""
+        aggregate: list[str] = []
         first = True
         poll: _SessionPoll | None = None
 
@@ -660,24 +600,19 @@ class WriteStdinTool(Tool):
                 close_stdin=close_stdin if first else False,
                 terminate=terminate if first else False,
                 yield_time_ms=step_ms,
-                max_output_chars=MAX_OUTPUT_CHARS,
+                max_output_chars=max_output_chars,
                 owner_session_key=current_request_session_key(),
             )
             first = False
-            upstream_truncated += poll.truncated_chars
             if poll.output:
                 aggregate.append(poll.output)
-                searchable = search_overlap + poll.output
-                if wait_for in searchable:
-                    poll.output, aggregate_truncated = aggregate.drain()
-                    poll.truncated_chars = upstream_truncated + aggregate_truncated
+                joined = "".join(aggregate)
+                if wait_for in joined:
+                    poll.output = joined
                     result = format_session_poll(session_id, poll)
                     return ToolResult.error(result) if poll.timed_out else result
-                overlap_chars = max(0, len(wait_for) - 1)
-                search_overlap = searchable[-overlap_chars:] if overlap_chars else ""
             if poll.done or remaining_ms <= 0:
-                poll.output, aggregate_truncated = aggregate.drain()
-                poll.truncated_chars = upstream_truncated + aggregate_truncated
+                poll.output = "".join(aggregate)
                 result = format_session_poll(session_id, poll)
                 if wait_for not in poll.output:
                     result += f"\nWait target not observed: {wait_for!r}"

nanobot/agent/tools/mcp.py

@@ -12,7 +12,7 @@ from contextlib import AsyncExitStack, suppress
 from typing import TYPE_CHECKING, Any, Mapping, Protocol, cast
 from weakref import WeakKeyDictionary
 
-import httpx
+import httpx2 as httpx
 from loguru import logger
 
 from nanobot.agent.tools.base import Tool, ToolResult
@@ -25,9 +25,9 @@ from nanobot.bus.events import (
 )
 from nanobot.bus.queue import MessageBus
 from nanobot.security.network import (
-    PinnedDNSAsyncTransport,
+    Httpx2PinnedDNSAsyncTransport,
     env_proxy_applies_to_url,
-    httpx_env_proxy_mounts,
+    httpx2_env_proxy_mounts,
     resolve_url_target,
     validate_url_target,
 )
@@ -194,7 +194,7 @@ def _is_session_terminated(exc: BaseException) -> bool:
         messages.append(str(getattr(error, "message", "")))
     return any(
         marker in message.lower()
-        for marker in ("session terminated", "connection closed")
+        for marker in ("session terminated", "session not found", "connection closed")
         for message in messages
     )
 
@@ -252,8 +252,8 @@ def _redact_url(url: str) -> str:
 
 
 def _pinned_transport_kwargs() -> dict[str, Any]:
-    kwargs: dict[str, Any] = {"transport": PinnedDNSAsyncTransport()}
-    mounts = httpx_env_proxy_mounts()
+    kwargs: dict[str, Any] = {"transport": Httpx2PinnedDNSAsyncTransport()}
+    mounts = httpx2_env_proxy_mounts()
     if mounts:
         kwargs["mounts"] = mounts
     return kwargs
@@ -518,7 +518,7 @@ def _image_block_data_url(block: Any, types: Any) -> str | None:
     """
     image_cls = getattr(types, "ImageContent", None)
     if image_cls is not None and isinstance(block, image_cls):
-        mime = getattr(block, "mimeType", None) or "image/png"
+        mime = getattr(block, "mime_type", None) or "image/png"
         return f"data:{mime};base64,{block.data}"
 
     embedded_cls = getattr(types, "EmbeddedResource", None)
@@ -527,7 +527,7 @@ def _image_block_data_url(block: Any, types: Any) -> str | None:
         resource = getattr(block, "resource", None)
         if blob_cls is not None and isinstance(resource, blob_cls):
             blob_resource = cast(Any, resource)
-            mime = getattr(blob_resource, "mimeType", None) or ""
+            mime = getattr(blob_resource, "mime_type", None) or ""
             if isinstance(mime, str) and mime.startswith("image/"):
                 return f"data:{mime};base64,{blob_resource.blob}"
     return None
@@ -571,7 +571,7 @@ class MCPToolWrapper(_MCPWrapperBase):
         self._original_name = tool_def.name
         self._name = _sanitize_mcp_tool_name(f"mcp_{server_name}_{tool_def.name}")
         self._description = tool_def.description or tool_def.name
-        raw_schema = tool_def.inputSchema or {"type": "object", "properties": {}}
+        raw_schema = tool_def.input_schema or {"type": "object", "properties": {}}
         self._parameters = _normalize_schema_for_openai(raw_schema)
         self._tool_timeout = tool_timeout
 
@@ -650,7 +650,7 @@ class MCPToolWrapper(_MCPWrapperBase):
                 # Success — extract text and persist any image content as artifacts.
                 try:
                     rendered = self._render_call_result(result.content, kwargs)
-                    if getattr(result, "isError", False):
+                    if getattr(result, "is_error", False):
                         return ToolResult.error(rendered)
                     return rendered
                 except Exception as exc:
@@ -876,8 +876,7 @@ class MCPPromptWrapper(_MCPWrapperBase):
         return True
 
     async def execute(self, **kwargs: Any) -> str:
-        from mcp import types
-        from mcp.shared.exceptions import McpError
+        from mcp import MCPError, types
 
         retried_transient = False
         refreshed_session = False
@@ -897,7 +896,7 @@ class MCPPromptWrapper(_MCPWrapperBase):
                     raise
                 logger.warning("MCP prompt '{}' was cancelled by server/SDK", self._name)
                 return "(MCP prompt call was cancelled)"
-            except McpError as exc:
+            except MCPError as exc:
                 if await self._refresh_session_after_termination(
                     exc,
                     refreshed_session,
@@ -1062,7 +1061,7 @@ async def connect_mcp_servers(
                         **_pinned_transport_kwargs(),
                     )
                 )
-                read, write, _ = await server_stack.enter_async_context(
+                read, write = await server_stack.enter_async_context(
                     streamable_http_client(cfg.url, http_client=http_client)
                 )
             else:

nanobot/bus/events.py

@@ -18,7 +18,6 @@ INBOUND_META_RUNTIME_CONTROL = "_runtime_control"
 RUNTIME_CONTROL_ACK = "_ack"
 RUNTIME_CONTROL_MCP_RELOAD = "mcp_reload"
 RUNTIME_CONTROL_IMAGE_GENERATION_RELOAD = "image_generation_reload"
-INBOUND_META_TRANSIENT_SESSION = "_transient_session"
 
 
 @dataclass
@@ -33,7 +32,6 @@ class InboundMessage:
     media: list[str] = field(default_factory=list)  # Media URLs
     metadata: dict[str, Any] = field(default_factory=dict)  # Channel-specific data
     session_key_override: str | None = None  # Optional override for thread-scoped sessions
-    transient_session: bool = False  # In-memory session whose lifetime is owned by the channel
 
     @property
     def session_key(self) -> str:

nanobot/channels/base.py

@@ -8,11 +8,7 @@ from typing import Any, cast
 
 from loguru import logger
 
-from nanobot.bus.events import (
-    INBOUND_META_TRANSIENT_SESSION,
-    InboundMessage,
-    OutboundMessage,
-)
+from nanobot.bus.events import InboundMessage, OutboundMessage
 from nanobot.bus.queue import MessageBus
 from nanobot.pairing import (
     PAIRING_CODE_META_KEY,
@@ -252,15 +248,7 @@ class BaseChannel(ABC):
         permission_id = authorization_id if authorization_id is not None else sender_id
         if not self.is_allowed(permission_id):
             if is_dm:
-                try:
-                    code = generate_code(self.name, str(sender_id))
-                except OSError:
-                    # Transient pairing-store I/O failure: skip the pairing
-                    # reply for this message rather than crash the handler.
-                    self.logger.warning(
-                        "Pairing store unavailable; dropping DM from {}", sender_id
-                    )
-                    return
+                code = generate_code(self.name, str(sender_id))
                 await self.send(
                     OutboundMessage(
                         channel=self.name,
@@ -281,8 +269,7 @@ class BaseChannel(ABC):
                 )
             return
 
-        meta = dict(metadata or {})
-        transient_session = meta.pop(INBOUND_META_TRANSIENT_SESSION, False) is True
+        meta = metadata or {}
         if self.supports_streaming:
             meta = {**meta, "_wants_stream": True}
 
@@ -294,7 +281,6 @@ class BaseChannel(ABC):
             media=media or [],
             metadata=meta,
             session_key_override=session_key,
-            transient_session=transient_session,
         )
 
         await self.bus.publish_inbound(msg)

nanobot/channels/manager.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 import asyncio
 import hashlib
 import inspect
-from collections.abc import Awaitable, Callable, Iterable
+from collections.abc import Callable, Iterable
 from contextlib import suppress
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, cast
@@ -97,7 +97,6 @@ class ChannelManager:
         webui_runtime_model_name: Callable[[], str | None] | None = None,
         webui_cron_pending_job_ids: Callable[[str], set[str]] | None = None,
         webui_local_trigger_pending_ids: Callable[[str], set[str]] | None = None,
-        webui_cancel_active_turn: Callable[[str], Awaitable[int]] | None = None,
         webui_static_dist: bool = True,
         webui_runtime_surface: str = "browser",
         webui_runtime_capabilities: dict[str, Any] | None = None,
@@ -111,7 +110,6 @@ class ChannelManager:
         self._webui_runtime_model_name = webui_runtime_model_name
         self._webui_cron_pending_job_ids = webui_cron_pending_job_ids
         self._webui_local_trigger_pending_ids = webui_local_trigger_pending_ids
-        self._webui_cancel_active_turn = webui_cancel_active_turn
         self._webui_static_dist = webui_static_dist
         self._webui_runtime_surface = webui_runtime_surface
         self._webui_runtime_capabilities = dict(webui_runtime_capabilities or {})
@@ -180,7 +178,6 @@ class ChannelManager:
                 local_trigger_store=self._local_trigger_store,
                 cron_pending_job_ids=self._webui_cron_pending_job_ids,
                 local_trigger_pending_ids=self._webui_local_trigger_pending_ids,
-                cancel_active_turn=self._webui_cancel_active_turn,
                 channel_feature_action=self.apply_channel_feature_action,
                 channel_runtime_status=self.get_status,
                 skill_state_action=self._webui_skill_state_action,

nanobot/channels/slack/runtime.py

@@ -493,11 +493,12 @@ class SlackChannel(BaseChannel):
         except Exception as e:
             self.logger.debug("reactions_add failed: {}", e)
 
-        # Thread-scoped session key whenever the turn lives in a thread: either the
-        # message arrived inside one (raw_thread_ts) or reply_in_thread opens a new
-        # thread for this channel message. DM roots have no thread_ts and keep the
-        # default per-chat session, so context doesn't bleed across thread boundaries.
-        session_key = f"slack:{chat_id}:{thread_ts}" if thread_ts else None
+        # Thread-scoped session key whenever the user is in a real thread
+        # (raw_thread_ts is set). DM threads get their own session, separate
+        # from the DM root, so context doesn't bleed across thread boundaries.
+        session_key = (
+            f"slack:{chat_id}:{thread_ts}" if thread_ts and raw_thread_ts else None
+        )
         media_paths: list[str] = []
         file_markers: list[str] = []
         for file_info in _as_json_list(event.get("files")) or []:

nanobot/channels/slack/tests/test_slack_channel.py

@@ -555,113 +555,6 @@ async def test_dm_thread_message_keeps_thread_ts_and_threaded_session() -> None:
     assert kwargs["metadata"]["slack"]["thread_ts"] == "1700000000.000100"
 
 
-def _channel_mention_request(envelope_id: str, ts: str) -> SimpleNamespace:
-    return SimpleNamespace(
-        type="events_api",
-        envelope_id=envelope_id,
-        payload={
-            "event": {
-                "type": "app_mention",
-                "user": "U1",
-                "channel": "C123",
-                "text": "<@UBOT> hello",
-                "ts": ts,
-            }
-        },
-    )
-
-
-@pytest.mark.asyncio
-async def test_channel_root_message_uses_thread_scoped_session() -> None:
-    """A channel mention that opens a thread belongs to that thread's session."""
-    channel = SlackChannel(SlackConfig(enabled=True), MessageBus())
-    channel._bot_user_id = "UBOT"
-    channel._web_client = _FakeAsyncWebClient()
-    channel._handle_message = AsyncMock()  # type: ignore[method-assign]
-    client = SimpleNamespace(send_socket_mode_response=AsyncMock())
-
-    req = _channel_mention_request("env-c1", "1700000000.000100")
-
-    await channel._on_socket_request(client, req)
-
-    channel._handle_message.assert_awaited_once()
-    kwargs = channel._handle_message.await_args.kwargs
-    assert kwargs["session_key"] == "slack:C123:1700000000.000100"
-    assert kwargs["metadata"]["slack"]["thread_ts"] == "1700000000.000100"
-
-
-@pytest.mark.asyncio
-async def test_channel_root_messages_do_not_share_one_session() -> None:
-    """Two threads opened in the same channel must not collapse into one session."""
-    channel = SlackChannel(SlackConfig(enabled=True), MessageBus())
-    channel._bot_user_id = "UBOT"
-    channel._web_client = _FakeAsyncWebClient()
-    channel._handle_message = AsyncMock()  # type: ignore[method-assign]
-    client = SimpleNamespace(send_socket_mode_response=AsyncMock())
-
-    first = _channel_mention_request("env-c1", "1700000000.000100")
-    second = _channel_mention_request("env-c2", "1700000000.000200")
-
-    await channel._on_socket_request(client, first)
-    await channel._on_socket_request(client, second)
-
-    session_keys = [call.kwargs["session_key"] for call in channel._handle_message.await_args_list]
-    assert session_keys == [
-        "slack:C123:1700000000.000100",
-        "slack:C123:1700000000.000200",
-    ]
-
-
-@pytest.mark.asyncio
-async def test_channel_root_message_without_reply_in_thread_uses_channel_session() -> None:
-    """With reply_in_thread disabled no thread is opened, so the channel session is used."""
-    channel = SlackChannel(SlackConfig(enabled=True, reply_in_thread=False), MessageBus())
-    channel._bot_user_id = "UBOT"
-    channel._web_client = _FakeAsyncWebClient()
-    channel._handle_message = AsyncMock()  # type: ignore[method-assign]
-    client = SimpleNamespace(send_socket_mode_response=AsyncMock())
-
-    req = _channel_mention_request("env-c3", "1700000000.000300")
-
-    await channel._on_socket_request(client, req)
-
-    channel._handle_message.assert_awaited_once()
-    kwargs = channel._handle_message.await_args.kwargs
-    assert kwargs["session_key"] is None
-    assert kwargs["metadata"]["slack"]["thread_ts"] is None
-
-
-@pytest.mark.asyncio
-async def test_channel_thread_reply_keeps_thread_session() -> None:
-    """A reply inside a channel thread stays in the session opened by the root message."""
-    channel = SlackChannel(SlackConfig(enabled=True), MessageBus())
-    channel._bot_user_id = "UBOT"
-    channel._web_client = _FakeAsyncWebClient()
-    channel._handle_message = AsyncMock()  # type: ignore[method-assign]
-    channel._with_thread_context = AsyncMock(return_value="hello")  # type: ignore[method-assign]
-    client = SimpleNamespace(send_socket_mode_response=AsyncMock())
-    req = SimpleNamespace(
-        type="events_api",
-        envelope_id="env-c4",
-        payload={
-            "event": {
-                "type": "app_mention",
-                "user": "U1",
-                "channel": "C123",
-                "text": "<@UBOT> follow up",
-                "ts": "1700000000.000400",
-                "thread_ts": "1700000000.000100",
-            }
-        },
-    )
-
-    await channel._on_socket_request(client, req)
-
-    channel._handle_message.assert_awaited_once()
-    kwargs = channel._handle_message.await_args.kwargs
-    assert kwargs["session_key"] == "slack:C123:1700000000.000100"
-
-
 @pytest.mark.asyncio
 async def test_slack_slash_command_skips_thread_context() -> None:
     channel = SlackChannel(SlackConfig(enabled=True, allow_from=[]), MessageBus())

nanobot/channels/websocket/runtime.py

@@ -18,11 +18,7 @@ from websockets.asyncio.server import ServerConnection, serve, unix_serve
 from websockets.exceptions import ConnectionClosed
 from websockets.http11 import Request as WsRequest
 
-from nanobot.bus.events import (
-    INBOUND_META_TRANSIENT_SESSION,
-    OUTBOUND_META_AGENT_UI,
-    OutboundMessage,
-)
+from nanobot.bus.events import OUTBOUND_META_AGENT_UI, OutboundMessage
 from nanobot.bus.outbound_events import (
     GoalStateSyncEvent,
     GoalStatusEvent,
@@ -36,10 +32,6 @@ from nanobot.bus.outbound_events import (
 )
 from nanobot.bus.queue import MessageBus
 from nanobot.channels.base import BaseChannel
-from nanobot.channels.websocket.temporary_chat import (
-    TemporaryChatLifecycle,
-    TemporaryChatLifecycleError,
-)
 from nanobot.command.builtin import builtin_command_starts_agent_turn
 from nanobot.config.schema import Base
 from nanobot.runtime_context import (
@@ -84,8 +76,6 @@ from nanobot.webui.websocket_logging import websockets_server_logger
 
 # Plain HTTP WebUI routes also run through websockets.process_request.
 _WEBUI_HTTP_OPEN_TIMEOUT_S = 360.0
-_TEMPORARY_CHAT_ID_PREFIX = "temporary-"
-_TEMPORARY_COMMANDS = frozenset({"/model", "/stop"})
 
 
 class WebSocketConfig(Base):
@@ -225,10 +215,6 @@ def _is_valid_chat_id(value: Any) -> TypeGuard[str]:
     return isinstance(value, str) and _CHAT_ID_RE.match(value) is not None
 
 
-def _is_temporary_chat_id(value: Any) -> TypeGuard[str]:
-    return _is_valid_chat_id(value) and value.startswith(_TEMPORARY_CHAT_ID_PREFIX)
-
-
 def _parse_envelope(raw: str) -> dict[str, Any] | None:
     """Return a typed envelope dict if the frame is a new-style JSON envelope, else None.
 
@@ -300,13 +286,6 @@ class WebSocketChannel(BaseChannel):
         self._workspaces = gateway.workspaces
 
         self._stream_text_buffers: dict[tuple[str, str], list[str]] = {}
-        self._temporary_chats = TemporaryChatLifecycle(
-            sessions=gateway.session_manager,
-            cancel_active_turn=gateway.cancel_active_turn,
-            attach=self._attach,
-            detach=self._detach,
-            clear_stream_buffers=self._clear_stream_buffers,
-        )
 
     # -- Subscription bookkeeping -------------------------------------------
 
@@ -318,23 +297,6 @@ class WebSocketChannel(BaseChannel):
         self._subs.setdefault(chat_id, set()).add(connection)
         self._conn_chats.setdefault(connection, set()).add(chat_id)
 
-    def _detach(self, connection: ServerConnection, chat_id: str) -> None:
-        chats = self._conn_chats.get(connection)
-        if chats is not None:
-            chats.discard(chat_id)
-            if not chats:
-                self._conn_chats.pop(connection, None)
-        subscribers = self._subs.get(chat_id)
-        if subscribers is not None:
-            subscribers.discard(connection)
-            if not subscribers:
-                self._subs.pop(chat_id, None)
-
-    def _clear_stream_buffers(self, chat_id: str) -> None:
-        for key in tuple(self._stream_text_buffers):
-            if key[0] == chat_id:
-                self._stream_text_buffers.pop(key, None)
-
     async def send_webui_protocol_error(
         self,
         connection: ServerConnection,
@@ -363,15 +325,18 @@ class WebSocketChannel(BaseChannel):
         )
         await self._hydrate_after_subscribe(fork_id)
 
-    async def _cleanup_connection(self, connection: ServerConnection) -> None:
+    def _cleanup_connection(self, connection: ServerConnection) -> None:
         """Remove *connection* from every subscription set; safe to call multiple times."""
-        try:
-            await self._temporary_chats.discard_owner(connection)
-        finally:
-            for chat_id in tuple(self._conn_chats.get(connection, ())):
-                self._detach(connection, chat_id)
-            self._conn_default.pop(connection, None)
-            self._webui_connections.discard(connection)
+        chat_ids = self._conn_chats.pop(connection, set())
+        for cid in chat_ids:
+            subs = self._subs.get(cid)
+            if subs is None:
+                continue
+            subs.discard(connection)
+            if not subs:
+                self._subs.pop(cid, None)
+        self._conn_default.pop(connection, None)
+        self._webui_connections.discard(connection)
 
     async def _maybe_push_active_goal_state(self, chat_id: str) -> None:
         """Replay an active sustained goal from session metadata after *chat_id* is subscribed.
@@ -422,7 +387,7 @@ class WebSocketChannel(BaseChannel):
         try:
             await connection.send(raw)
         except ConnectionClosed:
-            await self._cleanup_connection(connection)
+            self._cleanup_connection(connection)
         except Exception as e:
             self.logger.warning("failed to send {} event: {}", event, e)
 
@@ -644,7 +609,7 @@ class WebSocketChannel(BaseChannel):
         except Exception as e:
             self.logger.debug("connection ended: {}", e)
         finally:
-            await self._cleanup_connection(connection)
+            self._cleanup_connection(connection)
 
     # -- Inbound WebSocket envelopes ---------------------------------------
 
@@ -682,36 +647,11 @@ class WebSocketChannel(BaseChannel):
         if t == "fork_chat":
             await handle_webui_fork_chat(self, connection, envelope)
             return
-        if t == "discard_temporary_chat":
-            cid = envelope.get("chat_id")
-            if not _is_temporary_chat_id(cid):
-                await self._send_event(connection, "error", detail="invalid temporary chat_id")
-                return
-            try:
-                await self._temporary_chats.discard(connection, cid)
-            except TemporaryChatLifecycleError as exc:
-                await self._send_event(
-                    connection,
-                    "error",
-                    detail=exc.detail,
-                    chat_id=cid,
-                )
-                return
-            await self._send_event(connection, "temporary_chat_discarded", chat_id=cid)
-            return
         if t == "attach":
             cid = envelope.get("chat_id")
             if not _is_valid_chat_id(cid):
                 await self._send_event(connection, "error", detail="invalid chat_id")
                 return
-            if _is_temporary_chat_id(cid):
-                await self._send_event(
-                    connection,
-                    "error",
-                    detail="temporary_chat_cannot_attach",
-                    chat_id=cid,
-                )
-                return
             self._attach(connection, cid)
             await self._send_event(connection, "attached", chat_id=cid)
             await self._hydrate_after_subscribe(cid)
@@ -721,14 +661,6 @@ class WebSocketChannel(BaseChannel):
             if not _is_valid_chat_id(cid):
                 await self._send_event(connection, "error", detail="invalid chat_id")
                 return
-            if _is_temporary_chat_id(cid):
-                await self._send_event(
-                    connection,
-                    "error",
-                    detail="temporary_chat_has_no_workspace",
-                    chat_id=cid,
-                )
-                return
             scope = await self._workspace_scope_or_error(
                 connection,
                 lambda: self._workspaces.scope_for_set_request(
@@ -760,15 +692,6 @@ class WebSocketChannel(BaseChannel):
             if not _is_valid_chat_id(cid):
                 await self._send_event(connection, "error", detail="invalid chat_id")
                 return
-            temporary = envelope.get("temporary") is True
-            if _is_temporary_chat_id(cid) != temporary:
-                await self._send_event(
-                    connection,
-                    "error",
-                    detail="temporary_chat_mismatch",
-                    chat_id=cid,
-                )
-                return
             raw_turn_id = envelope.get("turn_id")
             turn_id = raw_turn_id if isinstance(raw_turn_id, str) and raw_turn_id else None
             rejection_fields = {
@@ -805,17 +728,6 @@ class WebSocketChannel(BaseChannel):
                     **rejection_fields,
                 )
                 return
-            if temporary:
-                await self._dispatch_temporary_message(
-                    connection,
-                    client_id=client_id,
-                    chat_id=cid,
-                    content=content,
-                    turn_id=turn_id,
-                    envelope=envelope,
-                    rejection_fields=rejection_fields,
-                )
-                return
 
             raw_media = envelope.get("media")
             media_paths: list[str] = []
@@ -937,103 +849,6 @@ class WebSocketChannel(BaseChannel):
             return
         await self._send_event(connection, "error", detail=f"unknown type: {t!r}")
 
-    async def _dispatch_temporary_message(
-        self,
-        connection: ServerConnection,
-        *,
-        client_id: str,
-        chat_id: str,
-        content: str,
-        turn_id: str | None,
-        envelope: dict[str, Any],
-        rejection_fields: dict[str, str],
-    ) -> None:
-        """Admit a WebUI-only message without durable or local-agent capabilities."""
-        if connection not in self._webui_connections:
-            await self._send_event(
-                connection,
-                "error",
-                detail="temporary_chat_unavailable",
-                **rejection_fields,
-            )
-            return
-        forbidden = (
-            "media",
-            "cli_apps",
-            "mcp_presets",
-            "quoted_context",
-            "workspace_scope",
-        )
-        if any(field in envelope for field in forbidden):
-            await self._send_event(
-                connection,
-                "error",
-                detail="temporary_chat_capability_rejected",
-                **rejection_fields,
-            )
-            return
-        if not content.strip():
-            await self._send_event(
-                connection,
-                "error",
-                detail="missing content",
-                **rejection_fields,
-            )
-            return
-        command = content.strip().partition(" ")[0].lower()
-        if command.startswith("/") and command not in _TEMPORARY_COMMANDS:
-            await self._send_event(
-                connection,
-                "error",
-                detail="temporary_chat_command_rejected",
-                **rejection_fields,
-            )
-            return
-
-        try:
-            session_key = self._temporary_chats.claim(connection, chat_id)
-        except TemporaryChatLifecycleError as exc:
-            await self._send_event(
-                connection,
-                "error",
-                detail=exc.detail,
-                **rejection_fields,
-            )
-            return
-
-        metadata: dict[str, Any] = {
-            "remote": getattr(connection, "remote_address", None),
-            "webui": True,
-            INBOUND_META_TRANSIENT_SESSION: True,
-            **self._transcripts.client_turn_metadata(turn_id),
-        }
-        queued_owner = None
-        if builtin_command_starts_agent_turn(content):
-            queued_owner = register_queued_websocket_turn_if_idle(chat_id, turn_id)
-            if queued_owner is not None:
-                metadata[WEBSOCKET_TURN_OWNER_METADATA_KEY] = queued_owner
-        accepted = False
-        try:
-            await self._handle_message(
-                sender_id=client_id,
-                chat_id=chat_id,
-                content=content,
-                metadata=metadata,
-                session_key=session_key,
-                is_dm=False,
-            )
-            accepted = True
-        finally:
-            if not accepted and queued_owner is not None:
-                clear_websocket_turn_if_current(chat_id, queued_owner)
-        if turn_id:
-            await self._send_event(
-                connection,
-                "message_accepted",
-                chat_id=chat_id,
-                turn_id=turn_id,
-            )
-
     async def _workspace_scope_or_error(
         self,
         connection: ServerConnection,
@@ -1074,8 +889,6 @@ class WebSocketChannel(BaseChannel):
             except Exception as e:
                 self.logger.warning("server task error during shutdown: {}", e)
             self._server_task = None
-        for connection in tuple(self._conn_chats):
-            await self._temporary_chats.discard_owner(connection)
         self._subs.clear()
         self._conn_chats.clear()
         self._conn_default.clear()
@@ -1093,7 +906,7 @@ class WebSocketChannel(BaseChannel):
         try:
             await connection.send(raw)
         except ConnectionClosed:
-            await self._cleanup_connection(connection)
+            self._cleanup_connection(connection)
             self.logger.warning("connection gone{}", label)
         except Exception:
             self.logger.exception("send failed{}", label)
@@ -1110,8 +923,6 @@ class WebSocketChannel(BaseChannel):
         transcript_overrides: dict[str, Any] | None = None,
     ) -> bool:
         """Persist one canonical turn event and retain unsafe owners on failure."""
-        if _is_temporary_chat_id(chat_id):
-            return True
         persisted = self._transcripts.prepare_and_append(
             chat_id,
             event,
@@ -1405,7 +1216,6 @@ class WebSocketChannel(BaseChannel):
             body,
             metadata=meta,
             phase="answer",
-            include_source=True,
         )
         raw = json.dumps(body, ensure_ascii=False)
         if not conns:

nanobot/channels/websocket/temporary_chat.py

@@ -1,85 +0,0 @@
-"""Connection-owned lifecycle for WebUI Temporary Chat sessions."""
-
-from __future__ import annotations
-
-from collections.abc import Awaitable, Callable
-
-from websockets.asyncio.server import ServerConnection
-
-from nanobot.session.manager import SessionManager
-from nanobot.session.webui_turns import clear_websocket_turns
-
-
-class TemporaryChatLifecycleError(RuntimeError):
-    """A stable WebSocket protocol error raised by the temporary-chat lifecycle."""
-
-    def __init__(self, detail: str) -> None:
-        self.detail = detail
-        super().__init__(detail)
-
-
-class TemporaryChatLifecycle:
-    """Own temporary session identity, cancellation, and cleanup ordering."""
-
-    def __init__(
-        self,
-        *,
-        sessions: SessionManager | None,
-        cancel_active_turn: Callable[[str], Awaitable[int]] | None,
-        attach: Callable[[ServerConnection, str], None],
-        detach: Callable[[ServerConnection, str], None],
-        clear_stream_buffers: Callable[[str], None],
-    ) -> None:
-        self._sessions = sessions
-        self._cancel_active_turn = cancel_active_turn
-        self._attach = attach
-        self._detach = detach
-        self._clear_stream_buffers = clear_stream_buffers
-        self._owners: dict[str, ServerConnection] = {}
-
-    def claim(self, owner: ServerConnection, chat_id: str) -> str:
-        """Claim *chat_id* for *owner* and return its in-memory session key."""
-        if self._sessions is None or self._cancel_active_turn is None:
-            raise TemporaryChatLifecycleError("temporary_chat_unavailable")
-        current = self._owners.get(chat_id)
-        if current is not None and current is not owner:
-            raise TemporaryChatLifecycleError("temporary_chat_not_owned")
-
-        session_key = f"websocket:{chat_id}"
-        self._sessions.get_or_create_transient(session_key)
-        self._owners[chat_id] = owner
-        self._attach(owner, chat_id)
-        return session_key
-
-    async def discard(self, owner: ServerConnection, chat_id: str) -> None:
-        """Discard an owned chat; an unused chat is already discarded."""
-        current = self._owners.get(chat_id)
-        if current is None:
-            return
-        if current is not owner:
-            raise TemporaryChatLifecycleError("temporary_chat_not_owned")
-        await self._discard_owned(owner, chat_id)
-
-    async def discard_owner(self, owner: ServerConnection) -> None:
-        """Discard every temporary chat held by a disconnected owner."""
-        chat_ids = (
-            chat_id
-            for chat_id, current in self._owners.items()
-            if current is owner
-        )
-        for chat_id in tuple(chat_ids):
-            await self._discard_owned(owner, chat_id)
-
-    async def _discard_owned(self, owner: ServerConnection, chat_id: str) -> None:
-        self._owners.pop(chat_id, None)
-        self._detach(owner, chat_id)
-
-        session_key = f"websocket:{chat_id}"
-        assert self._sessions is not None
-        assert self._cancel_active_turn is not None
-        self._sessions.discard_transient(session_key)
-        try:
-            await self._cancel_active_turn(session_key)
-        finally:
-            clear_websocket_turns(chat_id)
-            self._clear_stream_buffers(chat_id)

nanobot/channels/websocket/tests/test_websocket_channel.py

@@ -51,7 +51,6 @@ from nanobot.webui.http_utils import (
 )
 from nanobot.webui.metadata import (
     WEBSOCKET_TURN_OWNER_METADATA_KEY,
-    WEBUI_MESSAGE_SOURCE_METADATA_KEY,
     WEBUI_SYSTEM_COMMAND_TURN_PREFIX,
     WEBUI_TURN_METADATA_KEY,
 )
@@ -111,7 +110,6 @@ def _basic_handler(bus: Any, **kw: Any) -> GatewayServices:
         runtime_model_name=None,
         runtime_surface=kw.get("runtime_surface", "browser"),
         runtime_capabilities_overrides=kw.get("runtime_capabilities_overrides"),
-        cancel_active_turn=kw.get("cancel_active_turn"),
     )
 
 
@@ -191,182 +189,6 @@ def isolate_webui_workspace_state(tmp_path, monkeypatch) -> None:
     wth._WEBSOCKET_TURN_OWNERS.clear()
 
 
-@pytest.mark.asyncio
-async def test_temporary_message_registers_in_memory_session(bus, tmp_path) -> None:
-    sessions = SessionManager(tmp_path)
-    cancel = AsyncMock(return_value=0)
-    channel = WebSocketChannel(
-        {"enabled": True, "allowFrom": ["*"]},
-        bus,
-        gateway=_basic_handler(
-            bus,
-            session_manager=sessions,
-            cancel_active_turn=cancel,
-        ),
-    )
-    connection = AsyncMock()
-    connection.remote_address = None
-    channel._webui_connections.add(connection)
-    chat_id = "temporary-test"
-
-    await channel._dispatch_envelope(
-        connection,
-        "client",
-        {
-            "type": "message",
-            "chat_id": chat_id,
-            "content": "hello",
-            "turn_id": "turn-1",
-            "temporary": True,
-            "webui": True,
-        },
-    )
-
-    inbound = bus.publish_inbound.await_args.args[0]
-    assert inbound.session_key == f"websocket:{chat_id}"
-    assert inbound.transient_session is True
-    assert sessions.is_transient_active(inbound.session_key) is True
-    assert sessions.get_cached(inbound.session_key).transient is True
-    assert read_transcript_lines(inbound.session_key) == []
-    assert json.loads(connection.send.await_args.args[0])["event"] == "message_accepted"
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize(
-    "envelope",
-    [
-        {"type": "attach", "chat_id": "temporary-test"},
-        {
-            "type": "set_workspace_scope",
-            "chat_id": "temporary-test",
-            "workspace_scope": {},
-        },
-        {
-            "type": "message",
-            "chat_id": "temporary-test",
-            "content": "hello",
-            "temporary": True,
-            "media": [],
-        },
-        {
-            "type": "message",
-            "chat_id": "temporary-test",
-            "content": "/history",
-            "temporary": True,
-        },
-    ],
-)
-async def test_temporary_chat_rejects_persistent_capabilities(
-    bus,
-    tmp_path,
-    envelope,
-) -> None:
-    channel = WebSocketChannel(
-        {"enabled": True, "allowFrom": ["*"]},
-        bus,
-        gateway=_basic_handler(
-            bus,
-            session_manager=SessionManager(tmp_path),
-            cancel_active_turn=AsyncMock(return_value=0),
-        ),
-    )
-    connection = AsyncMock()
-    connection.remote_address = None
-    channel._webui_connections.add(connection)
-
-    await channel._dispatch_envelope(connection, "client", envelope)
-
-    payload = json.loads(connection.send.await_args.args[0])
-    assert payload["event"] == "error"
-    bus.publish_inbound.assert_not_awaited()
-
-
-@pytest.mark.asyncio
-async def test_discard_temporary_chat_cancels_then_forgets_session(bus, tmp_path) -> None:
-    sessions = SessionManager(tmp_path)
-    cancel = AsyncMock(return_value=1)
-    channel = WebSocketChannel(
-        {"enabled": True, "allowFrom": ["*"]},
-        bus,
-        gateway=_basic_handler(
-            bus,
-            session_manager=sessions,
-            cancel_active_turn=cancel,
-        ),
-    )
-    connection = AsyncMock()
-    connection.remote_address = None
-    channel._webui_connections.add(connection)
-    chat_id = "temporary-test"
-    session_key = channel._temporary_chats.claim(connection, chat_id)
-    sessions.get_cached(session_key).add_message("user", "private")
-
-    await channel._dispatch_envelope(
-        connection,
-        "client",
-        {"type": "discard_temporary_chat", "chat_id": chat_id},
-    )
-
-    cancel.assert_awaited_once_with(session_key)
-    assert sessions.get_cached(session_key) is None
-    assert chat_id not in channel._subs
-    assert json.loads(connection.send.await_args.args[0]) == {
-        "event": "temporary_chat_discarded",
-        "chat_id": chat_id,
-    }
-
-
-@pytest.mark.asyncio
-async def test_discard_unused_temporary_chat_is_idempotent(bus, tmp_path) -> None:
-    cancel = AsyncMock(return_value=0)
-    channel = WebSocketChannel(
-        {"enabled": True, "allowFrom": ["*"]},
-        bus,
-        gateway=_basic_handler(
-            bus,
-            session_manager=SessionManager(tmp_path),
-            cancel_active_turn=cancel,
-        ),
-    )
-    connection = AsyncMock()
-
-    await channel._dispatch_envelope(
-        connection,
-        "client",
-        {"type": "discard_temporary_chat", "chat_id": "temporary-unused"},
-    )
-
-    cancel.assert_not_awaited()
-    assert json.loads(connection.send.await_args.args[0]) == {
-        "event": "temporary_chat_discarded",
-        "chat_id": "temporary-unused",
-    }
-
-
-@pytest.mark.asyncio
-async def test_disconnect_discards_owned_temporary_chat(bus, tmp_path) -> None:
-    sessions = SessionManager(tmp_path)
-    cancel = AsyncMock(return_value=1)
-    channel = WebSocketChannel(
-        {"enabled": True, "allowFrom": ["*"]},
-        bus,
-        gateway=_basic_handler(
-            bus,
-            session_manager=sessions,
-            cancel_active_turn=cancel,
-        ),
-    )
-    connection = AsyncMock()
-    chat_id = "temporary-disconnect"
-    session_key = channel._temporary_chats.claim(connection, chat_id)
-
-    await channel._cleanup_connection(connection)
-
-    cancel.assert_awaited_once_with(session_key)
-    assert sessions.get_cached(session_key) is None
-    assert chat_id not in channel._subs
-
-
 @pytest.mark.asyncio
 async def test_send_session_updated_broadcasts_to_other_webui_connections(bus) -> None:
     class Conn:
@@ -1528,35 +1350,6 @@ async def test_send_delta_emits_delta_and_stream_end() -> None:
     assert "text" not in second
 
 
-@pytest.mark.asyncio
-async def test_send_delta_preserves_webui_source_metadata() -> None:
-    bus = MagicMock()
-    channel = WebSocketChannel({"enabled": True, "allowFrom": ["*"], "streaming": True}, bus, gateway=_basic_handler(bus))
-    mock_ws = AsyncMock()
-    channel._attach(mock_ws, "chat-source-stream")
-    source = {"kind": "cron", "label": "Repo check"}
-    metadata = {WEBUI_MESSAGE_SOURCE_METADATA_KEY: source}
-
-    await channel.send_delta("chat-source-stream", "done", metadata=metadata, stream_id="sid")
-    await channel.send_delta(
-        "chat-source-stream",
-        "",
-        metadata=metadata,
-        stream_id="sid",
-        stream_end=True,
-    )
-
-    first = json.loads(mock_ws.send.call_args_list[0][0][0])
-    second = json.loads(mock_ws.send.call_args_list[1][0][0])
-    assert first["event"] == "delta"
-    assert first["source"] == source
-    assert second["event"] == "stream_end"
-    assert second["source"] == source
-    lines = read_transcript_lines("websocket:chat-source-stream")
-    assert lines[-2]["source"] == source
-    assert lines[-1]["source"] == source
-
-
 @pytest.mark.asyncio
 async def test_send_delta_marks_resuming_stream_end() -> None:
     bus = MagicMock()

nanobot/channels/weixin/runtime.py

@@ -230,30 +230,9 @@ class WeixinChannel(BaseChannel):
             self.logger.error("Failed to load Weixin account state", exc_info=True)
             return False
 
-    def _save_state(self, *, force: bool = False) -> None:
+    def _save_state(self) -> None:
         state_file = self._get_state_dir() / "account.json"
         with suppress(Exception):
-            if not force and state_file.exists():
-                persisted: object = None
-                try:
-                    persisted = json.loads(state_file.read_text())
-                except Exception:
-                    persisted = None
-                persisted_token = ""
-                if isinstance(persisted, dict):
-                    persisted_mapping = cast(dict[str, object], persisted)
-                    persisted_token = str(persisted_mapping.get("token", "") or "")
-                configured_token_is_authoritative: bool = bool(self.config.token) and (
-                    self._token == self.config.token
-                )
-                if (
-                    persisted_token
-                    and persisted_token != self._token
-                    and not configured_token_is_authoritative
-                ):
-                    # A concurrent QR login may have committed a newer token.
-                    # Never let an older runtime snapshot overwrite it.
-                    return
             data = {
                 "token": self._token,
                 "get_updates_buf": self._get_updates_buf,
@@ -510,7 +489,7 @@ class WeixinChannel(BaseChannel):
         self._token = token
         if base_url:
             self.config.base_url = base_url
-        self._save_state(force=True)
+        self._save_state()
 
     async def connect_close_client(self) -> None:
         self._running = False
@@ -634,8 +613,6 @@ class WeixinChannel(BaseChannel):
         remaining = self._session_pause_remaining_s()
         if remaining > 0:
             await asyncio.sleep(remaining)
-            if not self.config.token:
-                self._load_state()
             return
 
         body: dict[str, Any] = {

nanobot/channels/weixin/tests/test_weixin_channel.py

@@ -98,80 +98,6 @@ def test_save_and_load_state_persists_context_tokens(tmp_path) -> None:
     assert restored._context_tokens == {"wx-user": "ctx-1"}
 
 
-def test_save_state_preserves_token_committed_by_another_instance(tmp_path) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(enabled=True, allow_from=["*"], state_dir=str(tmp_path)),
-        MessageBus(),
-    )
-    channel._token = "old-token"
-    channel._save_state()
-
-    replacement = {
-        "token": "new-token",
-        "base_url": "https://new.example",
-        "get_updates_buf": "",
-        "context_tokens": {},
-        "typing_tickets": {},
-    }
-    (tmp_path / "account.json").write_text(json.dumps(replacement), encoding="utf-8")
-
-    channel._get_updates_buf = "stale-cursor"
-    channel._save_state()
-
-    assert json.loads((tmp_path / "account.json").read_text()) == replacement
-
-
-def test_save_state_force_overwrites_replaced_token(tmp_path) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(enabled=True, allow_from=["*"], state_dir=str(tmp_path)),
-        MessageBus(),
-    )
-    (tmp_path / "account.json").write_text(json.dumps({"token": "old-token"}), encoding="utf-8")
-
-    channel.connect_commit_account(token="new-token", base_url="https://new.example")
-
-    saved = json.loads((tmp_path / "account.json").read_text())
-    assert saved["token"] == "new-token"
-    assert saved["base_url"] == "https://new.example"
-
-
-def test_save_state_persists_explicit_config_token_over_stale_state(tmp_path) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(
-            enabled=True,
-            allow_from=["*"],
-            token="configured-token",
-            state_dir=str(tmp_path),
-        ),
-        MessageBus(),
-    )
-    channel._token = "configured-token"
-    channel._get_updates_buf = "current-cursor"
-    (tmp_path / "account.json").write_text(
-        json.dumps({"token": "stale-token", "get_updates_buf": "stale-cursor"}),
-        encoding="utf-8",
-    )
-
-    channel._save_state()
-
-    saved = json.loads((tmp_path / "account.json").read_text())
-    assert saved["token"] == "configured-token"
-    assert saved["get_updates_buf"] == "current-cursor"
-
-
-def test_save_state_with_empty_runtime_token_preserves_persisted_account(tmp_path) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(enabled=True, allow_from=["*"], state_dir=str(tmp_path)),
-        MessageBus(),
-    )
-    persisted = {"token": "persisted-token", "get_updates_buf": "persisted-cursor"}
-    (tmp_path / "account.json").write_text(json.dumps(persisted), encoding="utf-8")
-
-    channel._save_state()
-
-    assert json.loads((tmp_path / "account.json").read_text()) == persisted
-
-
 @pytest.mark.asyncio
 async def test_process_message_deduplicates_inbound_ids() -> None:
     channel, bus = _make_channel()
@@ -536,56 +462,6 @@ async def test_poll_once_pauses_session_on_expired_errcode() -> None:
     assert channel._session_pause_remaining_s() > 0
 
 
-@pytest.mark.asyncio
-async def test_poll_once_reloads_refreshed_state_after_session_pause(
-    tmp_path, monkeypatch: pytest.MonkeyPatch
-) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(enabled=True, allow_from=["*"], state_dir=str(tmp_path)),
-        MessageBus(),
-    )
-    channel._token = "old-token"
-    channel._save_state()
-    (tmp_path / "account.json").write_text(
-        json.dumps({"token": "new-token", "base_url": "https://new.example"}),
-        encoding="utf-8",
-    )
-    channel._session_pause_until = time.time() + 10
-    monkeypatch.setattr(weixin_mod.asyncio, "sleep", AsyncMock())
-
-    await channel._poll_once()
-
-    assert channel._token == "new-token"
-    assert channel.config.base_url == "https://new.example"
-
-
-@pytest.mark.asyncio
-async def test_poll_once_keeps_explicit_token_after_session_pause(
-    tmp_path, monkeypatch: pytest.MonkeyPatch
-) -> None:
-    channel = WeixinChannel(
-        WeixinConfig(
-            enabled=True,
-            allow_from=["*"],
-            token="configured-token",
-            state_dir=str(tmp_path),
-        ),
-        MessageBus(),
-    )
-    channel._token = "configured-token"
-    (tmp_path / "account.json").write_text(
-        json.dumps({"token": "stale-token", "base_url": "https://stale.example"}),
-        encoding="utf-8",
-    )
-    channel._session_pause_until = time.time() + 10
-    monkeypatch.setattr(weixin_mod.asyncio, "sleep", AsyncMock())
-
-    await channel._poll_once()
-
-    assert channel._token == "configured-token"
-    assert channel.config.base_url == "https://ilinkai.weixin.qq.com"
-
-
 @pytest.mark.asyncio
 async def test_qr_login_refreshes_expired_qr_and_then_succeeds(
     no_qr_poll_delay,

nanobot/cli/gateway.py

@@ -1,5 +1,7 @@
 """Typer commands for foreground and background gateway control."""
 
+# pyright: reportUnusedFunction=false
+
 from __future__ import annotations
 
 import subprocess
@@ -133,9 +135,8 @@ def create_gateway_app(
             console.print()
             console.print(result.content)
 
-    # Typer consumes these callbacks through decorator registration.
     @gateway_app.callback(invoke_without_command=True)
-    def gateway(  # pyright: ignore[reportUnusedFunction]
+    def gateway(
         ctx: typer.Context,
         port: int | None = typer.Option(None, "--port", "-p", help="Gateway port"),
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
@@ -190,7 +191,7 @@ def create_gateway_app(
             )
 
     @gateway_app.command("status")
-    def gateway_status(  # pyright: ignore[reportUnusedFunction]
+    def gateway_status(
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
         config: str | None = typer.Option(None, "--config", "-c", help="Path to config file"),
     ) -> None:
@@ -198,7 +199,7 @@ def create_gateway_app(
         print_status(runtime_for_instance(workspace=workspace, config=config).status())
 
     @gateway_app.command("logs")
-    def gateway_logs(  # pyright: ignore[reportUnusedFunction]
+    def gateway_logs(
         tail: int = typer.Option(200, "--tail", help="Number of recent lines to show"),
         follow: bool = typer.Option(True, "--follow/--no-follow", help="Follow new log output"),
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
@@ -216,7 +217,7 @@ def create_gateway_app(
             console.print(line)
 
     @gateway_app.command("stop")
-    def gateway_stop(  # pyright: ignore[reportUnusedFunction]
+    def gateway_stop(
         timeout: int = typer.Option(20, "--timeout", help="Stop timeout in seconds"),
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
         config: str | None = typer.Option(None, "--config", "-c", help="Path to config file"),
@@ -232,7 +233,7 @@ def create_gateway_app(
             raise typer.Exit(1)
 
     @gateway_app.command("restart")
-    def gateway_restart(  # pyright: ignore[reportUnusedFunction]
+    def gateway_restart(
         port: int | None = typer.Option(None, "--port", "-p", help="Gateway port"),
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
         verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
@@ -265,7 +266,7 @@ def create_gateway_app(
         raise typer.Exit(1)
 
     @gateway_app.command("install-service")
-    def gateway_install_service(  # pyright: ignore[reportUnusedFunction]
+    def gateway_install_service(
         port: int | None = typer.Option(None, "--port", "-p", help="Gateway port"),
         workspace: str | None = typer.Option(None, "--workspace", "-w", help="Workspace directory"),
         verbose: bool = typer.Option(False, "--verbose", "-v", help="Verbose output"),
@@ -301,7 +302,7 @@ def create_gateway_app(
         raise typer.Exit(1)
 
     @gateway_app.command("uninstall-service")
-    def gateway_uninstall_service(  # pyright: ignore[reportUnusedFunction]
+    def gateway_uninstall_service(
         name: str = typer.Option("nanobot-gateway", "--name", help="Service name"),
         manager: ServiceManagerKind = typer.Option("auto", "--manager", help="auto, systemd, or launchd"),
         dry_run: bool = typer.Option(False, "--dry-run", help="Print actions without uninstalling"),

nanobot/cli/gateway_runtime.py

@@ -581,7 +581,6 @@ def _run_gateway(
         webui_runtime_model_name=_webui_runtime_model_name,
         webui_cron_pending_job_ids=agent.pending_cron_job_ids_for_session,
         webui_local_trigger_pending_ids=agent.pending_local_trigger_ids_for_session,
-        webui_cancel_active_turn=getattr(agent, "cancel_active_turn", None),
         webui_static_dist=webui_static_dist,
         webui_runtime_surface=webui_runtime_surface,
         webui_runtime_capabilities=webui_runtime_capabilities,

nanobot/cli/onboard.py

@@ -1,5 +1,7 @@
 """Interactive onboarding questionnaire for nanobot."""
 
+# pyright: reportMissingTypeStubs=false, reportUnusedFunction=false
+
 import asyncio
 import json
 import types
@@ -204,36 +206,35 @@ def _select_with_back(
     # Key bindings
     bindings = KeyBindings()
 
-    # KeyBindings consumes these handlers through decorator registration.
     @bindings.add(Keys.Up)
-    def _up(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _up(event: KeyPressEvent) -> None:
         nonlocal selected_index
         selected_index = (selected_index - 1) % len(choices)
         event.app.invalidate()
 
     @bindings.add(Keys.Down)
-    def _down(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _down(event: KeyPressEvent) -> None:
         nonlocal selected_index
         selected_index = (selected_index + 1) % len(choices)
         event.app.invalidate()
 
     @bindings.add(Keys.Enter)
-    def _enter(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _enter(event: KeyPressEvent) -> None:
         state["result"] = choices[selected_index]
         event.app.exit()
 
     @bindings.add("escape")
-    def _escape(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _escape(event: KeyPressEvent) -> None:
         state["result"] = _BACK_PRESSED
         event.app.exit()
 
     @bindings.add(Keys.Left)
-    def _left(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _left(event: KeyPressEvent) -> None:
         state["result"] = _BACK_PRESSED
         event.app.exit()
 
     @bindings.add(Keys.ControlC)
-    def _ctrl_c(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _ctrl_c(event: KeyPressEvent) -> None:
         state["result"] = None
         event.app.exit()
 
@@ -531,9 +532,8 @@ def _input_back_key_bindings() -> KeyBindings:
     """Return key bindings that make Escape behave like a local back action."""
     bindings = KeyBindings()
 
-    # KeyBindings consumes this handler through decorator registration.
     @bindings.add("escape")
-    def _escape(event: KeyPressEvent) -> None:  # pyright: ignore[reportUnusedFunction]
+    def _escape(event: KeyPressEvent) -> None:
         event.app.exit(result=_BACK_PRESSED)
 
     return bindings
@@ -1668,11 +1668,7 @@ def _quick_start_oauth_login(config: Config, provider_name: str) -> bool:
         return False
 
     try:
-        # oauth-cli-kit does not publish type information.
-        from oauth_cli_kit import (  # pyright: ignore[reportMissingTypeStubs]
-            get_token,
-            login_oauth_interactive,
-        )
+        from oauth_cli_kit import get_token, login_oauth_interactive
     except ImportError:
         console.print("[red]oauth_cli_kit not installed. Run: pip install oauth-cli-kit[/red]")
         return False
@@ -1713,8 +1709,7 @@ def _quick_start_oauth_is_authenticated(config: Config, provider_name: str) -> b
     if provider_name != "openai_codex":
         return False
     try:
-        # oauth-cli-kit does not publish type information.
-        from oauth_cli_kit import get_token  # pyright: ignore[reportMissingTypeStubs]
+        from oauth_cli_kit import get_token
 
         proxy = _quick_start_codex_proxy(config)
         token = get_token(proxy=proxy)

nanobot/command/builtin.py

@@ -203,7 +203,16 @@ async def cmd_stop(ctx: CommandContext) -> OutboundMessage:
     """Cancel all active tasks and subagents for the session."""
     loop = ctx.loop
     msg = ctx.msg
-    total = await loop.cancel_active_turn(ctx.key)
+    total = await loop._cancel_active_tasks(ctx.key)  # pyright: ignore[reportPrivateUsage]
+    # Also drain pending queue to prevent mid-turn injection deadlock
+    pending = loop._pending_queues.pop(ctx.key, None)  # pyright: ignore[reportPrivateUsage]
+    if pending is not None:
+        while not pending.empty():
+            try:
+                pending.get_nowait()
+                total += 1
+            except Exception:
+                break
     content = f"Stopped {total} task(s)." if total else "No active task to stop."
     return OutboundMessage(
         channel=msg.channel, chat_id=msg.chat_id, content=content,
@@ -292,7 +301,7 @@ async def cmd_status(ctx: CommandContext) -> OutboundMessage:
 async def cmd_new(ctx: CommandContext) -> OutboundMessage:
     """Stop active task and start a fresh session."""
     loop = ctx.loop
-    await loop.cancel_active_turn(ctx.key)
+    await loop._cancel_active_tasks(ctx.key)  # pyright: ignore[reportPrivateUsage]
     session = ctx.session or loop.sessions.get_or_create(ctx.key)
     snapshot = session.messages[session.last_consolidated:]
     runtime = None

nanobot/config/schema.py

@@ -504,7 +504,6 @@ class Config(BaseSettings):
         model_normalized = model_lower.replace("-", "_")
         model_prefix = model_lower.split("/", 1)[0] if "/" in model_lower else ""
         normalized_prefix = model_prefix.replace("-", "_")
-        prefixed_provider = find_by_name(model_prefix) if model_prefix else None
 
         def _kw_matches(kw: str) -> bool:
             kw = kw.lower()
@@ -534,22 +533,6 @@ class Config(BaseSettings):
                 continue
             p = getattr(self.providers, spec.name, None)
             if p and any(_kw_matches(kw) for kw in spec.keywords):
-                # Local providers (Ollama, vLLM, …) keep model-family keywords
-                # like "nemotron" or "llama" to enable bare-model auto-routing,
-                # but those keywords collide with cloud-hosted variants of the
-                # same family (e.g. `nvidia/nemotron-...` via OpenRouter). Only
-                # honor a local keyword match when the user has actually
-                # configured that local endpoint via `api_base` — mirrors the
-                # gate already used by the local-fallback loop below.
-                if spec.is_local:
-                    # A qualified model belongs to its explicit provider or a
-                    # gateway fallback, never to a different local provider
-                    # whose model-family keyword happens to match.
-                    foreign_prefix = bool(
-                        prefixed_provider is not None and prefixed_provider.name != spec.name
-                    )
-                    if not p.api_base or foreign_prefix:
-                        continue
                 if spec.is_oauth or spec.is_local or spec.is_direct or p.api_key:
                     return p, spec.name
 
@@ -558,17 +541,16 @@ class Config(BaseSettings):
         # Prefer providers whose detect_by_base_keyword matches the configured api_base
         # (e.g. Ollama's "11434" in "http://localhost:11434") over plain registry order.
         local_fallback: tuple[ProviderConfig, str] | None = None
-        if prefixed_provider is None:
-            for spec in PROVIDERS:
-                if not spec.is_local:
-                    continue
-                p = getattr(self.providers, spec.name, None)
-                if not (p and p.api_base):
-                    continue
-                if spec.detect_by_base_keyword and spec.detect_by_base_keyword in p.api_base:
-                    return p, spec.name
-                if local_fallback is None:
-                    local_fallback = (p, spec.name)
+        for spec in PROVIDERS:
+            if not spec.is_local:
+                continue
+            p = getattr(self.providers, spec.name, None)
+            if not (p and p.api_base):
+                continue
+            if spec.detect_by_base_keyword and spec.detect_by_base_keyword in p.api_base:
+                return p, spec.name
+            if local_fallback is None:
+                local_fallback = (p, spec.name)
         if local_fallback:
             return local_fallback
 

nanobot/cron/service.py

@@ -163,13 +163,9 @@ class CronService:
         self._store: CronStore | None = None
         self._timer_task: asyncio.Task[None] | None = None
         self._running = False
-        self._active_executions = 0
+        self._timer_active = False
         self.max_sleep_ms = max_sleep_ms
 
-    def _should_persist_store(self) -> bool:
-        """Return whether this instance currently owns the live store."""
-        return self._running or self._active_executions > 0
-
     def _is_unbound_agent_job(self, job: CronJob) -> bool:
         return job.payload.kind == "agent_turn" and not is_bound_cron_job(job)
 
@@ -282,24 +278,23 @@ class CronService:
                         logger.exception("load action line error")
                         continue
             self._store.jobs = list(jobs_map.values())  # pyright: ignore[reportOptionalMemberAccess]
-            if self._should_persist_store() and changed:
+            if self._running and changed:
                 self._action_path.write_text("", encoding="utf-8")
                 self._save_store()
         return
 
-    def _load_store(self, *, reload_during_execution: bool = False) -> CronStore | None:
+    def _load_store(self) -> CronStore | None:
         """Load jobs from disk. Reloads automatically if file was modified externally.
         - Reload every time because it needs to merge operations on the jobs object from other instances.
-        - During job execution, return the existing store to prevent concurrent
+        - During _on_timer execution, return the existing store to prevent concurrent
           _load_store calls (e.g. from list_jobs polling) from replacing it mid-execution.
-          The first execution explicitly reloads once when it takes ownership.
         - When the on-disk store exists but is unreadable: keep using the
           previous in-memory ``self._store`` if we already have one (so a
           transient corruption does not drop live jobs); only the very first
           load (during ``start``) can return ``None`` to signal an unrecoverable
           state to the caller.
         """
-        if self._active_executions > 0 and self._store and not reload_during_execution:
+        if self._timer_active and self._store:
             return self._store
         loaded = self._load_jobs()
         if loaded is None:
@@ -312,12 +307,12 @@ class CronService:
         jobs, version = loaded
         self._store = CronStore(version=version, jobs=jobs)
         self._merge_action()
-        if self._enforce_store_agent_bindings() and self._should_persist_store():
+        if self._enforce_store_agent_bindings() and self._running:
             self._save_store()
 
         return self._store
 
-    def _require_store(self, *, reload_during_execution: bool = False) -> CronStore:
+    def _require_store(self) -> CronStore:
         """Return a usable store or raise a clear error.
 
         ``_load_store`` deliberately returns ``None`` when the first load sees
@@ -327,7 +322,7 @@ class CronService:
         ``AttributeError`` and, more importantly, prevents follow-up saves from
         treating a corrupt store as an empty one.
         """
-        store = self._load_store(reload_during_execution=reload_during_execution)
+        store = self._load_store()
         if store is None:
             raise RuntimeError(
                 f"cron store at {self.store_path} could not be loaded and was preserved "
@@ -509,20 +504,19 @@ class CronService:
 
     async def _on_timer(self) -> None:
         """Handle timer tick - run due jobs."""
-        reload_store = self._active_executions == 0
-        self._active_executions += 1
-        try:
-            store = self._load_store(reload_during_execution=reload_store)
-            # If a hot reload found a corrupt store on disk, ``self._store`` may
-            # still hold the previous, known-good in-memory snapshot.  Keep using
-            # it rather than crashing the timer or wiping live jobs.
-            if store is None:
-                self._arm_timer()
-                return
+        self._load_store()
+        # If a hot reload found a corrupt store on disk, ``self._store`` may
+        # still hold the previous, known-good in-memory snapshot.  Keep using
+        # it rather than crashing the timer or wiping live jobs.
+        if not self._store:
+            self._arm_timer()
+            return
 
+        self._timer_active = True
+        try:
             now = _now_ms()
             due_jobs = [
-                j for j in store.jobs
+                j for j in self._store.jobs
                 if j.enabled and j.state.next_run_at_ms and now >= j.state.next_run_at_ms
             ]
 
@@ -531,7 +525,7 @@ class CronService:
 
             self._save_store()
         finally:
-            self._active_executions -= 1
+            self._timer_active = False
         self._arm_timer()
 
     async def _execute_job(self, job: CronJob) -> None:
@@ -663,7 +657,7 @@ class CronService:
         )
         _normalize_agent_turn_job(job)
         self._enforce_agent_binding(job)
-        if self._should_persist_store():
+        if self._running:
             store = self._require_store()
             store.jobs.append(job)
             self._save_store()
@@ -703,7 +697,7 @@ class CronService:
         removed = len(store.jobs) < before
 
         if removed:
-            if self._should_persist_store():
+            if self._running:
                 self._save_store()
                 self._arm_timer()
             else:
@@ -725,7 +719,7 @@ class CronService:
                     job.state.next_run_at_ms = _compute_next_run(job.schedule, _now_ms())
                 else:
                     job.state.next_run_at_ms = None
-                if self._should_persist_store():
+                if self._running:
                     self._save_store()
                     self._arm_timer()
                 else:
@@ -781,7 +775,7 @@ class CronService:
         else:
             job.state.next_run_at_ms = None
 
-        if self._should_persist_store():
+        if self._running:
             self._save_store()
             self._arm_timer()
         else:
@@ -792,10 +786,10 @@ class CronService:
 
     async def run_job(self, job_id: str, force: bool = False) -> bool:
         """Manually run a job without disturbing the service's running state."""
-        reload_store = self._active_executions == 0
-        self._active_executions += 1
+        was_running = self._running
+        self._running = True
         try:
-            store = self._require_store(reload_during_execution=reload_store)
+            store = self._require_store()
             for job in store.jobs:
                 if job.id == job_id:
                     if self._is_unbound_agent_job(job):
@@ -809,8 +803,8 @@ class CronService:
                     return True
             return False
         finally:
-            self._active_executions -= 1
-            if self._running and self._active_executions == 0:
+            self._running = was_running
+            if was_running:
                 self._arm_timer()
 
     def get_job(self, job_id: str) -> CronJob | None:

nanobot/pairing/store.py

@@ -40,15 +40,9 @@ def _load() -> dict[str, Any]:
             data = json.load(f)
     except FileNotFoundError:
         return {"approved": {}, "pending": {}}
-    except json.JSONDecodeError:
+    except (json.JSONDecodeError, OSError):
         logger.warning("Corrupted pairing store, resetting")
         return {"approved": {}, "pending": {}}
-    except OSError:
-        # A transiently locked or busy file is not corruption. Propagate so
-        # mutating callers fail loudly instead of persisting an empty view
-        # that would erase every approved sender.
-        logger.warning("Pairing store temporarily unreadable: {}", path)
-        raise
     if not isinstance(data, dict):
         logger.warning("Corrupted pairing store, resetting")
         return {"approved": {}, "pending": {}}
@@ -177,11 +171,7 @@ def deny_code(code: str) -> bool:
 def is_approved(channel: str, sender_id: str) -> bool:
     """Check whether *sender_id* has been approved on *channel*."""
     with _LOCK:
-        try:
-            data = _load()
-        except OSError:
-            # Fail closed for this check; the store itself stays untouched.
-            return False
+        data = _load()
         approved: dict[str, set[str]] = data.get("approved", {})
         return str(sender_id) in approved.get(channel, set())
 
@@ -189,10 +179,7 @@ def is_approved(channel: str, sender_id: str) -> bool:
 def list_pending() -> list[dict[str, Any]]:
     """Return all non-expired pending pairing requests."""
     with _LOCK:
-        try:
-            data = _load()
-        except OSError:
-            return []
+        data = _load()
         _gc_pending(data)
         return [
             {"code": code, **info}
@@ -270,10 +257,7 @@ def clear_channel(channel: str) -> dict[str, int]:
 def get_approved(channel: str) -> list[str]:
     """Return all approved sender IDs for *channel*."""
     with _LOCK:
-        try:
-            data = _load()
-        except OSError:
-            return []
+        data = _load()
         return sorted(data.get("approved", {}).get(channel, set()))
 
 
@@ -299,15 +283,6 @@ def handle_pairing_command(channel: str, subcommand_text: str) -> str:
     This is a pure function (no side effects other than store mutations)
     so it can be used from both the CLI and the agent CommandRouter.
     """
-    try:
-        return _handle_pairing_subcommand(channel, subcommand_text)
-    except OSError:
-        # Mutations fail loudly on a transient I/O error instead of lying
-        # ("invalid code") or silently rewriting the store from an empty view.
-        return "The pairing store is temporarily unavailable. Please try again."
-
-
-def _handle_pairing_subcommand(channel: str, subcommand_text: str) -> str:
     parts = subcommand_text.split()
     sub = parts[0] if parts else "list"
     arg = parts[1] if len(parts) > 1 else None

nanobot/providers/azure_openai_provider.py

@@ -23,26 +23,14 @@ import uuid
 from collections.abc import Awaitable, Callable
 from typing import Any, cast
 
-from loguru import logger
 from openai import AsyncOpenAI
 
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-)
+from nanobot.providers.base import LLMProvider, LLMResponse
 from nanobot.providers.openai_responses import (
-    ResponsesStreamCapture,
-    build_responses_state,
     consume_sdk_stream,
+    convert_messages,
     convert_tools,
-    is_compaction_compatibility_error,
-    is_replayable_finish_reason,
     parse_response_output,
-    prepare_responses_input,
-    resolve_compact_threshold,
-    responses_state_matches,
 )
 
 _AZURE_OPENAI_SCOPE = "https://cognitiveservices.azure.com/.default"
@@ -109,7 +97,6 @@ class AzureOpenAIProvider(LLMProvider):
     ):
         super().__init__(api_key, api_base)
         self.default_model = default_model
-        self._native_compaction_available = True
 
         if not api_base:
             raise ValueError("Azure OpenAI api_base is required")
@@ -155,25 +142,6 @@ class AzureOpenAIProvider(LLMProvider):
         name = deployment_name.lower()
         return not any(token in name for token in ("gpt-5", "o1", "o3", "o4"))
 
-    def _responses_state_provider(self) -> str:
-        return f"azure_openai:{str(self.api_base).rstrip('/')}"
-
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        return responses_state_matches(
-            state,
-            provider=self._responses_state_provider(),
-            model=model or self.default_model,
-        )
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        """Azure's native Responses endpoint accepts context management."""
-        _ = model
-        return self._native_compaction_available
-
     def _build_body(
         self,
         messages: list[dict[str, Any]],
@@ -183,26 +151,10 @@ class AzureOpenAIProvider(LLMProvider):
         temperature: float,
         reasoning_effort: str | None,
         tool_choice: str | dict[str, Any] | None,
-        provider_context: ProviderCallContext | None = None,
     ) -> dict[str, Any]:
         """Build the Responses API request body from Chat-Completions-style args."""
         deployment = model or self.default_model
-        sanitized_messages = self._sanitize_empty_content(messages)
-        sanitized_state = (
-            provider_context.conversation_state
-            if provider_context is not None
-            else None
-        )
-        if sanitized_state is not None:
-            sanitized_state = sanitized_state.with_pending_messages(
-                self._sanitize_empty_content(sanitized_state.pending_messages)
-            )
-        instructions, input_items, replayed = prepare_responses_input(
-            sanitized_messages,
-            state=sanitized_state,
-            provider=self._responses_state_provider(),
-            model=deployment,
-        )
+        instructions, input_items = convert_messages(self._sanitize_empty_content(messages))
 
         body: dict[str, Any] = {
             "model": deployment,
@@ -212,29 +164,13 @@ class AzureOpenAIProvider(LLMProvider):
             "store": False,
             "stream": False,
         }
-        compact_threshold = resolve_compact_threshold(
-            (
-                provider_context.context_window_tokens
-                if provider_context is not None
-                else None
-            ),
-            max_tokens,
-        )
-        if self.supports_native_compaction(deployment) and compact_threshold is not None:
-            body["context_management"] = [{
-                "type": "compaction",
-                "compact_threshold": compact_threshold,
-            }]
 
         if self._supports_temperature(deployment, reasoning_effort):
             body["temperature"] = temperature
 
-        if not self._supports_temperature(deployment, reasoning_effort):
-            body["include"] = ["reasoning.encrypted_content"]
         if reasoning_effort and reasoning_effort.lower() != "none":
             body["reasoning"] = {"effort": reasoning_effort}
-        if replayed and "gpt-5.6" in deployment.lower():
-            body.setdefault("reasoning", {})["context"] = "all_turns"
+            body["include"] = ["reasoning.encrypted_content"]
 
         if tools:
             body["tools"] = convert_tools(tools)
@@ -242,97 +178,21 @@ class AzureOpenAIProvider(LLMProvider):
 
         return body
 
-    async def _create_response_with_compaction_fallback(
-        self,
-        body: dict[str, Any],
-    ) -> Any:
-        """Retry once without server compaction when Azure rejects the option."""
-        try:
-            return cast(Any, await self._client.responses.create(**body))
-        except Exception as exc:
-            if (
-                "context_management" not in body
-                or not is_compaction_compatibility_error(exc)
-            ):
-                raise
-            self._native_compaction_available = False
-            body.pop("context_management", None)
-            logger.warning(
-                "Azure Responses server compaction unsupported; disabled for this provider "
-                "instance (status={})",
-                getattr(exc, "status_code", None),
-            )
-            return cast(Any, await self._client.responses.create(**body))
-
     @staticmethod
     def _handle_error(e: Exception) -> LLMResponse:
         response = getattr(e, "response", None)
         body = getattr(e, "body", None) or getattr(response, "text", None)
         body_text = str(body).strip() if body is not None else ""
         msg = f"Error: {body_text[:500]}" if body_text else f"Error calling Azure OpenAI: {e}"
-        headers = getattr(response, "headers", None)
-        retry_after = LLMProvider._extract_retry_after_from_headers(headers)
+        retry_after = LLMProvider._extract_retry_after_from_headers(getattr(response, "headers", None))
         if retry_after is None:
             retry_after = LLMProvider._extract_retry_after(msg)
-        status_code = getattr(e, "status_code", None)
-        if status_code is None and response is not None:
-            status_code = getattr(response, "status_code", None)
-        error_type, error_code = LLMProvider._extract_error_type_code(body)
-        should_retry: bool | None = None
-        if headers is not None:
-            raw_should_retry = headers.get("x-should-retry")
-            if isinstance(raw_should_retry, str):
-                lowered = raw_should_retry.strip().lower()
-                if lowered == "true":
-                    should_retry = True
-                elif lowered == "false":
-                    should_retry = False
-        error_name = type(e).__name__.lower()
-        error_kind = (
-            "timeout"
-            if "timeout" in error_name
-            else "connection"
-            if "connection" in error_name
-            else None
-        )
-        return LLMResponse(
-            content=msg,
-            finish_reason="error",
-            retry_after=retry_after,
-            error_status_code=int(status_code) if status_code is not None else None,
-            error_kind=error_kind,
-            error_type=error_type,
-            error_code=error_code,
-            error_retry_after_s=retry_after,
-            error_should_retry=should_retry,
-        )
+        return LLMResponse(content=msg, finish_reason="error", retry_after=retry_after)
 
     # ------------------------------------------------------------------
     # Public API
     # ------------------------------------------------------------------
 
-    async def chat_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat(
-            **kwargs,
-            provider_context=provider_context,
-        )
-
-    async def chat_stream_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat_stream(
-            **kwargs,
-            provider_context=provider_context,
-        )
-
     async def chat(
         self,
         messages: list[dict[str, Any]],
@@ -342,21 +202,14 @@ class AzureOpenAIProvider(LLMProvider):
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
         tool_choice: str | dict[str, Any] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         body = self._build_body(
             messages, tools, model, max_tokens, temperature,
             reasoning_effort, tool_choice,
-            provider_context,
         )
         try:
-            response = await self._create_response_with_compaction_fallback(body)
-            return parse_response_output(
-                response,
-                state_provider=self._responses_state_provider(),
-                state_model=str(body["model"]),
-                state_input_items=cast(list[dict[str, Any]], body["input"]),
-            )
+            response = cast(Any, await self._client.responses.create(**body))
+            return parse_response_output(response)
         except Exception as e:
             return self._handle_error(e)
 
@@ -372,43 +225,26 @@ class AzureOpenAIProvider(LLMProvider):
         on_content_delta: Callable[[str], Awaitable[None]] | None = None,
         on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
         on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         _ = on_thinking_delta
         body = self._build_body(
             messages, tools, model, max_tokens, temperature,
             reasoning_effort, tool_choice,
-            provider_context,
         )
         body["stream"] = True
 
         try:
-            stream = await self._create_response_with_compaction_fallback(body)
-            capture = ResponsesStreamCapture()
+            stream = cast(Any, await self._client.responses.create(**body))
             content, tool_calls, finish_reason, usage, reasoning_content = (
-                await consume_sdk_stream(
-                    stream,
-                    on_content_delta,
-                    on_tool_call_delta,
-                    capture=capture,
-                )
+                await consume_sdk_stream(stream, on_content_delta, on_tool_call_delta)
             )
-            result = LLMResponse(
+            return LLMResponse(
                 content=content or None,
                 tool_calls=tool_calls,
                 finish_reason=finish_reason,
                 usage=usage,
                 reasoning_content=reasoning_content,
             )
-            if capture.completed and is_replayable_finish_reason(finish_reason):
-                result.provider_state = build_responses_state(
-                    provider=self._responses_state_provider(),
-                    model=str(body["model"]),
-                    input_items=cast(list[dict[str, Any]], body["input"]),
-                    output_items=capture.output_items,
-                    usage=usage,
-                )
-            return result
         except Exception as e:
             return self._handle_error(e)
 

nanobot/providers/base.py

@@ -1,7 +1,5 @@
 """Base LLM provider interface."""
 
-from __future__ import annotations
-
 import asyncio
 import json
 import os
@@ -9,7 +7,6 @@ import re
 from abc import ABC, abstractmethod
 from collections.abc import Awaitable, Callable
 from contextlib import suppress
-from copy import deepcopy
 from dataclasses import dataclass, field
 from datetime import datetime, timezone
 from email.utils import parsedate_to_datetime
@@ -153,104 +150,6 @@ def tool_arguments_json_for_replay(arguments: Any) -> str:
     return json.dumps(tool_arguments_object_for_replay(arguments), ensure_ascii=False)
 
 
-@dataclass
-class ProviderConversationState:
-    """Opaque provider-owned continuation state.
-
-    ``payload`` may contain encrypted reasoning or other provider-private
-    protocol items. Keep it out of normal logs and public chat history.
-    ``pending_messages`` are Chat-style messages produced after the most
-    recent provider response and are materialized by the owning provider on
-    the next request.
-    """
-
-    kind: str
-    provider: str
-    model: str
-    version: int
-    payload: dict[str, Any] = field(default_factory=dict, repr=False)
-    pending_messages: list[dict[str, Any]] = field(default_factory=list, repr=False)
-
-    def with_pending_messages(
-        self,
-        messages: list[dict[str, Any]],
-    ) -> ProviderConversationState:
-        """Return a state copy with an isolated pending-message list."""
-        return ProviderConversationState(
-            kind=self.kind,
-            provider=self.provider,
-            model=self.model,
-            version=self.version,
-            payload=self.payload,
-            pending_messages=deepcopy(messages),
-        )
-
-    def to_private_record(self) -> dict[str, Any]:
-        """Serialize for the private session sidecar, never for public history."""
-        return {
-            "kind": self.kind,
-            "provider": self.provider,
-            "model": self.model,
-            "version": self.version,
-            "payload": deepcopy(self.payload),
-            "pending_messages": deepcopy(self.pending_messages),
-        }
-
-    @classmethod
-    def from_private_record(
-        cls,
-        value: object,
-    ) -> ProviderConversationState | None:
-        """Validate and deserialize a private session-sidecar value."""
-        if not isinstance(value, dict):
-            return None
-        data = cast(dict[str, Any], value)
-        kind = data.get("kind")
-        provider = data.get("provider")
-        model = data.get("model")
-        version = data.get("version")
-        payload = data.get("payload")
-        pending = data.get("pending_messages", [])
-        if (
-            not isinstance(kind, str)
-            or not kind
-            or not isinstance(provider, str)
-            or not provider
-            or not isinstance(model, str)
-            or not model
-            or isinstance(version, bool)
-            or not isinstance(version, int)
-            or not isinstance(payload, dict)
-            or not isinstance(pending, list)
-            or any(
-                not isinstance(message, dict)
-                for message in cast(list[object], pending)
-            )
-        ):
-            return None
-        return cls(
-            kind=kind,
-            provider=provider,
-            model=model,
-            version=version,
-            payload=deepcopy(cast(dict[str, Any], payload)),
-            pending_messages=deepcopy(cast(list[dict[str, Any]], pending)),
-        )
-
-
-@dataclass(frozen=True)
-class ProviderCallContext:
-    """Optional provider-owned continuation data for one model request.
-
-    The regular ``chat`` contract stays provider-agnostic. Responses-capable
-    providers consume this context through the opt-in ``chat_with_context``
-    hooks, while every other provider inherits the context-free delegation.
-    """
-
-    conversation_state: ProviderConversationState | None = field(default=None, repr=False)
-    context_window_tokens: int | None = None
-
-
 @dataclass
 class LLMResponse:
     """Response from an LLM provider."""
@@ -261,10 +160,6 @@ class LLMResponse:
     retry_after: float | None = None  # Provider supplied retry wait in seconds.
     reasoning_content: str | None = None  # Kimi, DeepSeek-R1, MiMo etc.
     thinking_blocks: list[dict[str, Any]] | None = None  # Anthropic extended thinking
-    provider_state: ProviderConversationState | None = field(default=None, repr=False)
-    # Routing wrappers may preserve or discard an incoming provider-owned
-    # continuation independently of the final fallback error's retry policy.
-    preserve_provider_state_on_error: bool | None = field(default=None, repr=False)
     # Structured error metadata used by retry policy when finish_reason == "error".
     error_status_code: int | None = None
     error_kind: str | None = None  # e.g. "timeout", "connection"
@@ -379,18 +274,6 @@ class LLMProvider(ABC):
         self.api_base = api_base
         self.generation: GenerationSettings = GenerationSettings()
 
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        """Whether this provider can safely consume an opaque saved state."""
-        return False
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        """Whether requests may include provider-native context compaction."""
-        return False
-
     @staticmethod
     def _sanitize_empty_content(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
         """Sanitize message content: fix empty blocks, strip internal _meta fields.
@@ -533,7 +416,7 @@ class LLMProvider(ABC):
         return any(marker in err for marker in cls._TRANSIENT_ERROR_MARKERS)
 
     @classmethod
-    def is_transient_response(cls, response: LLMResponse) -> bool:
+    def _is_transient_response(cls, response: LLMResponse) -> bool:
         """Prefer structured error metadata, fallback to text markers for legacy providers."""
         if response.error_should_retry is not None:
             return bool(response.error_should_retry)
@@ -724,21 +607,6 @@ class LLMProvider(ABC):
                 result.append(msg)
         return result if found else None
 
-    @staticmethod
-    def _contains_image_content(value: object) -> bool:
-        """Return whether a JSON-like provider payload contains an input image."""
-        if isinstance(value, dict):
-            mapping = cast(dict[str, object], value)
-            if mapping.get("type") in {"image_url", "input_image"}:
-                return True
-            return any(LLMProvider._contains_image_content(item) for item in mapping.values())
-        if isinstance(value, list):
-            return any(
-                LLMProvider._contains_image_content(item)
-                for item in cast(list[object], value)
-            )
-        return False
-
     @staticmethod
     def _strip_image_content_inplace(messages: list[dict[str, Any]]) -> bool:
         """Replace image_url blocks with text placeholder *in-place*.
@@ -765,12 +633,6 @@ class LLMProvider(ABC):
     async def _safe_chat(self, **kwargs: Any) -> LLMResponse:
         """Call chat() and convert unexpected exceptions to error responses."""
         try:
-            provider_context = kwargs.pop("provider_context", None)
-            if isinstance(provider_context, ProviderCallContext):
-                return await self.chat_with_context(
-                    provider_context=provider_context,
-                    **kwargs,
-                )
             return await self.chat(**kwargs)
         except asyncio.CancelledError:
             raise
@@ -804,47 +666,17 @@ class LLMProvider(ABC):
         """
         _ = on_thinking_delta, on_tool_call_delta
         response = await self.chat(
-            messages=messages,
-            tools=tools,
-            model=model,
-            max_tokens=max_tokens,
-            temperature=temperature,
-            reasoning_effort=reasoning_effort,
-            tool_choice=tool_choice,
+            messages=messages, tools=tools, model=model,
+            max_tokens=max_tokens, temperature=temperature,
+            reasoning_effort=reasoning_effort, tool_choice=tool_choice,
         )
         if on_content_delta and response.content:
             await on_content_delta(response.content)
         return response
 
-    async def chat_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        """Opt-in continuation hook; ordinary providers delegate to ``chat``."""
-        _ = provider_context
-        return await self.chat(**kwargs)
-
-    async def chat_stream_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        """Streaming continuation hook with a context-free default."""
-        _ = provider_context
-        return await self.chat_stream(**kwargs)
-
     async def _safe_chat_stream(self, **kwargs: Any) -> LLMResponse:
         """Call chat_stream() and convert unexpected exceptions to error responses."""
         try:
-            provider_context = kwargs.pop("provider_context", None)
-            if isinstance(provider_context, ProviderCallContext):
-                return await self.chat_stream_with_context(
-                    provider_context=provider_context,
-                    **kwargs,
-                )
             return await self.chat_stream(**kwargs)
         except asyncio.CancelledError:
             raise
@@ -866,7 +698,6 @@ class LLMProvider(ABC):
         on_stream_recover: Callable[[], Awaitable[None]] | None = None,
         retry_mode: str = "standard",
         on_retry_wait: Callable[[str], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         """Call chat_stream() with retry on transient provider failures."""
         if max_tokens is self._SENTINEL or max_tokens is None:
@@ -899,8 +730,6 @@ class LLMProvider(ABC):
             on_thinking_delta=on_thinking_delta,
             on_tool_call_delta=on_tool_call_delta,
         )
-        if provider_context is not None:
-            kw["provider_context"] = provider_context
         if on_stream_recover and getattr(self, "supports_stream_recover_callback", False):
             kw["on_stream_recover"] = _recover_stream
         return await self._run_with_retry(
@@ -924,7 +753,6 @@ class LLMProvider(ABC):
         tool_choice: str | dict[str, Any] | None = None,
         retry_mode: str = "standard",
         on_retry_wait: Callable[[str], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         """Call chat() with retry on transient provider failures.
 
@@ -947,8 +775,6 @@ class LLMProvider(ABC):
             max_tokens=max_tokens, temperature=temperature,
             reasoning_effort=reasoning_effort, tool_choice=tool_choice,
         )
-        if provider_context is not None:
-            kw["provider_context"] = provider_context
         return await self._run_with_retry(
             self._safe_chat,
             kw,
@@ -1106,33 +932,14 @@ class LLMProvider(ABC):
                 last_error_key = error_key
                 identical_error_count = 1 if error_key else 0
 
-            if not self.is_transient_response(response):
-                stripped = self._strip_image_content(kw["messages"])
-                provider_context = kw.get("provider_context")
-                stripped_context: ProviderCallContext | None = None
-                if isinstance(provider_context, ProviderCallContext):
-                    state = provider_context.conversation_state
-                    if state is not None and (
-                        stripped is not None
-                        or self._strip_image_content(state.pending_messages) is not None
-                        or self._contains_image_content(state.payload)
-                    ):
-                        # Provider-owned payloads may retain earlier input_image items.
-                        # Rebuild from the stripped public transcript for this retry.
-                        stripped_context = ProviderCallContext(
-                            context_window_tokens=(
-                                provider_context.context_window_tokens
-                            ),
-                        )
-                if stripped is not None or stripped_context is not None:
+            if not self._is_transient_response(response):
+                stripped = self._strip_image_content(original_messages)
+                if stripped is not None and stripped != kw["messages"]:
                     logger.warning(
                         "Non-transient LLM error with image content, retrying without images"
                     )
                     retry_kw = dict(kw)
-                    if stripped is not None:
-                        retry_kw["messages"] = stripped
-                    if stripped_context is not None:
-                        retry_kw["provider_context"] = stripped_context
+                    retry_kw["messages"] = stripped
                     result = await call(**retry_kw)
                     # Permanently strip images from the original messages so
                     # subsequent iterations do not repeat the error-retry cycle.

nanobot/providers/conversation_state.py

@@ -1,262 +0,0 @@
-"""Provider-owned conversation-state lifecycle coordination."""
-
-from __future__ import annotations
-
-from copy import deepcopy
-from typing import Any, cast
-
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-)
-
-_PROVIDER_STATE_OUTPUT_META = "provider_state_output"
-_PROVIDER_STATE_BOUNDARY_META = "provider_state_boundary"
-
-
-def allows_conversation_message_merge(message: dict[str, Any]) -> bool:
-    """Return whether new same-role input may merge into *message*."""
-    internal_meta = cast(object, message.get("_meta"))
-    return not (
-        isinstance(internal_meta, dict)
-        and cast(dict[str, Any], internal_meta).get(
-            _PROVIDER_STATE_BOUNDARY_META
-        ) is True
-    )
-
-
-class ProviderConversationStateController:
-    """Keep provider conversation-state semantics outside the agent runner.
-
-    The runner owns the tool loop and reports lifecycle events here. This
-    controller owns capability checks, transcript deltas, response projections,
-    retry transitions, and durable snapshots for provider-private state.
-    """
-
-    def __init__(
-        self,
-        *,
-        provider: LLMProvider,
-        model: str | None,
-        messages: list[dict[str, Any]],
-        state: ProviderConversationState | None = None,
-    ) -> None:
-        self._provider = provider
-        self._model = model
-        self._state = (
-            state
-            if state is not None
-            and provider.can_resume_conversation_state(state, model)
-            else None
-        )
-        self._boundary = len(messages)
-        self._request_messages: list[dict[str, Any]] = []
-
-    def independent_request_context(
-        self,
-        *,
-        context_window_tokens: int | None,
-    ) -> ProviderCallContext | None:
-        """Return typed provider context for a request that does not resume state."""
-        if context_window_tokens is None:
-            return None
-        return ProviderCallContext(context_window_tokens=context_window_tokens)
-
-    def prepare_request(
-        self,
-        messages: list[dict[str, Any]],
-        *,
-        context_window_tokens: int | None,
-        model_messages: list[dict[str, Any]] | None = None,
-        supplemental_messages: list[dict[str, Any]] | None = None,
-    ) -> ProviderCallContext | None:
-        """Build typed context for the next request and remember its durable delta."""
-        independent_context = self.independent_request_context(
-            context_window_tokens=context_window_tokens,
-        )
-        if self._state is None:
-            self._request_messages = []
-            return independent_context
-        if not self._provider.can_resume_conversation_state(
-            self._state,
-            self._model,
-        ):
-            self._state = None
-            self._request_messages = []
-            return independent_context
-
-        durable_messages = self._messages_after_boundary(messages)
-        governed_messages = (
-            self._model_messages_after_boundary(model_messages)
-            if model_messages is not None and durable_messages
-            else None
-        )
-        request_messages = (
-            governed_messages
-            if governed_messages is not None
-            else durable_messages
-        )
-        supplemental = deepcopy(supplemental_messages or [])
-        self._request_messages = deepcopy(request_messages)
-        request_state = self._state.with_pending_messages([
-            *self._state.pending_messages,
-            *request_messages,
-            *supplemental,
-        ])
-        return ProviderCallContext(
-            conversation_state=request_state,
-            context_window_tokens=(
-                independent_context.context_window_tokens
-                if independent_context is not None
-                else None
-            ),
-        )
-
-    def observe_response(
-        self,
-        response: LLMResponse,
-        messages: list[dict[str, Any]],
-        *,
-        adopt_candidate_state: bool = True,
-    ) -> None:
-        """Advance, preserve, or discard state after one provider response."""
-        candidate = response.provider_state if adopt_candidate_state else None
-        candidate_is_replayable = response.finish_reason in {
-            "stop",
-            "tool_calls",
-            "function_call",
-        }
-        if (
-            candidate is not None
-            and candidate_is_replayable
-            and self._provider.can_resume_conversation_state(
-                candidate,
-                self._model,
-            )
-        ):
-            self._state = candidate
-            self._boundary = len(messages)
-            self._seal_boundary(messages)
-        elif response.finish_reason == "error" and (
-            response.preserve_provider_state_on_error is True
-            or (
-                response.preserve_provider_state_on_error is None
-                and LLMProvider.is_transient_response(response)
-            )
-        ):
-            if self._state is not None and self._request_messages:
-                self._state = self._state.with_pending_messages([
-                    *self._state.pending_messages,
-                    *self._request_messages,
-                ])
-            self._boundary = len(messages)
-        else:
-            self._state = None
-            self._boundary = len(messages)
-        self._request_messages = []
-
-    @staticmethod
-    def project_response_message(
-        message: dict[str, Any],
-        response: LLMResponse,
-    ) -> dict[str, Any]:
-        """Mark a Chat projection already represented by provider output."""
-        if response.provider_state is None:
-            return message
-        internal_meta = dict(message.get("_meta") or {})
-        internal_meta[_PROVIDER_STATE_OUTPUT_META] = True
-        message["_meta"] = internal_meta
-        return message
-
-    def checkpoint(
-        self,
-        messages: list[dict[str, Any]],
-        *,
-        model_messages: list[dict[str, Any]] | None = None,
-    ) -> ProviderConversationState | None:
-        """Return a durable state snapshot without changing live state."""
-        if self._state is None:
-            return None
-        durable_messages = self._messages_after_boundary(messages)
-        governed_messages = (
-            self._model_messages_after_boundary(model_messages)
-            if model_messages is not None and durable_messages
-            else None
-        )
-        pending_messages = (
-            governed_messages
-            if governed_messages is not None
-            else durable_messages
-        )
-        return self._state.with_pending_messages([
-            *self._state.pending_messages,
-            *pending_messages,
-        ])
-
-    def finish(
-        self,
-        messages: list[dict[str, Any]],
-    ) -> ProviderConversationState | None:
-        """Return the final durable state after all runner messages are known."""
-        self._state = self.checkpoint(messages)
-        return self._state
-
-    def _messages_after_boundary(
-        self,
-        messages: list[dict[str, Any]],
-    ) -> list[dict[str, Any]]:
-        pending: list[dict[str, Any]] = []
-        for message in messages[self._boundary:]:
-            internal_meta = cast(object, message.get("_meta"))
-            if (
-                isinstance(internal_meta, dict)
-                and cast(dict[str, Any], internal_meta).get(
-                    _PROVIDER_STATE_OUTPUT_META
-                ) is True
-            ):
-                continue
-            pending.append(deepcopy(message))
-        return pending
-
-    @staticmethod
-    def _model_messages_after_boundary(
-        messages: list[dict[str, Any]],
-    ) -> list[dict[str, Any]] | None:
-        """Return the governed delta after the latest provider-owned boundary."""
-        boundary = None
-        for idx in range(len(messages) - 1, -1, -1):
-            internal_meta = cast(object, messages[idx].get("_meta"))
-            if (
-                isinstance(internal_meta, dict)
-                and cast(dict[str, Any], internal_meta).get(
-                    _PROVIDER_STATE_BOUNDARY_META
-                ) is True
-            ):
-                boundary = idx
-                break
-        if boundary is None:
-            return None
-
-        pending: list[dict[str, Any]] = []
-        for message in messages[boundary + 1:]:
-            internal_meta = cast(object, message.get("_meta"))
-            if (
-                isinstance(internal_meta, dict)
-                and cast(dict[str, Any], internal_meta).get(
-                    _PROVIDER_STATE_OUTPUT_META
-                ) is True
-            ):
-                continue
-            pending.append(deepcopy(message))
-        return pending
-
-    @staticmethod
-    def _seal_boundary(messages: list[dict[str, Any]]) -> None:
-        """Prevent later same-role injection merging across a state boundary."""
-        if not messages:
-            return
-        internal_meta = dict(messages[-1].get("_meta") or {})
-        internal_meta[_PROVIDER_STATE_BOUNDARY_META] = True
-        messages[-1]["_meta"] = internal_meta

nanobot/providers/factory.py

@@ -261,7 +261,6 @@ def make_provider(
             primary=provider,
             fallback_presets=fallback_presets,
             provider_factory=lambda fb: _make_provider_core(config, preset=fb),
-            primary_context_window_tokens=resolved.context_window_tokens,
         )
 
     return provider

nanobot/providers/fallback_provider.py

@@ -6,18 +6,11 @@ from __future__ import annotations
 
 import time
 from collections.abc import Awaitable, Callable
-from dataclasses import replace
 from typing import Any
 
 from loguru import logger
 
-from nanobot.providers.base import (
-    GenerationSettings,
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-)
+from nanobot.providers.base import GenerationSettings, LLMProvider, LLMResponse
 
 # Circuit breaker tuned to match OpenAICompatProvider's Responses API breaker.
 _PRIMARY_FAILURE_THRESHOLD = 3
@@ -120,13 +113,11 @@ class FallbackProvider(LLMProvider):
         fallback_presets: list[Any],
         provider_factory: Callable[[Any], LLMProvider],
         fallback_model_observer: FallbackModelObserver | None = None,
-        primary_context_window_tokens: int | None = None,
     ):
         self._primary = primary
         self._fallback_presets = list(fallback_presets)
         self._provider_factory = provider_factory
         self._fallback_model_observer = fallback_model_observer
-        self._primary_context_window_tokens = primary_context_window_tokens
         self._has_fallbacks = bool(fallback_presets)
         self._primary_failures = 0
         self._primary_tripped_at: float | None = None
@@ -150,33 +141,6 @@ class FallbackProvider(LLMProvider):
     def supports_progress_deltas(self) -> bool:
         return bool(getattr(self._primary, "supports_progress_deltas", False))
 
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        return self._primary.can_resume_conversation_state(state, model)
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        return self._primary.supports_native_compaction(model)
-
-    def _primary_call_context(
-        self,
-        provider_context: ProviderCallContext,
-        model: str | None,
-    ) -> ProviderCallContext:
-        context_window_tokens = (
-            self._primary_context_window_tokens
-            if self._primary_context_window_tokens is not None
-            else provider_context.context_window_tokens
-        )
-        if not self._primary.supports_native_compaction(model):
-            context_window_tokens = None
-        return ProviderCallContext(
-            conversation_state=provider_context.conversation_state,
-            context_window_tokens=context_window_tokens,
-        )
-
     def _primary_available(self) -> bool:
         """Return True if the primary provider is not currently tripped."""
         if self._primary_tripped_at is None:
@@ -193,25 +157,6 @@ class FallbackProvider(LLMProvider):
             lambda p, kw: p.chat(**kw), kwargs, has_streamed=None
         )
 
-    async def chat_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        call_kwargs: dict[str, Any] = dict(kwargs)
-        call_kwargs["provider_context"] = self._primary_call_context(
-            provider_context,
-            kwargs.get("model"),
-        )
-        if not self._has_fallbacks:
-            return await self._primary.chat_with_context(**call_kwargs)
-        return await self._try_with_fallback(
-            lambda p, kw: p.chat_with_context(**kw),
-            call_kwargs,
-            has_streamed=None,
-        )
-
     async def chat_stream(self, **kwargs: Any) -> LLMResponse:
         on_stream_recover = kwargs.pop("on_stream_recover", None)
         if not self._has_fallbacks:
@@ -234,38 +179,6 @@ class FallbackProvider(LLMProvider):
             on_stream_recover=on_stream_recover,
         )
 
-    async def chat_stream_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        on_stream_recover = kwargs.pop("on_stream_recover", None)
-        call_kwargs: dict[str, Any] = dict(kwargs)
-        call_kwargs["provider_context"] = self._primary_call_context(
-            provider_context,
-            kwargs.get("model"),
-        )
-        if not self._has_fallbacks:
-            return await self._primary.chat_stream_with_context(**call_kwargs)
-
-        has_streamed: list[bool] = [False]
-        original_delta = call_kwargs.get("on_content_delta")
-
-        async def _tracking_delta(text: str) -> None:
-            if text:
-                has_streamed[0] = True
-            if original_delta:
-                await original_delta(text)
-
-        call_kwargs["on_content_delta"] = _tracking_delta
-        return await self._try_with_fallback(
-            lambda p, kw: p.chat_stream_with_context(**kw),
-            call_kwargs,
-            has_streamed=has_streamed,
-            on_stream_recover=on_stream_recover,
-        )
-
     async def _try_with_fallback(
         self,
         call: Callable[[LLMProvider, dict[str, Any]], Awaitable[LLMResponse]],
@@ -276,9 +189,6 @@ class FallbackProvider(LLMProvider):
         primary_model = kwargs.get("model") or self._primary.get_default_model()
         primary_was_attempted = False
         primary_error = "unknown error"
-        # A primary error eligible for failover did not return a replacement
-        # continuation, so the incoming primary state remains reusable.
-        preserve_primary_state = True
 
         if self._primary_available():
             primary_was_attempted = True
@@ -376,23 +286,6 @@ class FallbackProvider(LLMProvider):
                 "max_tokens": fallback.max_tokens,
                 "temperature": fallback.temperature,
             }
-            provider_context = fallback_kwargs.get("provider_context")
-            if isinstance(provider_context, ProviderCallContext):
-                state = provider_context.conversation_state
-                if state is not None and not fallback_provider.can_resume_conversation_state(
-                    state,
-                    fallback_model,
-                ):
-                    state = None
-                context_window_tokens = (
-                    fallback.context_window_tokens
-                    if fallback_provider.supports_native_compaction(fallback_model)
-                    else None
-                )
-                fallback_kwargs["provider_context"] = ProviderCallContext(
-                    conversation_state=state,
-                    context_window_tokens=context_window_tokens,
-                )
             if fallback.reasoning_effort is None:
                 fallback_kwargs.pop("reasoning_effort", None)
             else:
@@ -419,15 +312,11 @@ class FallbackProvider(LLMProvider):
         )
         # Return the last error response we saw (primary or last fallback).
         if last_response is not None:
-            return replace(
-                last_response,
-                preserve_provider_state_on_error=preserve_primary_state,
-            )
+            return last_response
         # Primary was tripped and we have no fallbacks — synthesize an error.
         return LLMResponse(
             content=f"Primary model '{primary_model}' circuit open and no fallbacks available",
             finish_reason="error",
-            preserve_provider_state_on_error=preserve_primary_state,
         )
 
     async def _notify_fallback_model(self, model: str) -> None:

nanobot/providers/github_copilot_provider.py

@@ -16,7 +16,7 @@ import httpx
 from oauth_cli_kit.models import OAuthToken
 from oauth_cli_kit.storage import FileTokenStorage
 
-from nanobot.providers.base import LLMResponse, ProviderCallContext
+from nanobot.providers.base import LLMResponse
 from nanobot.providers.openai_compat_provider import OpenAICompatProvider
 
 DEFAULT_GITHUB_DEVICE_CODE_URL = "https://github.com/login/device/code"
@@ -248,7 +248,6 @@ class GitHubCopilotProvider(OpenAICompatProvider):
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
         tool_choice: str | dict[str, Any] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         await self._refresh_client_api_key()
         return await super().chat(
@@ -259,7 +258,6 @@ class GitHubCopilotProvider(OpenAICompatProvider):
             temperature=temperature,
             reasoning_effort=reasoning_effort,
             tool_choice=tool_choice,
-            provider_context=provider_context,
         )
 
     async def chat_stream(
@@ -274,7 +272,6 @@ class GitHubCopilotProvider(OpenAICompatProvider):
         on_content_delta: Callable[[str], Awaitable[None]] | None = None,
         on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
         on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         await self._refresh_client_api_key()
         return await super().chat_stream(
@@ -288,5 +285,4 @@ class GitHubCopilotProvider(OpenAICompatProvider):
             on_content_delta=on_content_delta,
             on_thinking_delta=on_thinking_delta,
             on_tool_call_delta=on_tool_call_delta,
-            provider_context=provider_context,
         )

nanobot/providers/openai_codex_provider.py

@@ -17,27 +17,17 @@ from oauth_cli_kit import get_token as get_codex_token
 from nanobot.providers.base import (
     LLMProvider,
     LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
+    ToolCallRequest,
     resolve_stream_idle_timeout_s,
 )
 from nanobot.providers.openai_responses import (
-    ResponsesStreamCapture,
-    build_responses_state,
     consume_sse_with_reasoning,
+    convert_messages,
     convert_tools,
-    is_compaction_compatibility_error,
-    is_replayable_finish_reason,
-    prepare_responses_input,
-    resolve_compact_threshold,
-    responses_state_context_tokens,
-    responses_state_items,
-    responses_state_matches,
 )
 
 DEFAULT_CODEX_URL = "https://chatgpt.com/backend-api/codex/responses"
 DEFAULT_ORIGINATOR = "nanobot"
-_COMPACTION_RETAINED_CHAR_BUDGET = 256_000
 
 
 class OpenAICodexProvider(LLMProvider):
@@ -55,39 +45,21 @@ class OpenAICodexProvider(LLMProvider):
         self.default_model = default_model
         self.proxy = proxy or None
         self._extra_body = dict(extra_body or {})
-        self._native_compaction_available = True
 
     async def _call_codex(
         self,
         messages: list[dict[str, Any]],
         tools: list[dict[str, Any]] | None,
         model: str | None,
-        max_tokens: int,
         reasoning_effort: str | None,
         tool_choice: str | dict[str, Any] | None,
         on_content_delta: Callable[[str], Awaitable[None]] | None = None,
         on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
         on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         """Shared request logic for both chat() and chat_stream()."""
         model = model or self.default_model
-        sanitized_messages = self._sanitize_empty_content(messages)
-        sanitized_state = (
-            provider_context.conversation_state
-            if provider_context is not None
-            else None
-        )
-        if sanitized_state is not None:
-            sanitized_state = sanitized_state.with_pending_messages(
-                self._sanitize_empty_content(sanitized_state.pending_messages)
-            )
-        system_prompt, input_items, replayed = prepare_responses_input(
-            sanitized_messages,
-            state=sanitized_state,
-            provider=self._responses_state_provider(),
-            model=_strip_model_prefix(model),
-        )
+        system_prompt, input_items = convert_messages(messages)
 
         body: dict[str, Any] = {
             "model": _strip_model_prefix(model),
@@ -96,15 +68,12 @@ class OpenAICodexProvider(LLMProvider):
             "instructions": system_prompt,
             "input": input_items,
             "text": {"verbosity": "medium"},
+            "include": ["reasoning.encrypted_content"],
             "prompt_cache_key": _prompt_cache_key(messages[:2]),
             "tool_choice": tool_choice or "auto",
             "parallel_tool_calls": True,
         }
-        body["include"] = ["reasoning.encrypted_content"]
         reasoning_options = _build_reasoning_options(reasoning_effort)
-        if replayed and "gpt-5.6" in _strip_model_prefix(model).lower():
-            reasoning_options = dict(reasoning_options or {})
-            reasoning_options["context"] = "all_turns"
         if reasoning_options:
             body["reasoning"] = reasoning_options
         if tools:
@@ -118,90 +87,33 @@ class OpenAICodexProvider(LLMProvider):
             token = await asyncio.to_thread(get_codex_token, proxy=self.proxy)
             headers = _build_headers(cast(str, token.account_id), token.access)
 
-            async def _send(
-                request_body: dict[str, Any],
-                *,
-                emit_deltas: bool,
-            ) -> LLMResponse:
-                wire_body = _without_response_item_ids(request_body)
-                try:
-                    return await _request_codex(
-                        DEFAULT_CODEX_URL,
-                        headers,
-                        wire_body,
-                        verify=True,
-                        proxy=self.proxy,
-                        on_content_delta=on_content_delta if emit_deltas else None,
-                        on_thinking_delta=on_thinking_delta if emit_deltas else None,
-                        on_tool_call_delta=on_tool_call_delta if emit_deltas else None,
-                    )
-                except Exception as exc:
-                    if "CERTIFICATE_VERIFY_FAILED" not in str(exc):
-                        raise
-                    logger.warning(
-                        "SSL verification failed for Codex API; retrying with verify=False"
-                    )
-                    return await _request_codex(
-                        DEFAULT_CODEX_URL,
-                        headers,
-                        wire_body,
-                        verify=False,
-                        proxy=self.proxy,
-                        on_content_delta=on_content_delta if emit_deltas else None,
-                        on_thinking_delta=on_thinking_delta if emit_deltas else None,
-                        on_tool_call_delta=on_tool_call_delta if emit_deltas else None,
-                    )
-
-            compact_threshold = resolve_compact_threshold(
-                (
-                    provider_context.context_window_tokens
-                    if provider_context is not None
-                    else None
-                ),
-                max_tokens,
-            )
-            if (
-                self.supports_native_compaction(model)
-                and replayed
-                and sanitized_state is not None
-                and compact_threshold is not None
-                and responses_state_context_tokens(sanitized_state) >= compact_threshold
-            ):
-                stage = "codex_compaction"
-                compact_body = {
-                    **body,
-                    "input": [*input_items, {"type": "compaction_trigger"}],
-                }
-                try:
-                    compact_result = await _send(compact_body, emit_deltas=False)
-                    compact_items = (
-                        responses_state_items(compact_result.provider_state)
-                        if compact_result.provider_state is not None
-                        else None
-                    )
-                    if not compact_items or compact_items[-1].get("type") not in {
-                        "compaction",
-                        "compaction_summary",
-                        "context_compaction",
-                    }:
-                        raise RuntimeError("Codex compaction returned no compaction item")
-                    body["input"] = [
-                        *_retained_compaction_messages(input_items),
-                        *compact_items,
-                    ]
-                except Exception as compact_error:
-                    if is_compaction_compatibility_error(compact_error):
-                        self._native_compaction_available = False
-                    logger.warning(
-                        "Codex native compaction unavailable; continuing without it "
-                        "(type={} status={} disabled={})",
-                        type(compact_error).__name__,
-                        getattr(compact_error, "status_code", None),
-                        not self._native_compaction_available,
-                    )
-
             stage = "codex_request"
-            return await _send(body, emit_deltas=True)
+            try:
+                content, tool_calls, finish_reason, usage, reasoning_content = await _request_codex(
+                    DEFAULT_CODEX_URL, headers, body, verify=True,
+                    proxy=self.proxy,
+                    on_content_delta=on_content_delta,
+                    on_thinking_delta=on_thinking_delta,
+                    on_tool_call_delta=on_tool_call_delta,
+                )
+            except Exception as e:
+                if "CERTIFICATE_VERIFY_FAILED" not in str(e):
+                    raise
+                logger.warning("SSL verification failed for Codex API; retrying with verify=False")
+                content, tool_calls, finish_reason, usage, reasoning_content = await _request_codex(
+                    DEFAULT_CODEX_URL, headers, body, verify=False,
+                    proxy=self.proxy,
+                    on_content_delta=on_content_delta,
+                    on_thinking_delta=on_thinking_delta,
+                    on_tool_call_delta=on_tool_call_delta,
+                )
+            return LLMResponse(
+                content=content,
+                tool_calls=tool_calls,
+                finish_reason=finish_reason,
+                usage=usage,
+                reasoning_content=reasoning_content,
+            )
         except Exception as e:
             response = _codex_error_response(e)
             exc_type = "CodexHTTPError" if isinstance(e, _CodexHTTPError) else type(e).__name__
@@ -225,28 +137,8 @@ class OpenAICodexProvider(LLMProvider):
         model: str | None = None, max_tokens: int = 4096, temperature: float = 0.7,
         reasoning_effort: str | None = None,
         tool_choice: str | dict[str, Any] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
-        return await self._call_codex(
-            messages,
-            tools,
-            model,
-            max_tokens,
-            reasoning_effort,
-            tool_choice,
-            provider_context=provider_context,
-        )
-
-    async def chat_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat(
-            **kwargs,
-            provider_context=provider_context,
-        )
+        return await self._call_codex(messages, tools, model, reasoning_effort, tool_choice)
 
     async def chat_stream(
         self, messages: list[dict[str, Any]], tools: list[dict[str, Any]] | None = None,
@@ -256,55 +148,21 @@ class OpenAICodexProvider(LLMProvider):
         on_content_delta: Callable[[str], Awaitable[None]] | None = None,
         on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
         on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         return await self._call_codex(
-            messages=messages,
-            tools=tools,
-            model=model,
-            max_tokens=max_tokens,
-            reasoning_effort=reasoning_effort,
-            tool_choice=tool_choice,
-            on_content_delta=on_content_delta,
-            on_thinking_delta=on_thinking_delta,
-            on_tool_call_delta=on_tool_call_delta,
-            provider_context=provider_context,
-        )
-
-    async def chat_stream_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat_stream(
-            **kwargs,
-            provider_context=provider_context,
+            messages,
+            tools,
+            model,
+            reasoning_effort,
+            tool_choice,
+            on_content_delta,
+            on_thinking_delta,
+            on_tool_call_delta,
         )
 
     def get_default_model(self) -> str:
         return self.default_model
 
-    @staticmethod
-    def _responses_state_provider() -> str:
-        return f"openai_codex:{DEFAULT_CODEX_URL.rstrip('/')}"
-
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        return responses_state_matches(
-            state,
-            provider=self._responses_state_provider(),
-            model=_strip_model_prefix(model or self.default_model),
-        )
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        """Use the Codex backend's inline compaction trigger when needed."""
-        _ = model
-        return self._native_compaction_available
-
 
 def _strip_model_prefix(model: str) -> str:
     if model.startswith("openai-codex/") or model.startswith("openai_codex/"):
@@ -312,58 +170,6 @@ def _strip_model_prefix(model: str) -> str:
     return model
 
 
-def _without_response_item_ids(
-    request_body: dict[str, Any],
-) -> dict[str, Any]:
-    """Match Codex's default ``store=false`` request-item contract."""
-    if request_body.get("store") is True:
-        return request_body
-    raw_input = request_body.get("input")
-    if not isinstance(raw_input, list):
-        return request_body
-
-    input_items: list[object] = cast(list[object], raw_input)
-    sanitized_input: list[object] = []
-    for raw_item in input_items:
-        if not isinstance(raw_item, dict):
-            sanitized_input.append(raw_item)
-            continue
-        item = cast(dict[str, Any], raw_item)
-        sanitized_input.append({
-            key: value
-            for key, value in item.items()
-            if key != "id"
-        })
-
-    body = dict(request_body)
-    body["input"] = sanitized_input
-    return body
-
-
-def _retained_compaction_messages(
-    input_items: list[dict[str, Any]],
-) -> list[dict[str, Any]]:
-    """Mirror Codex's bounded retention of user/developer/system messages."""
-    retained_reversed: list[dict[str, Any]] = []
-    remaining = _COMPACTION_RETAINED_CHAR_BUDGET
-    for item in reversed(input_items):
-        if item.get("type") not in {None, "message"} or item.get("role") not in {
-            "user",
-            "developer",
-            "system",
-        }:
-            continue
-        size = len(json.dumps(item, ensure_ascii=False))
-        if size > remaining and retained_reversed:
-            continue
-        retained_reversed.append(item)
-        remaining = max(0, remaining - size)
-        if remaining == 0:
-            break
-    retained_reversed.reverse()
-    return retained_reversed
-
-
 def _build_reasoning_options(reasoning_effort: str | None) -> dict[str, str] | None:
     """Opt in to visible summaries without changing provider-default effort."""
     if reasoning_effort and reasoning_effort.lower() == "none":
@@ -396,7 +202,6 @@ class _CodexHTTPError(RuntimeError):
         error_type: str | None = None,
         error_code: str | None = None,
         should_retry: bool | None = None,
-        compaction_unsupported: bool = False,
     ):
         super().__init__(message)
         self.status_code = status_code
@@ -404,7 +209,6 @@ class _CodexHTTPError(RuntimeError):
         self.error_type = error_type
         self.error_code = error_code
         self.should_retry = should_retry
-        self.compaction_unsupported = compaction_unsupported
 
 
 async def _request_codex(
@@ -416,7 +220,7 @@ async def _request_codex(
     on_content_delta: Callable[[str], Awaitable[None]] | None = None,
     on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
     on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-) -> LLMResponse:
+) -> tuple[str, list[ToolCallRequest], str, dict[str, int], str | None]:
     idle_timeout_s = resolve_stream_idle_timeout_s()
     client_kwargs: dict[str, Any] = {"timeout": idle_timeout_s, "verify": verify}
     if proxy:
@@ -429,17 +233,6 @@ async def _request_codex(
                 raw = text.decode("utf-8", "ignore")
                 retry_after = LLMProvider._extract_retry_after_from_headers(response.headers)
                 error_type, error_code = LLMProvider._extract_error_type_code(raw)
-                compaction_unsupported = (
-                    response.status_code in {400, 404, 422}
-                    and any(
-                        marker in raw.lower()
-                        for marker in (
-                            "context_management",
-                            "compact_threshold",
-                            "compaction_trigger",
-                        )
-                    )
-                )
                 raise _CodexHTTPError(
                     _friendly_error(response.status_code, raw),
                     status_code=response.status_code,
@@ -447,38 +240,13 @@ async def _request_codex(
                     error_type=error_type,
                     error_code=error_code,
                     should_retry=_should_retry_status(response.status_code, error_type, error_code, raw),
-                    compaction_unsupported=compaction_unsupported,
                 )
-            capture = ResponsesStreamCapture()
-            (
-                content,
-                tool_calls,
-                finish_reason,
-                usage,
-                reasoning_content,
-            ) = await consume_sse_with_reasoning(
+            return await consume_sse_with_reasoning(
                 response,
                 on_content_delta=on_content_delta,
                 on_tool_call_delta=on_tool_call_delta,
                 on_reasoning_delta=on_thinking_delta,
-                capture=capture,
             )
-            result = LLMResponse(
-                content=content,
-                tool_calls=tool_calls,
-                finish_reason=finish_reason,
-                usage=usage,
-                reasoning_content=reasoning_content,
-            )
-            if capture.completed and is_replayable_finish_reason(finish_reason):
-                result.provider_state = build_responses_state(
-                    provider=f"openai_codex:{url.rstrip('/')}",
-                    model=str(body.get("model") or ""),
-                    input_items=cast(list[dict[str, Any]], body.get("input") or []),
-                    output_items=capture.output_items,
-                    usage=usage,
-                )
-            return result
 
 
 def _prompt_cache_key(messages: list[dict[str, Any]]) -> str:

nanobot/providers/openai_compat_provider.py

@@ -26,24 +26,16 @@ from pydantic.alias_generators import to_snake
 from nanobot.providers.base import (
     LLMProvider,
     LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
     ToolCallRequest,
     parse_tool_arguments,
     resolve_stream_idle_timeout_s,
     tool_arguments_json_for_replay,
 )
 from nanobot.providers.openai_responses import (
-    ResponsesStreamCapture,
-    build_responses_state,
     consume_sdk_stream,
+    convert_messages,
     convert_tools,
-    is_compaction_compatibility_error,
-    is_replayable_finish_reason,
     parse_response_output,
-    prepare_responses_input,
-    resolve_compact_threshold,
-    responses_state_matches,
 )
 
 if TYPE_CHECKING:
@@ -451,8 +443,6 @@ class OpenAICompatProvider(LLMProvider):
     registry lookups needed.
     """
 
-    _native_compaction_available = True
-
     def __init__(
         self,
         api_key: str | None = None,
@@ -473,7 +463,6 @@ class OpenAICompatProvider(LLMProvider):
         self._api_type = api_type if spec and spec.name == "openai" else "auto"
         self._extra_query = extra_query or {}
         self._proxy = proxy or None
-        self._native_compaction_available = True
 
         if api_key and spec and spec.env_key:
             self._setup_env(api_key, api_base)
@@ -958,34 +947,22 @@ class OpenAICompatProvider(LLMProvider):
         model: str | None,
         reasoning_effort: str | None,
     ) -> bool:
-        """Choose Responses for providers/models that explicitly support it."""
+        """Use Responses API only for direct OpenAI requests that benefit from it."""
         if self._api_type == "chat_completions":
             return False
-        spec_name = self._spec.name if self._spec is not None else None
-        model_name = self._request_model_name(model or self.default_model).lower()
-        supported_models = {
-            supported.lower()
-            for supported in getattr(self._spec, "responses_models", ())
-        }
-        model_responses = any(
-            model_name == supported or model_name.endswith(f"/{supported}")
-            for supported in supported_models
-        )
-        provider_responses = spec_name in ("openai", "github_copilot")
-        if not provider_responses and not model_responses:
+        if self._spec and self._spec.name not in ("openai", "github_copilot"):
             return False
         if self._api_type == "responses":
             # Explicit configuration means Responses is mandatory; do not
             # consult the circuit breaker or fall back to Chat Completions.
             return True
-        if provider_responses and (self._spec is None or self._spec.name != "github_copilot"):
+        if self._spec is None or self._spec.name != "github_copilot":
             if not _is_direct_openai_base(self._effective_base):
                 return False
 
+        model_name = (model or self.default_model).lower()
         wants = False
-        if model_responses:
-            wants = True
-        elif reasoning_effort and reasoning_effort.lower() != "none":
+        if reasoning_effort and reasoning_effort.lower() != "none":
             wants = True
         elif any(token in model_name for token in ("gpt-5", "o1", "o3", "o4")):
             wants = True
@@ -994,37 +971,6 @@ class OpenAICompatProvider(LLMProvider):
 
         return self._responses_circuit_allows_probe(model, reasoning_effort)
 
-    def _responses_state_provider(self) -> str:
-        spec_name = self._spec.name if self._spec is not None else "custom"
-        effective_base = self._effective_base or "https://api.openai.com/v1"
-        return f"openai_compat:{spec_name}:{effective_base.rstrip('/')}"
-
-    def _responses_state_model(self, model: str | None) -> str:
-        return self._request_model_name(model or self.default_model)
-
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        return responses_state_matches(
-            state,
-            provider=self._responses_state_provider(),
-            model=self._responses_state_model(model),
-        )
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        """Enable server compaction only on direct OpenAI Responses endpoints."""
-        _ = model
-        if (
-            not self._native_compaction_available
-            or self._api_type == "chat_completions"
-        ):
-            return False
-        if self._spec is not None and self._spec.name != "openai":
-            return False
-        return _is_direct_openai_base(self._effective_base)
-
     def _responses_circuit_allows_probe(
         self,
         model: str | None,
@@ -1094,31 +1040,12 @@ class OpenAICompatProvider(LLMProvider):
         temperature: float,
         reasoning_effort: str | None,
         tool_choice: str | dict[str, Any] | None,
-        provider_context: ProviderCallContext | None = None,
     ) -> dict[str, Any]:
         """Build a Responses API body for direct OpenAI requests."""
         model_name = model or self.default_model
         model_name = self._request_model_name(model_name)
         sanitized_messages = self._sanitize_messages(self._sanitize_empty_content(messages))
-        sanitized_state = (
-            provider_context.conversation_state
-            if provider_context is not None
-            else None
-        )
-        if sanitized_state is not None:
-            sanitized_state = sanitized_state.with_pending_messages(
-                self._sanitize_messages(
-                    self._sanitize_empty_content(sanitized_state.pending_messages)
-                )
-            )
-        preserve_reasoning = bool(self._spec and self._spec.name == "deepseek")
-        instructions, input_items, replayed = prepare_responses_input(
-            sanitized_messages,
-            state=sanitized_state,
-            provider=self._responses_state_provider(),
-            model=model_name,
-            preserve_reasoning=preserve_reasoning,
-        )
+        instructions, input_items = convert_messages(sanitized_messages)
 
         body: dict[str, Any] = {
             "model": model_name,
@@ -1128,29 +1055,13 @@ class OpenAICompatProvider(LLMProvider):
             "store": False,
             "stream": False,
         }
-        compact_threshold = resolve_compact_threshold(
-            (
-                provider_context.context_window_tokens
-                if provider_context is not None
-                else None
-            ),
-            max_tokens,
-        )
-        if self.supports_native_compaction(model_name) and compact_threshold is not None:
-            body["context_management"] = [{
-                "type": "compaction",
-                "compact_threshold": compact_threshold,
-            }]
 
         if self._supports_temperature(model_name, reasoning_effort):
             body["temperature"] = temperature
 
-        if not self._supports_temperature(model_name, reasoning_effort) and not preserve_reasoning:
-            body["include"] = ["reasoning.encrypted_content"]
         if reasoning_effort and reasoning_effort.lower() != "none":
             body["reasoning"] = {"effort": reasoning_effort}
-        if replayed and "gpt-5.6" in model_name.lower():
-            body.setdefault("reasoning", {})["context"] = "all_turns"
+            body["include"] = ["reasoning.encrypted_content"]
 
         if tools:
             body["tools"] = convert_tools(tools)
@@ -1162,29 +1073,6 @@ class OpenAICompatProvider(LLMProvider):
 
         return body
 
-    async def _create_response_with_compaction_fallback(
-        self,
-        client: Any,
-        body: dict[str, Any],
-    ) -> Any:
-        """Retry Responses once without server compaction on compatibility errors."""
-        try:
-            return await client.responses.create(**body)
-        except Exception as exc:
-            if (
-                "context_management" not in body
-                or not is_compaction_compatibility_error(exc)
-            ):
-                raise
-            self._native_compaction_available = False
-            body.pop("context_management", None)
-            logger.warning(
-                "Responses server compaction unsupported; disabled for this provider instance "
-                "(status={})",
-                getattr(exc, "status_code", None),
-            )
-            return await client.responses.create(**body)
-
     # ------------------------------------------------------------------
     # Response parsing
     # ------------------------------------------------------------------
@@ -1711,28 +1599,6 @@ class OpenAICompatProvider(LLMProvider):
     # Public API
     # ------------------------------------------------------------------
 
-    async def chat_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat(
-            **kwargs,
-            provider_context=provider_context,
-        )
-
-    async def chat_stream_with_context(
-        self,
-        *,
-        provider_context: ProviderCallContext,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        return await self.chat_stream(
-            **kwargs,
-            provider_context=provider_context,
-        )
-
     async def chat(
         self,
         messages: list[dict[str, Any]],
@@ -1742,7 +1608,6 @@ class OpenAICompatProvider(LLMProvider):
         temperature: float = 0.7,
         reasoning_effort: str | None = None,
         tool_choice: str | dict[str, Any] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         client = await self._ensure_client()
         try:
@@ -1751,18 +1616,12 @@ class OpenAICompatProvider(LLMProvider):
                     body = self._build_responses_body(
                         messages, tools, model, max_tokens, temperature,
                         reasoning_effort, tool_choice,
-                        provider_context,
                     )
-                    responses_raw = await self._create_response_with_compaction_fallback(
-                        client,
-                        body,
-                    )
-                    result = parse_response_output(
-                        responses_raw,
-                        state_provider=self._responses_state_provider(),
-                        state_model=str(body["model"]),
-                        state_input_items=cast(list[dict[str, Any]], body["input"]),
+                    responses_raw = cast(
+                        Any,
+                        await client.responses.create(**body),
                     )
+                    result = parse_response_output(responses_raw)
                     self._record_responses_success(model, reasoning_effort)
                     return result
                 except Exception as responses_error:
@@ -1801,7 +1660,6 @@ class OpenAICompatProvider(LLMProvider):
         on_content_delta: Callable[[str], Awaitable[None]] | None = None,
         on_thinking_delta: Callable[[str], Awaitable[None]] | None = None,
         on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-        provider_context: ProviderCallContext | None = None,
     ) -> LLMResponse:
         client = await self._ensure_client()
         idle_timeout_s = resolve_stream_idle_timeout_s()
@@ -1811,12 +1669,11 @@ class OpenAICompatProvider(LLMProvider):
                     body = self._build_responses_body(
                         messages, tools, model, max_tokens, temperature,
                         reasoning_effort, tool_choice,
-                        provider_context,
                     )
                     body["stream"] = True
-                    responses_stream = await self._create_response_with_compaction_fallback(
-                        client,
-                        body,
+                    responses_stream = cast(
+                        Any,
+                        await client.responses.create(**body),
                     )
 
                     async def _timed_stream() -> AsyncIterator[Any]:
@@ -1830,7 +1687,6 @@ class OpenAICompatProvider(LLMProvider):
                             except StopAsyncIteration:
                                 break
 
-                    capture = ResponsesStreamCapture()
                     (
                         content,
                         tool_calls,
@@ -1841,26 +1697,15 @@ class OpenAICompatProvider(LLMProvider):
                         _timed_stream(),
                         on_content_delta,
                         on_tool_call_delta=on_tool_call_delta,
-                        on_reasoning_delta=on_thinking_delta,
-                        capture=capture,
                     )
                     self._record_responses_success(model, reasoning_effort)
-                    result = LLMResponse(
+                    return LLMResponse(
                         content=content or None,
                         tool_calls=tool_calls,
                         finish_reason=finish_reason,
                         usage=usage,
                         reasoning_content=reasoning_content,
                     )
-                    if capture.completed and is_replayable_finish_reason(finish_reason):
-                        result.provider_state = build_responses_state(
-                            provider=self._responses_state_provider(),
-                            model=str(body["model"]),
-                            input_items=cast(list[dict[str, Any]], body["input"]),
-                            output_items=capture.output_items,
-                            usage=usage,
-                        )
-                    return result
                 except Exception as responses_error:
                     if self._spec and self._spec.name == "github_copilot":
                         # Copilot gateway exposes GPT-5/o-series only via /responses;

nanobot/providers/openai_responses/__init__.py

@@ -1,4 +1,4 @@
-"""Shared helpers for provider backends that implement the OpenAI Responses protocol."""
+"""Shared helpers for OpenAI Responses API providers (Codex, Azure OpenAI)."""
 
 from nanobot.providers.openai_responses.converters import (
     convert_messages,
@@ -8,24 +8,13 @@ from nanobot.providers.openai_responses.converters import (
 )
 from nanobot.providers.openai_responses.parsing import (
     FINISH_REASON_MAP,
-    ResponsesStreamCapture,
     consume_sdk_stream,
     consume_sse,
     consume_sse_with_reasoning,
-    is_replayable_finish_reason,
     iter_sse,
     map_finish_reason,
     parse_response_output,
 )
-from nanobot.providers.openai_responses.state import (
-    build_responses_state,
-    is_compaction_compatibility_error,
-    prepare_responses_input,
-    resolve_compact_threshold,
-    responses_state_context_tokens,
-    responses_state_items,
-    responses_state_matches,
-)
 
 __all__ = [
     "convert_messages",
@@ -36,16 +25,7 @@ __all__ = [
     "consume_sse",
     "consume_sse_with_reasoning",
     "consume_sdk_stream",
-    "ResponsesStreamCapture",
-    "is_replayable_finish_reason",
     "map_finish_reason",
     "parse_response_output",
-    "build_responses_state",
-    "is_compaction_compatibility_error",
-    "prepare_responses_input",
-    "resolve_compact_threshold",
-    "responses_state_context_tokens",
-    "responses_state_items",
-    "responses_state_matches",
     "FINISH_REASON_MAP",
 ]

nanobot/providers/openai_responses/converters.py

@@ -12,11 +12,7 @@ def _as_json_object(value: object) -> dict[str, Any] | None:
     return cast(dict[str, Any], value) if isinstance(value, dict) else None
 
 
-def convert_messages(
-    messages: list[dict[str, Any]],
-    *,
-    preserve_reasoning: bool = False,
-) -> tuple[str, list[dict[str, Any]]]:
+def convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str, Any]]]:
     """Convert Chat Completions messages to Responses API input items.
 
     Returns ``(system_prompt, input_items)`` where *system_prompt* is extracted
@@ -40,13 +36,6 @@ def convert_messages(
             continue
 
         if role == "assistant":
-            if preserve_reasoning:
-                reasoning = msg.get("reasoning_content")
-                if isinstance(reasoning, str) and reasoning:
-                    input_items.append({
-                        "type": "reasoning",
-                        "content": reasoning,
-                    })
             if isinstance(content, str) and content:
                 message_id = _unique_item_id(f"msg_{idx}", used_item_ids)
                 input_items.append({

nanobot/providers/openai_responses/parsing.py

@@ -4,14 +4,12 @@ from __future__ import annotations
 
 import json
 from collections.abc import Awaitable, Callable
-from dataclasses import dataclass, field
 from typing import Any, AsyncGenerator, cast
 
 import httpx
 from loguru import logger
 
 from nanobot.providers.base import LLMResponse, ToolCallRequest, parse_tool_arguments
-from nanobot.providers.openai_responses.state import build_responses_state
 
 FINISH_REASON_MAP = {
     "completed": "stop",
@@ -19,42 +17,6 @@ FINISH_REASON_MAP = {
     "failed": "error",
     "cancelled": "error",
 }
-REPLAYABLE_FINISH_REASONS = frozenset({"stop", "tool_calls", "function_call"})
-
-
-@dataclass(slots=True)
-class ResponsesStreamCapture:
-    """Losslessly capture terminal output items without changing stream results."""
-
-    completed: bool = False
-    response: dict[str, Any] | None = field(default=None, repr=False)
-    _items_by_index: dict[int, dict[str, Any]] = field(default_factory=dict, repr=False)
-
-    def record_output_item(self, index: object, item: object) -> None:
-        item_object = _response_object(item)
-        if item_object is None:
-            return
-        output_index = (
-            index
-            if isinstance(index, int) and not isinstance(index, bool)
-            else len(self._items_by_index)
-        )
-        self._items_by_index[output_index] = item_object
-
-    def record_completed(self, response: object) -> None:
-        response_object = _response_object(response)
-        if response_object is None:
-            return
-        self.completed = True
-        self.response = response_object
-
-    @property
-    def output_items(self) -> list[dict[str, Any]]:
-        if self.response is not None:
-            output = _response_object_list(self.response.get("output"))
-            if output:
-                return output
-        return [self._items_by_index[index] for index in sorted(self._items_by_index)]
 
 
 def _as_json_object(value: object) -> dict[str, Any] | None:
@@ -69,9 +31,7 @@ def _response_object(value: object) -> dict[str, Any] | None:
         return object_value
     dump = getattr(value, "model_dump", None)
     if callable(dump):
-        dumped = _as_json_object(dump())
-        if dumped is not None:
-            return dumped
+        return _as_json_object(dump())
     try:
         return _as_json_object(vars(value))
     except TypeError:
@@ -94,27 +54,6 @@ def map_finish_reason(status: str | None) -> str:
     return FINISH_REASON_MAP.get(status or "completed", "stop")
 
 
-def is_replayable_finish_reason(finish_reason: str) -> bool:
-    """Return whether a response can safely advance opaque conversation state."""
-    return finish_reason in REPLAYABLE_FINISH_REASONS
-
-
-def _response_finish_reason(
-    response: object,
-    *,
-    fallback_status: str | None = None,
-) -> str:
-    """Map terminal response details without treating content filtering as truncation."""
-    response_object = _response_object(response) or {}
-    status = response_object.get("status")
-    terminal_status = status if isinstance(status, str) else fallback_status
-    if terminal_status == "incomplete":
-        details = _response_object(response_object.get("incomplete_details"))
-        if details is not None and details.get("reason") == "content_filter":
-            return "content_filter"
-    return map_finish_reason(terminal_status)
-
-
 def _usage_from_response_obj(response: object) -> dict[str, int]:
     response_object = _response_object(response)
     usage_raw: object = (
@@ -160,47 +99,6 @@ def _tool_arguments_source(*values: Any) -> Any:
     return "{}"
 
 
-def _refusal_event_key(
-    item_id: object,
-    content_index: object,
-) -> tuple[str | None, int | None]:
-    """Identify one streamed refusal content part across delta/done events."""
-    return (
-        item_id if isinstance(item_id, str) else None,
-        (
-            content_index
-            if isinstance(content_index, int) and not isinstance(content_index, bool)
-            else None
-        ),
-    )
-
-
-def _remaining_refusal_text(streamed_text: str, refusal_text: str) -> str:
-    """Return only text not already surfaced by refusal deltas."""
-    if not streamed_text:
-        return refusal_text
-    if refusal_text.startswith(streamed_text):
-        return refusal_text[len(streamed_text):]
-    return ""
-
-
-def _extract_refusal_text_from_output(output: object) -> tuple[bool, str]:
-    """Extract refusal content from terminal Responses output items."""
-    refusal_seen = False
-    parts: list[str] = []
-    for item in _response_object_list(output):
-        if item.get("type") != "message":
-            continue
-        for block in _response_object_list(item.get("content")):
-            if block.get("type") != "refusal":
-                continue
-            refusal_seen = True
-            refusal_text = block.get("refusal")
-            if isinstance(refusal_text, str):
-                parts.append(refusal_text)
-    return refusal_seen, "".join(parts)
-
-
 async def iter_sse(response: httpx.Response) -> AsyncGenerator[dict[str, Any], None]:
     """Yield parsed JSON events from a Responses API SSE stream."""
     buffer: list[str] = []
@@ -255,7 +153,6 @@ async def consume_sse_with_reasoning(
     on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
     on_reasoning_delta: Callable[[str], Awaitable[None]] | None = None,
     on_response_event: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-    capture: ResponsesStreamCapture | None = None,
 ) -> tuple[str, list[ToolCallRequest], str, dict[str, int], str | None]:
     """Consume a Responses API SSE stream, including visible reasoning summaries."""
     content = ""
@@ -266,9 +163,6 @@ async def consume_sse_with_reasoning(
     usage: dict[str, int] = {}
     reasoning_content: str | None = None
     streamed_reasoning = False
-    refusal_seen = False
-    refusal_deltas: dict[tuple[str | None, int | None], str] = {}
-    emitted_refusal_text = ""
 
     async for event in iter_sse(response):
         if on_response_event:
@@ -297,33 +191,6 @@ async def consume_sse_with_reasoning(
             content += delta_text
             if on_content_delta and delta_text:
                 await on_content_delta(delta_text)
-        elif event_type == "response.refusal.delta":
-            refusal_seen = True
-            delta_text = event.get("delta")
-            if isinstance(delta_text, str) and delta_text:
-                key = _refusal_event_key(
-                    event.get("item_id"),
-                    event.get("content_index"),
-                )
-                refusal_deltas[key] = refusal_deltas.get(key, "") + delta_text
-                content += delta_text
-                emitted_refusal_text += delta_text
-                if on_content_delta:
-                    await on_content_delta(delta_text)
-        elif event_type == "response.refusal.done":
-            refusal_seen = True
-            refusal_text = event.get("refusal")
-            key = _refusal_event_key(
-                event.get("item_id"),
-                event.get("content_index"),
-            )
-            streamed_text = refusal_deltas.pop(key, "")
-            if isinstance(refusal_text, str) and refusal_text:
-                remaining_text = _remaining_refusal_text(streamed_text, refusal_text)
-                content += remaining_text
-                emitted_refusal_text += remaining_text
-                if on_content_delta and remaining_text:
-                    await on_content_delta(remaining_text)
         elif event_type == "response.reasoning_summary_text.delta":
             delta_text = event.get("delta") or ""
             if delta_text:
@@ -372,8 +239,6 @@ async def consume_sse_with_reasoning(
                     })
         elif event_type == "response.output_item.done":
             item = _as_json_object(event.get("item")) or {}
-            if capture is not None:
-                capture.record_output_item(event.get("output_index"), item)
             if item.get("type") == "function_call":
                 call_id = item.get("call_id")
                 if not call_id:
@@ -404,28 +269,11 @@ async def consume_sse_with_reasoning(
                     reasoning_content = summary
                     if on_reasoning_delta:
                         await on_reasoning_delta(summary)
-        elif event_type in {"response.completed", "response.incomplete"}:
+        elif event_type == "response.completed":
             response_obj = _response_object(event.get("response")) or {}
-            if capture is not None:
-                capture.record_completed(response_obj)
-            finish_reason = _response_finish_reason(
-                response_obj,
-                fallback_status=event_type.removeprefix("response."),
-            )
+            status = response_obj.get("status")
+            finish_reason = map_finish_reason(status)
             usage = _usage_from_response_obj(response_obj) or usage
-            terminal_refusal, terminal_refusal_text = _extract_refusal_text_from_output(
-                response_obj.get("output")
-            )
-            if terminal_refusal:
-                refusal_seen = True
-                remaining_text = _remaining_refusal_text(
-                    emitted_refusal_text,
-                    terminal_refusal_text,
-                )
-                content += remaining_text
-                emitted_refusal_text += remaining_text
-                if on_content_delta and remaining_text:
-                    await on_content_delta(remaining_text)
             if not reasoning_content:
                 summary = _extract_reasoning_summary_from_output(response_obj.get("output"))
                 if summary:
@@ -436,8 +284,6 @@ async def consume_sse_with_reasoning(
             detail = event.get("error") or event.get("message") or event
             raise RuntimeError(f"Response failed: {str(detail)[:500]}")
 
-    if refusal_seen:
-        finish_reason = "refusal"
     return content, tool_calls, finish_reason, usage, reasoning_content
 
 
@@ -446,14 +292,6 @@ def _extract_reasoning_summary_from_output(output: object) -> str | None:
     for item in _response_object_list(output):
         if item.get("type") != "reasoning":
             continue
-        content = item.get("content")
-        if isinstance(content, str) and content:
-            parts.append(content)
-        elif isinstance(content, list):
-            for block in _response_object_list(cast(list[object], content)):
-                text = block.get("text")
-                if isinstance(text, str) and text:
-                    parts.append(text)
         for summary in _response_object_list(item.get("summary")):
             if summary.get("type") == "summary_text" and summary.get("text"):
                 text = summary.get("text")
@@ -462,13 +300,7 @@ def _extract_reasoning_summary_from_output(output: object) -> str | None:
     return "".join(parts) or None
 
 
-def parse_response_output(
-    response: object,
-    *,
-    state_provider: str | None = None,
-    state_model: str | None = None,
-    state_input_items: list[dict[str, Any]] | None = None,
-) -> LLMResponse:
+def parse_response_output(response: object) -> LLMResponse:
     """Parse an SDK ``Response`` object into an ``LLMResponse``."""
     response_object = _response_object(response) or {}
 
@@ -476,26 +308,21 @@ def parse_response_output(
     content_parts: list[str] = []
     tool_calls: list[ToolCallRequest] = []
     reasoning_content: str | None = None
-    refusal_seen = False
 
     for item in output:
         item_type = item.get("type")
         if item_type == "message":
             for block in _response_object_list(item.get("content")):
-                block_type = block.get("type")
-                if block_type == "output_text":
+                if block.get("type") == "output_text":
                     text = block.get("text")
                     if isinstance(text, str):
                         content_parts.append(text)
-                elif block_type == "refusal":
-                    refusal_seen = True
-                    refusal = block.get("refusal")
-                    if isinstance(refusal, str):
-                        content_parts.append(refusal)
         elif item_type == "reasoning":
-            text = _extract_reasoning_summary_from_output([item])
-            if text:
-                reasoning_content = (reasoning_content or "") + text
+            for s in _response_object_list(item.get("summary")):
+                if s.get("type") == "summary_text" and s.get("text"):
+                    text = s.get("text")
+                    if isinstance(text, str):
+                        reasoning_content = (reasoning_content or "") + text
         elif item_type == "function_call":
             call_id = item.get("call_id") or ""
             item_id = item.get("id") or "fc_0"
@@ -510,38 +337,21 @@ def parse_response_output(
     usage = _usage_from_response_obj(response_object)
 
     status = response_object.get("status")
-    finish_reason = "refusal" if refusal_seen else _response_finish_reason(response_object)
+    finish_reason = map_finish_reason(status if isinstance(status, str) else None)
 
-    result = LLMResponse(
+    return LLMResponse(
         content="".join(content_parts) or None,
         tool_calls=tool_calls,
         finish_reason=finish_reason,
         usage=usage,
         reasoning_content=reasoning_content if isinstance(reasoning_content, str) else None,
     )
-    if (
-        state_provider is not None
-        and state_model is not None
-        and state_input_items is not None
-        and (status is None or status == "completed")
-        and is_replayable_finish_reason(finish_reason)
-    ):
-        result.provider_state = build_responses_state(
-            provider=state_provider,
-            model=state_model,
-            input_items=state_input_items,
-            output_items=output,
-            usage=usage,
-        )
-    return result
 
 
 async def consume_sdk_stream(
     stream: Any,
     on_content_delta: Callable[[str], Awaitable[None]] | None = None,
     on_tool_call_delta: Callable[[dict[str, Any]], Awaitable[None]] | None = None,
-    on_reasoning_delta: Callable[[str], Awaitable[None]] | None = None,
-    capture: ResponsesStreamCapture | None = None,
 ) -> tuple[str, list[ToolCallRequest], str, dict[str, int], str | None]:
     """Consume an SDK async stream from ``client.responses.create(stream=True)``."""
     content = ""
@@ -551,10 +361,6 @@ async def consume_sdk_stream(
     finish_reason = "stop"
     usage: dict[str, int] = {}
     reasoning_content: str | None = None
-    streamed_reasoning = False
-    refusal_seen = False
-    refusal_deltas: dict[tuple[str | None, int | None], str] = {}
-    emitted_refusal_text = ""
 
     async for raw_event in stream:
         event: Any = raw_event
@@ -582,46 +388,6 @@ async def consume_sdk_stream(
             content += delta_text
             if on_content_delta and delta_text:
                 await on_content_delta(delta_text)
-        elif event_type == "response.reasoning_text.delta":
-            delta_text = getattr(event, "delta", "") or ""
-            if delta_text:
-                reasoning_content = (reasoning_content or "") + delta_text
-                streamed_reasoning = True
-                if on_reasoning_delta:
-                    await on_reasoning_delta(delta_text)
-        elif event_type == "response.reasoning_text.done":
-            text = getattr(event, "text", "") or ""
-            if text and not streamed_reasoning and not reasoning_content:
-                reasoning_content = text
-                if on_reasoning_delta:
-                    await on_reasoning_delta(text)
-        elif event_type == "response.refusal.delta":
-            refusal_seen = True
-            delta_text = getattr(event, "delta", None)
-            if isinstance(delta_text, str) and delta_text:
-                key = _refusal_event_key(
-                    getattr(event, "item_id", None),
-                    getattr(event, "content_index", None),
-                )
-                refusal_deltas[key] = refusal_deltas.get(key, "") + delta_text
-                content += delta_text
-                emitted_refusal_text += delta_text
-                if on_content_delta:
-                    await on_content_delta(delta_text)
-        elif event_type == "response.refusal.done":
-            refusal_seen = True
-            refusal_text = getattr(event, "refusal", None)
-            key = _refusal_event_key(
-                getattr(event, "item_id", None),
-                getattr(event, "content_index", None),
-            )
-            streamed_text = refusal_deltas.pop(key, "")
-            if isinstance(refusal_text, str) and refusal_text:
-                remaining_text = _remaining_refusal_text(streamed_text, refusal_text)
-                content += remaining_text
-                emitted_refusal_text += remaining_text
-                if on_content_delta and remaining_text:
-                    await on_content_delta(remaining_text)
         elif event_type == "response.function_call_arguments.delta":
             call_id = getattr(event, "call_id", None)
             if call_id and call_id in tool_call_buffers:
@@ -650,8 +416,6 @@ async def consume_sdk_stream(
                     })
         elif event_type == "response.output_item.done":
             item = getattr(event, "item", None)
-            if capture is not None:
-                capture.record_output_item(getattr(event, "output_index", None), item)
             if item and getattr(item, "type", None) == "function_call":
                 call_id = getattr(item, "call_id", None)
                 if not call_id:
@@ -679,31 +443,10 @@ async def consume_sdk_stream(
                         arguments=args,
                     )
                 )
-        elif event_type in {"response.completed", "response.incomplete"}:
+        elif event_type == "response.completed":
             resp = getattr(event, "response", None)
-            response_obj = _response_object(resp) or {}
-            if capture is not None:
-                capture.record_completed(resp)
-            finish_reason = _response_finish_reason(
-                resp,
-                fallback_status=event_type.removeprefix("response."),
-            )
-            terminal_output = response_obj.get("output")
-            if terminal_output is None:
-                terminal_output = getattr(resp, "output", None)
-            terminal_refusal, terminal_refusal_text = _extract_refusal_text_from_output(
-                terminal_output
-            )
-            if terminal_refusal:
-                refusal_seen = True
-                remaining_text = _remaining_refusal_text(
-                    emitted_refusal_text,
-                    terminal_refusal_text,
-                )
-                content += remaining_text
-                emitted_refusal_text += remaining_text
-                if on_content_delta and remaining_text:
-                    await on_content_delta(remaining_text)
+            status = getattr(resp, "status", None) if resp else None
+            finish_reason = map_finish_reason(status)
             if resp:
                 usage_obj = getattr(resp, "usage", None)
                 if usage_obj:
@@ -712,16 +455,15 @@ async def consume_sdk_stream(
                         "completion_tokens": int(getattr(usage_obj, "output_tokens", 0) or 0),
                         "total_tokens": int(getattr(usage_obj, "total_tokens", 0) or 0),
                     }
-                if not reasoning_content:
-                    reasoning_content = _extract_reasoning_summary_from_output(
-                        getattr(resp, "output", None)
-                    )
-                    if reasoning_content and on_reasoning_delta:
-                        await on_reasoning_delta(reasoning_content)
+                for out_item in cast(list[Any], getattr(resp, "output", None) or []):
+                    if getattr(out_item, "type", None) == "reasoning":
+                        for s in cast(list[Any], getattr(out_item, "summary", None) or []):
+                            if getattr(s, "type", None) == "summary_text":
+                                text = getattr(s, "text", None)
+                                if text:
+                                    reasoning_content = (reasoning_content or "") + text
         elif event_type in {"error", "response.failed"}:
             detail = getattr(event, "error", None) or getattr(event, "message", None) or event
             raise RuntimeError(f"Response failed: {str(detail)[:500]}")
 
-    if refusal_seen:
-        finish_reason = "refusal"
     return content, tool_calls, finish_reason, usage, reasoning_content

nanobot/providers/openai_responses/state.py

@@ -1,204 +0,0 @@
-"""Opaque conversation state for Responses API item replay."""
-
-from __future__ import annotations
-
-from copy import deepcopy
-from typing import Any, cast
-
-from loguru import logger
-
-from nanobot.providers.base import ProviderConversationState
-from nanobot.providers.openai_responses.converters import convert_messages
-
-RESPONSES_STATE_KIND = "openai_responses"
-RESPONSES_STATE_VERSION = 1
-_ITEMS_KEY = "items"
-_CONTEXT_TOKENS_KEY = "context_tokens"
-_COMPACTION_ITEM_TYPES = frozenset({
-    "compaction",
-    "compaction_summary",
-    "context_compaction",
-})
-
-
-def responses_state_matches(
-    state: ProviderConversationState,
-    *,
-    provider: str,
-    model: str,
-) -> bool:
-    """Return whether *state* belongs to this exact Responses endpoint/model."""
-    return (
-        state.kind == RESPONSES_STATE_KIND
-        and state.version == RESPONSES_STATE_VERSION
-        and state.provider == provider
-        and state.model == model
-        and _state_items(state) is not None
-    )
-
-
-def prepare_responses_input(
-    messages: list[dict[str, Any]],
-    *,
-    state: ProviderConversationState | None,
-    provider: str,
-    model: str,
-    preserve_reasoning: bool = False,
-) -> tuple[str, list[dict[str, Any]], bool]:
-    """Build a request from exact prior items plus only newly appended messages.
-
-    The full Chat transcript remains the source for the current instructions.
-    When no compatible state exists, it is converted normally as a safe
-    fallback.
-    """
-    instructions, fallback_items = convert_messages(
-        messages,
-        preserve_reasoning=preserve_reasoning,
-    )
-    if state is None or not responses_state_matches(
-        state,
-        provider=provider,
-        model=model,
-    ):
-        return instructions, fallback_items, False
-
-    prior_items = _state_items(state)
-    if prior_items is None:
-        return instructions, fallback_items, False
-
-    _, delta_items = convert_messages(
-        state.pending_messages,
-        preserve_reasoning=preserve_reasoning,
-    )
-    logger.debug(
-        "Replaying Responses state: prior_items={} pending_messages={}",
-        len(prior_items),
-        len(state.pending_messages),
-    )
-    return instructions, [*deepcopy(prior_items), *delta_items], True
-
-
-def build_responses_state(
-    *,
-    provider: str,
-    model: str,
-    input_items: list[dict[str, Any]],
-    output_items: list[dict[str, Any]],
-    usage: dict[str, int] | None = None,
-) -> ProviderConversationState:
-    """Create the canonical next state from request input and every output item."""
-    unpruned_items = [*input_items, *output_items]
-    items = _prune_before_latest_output_compaction(input_items, output_items)
-    if len(items) < len(unpruned_items):
-        logger.info(
-            "Installed Responses compaction: dropped_items={} retained_items={}",
-            len(unpruned_items) - len(items),
-            len(items),
-        )
-    payload: dict[str, Any] = {_ITEMS_KEY: deepcopy(items)}
-    context_tokens = _context_tokens_from_usage(usage)
-    if context_tokens > 0:
-        payload[_CONTEXT_TOKENS_KEY] = context_tokens
-    return ProviderConversationState(
-        kind=RESPONSES_STATE_KIND,
-        provider=provider,
-        model=model,
-        version=RESPONSES_STATE_VERSION,
-        payload=payload,
-    )
-
-
-def responses_state_items(
-    state: ProviderConversationState,
-) -> list[dict[str, Any]] | None:
-    """Return an isolated copy of canonical input items for tests/consumers."""
-    items = _state_items(state)
-    return deepcopy(items) if items is not None else None
-
-
-def responses_state_context_tokens(state: ProviderConversationState) -> int:
-    """Return the last server-reported active context size."""
-    value = state.payload.get(_CONTEXT_TOKENS_KEY)
-    if isinstance(value, bool) or not isinstance(value, int):
-        return 0
-    return max(0, value)
-
-
-def resolve_compact_threshold(
-    context_window_tokens: int | None,
-    max_output_tokens: int,
-) -> int | None:
-    """Derive Codex-compatible 90% compaction headroom for a model window."""
-    if context_window_tokens is None or context_window_tokens <= 0:
-        return None
-    ninety_percent = max(1, context_window_tokens * 9 // 10)
-    output_headroom = max(1, context_window_tokens - max(1, max_output_tokens))
-    return min(ninety_percent, output_headroom)
-
-
-def is_compaction_compatibility_error(exc: Exception) -> bool:
-    """Recognize endpoints that reject native Responses compaction fields."""
-    if getattr(exc, "compaction_unsupported", False) is True:
-        return True
-    response = getattr(exc, "response", None)
-    status_code = getattr(exc, "status_code", None)
-    if status_code is None and response is not None:
-        status_code = getattr(response, "status_code", None)
-    body = (
-        getattr(exc, "body", None)
-        or getattr(exc, "doc", None)
-        or getattr(response, "text", None)
-        or str(exc)
-    )
-    text = str(body).lower()
-    has_compaction_marker = any(
-        marker in text
-        for marker in ("context_management", "compact_threshold", "compaction_trigger")
-    )
-    if not has_compaction_marker:
-        return False
-    return isinstance(exc, TypeError) or status_code in {400, 404, 422}
-
-
-def _prune_before_latest_output_compaction(
-    input_items: list[dict[str, Any]],
-    output_items: list[dict[str, Any]],
-) -> list[dict[str, Any]]:
-    """Drop old input only when this response emits a new compaction item.
-
-    A canonical compacted input may intentionally retain messages before its
-    compaction item. Those messages must survive ordinary subsequent responses.
-    """
-    latest = None
-    for index, item in enumerate(output_items):
-        if item.get("type") in _COMPACTION_ITEM_TYPES:
-            latest = index
-    if latest is None:
-        return [*input_items, *output_items]
-    return output_items[latest:]
-
-
-def _context_tokens_from_usage(usage: dict[str, int] | None) -> int:
-    if not usage:
-        return 0
-    prompt_tokens = usage.get("prompt_tokens", 0)
-    completion_tokens = usage.get("completion_tokens", 0)
-    total_tokens = usage.get("total_tokens", 0)
-    values = (prompt_tokens, completion_tokens, total_tokens)
-    if any(isinstance(value, bool) for value in values):
-        return 0
-    return max(0, total_tokens or prompt_tokens + completion_tokens)
-
-
-def _state_items(
-    state: ProviderConversationState,
-) -> list[dict[str, Any]] | None:
-    raw_items = state.payload.get(_ITEMS_KEY)
-    if not isinstance(raw_items, list):
-        return None
-    items: list[dict[str, Any]] = []
-    for raw in cast(list[object], raw_items):
-        if not isinstance(raw, dict):
-            return None
-        items.append(cast(dict[str, Any], raw))
-    return items

nanobot/providers/registry.py

@@ -111,11 +111,6 @@ class ProviderSpec:
     # Substring match against the wire model name (lowercased).
     implicit_reasoning_models: tuple[str, ...] = ()
 
-    # Models that expose the OpenAI Responses wire format.  This is model-level
-    # because providers may add Responses support incrementally (DeepSeek V4
-    # Flash is supported before V4 Pro).
-    responses_models: tuple[str, ...] = ()
-
     # When the model returns content as a list of {"type":"thinking",...} +
     # {"type":"text",...} blocks, extract the thinking text into
     # reasoning_content. Mistral's Magistral / reasoning-enabled responses use
@@ -466,7 +461,6 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         backend="openai_compat",
         default_api_base="https://api.deepseek.com",
         thinking_style="thinking_type",
-        responses_models=("deepseek-v4-flash",),
     ),
     # Gemini: Google's OpenAI-compatible endpoint
     ProviderSpec(

nanobot/security/network.py

@@ -12,6 +12,7 @@ from urllib.parse import urlparse
 from urllib.request import getproxies, proxy_bypass
 
 import httpx
+import httpx2
 
 _BLOCKED_NETWORKS = [
     ipaddress.ip_network("0.0.0.0/8"),
@@ -29,6 +30,7 @@ _BLOCKED_NETWORKS = [
 
 _URL_RE = re.compile(r"https?://[^\s\"'`;|<>]+", re.IGNORECASE)
 _allowed_networks: list[ipaddress.IPv4Network | ipaddress.IPv6Network] = []
+_DNS_PIN_RESOLVER_LOCK = asyncio.Lock()
 
 
 def is_loopback_host(host: str) -> bool:
@@ -195,6 +197,30 @@ def httpx_env_proxy_mounts() -> dict[str, httpx.AsyncBaseTransport | None]:
     return mounts
 
 
+def httpx2_env_proxy_mounts() -> dict[str, httpx2.AsyncBaseTransport | None]:
+    """Build HTTPX2 proxy mounts while leaving direct routes to the base transport."""
+    proxies = getproxies()
+    mounts: dict[str, httpx2.AsyncBaseTransport | None] = {}
+    for scheme in ("http", "https", "all"):
+        proxy_url = proxies.get(scheme)
+        if proxy_url:
+            if "://" not in proxy_url:
+                proxy_url = f"http://{proxy_url}"
+            mounts[f"{scheme}://"] = httpx2.AsyncHTTPTransport(proxy=httpx2.Proxy(proxy_url))
+
+    if not mounts:
+        return {}
+
+    no_proxy = proxies.get("no", "")
+    if no_proxy == "*":
+        return {}
+    for entry in no_proxy.split(","):
+        pattern = _no_proxy_mount_pattern(entry.strip())
+        if pattern:
+            mounts[pattern] = None
+    return mounts
+
+
 def _no_proxy_mount_pattern(hostname: str) -> str | None:
     if not hostname:
         return None
@@ -264,7 +290,7 @@ class UnsafeURLRequestError(httpx.RequestError):
 class PinnedDNSAsyncTransport(httpx.AsyncBaseTransport):
     """HTTPX transport that pins each request to the IPs validated for its URL."""
 
-    _resolver_lock = asyncio.Lock()
+    _resolver_lock = _DNS_PIN_RESOLVER_LOCK
 
     def __init__(
         self,
@@ -288,6 +314,37 @@ class PinnedDNSAsyncTransport(httpx.AsyncBaseTransport):
         await self._inner.aclose()
 
 
+class Httpx2UnsafeURLRequestError(httpx2.RequestError):
+    """Raised when an HTTPX2 request is rejected by URL safety validation."""
+
+
+class Httpx2PinnedDNSAsyncTransport(httpx2.AsyncBaseTransport):
+    """HTTPX2 transport that pins each request to the IPs validated for its URL."""
+
+    _resolver_lock = _DNS_PIN_RESOLVER_LOCK
+
+    def __init__(
+        self,
+        *,
+        allow_loopback: bool = False,
+        inner: httpx2.AsyncBaseTransport | None = None,
+    ) -> None:
+        self._allow_loopback = allow_loopback
+        self._inner = inner or httpx2.AsyncHTTPTransport()
+
+    async def handle_async_request(self, request: httpx2.Request) -> httpx2.Response:
+        url = str(request.url)
+        ok, error, resolved_ips = resolve_url_target(url, allow_loopback=self._allow_loopback)
+        if not ok:
+            raise Httpx2UnsafeURLRequestError(error, request=request)
+        async with self._resolver_lock:
+            with pin_resolved_url_dns(url, resolved_ips):
+                return await self._inner.handle_async_request(request)
+
+    async def aclose(self) -> None:
+        await self._inner.aclose()
+
+
 def validate_resolved_url(url: str) -> tuple[bool, str]:
     """Validate an already-fetched URL (e.g. after redirect). Only checks the IP, skips DNS."""
     try:

nanobot/session/manager.py

@@ -17,7 +17,6 @@ from weakref import WeakValueDictionary
 from loguru import logger
 
 from nanobot.config.paths import get_legacy_sessions_dir
-from nanobot.providers.base import ProviderConversationState
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_HISTORY_META,
     public_history_message,
@@ -44,10 +43,6 @@ _SESSION_PREVIEW_MAX_CHARS = 120
 _SESSION_LIST_PREVIEW_MAX_RECORDS = 200
 _SESSION_LIST_PREVIEW_MAX_CHARS = 1_000_000
 _SESSION_DATA_ERRORS = (ValueError, TypeError, AttributeError, KeyError)
-_PROVIDER_STATE_RECORD_TYPE = "provider_state"
-_PROVIDER_STATE_RECORD_PREFIX_RE = re.compile(
-    r'^\s*\{\s*"_type"\s*:\s*"provider_state"\s*(?:,|\})'
-)
 _FORK_VOLATILE_METADATA_KEYS = {
     "goal_state",
     "pending_user_turn",
@@ -65,11 +60,6 @@ def _json_object(value: object) -> dict[str, Any]:
     return cast(dict[str, Any], value)
 
 
-def _is_provider_state_record_line(line: str) -> bool:
-    """Recognize the canonical private record without decoding its opaque payload."""
-    return _PROVIDER_STATE_RECORD_PREFIX_RE.match(line) is not None
-
-
 def replay_max_messages_for_context(context_window_tokens: int | None) -> int:
     if not context_window_tokens or context_window_tokens <= 0:
         return FILE_MAX_MESSAGES
@@ -156,14 +146,10 @@ class Session:
     updated_at: datetime = field(default_factory=datetime.now)
     metadata: dict[str, Any] = field(default_factory=dict)
     last_consolidated: int = 0  # Number of messages already consolidated to files
-    provider_state: ProviderConversationState | None = field(default=None, repr=False)
-    transient: bool = field(default=False, repr=False, compare=False)
 
     def __post_init__(self) -> None:
         if not isinstance(cast(object, self.metadata), dict):
             self.metadata = {}
-        if not isinstance(cast(object, self.provider_state), ProviderConversationState):
-            self.provider_state = None
         # An out-of-range offset (corrupt metadata) would hide all history; reset it.
         last_consolidated = cast(object, self.last_consolidated)
         if (
@@ -318,7 +304,6 @@ class Session:
         """Clear all messages and reset session to initial state."""
         self.messages = []
         self.last_consolidated = 0
-        self.provider_state = None
         self.updated_at = datetime.now()
         self.metadata.pop("_last_summary", None)
 
@@ -411,8 +396,6 @@ class Session:
 
         self.messages = retained
         self.last_consolidated = new_lc
-        if dropped:
-            self.provider_state = None
         self.updated_at = datetime.now()
         return RetentionResult(
             dropped=dropped,
@@ -534,7 +517,6 @@ class JsonlSessionStore:
             created_at: datetime | None = None
             updated_at: datetime | None = None
             last_consolidated = 0
-            provider_state: ProviderConversationState | None = None
 
             with open(path, encoding="utf-8") as f:
                 for line in f:
@@ -545,8 +527,7 @@ class JsonlSessionStore:
                     raw_data: object = json.loads(line)
                     data = _json_object(raw_data)
 
-                    record_type = data.get("_type")
-                    if record_type == "metadata":
+                    if data.get("_type") == "metadata":
                         metadata_value = cast(object, data.get("metadata", {}))
                         metadata = (
                             cast(dict[str, Any], metadata_value)
@@ -571,10 +552,6 @@ class JsonlSessionStore:
                             if isinstance(offset, int) and not isinstance(offset, bool)
                             else 0
                         )
-                    elif record_type == _PROVIDER_STATE_RECORD_TYPE:
-                        provider_state = ProviderConversationState.from_private_record(
-                            data.get("state")
-                        )
                     else:
                         messages.append(data)
 
@@ -585,7 +562,6 @@ class JsonlSessionStore:
                 updated_at=updated_at or datetime.now(),
                 metadata=metadata,
                 last_consolidated=last_consolidated,
-                provider_state=provider_state,
             )
         except _SESSION_DATA_ERRORS as e:
             logger.warning("Failed to load session {}: {}", key, e)
@@ -610,7 +586,6 @@ class JsonlSessionStore:
             created_at: datetime | None = None
             updated_at: datetime | None = None
             last_consolidated = 0
-            provider_state: ProviderConversationState | None = None
             skipped = 0
 
             with open(path, encoding="utf-8") as f:
@@ -628,8 +603,7 @@ class JsonlSessionStore:
                         continue
                     data = cast(dict[str, Any], raw_data)
 
-                    record_type = data.get("_type")
-                    if record_type == "metadata":
+                    if data.get("_type") == "metadata":
                         metadata_value = cast(object, data.get("metadata", {}))
                         metadata = (
                             cast(dict[str, Any], metadata_value)
@@ -650,21 +624,13 @@ class JsonlSessionStore:
                             if isinstance(offset, int) and not isinstance(offset, bool)
                             else 0
                         )
-                    elif record_type == _PROVIDER_STATE_RECORD_TYPE:
-                        candidate = ProviderConversationState.from_private_record(
-                            data.get("state")
-                        )
-                        if candidate is None:
-                            skipped += 1
-                        else:
-                            provider_state = candidate
                     else:
                         messages.append(data)
 
             if skipped:
                 logger.warning("Skipped {} corrupt lines in session {}", skipped, key)
 
-            if not messages and not metadata and provider_state is None:
+            if not messages and not metadata:
                 return None
 
             return Session(
@@ -674,7 +640,6 @@ class JsonlSessionStore:
                 updated_at=updated_at or datetime.now(),
                 metadata=metadata,
                 last_consolidated=last_consolidated,
-                provider_state=provider_state,
             )
         except _SESSION_DATA_ERRORS as e:
             logger.warning("Repair failed for session {}: {}", key, e)
@@ -705,12 +670,6 @@ class JsonlSessionStore:
                     "last_consolidated": session.last_consolidated,
                 }
                 f.write(json.dumps(metadata_line, ensure_ascii=False) + "\n")
-                if session.provider_state is not None:
-                    provider_state_line = {
-                        "_type": _PROVIDER_STATE_RECORD_TYPE,
-                        "state": session.provider_state.to_private_record(),
-                    }
-                    f.write(json.dumps(provider_state_line, ensure_ascii=False) + "\n")
                 for msg in session.messages:
                     f.write(json.dumps(msg, ensure_ascii=False) + "\n")
                 if fsync:
@@ -767,8 +726,7 @@ class JsonlSessionStore:
                         continue
                     raw_data: object = json.loads(line)
                     data = _json_object(raw_data)
-                    record_type = data.get("_type")
-                    if record_type == "metadata":
+                    if data.get("_type") == "metadata":
                         metadata_value = cast(object, data.get("metadata", {}))
                         metadata = (
                             cast(dict[str, Any], metadata_value)
@@ -787,8 +745,6 @@ class JsonlSessionStore:
                         stored_key = (
                             stored_key_value if isinstance(stored_key_value, str) else None
                         )
-                    elif record_type == _PROVIDER_STATE_RECORD_TYPE:
-                        continue
                     else:
                         messages.append(data)
             return {
@@ -881,8 +837,6 @@ class JsonlSessionStore:
                             for line in f:
                                 if not line.strip():
                                     continue
-                                if _is_provider_state_record_line(line):
-                                    continue
                                 scanned_records += 1
                                 scanned_chars += len(line)
                                 if (
@@ -892,10 +846,7 @@ class JsonlSessionStore:
                                     break
                                 raw_item: object = json.loads(line)
                                 item = _json_object(raw_item)
-                                if item.get("_type") in {
-                                    "metadata",
-                                    _PROVIDER_STATE_RECORD_TYPE,
-                                }:
+                                if item.get("_type") == "metadata":
                                     continue
                                 text = _message_preview_text(item)
                                 if not text:
@@ -965,7 +916,6 @@ class SessionManager:
         self._cache: OrderedDict[str, Session] = OrderedDict()
         # Preserve identity for sessions held by active callers without retaining idle ones.
         self._overflow_cache: WeakValueDictionary[str, Session] = WeakValueDictionary()
-        self._transient_sessions: dict[str, Session] = {}
         self._max_cached_sessions = SESSION_CACHE_MAX_SIZE
         self._file_cap_archiver: Callable[..., None] | None = None
 
@@ -979,10 +929,6 @@ class SessionManager:
             self._overflow_cache[key] = evicted
 
     def _cached(self, key: str) -> Session | None:
-        transient = self._transient_sessions.get(key)
-        if transient is not None:
-            return transient
-
         session = self._cache.get(key)
         if session is not None:
             self._cache.move_to_end(key)
@@ -1059,24 +1005,6 @@ class SessionManager:
         self._remember(session)
         return session
 
-    def get_or_create_transient(self, key: str) -> Session:
-        """Return an active in-memory session that can never reach the store."""
-        session = self._transient_sessions.get(key)
-        if session is None:
-            self._cache.pop(key, None)
-            self._overflow_cache.pop(key, None)
-            session = Session(key=key, transient=True)
-            self._transient_sessions[key] = session
-        return session
-
-    def is_transient_active(self, key: str) -> bool:
-        """Return whether *key* still accepts transient turns."""
-        return key in self._transient_sessions
-
-    def discard_transient(self, key: str) -> bool:
-        """Forget all transient contents without retaining a discarded-key tombstone."""
-        return self._transient_sessions.pop(key, None) is not None
-
     def _load(self, key: str) -> Session | None:
         return self._store.load(key)
 
@@ -1090,9 +1018,6 @@ class SessionManager:
 
     def save(self, session: Session, *, fsync: bool = False) -> None:
         """Persist a session and retain it in the cache."""
-        if session.transient is True:
-            return
-
         archiver = self._file_cap_archiver
         if archiver is not None:
             session.enforce_file_cap(
@@ -1125,7 +1050,6 @@ class SessionManager:
 
     def invalidate(self, key: str) -> None:
         """Remove a session from the in-memory cache."""
-        self._transient_sessions.pop(key, None)
         self._cache.pop(key, None)
         self._overflow_cache.pop(key, None)
 

nanobot/session/webui_turns.py

@@ -334,16 +334,6 @@ def clear_websocket_turn_if_current(
     return False
 
 
-def clear_websocket_turns(chat_id: str) -> int:
-    """Clear every in-memory lifecycle owner for a discarded chat."""
-    turns = _WEBSOCKET_ACTIVE_TURNS.pop(chat_id, None)
-    count = len(turns) if turns is not None else 0
-    _WEBSOCKET_TURN_WALL_STARTED_AT.pop(chat_id, None)
-    _WEBSOCKET_TURN_IDS.pop(chat_id, None)
-    _WEBSOCKET_TURN_OWNERS.pop(chat_id, None)
-    return count
-
-
 def build_bus_progress_callback(
     bus: MessageBus,
     msg: InboundMessage,

nanobot/utils/gitstore.py

@@ -176,10 +176,7 @@ class GitStore:
             )
             if cast(object, sha_bytes) is None:
                 return None
-            # porcelain.commit returns the id as a 40-char hex string that is
-            # already encoded to bytes; .hex() would encode those ASCII bytes
-            # again and produce an id no git command can resolve.
-            sha = sha_bytes.decode()[:8]
+            sha = sha_bytes.hex()[:8]
             logger.debug("Git auto-commit: {} ({})", sha, message)
             return sha
         except Exception as exc:
@@ -203,7 +200,7 @@ class GitStore:
                     return None
 
                 while sha:
-                    if sha.decode().startswith(short_sha):
+                    if sha.hex().startswith(short_sha):
                         return sha
                     commit_obj = repo[sha]
                     if commit_obj.type_name != b"commit":
@@ -283,7 +280,7 @@ class GitStore:
                     msg = commit.message.decode("utf-8", errors="replace").strip()
                     if message_prefix is None or msg.startswith(message_prefix):
                         entries.append(CommitInfo(
-                            sha=sha.decode()[:8],
+                            sha=sha.hex()[:8],
                             message=msg,
                             timestamp=ts,
                         ))
@@ -487,7 +484,7 @@ class GitStore:
                     with Repo(str(self._workspace)) as repo:
                         commit = cast("Commit", repo[full_sha])
                         parent = commit.parents[0] if commit.parents else None
-                    diff = self.diff_commits(parent.decode()[:8], c.sha) if parent else ""
+                    diff = self.diff_commits(parent.hex()[:8], c.sha) if parent else ""
                     return c, diff
             return None
         except Exception as exc:

nanobot/webui/gateway_services.py

@@ -2,10 +2,9 @@
 
 from __future__ import annotations
 
-from collections.abc import Awaitable, Callable
 from dataclasses import dataclass
 from pathlib import Path
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Callable
 
 from loguru import logger as default_logger
 
@@ -39,7 +38,6 @@ class GatewayServices:
     local_trigger_store: LocalTriggerStore | None
     cron_pending_job_ids: Callable[[str], set[str]] | None
     local_trigger_pending_ids: Callable[[str], set[str]] | None
-    cancel_active_turn: Callable[[str], Awaitable[int]] | None
 
 
 def build_gateway_services(
@@ -58,7 +56,6 @@ def build_gateway_services(
     local_trigger_store: LocalTriggerStore | None = None,
     cron_pending_job_ids: Callable[[str], set[str]] | None = None,
     local_trigger_pending_ids: Callable[[str], set[str]] | None = None,
-    cancel_active_turn: Callable[[str], Awaitable[int]] | None = None,
     channel_feature_action: Callable[..., Any] | None = None,
     channel_runtime_status: Callable[[], dict[str, Any]] | None = None,
     skill_state_action: Callable[[set[str]], None] | None = None,
@@ -120,5 +117,4 @@ def build_gateway_services(
         local_trigger_store=local_trigger_store,
         cron_pending_job_ids=cron_pending_job_ids,
         local_trigger_pending_ids=local_trigger_pending_ids,
-        cancel_active_turn=cancel_active_turn,
     )

nanobot/webui/session_list_index.py

@@ -18,12 +18,10 @@ from loguru import logger
 from nanobot.config.paths import get_webui_dir
 from nanobot.session.history_visibility import is_hidden_history_message
 from nanobot.session.manager import (
-    _PROVIDER_STATE_RECORD_TYPE,  # pyright: ignore[reportPrivateUsage]
     _SESSION_LIST_PREVIEW_MAX_CHARS,  # pyright: ignore[reportPrivateUsage]
     _SESSION_LIST_PREVIEW_MAX_RECORDS,  # pyright: ignore[reportPrivateUsage]
     Session,
     SessionManager,
-    _is_provider_state_record_line,  # pyright: ignore[reportPrivateUsage]
     _message_preview_text,  # pyright: ignore[reportPrivateUsage]
     _metadata_title,  # pyright: ignore[reportPrivateUsage]
 )
@@ -300,11 +298,7 @@ def _scan_session_row(session_manager: SessionManager, path: Path) -> dict[str,
             for line in f:
                 if not line.strip():
                     continue
-                if _is_provider_state_record_line(line):
-                    continue
                 item = json.loads(line)
-                if item.get("_type") == _PROVIDER_STATE_RECORD_TYPE:
-                    continue
                 timestamp = _visible_message_timestamp(item)
                 if timestamp is not None:
                     visible_message_at = _latest_updated_at(visible_message_at, timestamp)

nanobot/webui/token_usage.py

@@ -159,13 +159,6 @@ def normalize_token_usage_state(raw: Any) -> dict[str, Any]:
         if not isinstance(date, str) or len(date) != 10 or not isinstance(row_value, dict):
             continue
         row = cast(dict[str, Any], row_value)
-        try:
-            datetime.fromisoformat(date)
-        except ValueError:
-            # A hand-edited or foreign day key that is not a real date would
-            # otherwise reach token_usage_payload's date parsing and fail every
-            # settings request; drop it like any other malformed row.
-            continue
         normalized = _normalize_usage_row(row)
         if normalized["total_tokens"] <= 0 and normalized["requests"] <= 0:
             continue

nanobot/webui/transcript.py

@@ -2026,7 +2026,6 @@ def replay_transcript_to_ui_messages(
                 continue
             close_activity_for_answer()
             turn_fields = _turn_fields(rec, "answer")
-            source_fields = _source_fields(rec)
             adopted = find_active_placeholder(messages, turn_fields) if buffer_message_id is None else None
             if buffer_message_id is None:
                 if adopted:
@@ -2039,8 +2038,7 @@ def replay_transcript_to_ui_messages(
                             "role": "assistant",
                             "content": "",
                             "isStreaming": True,
-                            **turn_fields,
-                            **source_fields,
+                            **_turn_fields(rec, "answer"),
                             "createdAt": _created_at_ms(rec, idx),
                         },
                     )
@@ -2052,8 +2050,7 @@ def replay_transcript_to_ui_messages(
                         **m,
                         "content": combined,
                         "isStreaming": True,
-                        **turn_fields,
-                        **source_fields,
+                        **_turn_fields(rec, "answer"),
                     }
                     break
             continue
@@ -2065,8 +2062,6 @@ def replay_transcript_to_ui_messages(
                 continue
             merge_next = rec.get("resuming") is True and rec.get("merge_next") is True
             final_text = rec.get("text")
-            turn_fields = _turn_fields(rec, "answer")
-            source_fields = _source_fields(rec)
             if isinstance(final_text, str):
                 if buffer_message_id is None:
                     buffer_message_id = _new_id("buf", idx)
@@ -2076,8 +2071,7 @@ def replay_transcript_to_ui_messages(
                             "role": "assistant",
                             "content": final_text,
                             "isStreaming": True,
-                            **turn_fields,
-                            **source_fields,
+                            **_turn_fields(rec, "answer"),
                             "createdAt": _created_at_ms(rec, idx),
                         },
                     )
@@ -2088,21 +2082,11 @@ def replay_transcript_to_ui_messages(
                                 **m,
                                 "content": final_text,
                                 "isStreaming": True,
-                                **turn_fields,
-                                **source_fields,
+                                **_turn_fields(rec, "answer"),
                             }
                             break
                 if merge_next:
                     buffer_parts = [final_text]
-            elif source_fields and buffer_message_id is not None:
-                for i, m in enumerate(messages):
-                    if m.get("id") == buffer_message_id:
-                        messages[i] = {
-                            **m,
-                            **turn_fields,
-                            **source_fields,
-                        }
-                        break
             if not merge_next:
                 buffer_message_id = None
                 buffer_parts = []

pyproject.toml

@@ -31,6 +31,8 @@ dependencies = [
     "websockets>=15.0,<17.0",
     "websocket-client>=1.9.0,<2.0.0",
     "httpx>=0.28.0,<1.0.0",
+    # MCP v2 uses the independently versioned httpx2 package for HTTP transports.
+    "httpx2>=2.5.0,<3.0.0",
     "ddgs>=9.5.5,<10.0.0",
     "oauth-cli-kit>=0.1.6,<1.0.0",
     "loguru>=0.7.3,<1.0.0",
@@ -40,7 +42,7 @@ dependencies = [
     "croniter>=6.0.0,<7.0.0",
     "prompt-toolkit>=3.0.50,<4.0.0",
     "questionary>=2.0.0,<3.0.0",
-    "mcp>=1.26.0,<2.0.0",
+    "mcp>=2.0.0,<3.0.0",
     "json-repair>=0.57.0,<1.0.0",
     "chardet>=3.0.2,<6.0.0",
     "openai>=2.8.0",
@@ -51,7 +53,7 @@ dependencies = [
     "filelock>=3.25.2",
     "watchfiles>=1.1.1,<2.0.0",
     "packaging>=24.0",
-    "tzdata>=2025.2",
+    "tzdata>=2025.2; sys_platform == 'win32'",
     "defusedxml>=0.7.1,<1.0.0",
     "pypdf>=5.0.0,<6.0.0",
     "python-docx>=1.1.0,<2.0.0",

tests/agent/test_autocompact_unit.py

@@ -154,26 +154,6 @@ class TestIsExpired:
         now_over = datetime(2026, 1, 1, 10, 10, 0)
         assert ac._is_expired(ts, now=now_over) is True
 
-    def test_unparseable_string_timestamp_returns_false(self):
-        """A persisted timestamp that no longer parses must not raise.
-
-        list_sessions() forwards the raw persisted updated_at string, and
-        SessionManager._load already tolerates a malformed value through its
-        recovery path. The idle scan must mirror that tolerance instead of crashing.
-        """
-        ac = _make_autocompact(ttl=15)
-        assert ac._is_expired("not-a-timestamp") is False
-
-    def test_tz_aware_string_timestamp_is_compared_by_instant(self):
-        """A valid timestamp with an offset remains eligible for expiry."""
-        ac = _make_autocompact(ttl=15)
-        now = datetime(2026, 1, 1, 12, 0, 0)
-        recent = (now - timedelta(minutes=10)).astimezone().isoformat()
-        expired = (now - timedelta(minutes=20)).astimezone().isoformat()
-
-        assert ac._is_expired(recent, now=now) is False
-        assert ac._is_expired(expired, now=now) is True
-
 
 # ---------------------------------------------------------------------------
 # _format_summary
@@ -241,36 +221,6 @@ class TestCheckExpired:
         assert len(scheduled) == 1
         assert "cli:old" in ac._archiving
 
-    def test_unparseable_updated_at_does_not_stop_scan(self):
-        """A malformed timestamp is skipped without hiding later sessions.
-
-        The idle scan runs from the agent loop's inbound-timeout branch, so a
-        raised exception here would tear down the loop. list_sessions() forwards
-        the raw string, so check_expired must tolerate it like SessionManager
-        does when loading.
-        """
-        ac = _make_autocompact(ttl=15)
-        mock_sm = MagicMock(spec=SessionManager)
-        old_dt = datetime.now() - timedelta(minutes=20)
-        session = _make_session("cli:old", updated_at=old_dt)
-        _add_turns(session, 5)
-        mock_sm.list_sessions.return_value = [
-            {"key": "cli:corrupt", "updated_at": "not-a-timestamp"},
-            {"key": "cli:old", "updated_at": old_dt.isoformat()},
-        ]
-        mock_sm.get_or_create.return_value = session
-        ac.sessions = mock_sm
-        scheduled = []
-
-        def scheduler(coro):
-            scheduled.append(coro)
-            coro.close()
-
-        ac.check_expired(scheduler, _runtime)
-
-        assert len(scheduled) == 1
-        assert ac._archiving == {"cli:old"}
-
     @pytest.mark.asyncio
     async def test_runtime_is_captured_before_background_starts(self):
         ac = _make_autocompact(ttl=15)
@@ -592,58 +542,6 @@ class TestPrepareSession:
         assert summary is not None
         assert "Cold summary." in summary
 
-    def test_cold_path_tolerates_malformed_last_active(self):
-        """A malformed persisted last_active must not raise on the turn path.
-
-        prepare_session runs from _compact_session on every turn. Persisted
-        _last_summary can be hand-edited or written by another version, so a bad
-        last_active should degrade gracefully (mirror estimate_session_prompt_tokens
-        and _archive) instead of crashing the turn.
-        """
-        ac = _make_autocompact(ttl=0)
-        fallback = datetime(2026, 1, 2, 3, 4, 5)
-        session = _make_session(
-            metadata={
-                "_last_summary": {"text": "Cold summary.", "last_active": "not-a-date"},
-            },
-            updated_at=fallback,
-        )
-
-        result_session, summary = ac.prepare_session(session, "cli:test")
-
-        assert result_session is session
-        assert summary is not None
-        assert "Cold summary." in summary
-        assert fallback.isoformat() in summary
-
-    def test_cold_path_tolerates_missing_last_active(self):
-        """A _last_summary dict without last_active must not raise."""
-        ac = _make_autocompact(ttl=0)
-        fallback = datetime(2026, 1, 2, 3, 4, 5)
-        session = _make_session(
-            metadata={"_last_summary": {"text": "Cold summary."}},
-            updated_at=fallback,
-        )
-
-        result_session, summary = ac.prepare_session(session, "cli:test")
-
-        assert result_session is session
-        assert summary is not None
-        assert "Cold summary." in summary
-        assert fallback.isoformat() in summary
-
-    def test_cold_path_missing_text_returns_none(self):
-        """A _last_summary without a non-empty string text yields no summary."""
-        ac = _make_autocompact()
-        session = _make_session(metadata={
-            "_last_summary": {"last_active": datetime(2026, 1, 1).isoformat()},
-        })
-
-        result_session, summary = ac.prepare_session(session, "cli:test")
-
-        assert result_session is session
-        assert summary is None
-
     def test_no_summary_available_returns_none(self):
         """When no summary is available, should return (session, None)."""
         ac = _make_autocompact()

tests/agent/test_consolidator.py

@@ -10,11 +10,7 @@ from nanobot.agent.memory import (
     Consolidator,
     MemoryStore,
 )
-from nanobot.providers.base import (
-    GenerationSettings,
-    LLMResponse,
-    ProviderConversationState,
-)
+from nanobot.providers.base import GenerationSettings, LLMResponse
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_HISTORY_META,
     RuntimeContextBlock,
@@ -78,16 +74,6 @@ def _tool_round(call_id: str) -> list[dict]:
     ]
 
 
-def _provider_state() -> ProviderConversationState:
-    return ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={"items": []},
-    )
-
-
 class TestConsolidatorSummarize:
     async def test_archive_prompt_includes_media_breadcrumb(
         self, consolidator, mock_provider, store, runtime
@@ -399,7 +385,6 @@ class TestConsolidatorTokenBudget:
         """Old messages that cannot be replayed should be materialized first."""
         consolidator._SAFETY_BUFFER = 0
         session = Session(key="test:replay-overflow")
-        session.provider_state = _provider_state()
         for i in range(10):
             session.add_message("user", f"u{i}")
             session.add_message("assistant", f"a{i}")
@@ -419,7 +404,6 @@ class TestConsolidatorTokenBudget:
         assert archived_chunk[-1]["content"] == "a6"
         assert session.last_consolidated == 14
         assert session.metadata["_last_summary"]["text"] == "old conversation summary"
-        assert session.provider_state is None
         consolidator.sessions.save.assert_called()
 
     async def test_replay_window_overflow_extends_to_long_recent_user_turn(
@@ -495,7 +479,6 @@ class TestConsolidatorTokenBudget:
         session = MagicMock()
         session.last_consolidated = 0
         session.key = "test:key"
-        session.provider_state = _provider_state()
         session.messages = [
             {
                 "role": "user" if i in {0, 50, 61} else "assistant",
@@ -517,7 +500,6 @@ class TestConsolidatorTokenBudget:
         # pick_consolidation_boundary returns (50, tokens) — user turn at idx 50
         assert archived_chunk[0]["content"] == "m0"
         assert session.last_consolidated > 0
-        assert session.provider_state is None
 
     async def test_raw_archive_fallback_advances_last_consolidated(
         self, consolidator, runtime
@@ -628,7 +610,6 @@ class TestCompactIdleSession:
         )
         sessions = real_consolidator.sessions
         session = sessions.get_or_create("cli:test")
-        session.provider_state = _provider_state()
         old_ts = session.updated_at
         for i in range(20):
             session.add_message("user", f"user msg {i}")
@@ -646,7 +627,6 @@ class TestCompactIdleSession:
         assert len(reloaded.messages) == 40
         assert reloaded.messages[0]["content"] == "user msg 0"
         assert reloaded.last_consolidated == 32
-        assert reloaded.provider_state is None
         visible = reloaded.get_history(max_messages=40)
         assert len(visible) == 8
         assert visible[0]["content"] == "user msg 16"

tests/agent/test_context_builder.py

@@ -15,20 +15,6 @@ def _builder(tmp_path: Path, **kw) -> ContextBuilder:
     return ContextBuilder(workspace=tmp_path, **kw)
 
 
-def test_conversation_only_messages_omit_the_system_prompt(tmp_path) -> None:
-    (tmp_path / "AGENTS.md").write_text("SECRET PROJECT INSTRUCTIONS", encoding="utf-8")
-    builder = _builder(tmp_path)
-
-    messages = builder.build_messages(
-        [],
-        "hello",
-        conversation_only=True,
-    )
-
-    assert messages == [{"role": "user", "content": "hello"}]
-    assert "SECRET PROJECT INSTRUCTIONS" not in str(messages)
-
-
 # ---------------------------------------------------------------------------
 # _merge_message_content (static)
 # ---------------------------------------------------------------------------
@@ -466,20 +452,6 @@ class TestBuildMessages:
         assert "previous user message" in str(messages[1]["content"])
         assert "new message" in str(messages[1]["content"])
 
-    def test_current_message_can_be_built_without_history_merge(self, tmp_path):
-        builder = _builder(tmp_path)
-        current = builder.build_current_message(
-            "new message",
-            runtime_context_blocks=[
-                RuntimeContextBlock(source="test", content="fresh context"),
-            ],
-        )
-
-        assert current["role"] == "user"
-        assert "new message" in current["content"]
-        assert "fresh context" in current["content"]
-        assert current["_meta"]["runtime_context"]["sources"] == ["test"]
-
     def test_different_role_appended(self, tmp_path):
         builder = _builder(tmp_path)
         history = [{"role": "assistant", "content": "previous response"}]

tests/agent/test_loop_save_turn.py

@@ -1,5 +1,4 @@
 import asyncio
-import json
 from pathlib import Path
 from types import SimpleNamespace
 from unittest.mock import AsyncMock, MagicMock
@@ -20,7 +19,7 @@ from nanobot.bus.outbound_events import (
 )
 from nanobot.bus.queue import MessageBus
 from nanobot.cron.session_turns import CRON_HISTORY_META, CRON_TRIGGER_META
-from nanobot.providers.base import LLMProvider, LLMResponse, ProviderConversationState
+from nanobot.providers.base import LLMResponse
 from nanobot.providers.factory import ProviderSnapshot
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_HISTORY_META,
@@ -60,16 +59,6 @@ def _mk_loop() -> AgentLoop:
     return loop
 
 
-def _provider_state() -> ProviderConversationState:
-    return ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={"items": []},
-    )
-
-
 def _runtime_message(content, blocks: list[RuntimeContextBlock]) -> dict:
     merged, marker = append_runtime_context(content, blocks)
     assert marker is not None
@@ -505,7 +494,6 @@ def test_restore_runtime_checkpoint_rehydrates_completed_and_pending_tools() ->
     loop = _mk_loop()
     session = Session(
         key="test:checkpoint",
-        provider_state=_provider_state(),
         metadata={
             AgentLoop._RUNTIME_CHECKPOINT_KEY: {
                 "assistant_message": {
@@ -551,104 +539,6 @@ def test_restore_runtime_checkpoint_rehydrates_completed_and_pending_tools() ->
     assert session.messages[1]["tool_call_id"] == "call_done"
     assert session.messages[2]["tool_call_id"] == "call_pending"
     assert "interrupted before this tool finished" in session.messages[2]["content"].lower()
-    assert session.provider_state is None
-
-
-def test_restore_final_response_checkpoint_preserves_matching_provider_state() -> None:
-    loop = _mk_loop()
-    state = _provider_state()
-    session = Session(
-        key="test:final-checkpoint",
-        provider_state=state,
-        metadata={
-            AgentLoop._RUNTIME_CHECKPOINT_KEY: {
-                "phase": "final_response",
-                AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION_KEY: (
-                    AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION
-                ),
-                "assistant_message": {
-                    "role": "assistant",
-                    "content": "finished",
-                },
-                "completed_tool_results": [],
-                "pending_tool_calls": [],
-            }
-        },
-    )
-
-    restored = loop._restore_runtime_checkpoint(session)
-
-    assert restored is True
-    assert session.messages[-1]["content"] == "finished"
-    assert session.provider_state is state
-    assert session.metadata.get(AgentLoop._RUNTIME_CHECKPOINT_KEY) is None
-
-
-def test_restore_legacy_final_checkpoint_discards_unproven_provider_state() -> None:
-    loop = _mk_loop()
-    session = Session(
-        key="test:legacy-final-checkpoint",
-        provider_state=_provider_state(),
-        metadata={
-            AgentLoop._RUNTIME_CHECKPOINT_KEY: {
-                "phase": "final_response",
-                "assistant_message": {
-                    "role": "assistant",
-                    "content": "finished",
-                },
-                "completed_tool_results": [],
-                "pending_tool_calls": [],
-            }
-        },
-    )
-
-    restored = loop._restore_runtime_checkpoint(session)
-
-    assert restored is True
-    assert session.messages[-1]["content"] == "finished"
-    assert session.provider_state is None
-
-
-def test_restore_completed_tools_checkpoint_preserves_matching_provider_state() -> None:
-    loop = _mk_loop()
-    tool_result = {
-        "role": "tool",
-        "tool_call_id": "call_done",
-        "name": "read_file",
-        "content": "compacted result",
-    }
-    state = _provider_state().with_pending_messages([tool_result])
-    session = Session(
-        key="test:completed-tools-checkpoint",
-        provider_state=state,
-        metadata={
-            AgentLoop._RUNTIME_CHECKPOINT_KEY: {
-                "phase": "tools_completed",
-                AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION_KEY: (
-                    AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION
-                ),
-                "assistant_message": {
-                    "role": "assistant",
-                    "content": None,
-                    "tool_calls": [
-                        {
-                            "id": "call_done",
-                            "type": "function",
-                            "function": {"name": "read_file", "arguments": "{}"},
-                        }
-                    ],
-                },
-                "completed_tool_results": [tool_result],
-                "pending_tool_calls": [],
-            }
-        },
-    )
-
-    restored = loop._restore_runtime_checkpoint(session)
-
-    assert restored is True
-    assert session.messages[-1]["content"] == "compacted result"
-    assert session.provider_state is state
 
 
 def test_restore_runtime_checkpoint_dedupes_overlapping_tail() -> None:
@@ -726,55 +616,6 @@ def test_restore_runtime_checkpoint_dedupes_overlapping_tail() -> None:
     assert session.messages[2]["tool_call_id"] == "call_pending"
 
 
-@pytest.mark.asyncio
-async def test_runtime_checkpoint_keeps_provider_state_out_of_public_metadata(
-    tmp_path: Path,
-) -> None:
-    loop = _make_full_loop(tmp_path)
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={
-            "items": [
-                {
-                    "type": "reasoning",
-                    "encrypted_content": "private-checkpoint-blob",
-                }
-            ]
-        },
-    )
-    loop.provider.can_resume_conversation_state.return_value = True
-    loop.provider.chat_with_retry = AsyncMock(
-        return_value=LLMResponse(content="done", provider_state=state)
-    )
-    session = loop.sessions.get_or_create("cli:private-checkpoint")
-
-    await loop._run_agent_loop(
-        [
-            {"role": "system", "content": "system"},
-            {"role": "user", "content": "question"},
-        ],
-        runtime=loop.llm_runtime(),
-        session=session,
-    )
-
-    assert session.provider_state is not None
-    checkpoint = session.metadata[AgentLoop._RUNTIME_CHECKPOINT_KEY]
-    assert "provider_state" not in checkpoint
-    assert checkpoint[AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION_KEY] == (
-        AgentLoop._PROVIDER_STATE_CHECKPOINT_VERSION
-    )
-    assert "private-checkpoint-blob" not in json.dumps(session.metadata)
-
-    public_payload = loop.sessions.read_session_file(session.key)
-    assert public_payload is not None
-    assert "private-checkpoint-blob" not in json.dumps(public_payload)
-    raw = loop.sessions._get_session_path(session.key).read_text(encoding="utf-8")
-    assert "private-checkpoint-blob" in raw
-
-
 @pytest.mark.asyncio
 async def test_process_message_persists_user_message_before_turn_completes(tmp_path: Path) -> None:
     loop = _make_full_loop(tmp_path)
@@ -793,150 +634,6 @@ async def test_process_message_persists_user_message_before_turn_completes(tmp_p
     assert persisted.updated_at >= persisted.created_at
 
 
-@pytest.mark.asyncio
-async def test_subagent_followup_stages_provider_state_before_turn_runs(
-    tmp_path: Path,
-) -> None:
-    loop = _make_full_loop(tmp_path)
-    loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False)  # type: ignore[method-assign]
-    loop._run_agent_loop = AsyncMock(side_effect=RuntimeError("boom"))  # type: ignore[method-assign]
-    loop.provider.can_resume_conversation_state.return_value = True
-    session = loop.sessions.get_or_create("cli:subagent-crash")
-    session.provider_state = _provider_state()
-    loop.sessions.save(session)
-
-    msg = InboundMessage(
-        channel="system",
-        sender_id="subagent",
-        chat_id="cli:subagent-crash",
-        content="subagent result",
-        metadata={"subagent_task_id": "sub-1"},
-    )
-    with pytest.raises(RuntimeError, match="boom"):
-        await loop._process_message(msg)
-
-    loop.sessions.invalidate("cli:subagent-crash")
-    persisted = loop.sessions.get_or_create("cli:subagent-crash")
-    assert persisted.messages[-1]["content"] == "subagent result"
-    assert persisted.provider_state is not None
-    assert persisted.provider_state.pending_messages[-1]["role"] == "user"
-    assert persisted.provider_state.pending_messages[-1]["content"] == "subagent result"
-
-
-@pytest.mark.asyncio
-async def test_subagent_followup_state_is_durable_before_prompt_assembly(
-    tmp_path: Path,
-) -> None:
-    loop = _make_full_loop(tmp_path)
-    loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False)  # type: ignore[method-assign]
-    loop.provider.can_resume_conversation_state.return_value = True
-    loop._build_initial_messages = MagicMock(  # type: ignore[method-assign]
-        side_effect=RuntimeError("prompt boom"),
-    )
-    session = loop.sessions.get_or_create("cli:subagent-prompt-crash")
-    session.provider_state = _provider_state()
-    loop.sessions.save(session)
-
-    msg = InboundMessage(
-        channel="system",
-        sender_id="subagent",
-        chat_id="cli:subagent-prompt-crash",
-        content="subagent result",
-        metadata={"subagent_task_id": "sub-1"},
-    )
-    with pytest.raises(RuntimeError, match="prompt boom"):
-        await loop._process_message(msg)
-
-    loop.sessions.invalidate("cli:subagent-prompt-crash")
-    persisted = loop.sessions.get_or_create("cli:subagent-prompt-crash")
-    assert persisted.messages[-1]["content"] == "subagent result"
-    assert persisted.provider_state is not None
-    assert persisted.provider_state.pending_messages[-1]["content"] == (
-        "subagent result"
-    )
-
-
-@pytest.mark.asyncio
-async def test_subagent_redelivery_does_not_duplicate_staged_provider_input(
-    tmp_path: Path,
-) -> None:
-    loop = _make_full_loop(tmp_path)
-    loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False)  # type: ignore[method-assign]
-    loop.provider.can_resume_conversation_state.return_value = True
-    build_initial_messages = loop._build_initial_messages
-    loop._build_initial_messages = MagicMock(  # type: ignore[method-assign]
-        side_effect=RuntimeError("prompt boom"),
-    )
-    session = loop.sessions.get_or_create("cli:subagent-redelivery")
-    session.provider_state = _provider_state()
-    loop.sessions.save(session)
-    msg = InboundMessage(
-        channel="system",
-        sender_id="subagent",
-        chat_id="cli:subagent-redelivery",
-        content="subagent result",
-        metadata={"subagent_task_id": "sub-1"},
-    )
-
-    with pytest.raises(RuntimeError, match="prompt boom"):
-        await loop._process_message(msg)
-
-    loop.sessions.invalidate("cli:subagent-redelivery")
-    persisted = loop.sessions.get_or_create("cli:subagent-redelivery")
-    assert persisted.provider_state is not None
-    assert [
-        message.get("content")
-        for message in persisted.provider_state.pending_messages
-    ].count("subagent result") == 1
-    loop._build_initial_messages = build_initial_messages  # type: ignore[method-assign]
-    loop._run_agent_loop = AsyncMock(  # type: ignore[method-assign]
-        side_effect=RuntimeError("provider boom"),
-    )
-    with pytest.raises(RuntimeError, match="provider boom"):
-        await loop._process_message(msg)
-
-    provider_state = loop._run_agent_loop.await_args.kwargs["provider_state"]
-    assert provider_state is not None
-    pending_results = [
-        message
-        for message in provider_state.pending_messages
-        if message.get("content") == "subagent result"
-    ]
-    assert len(pending_results) == 1
-    assert LLMProvider._sanitize_empty_content(pending_results) == [
-        {"role": "user", "content": "subagent result"},
-    ]
-
-
-@pytest.mark.asyncio
-async def test_subagent_followup_clears_state_before_compatibility_failure(
-    tmp_path: Path,
-) -> None:
-    loop = _make_full_loop(tmp_path)
-    loop.consolidator.maybe_consolidate_by_tokens = AsyncMock(return_value=False)  # type: ignore[method-assign]
-    loop.provider.can_resume_conversation_state.side_effect = RuntimeError(
-        "compatibility boom"
-    )
-    session = loop.sessions.get_or_create("cli:subagent-compat-crash")
-    session.provider_state = _provider_state()
-    loop.sessions.save(session)
-
-    msg = InboundMessage(
-        channel="system",
-        sender_id="subagent",
-        chat_id="cli:subagent-compat-crash",
-        content="subagent result",
-        metadata={"subagent_task_id": "sub-1"},
-    )
-    with pytest.raises(RuntimeError, match="compatibility boom"):
-        await loop._process_message(msg)
-
-    loop.sessions.invalidate("cli:subagent-compat-crash")
-    persisted = loop.sessions.get_or_create("cli:subagent-compat-crash")
-    assert persisted.messages[-1]["content"] == "subagent result"
-    assert persisted.provider_state is None
-
-
 @pytest.mark.asyncio
 async def test_process_message_persists_unified_session_delivery_route(tmp_path: Path) -> None:
     loop = _make_full_loop(tmp_path)
@@ -1548,9 +1245,6 @@ async def test_next_turn_after_crash_closes_pending_user_turn_before_new_input(t
     session = loop.sessions.get_or_create("feishu:c3")
     session.add_message("user", "old question")
     session.metadata[AgentLoop._PENDING_USER_TURN_KEY] = True
-    session.provider_state = _provider_state().with_pending_messages([
-        {"role": "user", "content": "old question"},
-    ])
     loop.sessions.save(session)
 
     loop._run_agent_loop = AsyncMock(return_value=(
@@ -1584,7 +1278,6 @@ async def test_next_turn_after_crash_closes_pending_user_turn_before_new_input(t
         {"role": "assistant", "content": "new answer"},
     ]
     assert AgentLoop._PENDING_USER_TURN_KEY not in session.metadata
-    assert session.provider_state is None
 
 
 @pytest.mark.asyncio

tests/agent/test_mcp_connection.py

@@ -10,10 +10,9 @@ from unittest.mock import MagicMock
 
 import anyio
 import pytest
+from mcp import MCPError
 from mcp import types as mcp_types
-from mcp.shared.exceptions import McpError
 from mcp.shared.message import SessionMessage
-from mcp.types import ErrorData
 
 from nanobot.agent.loop import AgentLoop
 from nanobot.agent.tools import mcp as mcp_runtime
@@ -26,12 +25,10 @@ from nanobot.config.schema import MCPServerConfig
 
 def _mcp_notification(method: str, params: dict[str, Any] | None = None) -> SessionMessage:
     return SessionMessage(
-        message=mcp_types.JSONRPCMessage(
-            mcp_types.JSONRPCNotification(
-                jsonrpc="2.0",
-                method=method,
-                params=params,
-            )
+        message=mcp_types.JSONRPCNotification(
+            jsonrpc="2.0",
+            method=method,
+            params=params,
         )
     )
 
@@ -428,7 +425,7 @@ async def test_mcp_tool_reconnects_after_session_terminated(
             self.call_count += 1
             assert arguments == {"symbol": "AAPL"}
             if self.index == 1:
-                raise McpError(ErrorData(code=-32000, message="Session terminated"))
+                raise MCPError(-32000, "Session terminated")
             return SimpleNamespace(
                 content=[mcp_types.TextContent(type="text", text="recovered")]
             )
@@ -443,7 +440,7 @@ async def test_mcp_tool_reconnects_after_session_terminated(
             tool_def = SimpleNamespace(
                 name="quote",
                 description="quote tool",
-                inputSchema={"type": "object", "properties": {}},
+                input_schema={"type": "object", "properties": {}},
             )
             registry.register(MCPToolWrapper(session, name, tool_def, tool_timeout=5))
             stack = AsyncExitStack()
@@ -484,7 +481,7 @@ async def test_mcp_reconnect_handler_uses_sanitized_server_prefix(
         async def call_tool(self, _name: str, arguments: dict[str, Any]) -> Any:
             assert arguments == {}
             if self.index == 1:
-                raise McpError(ErrorData(code=-32000, message="Session terminated"))
+                raise MCPError(-32000, "Session terminated")
             return SimpleNamespace(
                 content=[mcp_types.TextContent(type="text", text="recovered")]
             )
@@ -497,7 +494,7 @@ async def test_mcp_reconnect_handler_uses_sanitized_server_prefix(
             tool_def = SimpleNamespace(
                 name="quote",
                 description="quote tool",
-                inputSchema={"type": "object", "properties": {}},
+                input_schema={"type": "object", "properties": {}},
             )
             registry.register(MCPToolWrapper(_FakeSession(connect_count), name, tool_def))
             stack = AsyncExitStack()
@@ -532,7 +529,7 @@ async def test_concurrent_mcp_reconnect_reuses_fresh_session(
 
     class _DeadSession:
         async def read_resource(self, _uri: str) -> Any:
-            raise McpError(ErrorData(code=-32000, message="Session terminated"))
+            raise MCPError(-32000, "Session terminated")
 
     class _LiveSession:
         async def read_resource(self, uri: str) -> Any:

tests/agent/test_mcp_reconnect_crash.py

@@ -17,7 +17,7 @@ import socket
 import time
 from unittest.mock import MagicMock
 
-import httpx
+import httpx2 as httpx
 import pytest
 
 from nanobot.agent.loop import AgentLoop
@@ -27,10 +27,8 @@ from nanobot.bus.queue import MessageBus
 from nanobot.config.schema import MCPServerConfig
 from nanobot.security import network as security_network
 
-# Leave enough headroom for reconnect handshakes on slower CI hosts; each test
-# still waits beyond this deadline explicitly before exercising recovery.
-_IDLE_TIMEOUT_SECONDS = 1.0
-_IDLE_EXPIRY_GRACE_SECONDS = 0.5
+_IDLE_TIMEOUT_SECONDS = 0.25
+_IDLE_EXPIRY_GRACE_SECONDS = 0.25
 _TOOL_TIMEOUT_SECONDS = 10
 
 
@@ -41,31 +39,29 @@ def _free_port() -> int:
 
 
 def _run_mcp_server(port: int, ready_event: multiprocessing.Event) -> None:
-    """FastMCP server target for ``multiprocessing.Process``.
+    """MCPServer target for ``multiprocessing.Process``.
 
     The server exposes a single ``greet`` tool and terminates idle sessions
     after ``_IDLE_TIMEOUT_SECONDS``.
     """
-    from mcp.server.fastmcp import FastMCP
-    from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
+    import uvicorn
+    from mcp.server import MCPServer
 
-    mcp = FastMCP("IdleTimeoutDemo", json_response=True, port=port)
+    mcp = MCPServer("IdleTimeoutDemo")
 
     @mcp.tool()
     def greet(name: str = "World") -> str:  # noqa: N802
         """Greet someone."""
         return f"Hello, {name}!"
 
-    mcp._session_manager = StreamableHTTPSessionManager(
-        app=mcp._mcp_server,
-        json_response=mcp.settings.json_response,
-        stateless=mcp.settings.stateless_http,
-        security_settings=mcp.settings.transport_security,
-        session_idle_timeout=_IDLE_TIMEOUT_SECONDS,
+    app = mcp.streamable_http_app(
+        json_response=True,
+        host="127.0.0.1",
     )
+    mcp.session_manager.session_idle_timeout = _IDLE_TIMEOUT_SECONDS
 
     ready_event.set()
-    mcp.run(transport="streamable-http")
+    uvicorn.run(app, host="127.0.0.1", port=port, log_level="warning")
 
 
 async def _wait_for_server(url: str, timeout: float = 10.0) -> bool:
@@ -130,10 +126,14 @@ def _make_loop(tmp_path, *, mcp_servers: dict) -> AgentLoop:
 @pytest.fixture(autouse=True)
 def allow_loopback_mcp_urls(monkeypatch: pytest.MonkeyPatch):
     """The repro server runs on 127.0.0.1; allow nanobot to talk to it."""
-    class TestPinnedDNSAsyncTransport(security_network.PinnedDNSAsyncTransport):
+    class TestPinnedDNSAsyncTransport(security_network.Httpx2PinnedDNSAsyncTransport):
         _resolver_lock = asyncio.Lock()
 
-    monkeypatch.setattr(mcp_module, "PinnedDNSAsyncTransport", TestPinnedDNSAsyncTransport)
+    monkeypatch.setattr(
+        mcp_module,
+        "Httpx2PinnedDNSAsyncTransport",
+        TestPinnedDNSAsyncTransport,
+    )
     monkeypatch.setattr(
         mcp_module,
         "validate_url_target",
@@ -156,7 +156,7 @@ def allow_loopback_mcp_urls(monkeypatch: pytest.MonkeyPatch):
     )
     monkeypatch.setattr(
         mcp_module,
-        "httpx_env_proxy_mounts",
+        "httpx2_env_proxy_mounts",
         lambda: {},
     )
 

tests/agent/test_mcp_transient_retry.py

@@ -5,9 +5,8 @@ from types import SimpleNamespace
 from unittest.mock import AsyncMock, patch
 
 import pytest
+from mcp import MCPError
 from mcp import types as mcp_types
-from mcp.shared.exceptions import McpError
-from mcp.types import ErrorData
 
 from nanobot.agent.tools.mcp import (
     MCPPromptWrapper,
@@ -37,12 +36,16 @@ class _FakeEndOfStreamError(Exception):
 _FakeEndOfStreamError.__name__ = "EndOfStream"
 
 
-def _session_terminated_error() -> McpError:
-    return McpError(ErrorData(code=-32000, message="Session terminated"))
+def _session_terminated_error() -> MCPError:
+    return MCPError(-32000, "Session terminated")
 
 
-def _connection_closed_error() -> McpError:
-    return McpError(ErrorData(code=-32000, message="Connection closed"))
+def _connection_closed_error() -> MCPError:
+    return MCPError(-32000, "Connection closed")
+
+
+def _session_not_found_error() -> MCPError:
+    return MCPError(-32600, "Session not found")
 
 
 def test_is_transient_recognizes_closed_resource():
@@ -85,6 +88,10 @@ def test_is_session_terminated_recognizes_connection_closed_mcp_error():
     assert _is_session_terminated(_connection_closed_error())
 
 
+def test_is_session_terminated_recognizes_v2_session_not_found_error():
+    assert _is_session_terminated(_session_not_found_error())
+
+
 # ---------------------------------------------------------------------------
 # MCPToolWrapper retry behaviour
 # ---------------------------------------------------------------------------
@@ -94,7 +101,7 @@ def _make_tool_def(name="test_tool"):
     return SimpleNamespace(
         name=name,
         description="A test tool",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
 
 
@@ -415,10 +422,10 @@ async def test_prompt_fails_after_retry_exhausted():
 
 @pytest.mark.asyncio
 async def test_prompt_no_retry_on_mcp_error():
-    """McpError (application-level) should NOT trigger retry."""
+    """MCPError (application-level) should NOT trigger retry."""
     session = AsyncMock()
     session.get_prompt = AsyncMock(
-        side_effect=McpError(ErrorData(code=-1, message="not found"))
+        side_effect=MCPError(-1, "not found")
     )
 
     wrapper = MCPPromptWrapper(session, "test_server", _make_prompt_def())
@@ -443,7 +450,7 @@ async def test_prompt_no_retry_on_non_transient():
 
 @pytest.mark.asyncio
 async def test_prompt_reconnects_on_session_terminated():
-    """Prompt should reconnect once before falling back to McpError handling."""
+    """Prompt should reconnect once before falling back to MCPError handling."""
     old_session = AsyncMock()
     old_session.get_prompt = AsyncMock(side_effect=_session_terminated_error())
     new_session = AsyncMock()

tests/agent/test_memory_store.py

@@ -579,21 +579,3 @@ def test_history_skips_non_dict_jsonl_lines(tmp_path: Path) -> None:
     }]
     next_cursor = memory.append_history("next", session_key="cli:t")
     assert next_cursor == 2
-
-def test_raw_archive_handles_none_timestamp_and_missing_role(tmp_path: Path) -> None:
-    """raw_archive and _format_messages must safely format messages with None timestamp or missing role.
-
-    Prevents TypeError on NoneType[:16] slicing and KeyError on missing 'role'
-    when raw-dumping unconsolidated history entries without timestamps or role fields.
-    """
-    memory = MemoryStore(tmp_path)
-    messages = [
-        {"content": "message with none timestamp", "timestamp": None, "role": "user"},
-        {"content": "message with int timestamp", "timestamp": 1720000000, "role": "assistant"},
-        {"content": "message with missing role", "timestamp": "2026-07-28T12:00:00"},
-    ]
-    memory.raw_archive(messages, session_key="cli:test")
-    raw_history = memory.history_file.read_text(encoding="utf-8")
-    assert "[?] USER: message with none timestamp" in raw_history
-    assert "[1720000000] ASSISTANT: message with int timestamp" in raw_history
-    assert "[2026-07-28T12:00] UNKNOWN: message with missing role" in raw_history

tests/agent/test_runner_core.py

@@ -11,13 +11,7 @@ import pytest
 
 from agent.runner_helpers import make_run_spec
 from nanobot.config.schema import AgentDefaults
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-    ToolCallRequest,
-)
+from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
 
 _MAX_TOOL_RESULT_CHARS = AgentDefaults().max_tool_result_chars
 
@@ -79,311 +73,6 @@ async def test_runner_preserves_reasoning_fields_and_tool_results():
     )
 
 
-@pytest.mark.asyncio
-async def test_runner_replays_provider_state_without_chat_projection_duplicates():
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.supports_native_compaction.return_value = False
-    captured_second_kwargs: dict = {}
-    checkpoints: list[dict] = []
-    calls = 0
-
-    async def checkpoint(payload: dict) -> None:
-        checkpoints.append(payload)
-
-    first_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-    )
-    second_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "message", "role": "assistant"}]},
-    )
-
-    async def chat_with_retry(**kwargs):
-        nonlocal calls
-        calls += 1
-        if calls == 1:
-            provider_context = kwargs["provider_context"]
-            assert isinstance(provider_context, ProviderCallContext)
-            assert provider_context.conversation_state is None
-            return LLMResponse(
-                content=None,
-                tool_calls=[
-                    ToolCallRequest(
-                        id="call_1|fc_1",
-                        name="list_dir",
-                        arguments={"path": "."},
-                    ),
-                ],
-                provider_state=first_state,
-            )
-        captured_second_kwargs.update(kwargs)
-        return LLMResponse(content="done", provider_state=second_state)
-
-    provider.chat_with_retry = chat_with_retry
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    tools.execute = AsyncMock(return_value="tool result")
-
-    result = await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[
-            {"role": "system", "content": "system"},
-            {"role": "user", "content": "do task"},
-        ],
-        tools=tools,
-        model="gpt-5.6",
-        max_iterations=3,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-        checkpoint_callback=checkpoint,
-    ))
-
-    provider_context = captured_second_kwargs["provider_context"]
-    assert isinstance(provider_context, ProviderCallContext)
-    assert provider_context.conversation_state is not None
-    assert provider_context.conversation_state.payload == first_state.payload
-    assert provider_context.conversation_state.pending_messages == [{
-        "role": "tool",
-        "tool_call_id": "call_1|fc_1",
-        "name": "list_dir",
-        "content": "tool result",
-    }]
-    assert not any(
-        message.get("role") == "assistant"
-        for message in provider_context.conversation_state.pending_messages
-    )
-    assert result.provider_state is not None
-    assert result.provider_state.payload == second_state.payload
-    assert result.provider_state.pending_messages == []
-    assert checkpoints[0]["phase"] == "awaiting_tools"
-    assert "provider_state" not in checkpoints[0]
-    assert checkpoints[1]["phase"] == "tools_completed"
-    assert checkpoints[1]["provider_state"].pending_messages == [{
-        "role": "tool",
-        "tool_call_id": "call_1|fc_1",
-        "name": "list_dir",
-        "content": "tool result",
-    }]
-    assert checkpoints[2]["phase"] == "final_response"
-    assert checkpoints[2]["provider_state"].payload == second_state.payload
-
-
-@pytest.mark.asyncio
-async def test_runner_governs_tool_result_before_adding_it_to_provider_state():
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.supports_native_compaction.return_value = False
-    calls = 0
-    captured_context: ProviderCallContext | None = None
-    checkpoints: list[dict] = []
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-    )
-
-    async def chat_with_retry(**kwargs):
-        nonlocal calls, captured_context
-        calls += 1
-        if calls == 1:
-            return LLMResponse(
-                content=None,
-                tool_calls=[
-                    ToolCallRequest(
-                        id="call_1",
-                        name="read_file",
-                        arguments={"path": "large.txt"},
-                    ),
-                ],
-                provider_state=state,
-            )
-        captured_context = kwargs["provider_context"]
-        return LLMResponse(content="done")
-
-    provider.chat_with_retry = chat_with_retry
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    tools.execute = AsyncMock(return_value="x" * 5_000)
-
-    async def checkpoint(payload: dict) -> None:
-        checkpoints.append(payload)
-
-    await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[
-            {"role": "system", "content": "system"},
-            {"role": "user", "content": "read the file"},
-        ],
-        tools=tools,
-        model="gpt-5.6",
-        context_window_tokens=3_000,
-        context_block_limit=200,
-        max_tokens=1_000,
-        max_iterations=3,
-        max_tool_result_chars=10_000,
-        checkpoint_callback=checkpoint,
-    ))
-
-    assert captured_context is not None
-    assert captured_context.conversation_state is not None
-    pending = captured_context.conversation_state.pending_messages
-    assert len(pending) == 1
-    assert pending[0]["role"] == "tool"
-    assert "compacted to fit context" in pending[0]["content"]
-    assert pending[0]["content"] != "x" * 5_000
-    completed_checkpoint = next(
-        checkpoint
-        for checkpoint in checkpoints
-        if checkpoint["phase"] == "tools_completed"
-    )
-    checkpoint_pending = completed_checkpoint["provider_state"].pending_messages
-    assert "compacted to fit context" in checkpoint_pending[0]["content"]
-    assert checkpoint_pending[0]["content"] != "x" * 5_000
-
-
-@pytest.mark.asyncio
-async def test_injected_final_response_checkpoint_includes_provider_state():
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.supports_native_compaction.return_value = False
-    first_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "message", "content": "first answer"}]},
-    )
-    second_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "message", "content": "second answer"}]},
-    )
-    provider.chat_with_retry = AsyncMock(side_effect=[
-        LLMResponse(content="first answer", provider_state=first_state),
-        LLMResponse(content="second answer", provider_state=second_state),
-    ])
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    checkpoints: list[dict] = []
-    injections = [[{"role": "user", "content": "follow up"}], []]
-
-    async def checkpoint(payload: dict) -> None:
-        checkpoints.append(payload)
-
-    async def inject() -> list[dict]:
-        return injections.pop(0)
-
-    await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[{"role": "user", "content": "start"}],
-        tools=tools,
-        model="gpt-5.6",
-        max_iterations=3,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-        checkpoint_callback=checkpoint,
-        injection_callback=inject,
-    ))
-
-    assert checkpoints[0]["phase"] == "final_response"
-    assert checkpoints[0]["provider_state"].payload == first_state.payload
-
-
-@pytest.mark.asyncio
-async def test_runner_preserves_last_completed_provider_state_on_model_error():
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
-        content="temporary upstream failure",
-        finish_reason="error",
-        error_kind="timeout",
-    ))
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-    )
-    unsaved_input = {"role": "user", "content": "ephemeral follow-up"}
-
-    result = await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[
-            {"role": "system", "content": "system"},
-            unsaved_input,
-        ],
-        tools=tools,
-        model="gpt-5.6",
-        max_iterations=1,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-        provider_state=state.with_pending_messages([unsaved_input]),
-    ))
-
-    assert result.stop_reason == "error"
-    assert result.provider_state is not None
-    assert result.provider_state.payload == state.payload
-    assert result.provider_state.pending_messages[0] == unsaved_input
-    assert result.provider_state.pending_messages[1]["role"] == "assistant"
-    assert "model error" in result.provider_state.pending_messages[1]["content"]
-
-
-@pytest.mark.asyncio
-async def test_runner_discards_provider_state_on_non_retryable_model_error():
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
-        content="context length exceeded",
-        finish_reason="error",
-        error_status_code=400,
-        error_should_retry=False,
-    ))
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-    )
-
-    result = await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[{"role": "user", "content": "continue"}],
-        tools=tools,
-        model="gpt-5.6",
-        max_iterations=1,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-        provider_state=state,
-    ))
-
-    assert result.stop_reason == "error"
-    assert result.provider_state is None
-
-
 @pytest.mark.asyncio
 async def test_runner_returns_max_iterations_fallback():
     from nanobot.agent.runner import AgentRunner
@@ -733,66 +422,6 @@ async def test_runner_retries_empty_final_response_with_summary_prompt():
     assert result.usage["completion_tokens"] == 9
 
 
-@pytest.mark.asyncio
-@pytest.mark.parametrize("finish_reason", ["refusal", "content_filter"])
-async def test_runner_does_not_retry_blank_policy_terminal(
-    finish_reason: str,
-) -> None:
-    from nanobot.agent.runner import AgentRunner
-    from nanobot.utils.runtime import EMPTY_FINAL_RESPONSE_MESSAGE
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
-        content=None,
-        finish_reason=finish_reason,
-    ))
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-
-    result = await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[{"role": "user", "content": "do task"}],
-        tools=tools,
-        model="test-model",
-        max_iterations=3,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-    ))
-
-    assert provider.chat_with_retry.await_count == 1
-    assert result.final_content == EMPTY_FINAL_RESPONSE_MESSAGE
-    assert result.stop_reason == "empty_final_response"
-
-
-@pytest.mark.asyncio
-@pytest.mark.parametrize("finish_reason", ["refusal", "content_filter"])
-async def test_runner_does_not_auto_continue_goal_after_policy_terminal(
-    finish_reason: str,
-) -> None:
-    from nanobot.agent.runner import AgentRunner
-
-    provider = MagicMock(spec=LLMProvider)
-    provider.chat_with_retry = AsyncMock(return_value=LLMResponse(
-        content="Request blocked by provider policy.",
-        finish_reason=finish_reason,
-    ))
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-
-    result = await AgentRunner().run(make_run_spec(
-        provider,
-        initial_messages=[{"role": "user", "content": "do task"}],
-        tools=tools,
-        model="test-model",
-        max_iterations=3,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-        goal_active_predicate=lambda: True,
-    ))
-
-    assert provider.chat_with_retry.await_count == 1
-    assert result.final_content == "Request blocked by provider policy."
-    assert result.stop_reason == "completed"
-
-
 @pytest.mark.asyncio
 async def test_runner_uses_specific_message_after_empty_finalization_retry():
     """After silent retries + finalization all return empty, stop_reason is empty_final_response."""
@@ -821,56 +450,6 @@ async def test_runner_uses_specific_message_after_empty_finalization_retry():
     assert result.stop_reason == "empty_final_response"
 
 
-@pytest.mark.asyncio
-async def test_empty_finalization_retry_discards_candidate_provider_state():
-    from nanobot.agent.runner import AgentRunner
-
-    candidate = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={
-            "items": [{
-                "type": "function_call",
-                "call_id": "call_1",
-                "name": "exec",
-                "arguments": "{}",
-            }],
-        },
-    )
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = True
-    provider.chat_with_retry = AsyncMock(side_effect=[
-        LLMResponse(content=None, tool_calls=[], usage={}),
-        LLMResponse(content=None, tool_calls=[], usage={}),
-        LLMResponse(
-            content="finalized without tools",
-            tool_calls=[ToolCallRequest(id="call_1", name="exec", arguments={})],
-            finish_reason="stop",
-            provider_state=candidate,
-            usage={},
-        ),
-    ])
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-    tools.execute = AsyncMock(return_value="must not run")
-
-    runner = AgentRunner()
-    result = await runner.run(make_run_spec(
-        provider,
-        initial_messages=[{"role": "user", "content": "do task"}],
-        tools=tools,
-        model="test-model",
-        max_iterations=3,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-    ))
-
-    tools.execute.assert_not_awaited()
-    assert result.final_content == "finalized without tools"
-    assert result.provider_state is None
-
-
 @pytest.mark.asyncio
 async def test_runner_length_recovery_returns_all_segments():
     """Recovered output segments are returned together instead of only the tail."""

tests/agent/test_runner_errors.py

@@ -310,50 +310,3 @@ async def test_runner_tool_error_preserves_tool_results_in_messages():
         i for i, m in enumerate(result.messages) if m.get("role") == "tool"
     ]
     assert all(ti > asst_tc_idx for ti in tool_indices)
-
-
-@pytest.mark.asyncio
-async def test_length_finish_with_blank_content_routes_to_length_recovery():
-    """Regression test for #5133.
-
-    A response with finish_reason='length' and blank content (e.g. the model
-    spent its whole output budget on a tool call whose closing tag was
-    truncated) must take the length-recovery path, not the empty-response
-    retry path. Retrying the same prompt cannot recover from output-budget
-    exhaustion.
-    """
-    from nanobot.agent.runner import AgentRunner
-    from nanobot.utils.runtime import LENGTH_RECOVERY_PROMPT
-
-    provider = MagicMock(spec=LLMProvider)
-    # First call: truncated (length) with blank content and a dropped tool call.
-    # Second call: normal completion so the loop can terminate.
-    provider.chat_with_retry = AsyncMock(side_effect=[
-        LLMResponse(
-            content="",
-            finish_reason="length",
-            tool_calls=[ToolCallRequest(id="call_1", name="exec", arguments={})],
-            usage={},
-        ),
-        LLMResponse(content="done", finish_reason="stop", tool_calls=[], usage={}),
-    ])
-    tools = MagicMock()
-    tools.get_definitions.return_value = []
-
-    runner = AgentRunner()
-    result = await runner.run(make_run_spec(provider,
-        initial_messages=[{"role": "user", "content": "do a long task"}],
-        tools=tools,
-        model="test-model",
-        max_iterations=5,
-        max_tool_result_chars=_MAX_TOOL_RESULT_CHARS,
-    ))
-
-    # The runner must have injected a length-recovery prompt and continued,
-    # rather than exhausting empty-response retries into a generic apology.
-    user_msgs = [m.get("content") or "" for m in result.messages if m.get("role") == "user"]
-    assert any(LENGTH_RECOVERY_PROMPT in c for c in user_msgs), (
-        "expected a length-recovery message to be appended for a "
-        "finish_reason='length' response with blank content"
-    )
-    assert result.final_content == "done"

tests/agent/test_runner_fallback.py

@@ -9,15 +9,8 @@ import pytest
 from loguru import logger
 
 from nanobot.config.schema import ModelPresetConfig
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-)
-from nanobot.providers.conversation_state import ProviderConversationStateController
+from nanobot.providers.base import LLMProvider, LLMResponse
 from nanobot.providers.fallback_provider import FallbackProvider
-from nanobot.providers.openai_responses import resolve_compact_threshold
 
 
 def _make_response(
@@ -73,9 +66,6 @@ class _FakeProvider(LLMProvider):
         self._response = response or _make_response()
         self.chat_calls: list[dict[str, Any]] = []
         self.chat_stream_calls: list[dict[str, Any]] = []
-        self.context_calls: list[ProviderCallContext | None] = []
-        self.resumable = False
-        self.compact = False
 
     def get_default_model(self) -> str:
         return f"{self.name}/model"
@@ -91,26 +81,6 @@ class _FakeProvider(LLMProvider):
             await on_delta(self._response.content)
         return self._response
 
-    async def chat_with_context(
-        self,
-        provider_context: ProviderCallContext | None = None,
-        **kwargs: Any,
-    ) -> LLMResponse:
-        self.context_calls.append(provider_context)
-        return await self.chat(**kwargs)
-
-    def can_resume_conversation_state(
-        self,
-        state: ProviderConversationState,
-        model: str | None = None,
-    ) -> bool:
-        _ = state, model
-        return self.resumable
-
-    def supports_native_compaction(self, model: str | None = None) -> bool:
-        _ = model
-        return self.compact
-
 
 # -- config-level tests --
 
@@ -241,8 +211,6 @@ def test_provider_snapshot_uses_smallest_fallback_context_window() -> None:
         snapshot = build_provider_snapshot(config)
 
     assert snapshot.context_window_tokens == 64000
-    assert isinstance(snapshot.provider, FallbackProvider)
-    assert snapshot.provider._primary_context_window_tokens == 128000
 
 
 def test_inline_fallback_reasoning_effort_does_not_inherit_primary() -> None:
@@ -317,257 +285,6 @@ class TestFallbackOnPrimaryError:
         assert primary.chat_calls[0]["model"] == "primary-model"
         assert fallback.chat_calls[0]["model"] == "fallback-a"
 
-    @pytest.mark.asyncio
-    async def test_primary_compaction_uses_primary_context_window(self) -> None:
-        primary = _FakeProvider("primary", _make_response("primary ok"))
-        primary.compact = True
-        fb = FallbackProvider(
-            primary=primary,
-            fallback_presets=[
-                _fallback("small-chat", context_window_tokens=50_000),
-            ],
-            provider_factory=MagicMock(),
-            primary_context_window_tokens=200_000,
-        )
-
-        await fb.chat_with_context(
-            messages=[{"role": "user", "content": "hi"}],
-            model="gpt-5.6",
-            max_tokens=10_000,
-            provider_context=ProviderCallContext(context_window_tokens=50_000),
-        )
-
-        primary_context = primary.context_calls[0]
-        assert primary_context is not None
-        assert primary_context.context_window_tokens == 200_000
-        assert resolve_compact_threshold(
-            primary_context.context_window_tokens,
-            10_000,
-        ) == 180_000
-
-    @pytest.mark.asyncio
-    async def test_native_fallback_compaction_uses_its_own_context_window(self) -> None:
-        primary = _FakeProvider("primary", _error_response())
-        primary.compact = True
-        fallback = _FakeProvider("fallback", _make_response("fallback ok"))
-        fallback.compact = True
-        fb = FallbackProvider(
-            primary=primary,
-            fallback_presets=[
-                _fallback("fallback-a", context_window_tokens=120_000),
-            ],
-            provider_factory=MagicMock(return_value=fallback),
-            primary_context_window_tokens=200_000,
-        )
-
-        result = await fb.chat_with_context(
-            messages=[{"role": "user", "content": "hi"}],
-            model="gpt-5.6",
-            provider_context=ProviderCallContext(context_window_tokens=50_000),
-        )
-
-        assert result.content == "fallback ok"
-        assert primary.context_calls == [
-            ProviderCallContext(context_window_tokens=200_000)
-        ]
-        assert fallback.context_calls == [
-            ProviderCallContext(context_window_tokens=120_000)
-        ]
-
-    @pytest.mark.asyncio
-    async def test_native_fallback_gets_context_when_primary_does_not_use_it(self) -> None:
-        primary = _FakeProvider("primary", _error_response())
-        fallback = _FakeProvider("fallback", _make_response("fallback ok"))
-        fallback.compact = True
-        fb = FallbackProvider(
-            primary=primary,
-            fallback_presets=[
-                _fallback("fallback-a", context_window_tokens=120_000),
-            ],
-            provider_factory=MagicMock(return_value=fallback),
-            primary_context_window_tokens=200_000,
-        )
-        messages = [{"role": "user", "content": "hi"}]
-        controller = ProviderConversationStateController(
-            provider=fb,
-            model="primary-model",
-            messages=messages,
-        )
-        assert fb.supports_native_compaction("primary-model") is False
-        provider_context = controller.prepare_request(
-            messages,
-            context_window_tokens=50_000,
-        )
-
-        assert provider_context == ProviderCallContext(
-            context_window_tokens=50_000
-        )
-        result = await fb.chat_with_context(
-            messages=messages,
-            model="primary-model",
-            provider_context=provider_context,
-        )
-
-        assert result.content == "fallback ok"
-        assert primary.context_calls == [ProviderCallContext()]
-        assert fallback.context_calls == [
-            ProviderCallContext(context_window_tokens=120_000)
-        ]
-
-    @pytest.mark.asyncio
-    async def test_responses_chat_fallback_responses_rebuilds_state(self) -> None:
-        primary = _FakeProvider("primary", _error_response())
-        primary.resumable = True
-        primary.compact = True
-        fallback = _FakeProvider("fallback", _make_response("fallback ok"))
-        messages = [{"role": "user", "content": "hi"}]
-        state = ProviderConversationState(
-            kind="openai_responses",
-            provider="openai:test",
-            model="gpt-5.6",
-            version=1,
-            payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-            pending_messages=list(messages),
-        )
-        fb = FallbackProvider(
-            primary=primary,
-            fallback_presets=[_fallback("fallback-a")],
-            provider_factory=MagicMock(return_value=fallback),
-        )
-        controller = ProviderConversationStateController(
-            provider=fb,
-            model="gpt-5.6",
-            messages=messages,
-            state=state,
-        )
-        provider_context = controller.prepare_request(
-            messages,
-            context_window_tokens=200_000,
-        )
-        assert provider_context is not None
-
-        result = await fb.chat_with_context(
-            messages=messages,
-            model="gpt-5.6",
-            provider_context=provider_context,
-        )
-
-        assert result.content == "fallback ok"
-        assert primary.context_calls == [provider_context]
-        assert fallback.context_calls == [ProviderCallContext()]
-        assert fallback.chat_calls[0]["messages"] == messages
-
-        controller.observe_response(result, messages)
-        messages.append({"role": "assistant", "content": result.content})
-        assert controller.finish(messages) is None
-
-        recovered_state = ProviderConversationState(
-            kind="openai_responses",
-            provider="openai:test",
-            model="gpt-5.6",
-            version=1,
-            payload={"items": [{"type": "reasoning", "encrypted_content": "recovered"}]},
-        )
-        primary._response = LLMResponse(
-            content="primary recovered",
-            provider_state=recovered_state,
-        )
-        next_turn = ProviderConversationStateController(
-            provider=fb,
-            model="gpt-5.6",
-            messages=messages,
-        )
-        next_context = next_turn.prepare_request(
-            messages,
-            context_window_tokens=200_000,
-        )
-        assert next_context == ProviderCallContext(context_window_tokens=200_000)
-
-        recovered = await fb.chat_with_context(
-            messages=messages,
-            model="gpt-5.6",
-            provider_context=next_context,
-        )
-
-        assert recovered.provider_state is recovered_state
-        assert primary.context_calls[-1] == next_context
-        assert primary.chat_calls[-1]["messages"] == messages
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize(
-        ("primary_error_kind", "primary_status", "primary_should_retry"),
-        [
-            ("server_error", 503, True),
-            ("authentication", 401, False),
-        ],
-        ids=["transient", "authentication"],
-    )
-    async def test_final_fallback_error_uses_primary_state_disposition(
-        self,
-        primary_error_kind: str,
-        primary_status: int,
-        primary_should_retry: bool,
-    ) -> None:
-        primary = _FakeProvider(
-            "primary",
-            _make_response(
-                "primary unavailable",
-                finish_reason="error",
-                error_kind=primary_error_kind,
-                error_status_code=primary_status,
-                error_should_retry=primary_should_retry,
-            ),
-        )
-        primary.resumable = True
-        fallback = _FakeProvider(
-            "fallback",
-            _make_response(
-                "fallback invalid request",
-                finish_reason="error",
-                error_kind="invalid_request",
-                error_status_code=400,
-                error_should_retry=False,
-            ),
-        )
-        messages = [{"role": "user", "content": "continue"}]
-        state = ProviderConversationState(
-            kind="openai_responses",
-            provider="openai:test",
-            model="gpt-5.6",
-            version=1,
-            payload={"items": [{"type": "reasoning", "encrypted_content": "opaque"}]},
-            pending_messages=list(messages),
-        )
-        provider = FallbackProvider(
-            primary=primary,
-            fallback_presets=[_fallback("fallback-a")],
-            provider_factory=MagicMock(return_value=fallback),
-        )
-        controller = ProviderConversationStateController(
-            provider=provider,
-            model="gpt-5.6",
-            messages=messages,
-            state=state,
-        )
-        provider_context = controller.prepare_request(
-            messages,
-            context_window_tokens=200_000,
-        )
-        assert provider_context is not None
-
-        response = await provider.chat_with_context(
-            messages=messages,
-            model="gpt-5.6",
-            provider_context=provider_context,
-        )
-        controller.observe_response(response, messages)
-
-        assert response.content == "fallback invalid request"
-        assert response.preserve_provider_state_on_error is True
-        restored = controller.finish(messages)
-        assert restored is not None
-        assert restored.payload == state.payload
-
     @pytest.mark.asyncio
     async def test_reports_the_fallback_model_before_its_request(self) -> None:
         primary = _FakeProvider("primary", _error_response())

tests/agent/test_runner_governance.py

@@ -15,11 +15,7 @@ from nanobot.agent.context_governance import (
 )
 from nanobot.agent.runner import AgentRunSpec
 from nanobot.config.schema import AgentDefaults
-from nanobot.providers.base import (
-    LLMResponse,
-    ProviderConversationState,
-    ToolCallRequest,
-)
+from nanobot.providers.base import LLMResponse, ToolCallRequest
 
 _MAX_TOOL_RESULT_CHARS = AgentDefaults().max_tool_result_chars
 
@@ -890,13 +886,6 @@ def test_drop_malformed_tool_calls_trims_response():
     """LLM response tool_calls with a missing/empty name are dropped in place."""
     from nanobot.agent.runner import AgentRunner
 
-    candidate_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "function_call", "name": None}]},
-    )
     response = LLMResponse(
         content=None,
         tool_calls=[
@@ -906,11 +895,9 @@ def test_drop_malformed_tool_calls_trims_response():
             ToolCallRequest(id="4", name="read_file", arguments={}),
         ],
         finish_reason="tool_calls",
-        provider_state=candidate_state,
     )
     dropped, all_dropped, orig = AgentRunner._drop_malformed_tool_calls(response)
     assert [tc.name for tc in response.tool_calls] == ["read_file"]
-    assert response.provider_state is None
     assert response.finish_reason == "tool_calls"
     assert response.should_execute_tools is True
     assert dropped == 3

tests/agent/test_session_atomic.py

@@ -4,7 +4,6 @@ import json
 from datetime import datetime
 from pathlib import Path
 
-from nanobot.providers.base import ProviderConversationState
 from nanobot.session.manager import Session, SessionManager
 
 
@@ -102,137 +101,6 @@ class TestAtomicSave:
         for i in range(5):
             assert loaded.messages[i]["content"] == f"msg{i}"
 
-    def test_provider_state_round_trips_in_private_record_only(self, tmp_path: Path):
-        mgr = SessionManager(tmp_path)
-        secret = "encrypted-reasoning-blob"
-        session = Session(
-            key="test:provider-state",
-            provider_state=ProviderConversationState(
-                kind="openai_responses",
-                provider="openai:https://api.openai.com/v1",
-                model="gpt-5.6",
-                version=1,
-                payload={
-                    "items": [
-                        {
-                            "type": "reasoning",
-                            "encrypted_content": secret,
-                        }
-                    ]
-                },
-                pending_messages=[{"role": "user", "content": "continue"}],
-            ),
-        )
-        session.add_message("user", "hello")
-        mgr.save(session)
-
-        records = [
-            json.loads(line)
-            for line in mgr._get_session_path(session.key)
-            .read_text(encoding="utf-8")
-            .splitlines()
-        ]
-        assert [record.get("_type") for record in records] == [
-            "metadata",
-            "provider_state",
-            None,
-        ]
-        assert secret in records[1]["state"]["payload"]["items"][0]["encrypted_content"]
-
-        mgr.invalidate(session.key)
-        loaded = mgr.get_or_create(session.key)
-        assert loaded.provider_state is not None
-        assert loaded.provider_state.to_private_record() == session.provider_state.to_private_record()
-
-        public_payload = mgr.read_session_file(session.key)
-        assert public_payload is not None
-        assert public_payload["messages"] == [session.messages[0]]
-        assert secret not in json.dumps(public_payload)
-        assert secret not in json.dumps(mgr.list_sessions())
-
-    def test_provider_state_does_not_consume_list_preview_budget(
-        self,
-        tmp_path: Path,
-        monkeypatch,
-    ):
-        import nanobot.session.manager as session_manager
-
-        monkeypatch.setattr(session_manager, "_SESSION_LIST_PREVIEW_MAX_CHARS", 100)
-        mgr = SessionManager(tmp_path)
-        session = Session(
-            key="test:provider-state-preview",
-            provider_state=ProviderConversationState(
-                kind="openai_responses",
-                provider="openai:test",
-                model="test-model",
-                version=1,
-                payload={"items": [{"encrypted_content": "x" * 200}]},
-            ),
-        )
-        session.add_message("user", "visible preview")
-        mgr.save(session)
-
-        assert mgr.list_sessions()[0]["preview"] == "visible preview"
-
-    def test_clear_and_fork_discard_provider_state(self, tmp_path: Path):
-        mgr = SessionManager(tmp_path)
-        state = ProviderConversationState(
-            kind="openai_responses",
-            provider="openai:test",
-            model="gpt-5.6",
-            version=1,
-            payload={"items": []},
-        )
-        source = Session(key="test:state-source", provider_state=state)
-        source.add_message("user", "hello")
-        mgr.save(source)
-
-        fork = mgr.fork_session_before_user_index(
-            source.key,
-            "test:state-fork",
-            1,
-        )
-        assert fork is not None
-        assert fork.provider_state is None
-
-        source.clear()
-        assert source.provider_state is None
-
-    def test_invalid_provider_state_record_is_not_public_history(self, tmp_path: Path):
-        mgr = SessionManager(tmp_path)
-        path = mgr._get_session_path("test:bad-provider-state")
-        path.parent.mkdir(parents=True, exist_ok=True)
-        path.write_text(
-            "\n".join(
-                [
-                    json.dumps(
-                        {
-                            "_type": "metadata",
-                            "key": "test:bad-provider-state",
-                            "created_at": datetime.now().isoformat(),
-                            "updated_at": datetime.now().isoformat(),
-                            "metadata": {},
-                            "last_consolidated": 0,
-                        }
-                    ),
-                    json.dumps(
-                        {
-                            "_type": "provider_state",
-                            "state": {"kind": "openai_responses"},
-                        }
-                    ),
-                    json.dumps({"role": "user", "content": "safe"}),
-                ]
-            )
-            + "\n",
-            encoding="utf-8",
-        )
-
-        loaded = mgr._load("test:bad-provider-state")
-        assert loaded is not None
-        assert loaded.provider_state is None
-        assert loaded.messages == [{"role": "user", "content": "safe"}]
-
 
 class TestRepairCorruptFile:
     def _write_corrupt_jsonl(self, path: Path, lines: list[str]) -> None:

tests/agent/test_session_lock_lifecycle.py

@@ -1,53 +0,0 @@
-from __future__ import annotations
-
-import asyncio
-import gc
-from unittest.mock import MagicMock
-
-import pytest
-
-
-def _make_loop(loop_factory):
-    provider = MagicMock()
-    provider.get_default_model.return_value = "test-model"
-    return loop_factory(provider=provider)
-
-
-def test_idle_agent_session_locks_are_released(loop_factory):
-    loop = _make_loop(loop_factory)
-
-    for index in range(1000):
-        lock = loop._get_session_lock(f"api:temporary-{index}")
-
-    del lock
-    gc.collect()
-
-    assert len(loop._session_locks) == 0
-
-
-@pytest.mark.asyncio
-async def test_waiter_keeps_agent_session_lock_alive(loop_factory):
-    loop = _make_loop(loop_factory)
-    owner_lock = loop._get_session_lock("api:shared")
-    await owner_lock.acquire()
-    waiter_started = asyncio.Event()
-    waiter_entered = asyncio.Event()
-
-    async def wait_for_lock() -> None:
-        lock = loop._get_session_lock("api:shared")
-        waiter_started.set()
-        async with lock:
-            waiter_entered.set()
-
-    waiter = asyncio.create_task(wait_for_lock())
-    await waiter_started.wait()
-
-    assert loop._get_session_lock("api:shared") is owner_lock
-    assert not waiter_entered.is_set()
-
-    owner_lock.release()
-    await waiter
-    del owner_lock
-    gc.collect()
-
-    assert "api:shared" not in loop._session_locks

tests/agent/test_session_manager_history.py

@@ -1,4 +1,3 @@
-from nanobot.providers.base import ProviderConversationState
 from nanobot.runtime_context import (
     RUNTIME_CONTEXT_HISTORY_META,
     RuntimeContextBlock,
@@ -770,16 +769,7 @@ def test_get_history_extend_to_user_keeps_newer_user_inside_window():
 
 def test_retain_recent_legal_suffix_returns_dropped_messages():
     """retain_recent_legal_suffix returns the actually-dropped messages."""
-    session = Session(
-        key="test:return-dropped",
-        provider_state=ProviderConversationState(
-            kind="openai_responses",
-            provider="openai:test",
-            model="test-model",
-            version=1,
-            payload={"items": []},
-        ),
-    )
+    session = Session(key="test:return-dropped")
     for i in range(10):
         session.messages.append({"role": "user", "content": f"msg{i}"})
 
@@ -789,19 +779,11 @@ def test_retain_recent_legal_suffix_returns_dropped_messages():
     assert [m["content"] for m in result.dropped] == [f"msg{i}" for i in range(6)]
     assert len(session.messages) == 4
     assert result.already_consolidated_count == 0
-    assert session.provider_state is None
 
 
 def test_retain_recent_legal_suffix_returns_empty_when_no_drop():
     """No messages dropped → empty list returned."""
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={"items": []},
-    )
-    session = Session(key="test:no-drop", provider_state=state)
+    session = Session(key="test:no-drop")
     for i in range(3):
         session.messages.append({"role": "user", "content": f"msg{i}"})
 
@@ -810,7 +792,6 @@ def test_retain_recent_legal_suffix_returns_empty_when_no_drop():
     assert result.dropped == []
     assert result.already_consolidated_count == 0
     assert len(session.messages) == 3
-    assert session.provider_state is state
 
 
 def test_retain_recent_legal_suffix_returns_all_on_zero():

tests/agent/test_task_cancel.py

@@ -111,50 +111,8 @@ class TestHandleStop:
         assert all(e.is_set() for e in events)
         assert "2 task" in out.content
 
-    @pytest.mark.asyncio
-    async def test_cancel_active_turn_discards_pending_followups(self):
-        from nanobot.bus.events import InboundMessage
-
-        loop, _ = _make_loop()
-        pending = asyncio.Queue()
-        pending.put_nowait(
-            InboundMessage(channel="test", sender_id="u1", chat_id="c1", content="next")
-        )
-        loop._pending_queues["test:c1"] = pending
-
-        assert await loop.cancel_active_turn("test:c1") == 1
-        assert "test:c1" not in loop._pending_queues
-
 
 class TestDispatch:
-    @pytest.mark.asyncio
-    async def test_run_drops_deactivated_transient_message(self):
-        from nanobot.bus.events import InboundMessage
-
-        loop, bus = _make_loop()
-        msg = InboundMessage(
-            channel="websocket",
-            sender_id="u1",
-            chat_id="temporary-test",
-            content="private",
-            session_key_override="websocket:temporary-test",
-            transient_session=True,
-        )
-
-        async def consume_once():
-            loop.stop()
-            return msg
-
-        bus.consume_inbound = AsyncMock(side_effect=consume_once)
-        loop.sessions.is_transient_active.return_value = False
-        loop._dispatch = AsyncMock()
-        loop.close_mcp = AsyncMock()
-        loop._running = True
-
-        await loop.run()
-
-        loop._dispatch.assert_not_awaited()
-
     @pytest.mark.asyncio
     async def test_run_logs_and_continues_after_leaked_cancelled_error(self, monkeypatch):
         loop, bus = _make_loop()

tests/agent/test_temporary_chat.py

@@ -1,169 +0,0 @@
-import asyncio
-from unittest.mock import AsyncMock, MagicMock
-
-import pytest
-
-from nanobot.agent.loop import AgentLoop
-from nanobot.agent.tools.registry import ToolRegistry
-from nanobot.bus.events import InboundMessage
-from nanobot.bus.queue import MessageBus
-from nanobot.providers.base import GenerationSettings, LLMResponse
-from nanobot.runtime_context import RuntimeContextBlock
-from nanobot.session.manager import SessionManager
-
-
-@pytest.mark.asyncio
-async def test_temporary_chat_reuses_memory_only_history_without_tools(tmp_path) -> None:
-    (tmp_path / "AGENTS.md").write_text("private project instruction", encoding="utf-8")
-    provider = MagicMock()
-    provider.get_default_model.return_value = "test-model"
-    provider.generation = GenerationSettings()
-    provider.chat_with_retry = AsyncMock(
-        side_effect=[
-            LLMResponse(content="first answer", usage={}),
-            LLMResponse(content="second answer", usage={}),
-        ]
-    )
-    loop = AgentLoop(
-        bus=MessageBus(),
-        provider=provider,
-        workspace=tmp_path,
-        model="test-model",
-        unified_session=True,
-    )
-    key = "websocket:temporary-test"
-    loop.sessions.get_or_create_transient(key)
-
-    for content in ("first question", "second question"):
-        response = await loop._process_message(
-            InboundMessage(
-                channel="websocket",
-                sender_id="user",
-                chat_id="temporary-test",
-                content=content,
-                session_key_override=key,
-                transient_session=True,
-            )
-        )
-        assert response is not None
-
-    first_call, second_call = provider.chat_with_retry.await_args_list
-    assert first_call.kwargs["tools"] == []
-    assert second_call.kwargs["tools"] == []
-    assert all(
-        message["role"] != "system"
-        for call in (first_call, second_call)
-        for message in call.kwargs["messages"]
-    )
-    assert "private project instruction" not in str(first_call.kwargs["messages"])
-    assert str(tmp_path) not in str(first_call.kwargs["messages"])
-    assert "first answer" in str(second_call.kwargs["messages"])
-
-    transient = loop.sessions.get_cached(key)
-    assert transient is not None
-    assert [message["role"] for message in transient.messages] == [
-        "user",
-        "assistant",
-        "user",
-        "assistant",
-    ]
-    assert loop.sessions.read_session_file(key) is None
-    assert SessionManager(tmp_path).read_session_file(key) is None
-
-
-@pytest.mark.asyncio
-async def test_temporary_follow_up_does_not_resolve_runtime_context(tmp_path) -> None:
-    provider = MagicMock()
-    provider.get_default_model.return_value = "test-model"
-    provider.generation = GenerationSettings()
-    provider.chat_with_retry = AsyncMock(
-        side_effect=[
-            LLMResponse(content="first answer", usage={}),
-            LLMResponse(content="second answer", usage={}),
-        ]
-    )
-    loop = AgentLoop(
-        bus=MessageBus(),
-        provider=provider,
-        workspace=tmp_path,
-        model="test-model",
-    )
-    runtime_context_provider = AsyncMock(
-        return_value=RuntimeContextBlock(
-            source="project",
-            content="SECRET LOCAL PROJECT CONTEXT",
-        )
-    )
-    loop.register_runtime_context_provider(runtime_context_provider)
-
-    key = "websocket:temporary-follow-up"
-    session = loop.sessions.get_or_create_transient(key)
-    pending_queue: asyncio.Queue[InboundMessage] = asyncio.Queue()
-    await pending_queue.put(
-        InboundMessage(
-            channel="websocket",
-            sender_id="user",
-            chat_id="temporary-follow-up",
-            content="follow up",
-            session_key_override=key,
-            transient_session=True,
-        )
-    )
-
-    _, _, messages, _, _ = await loop._run_agent_loop(
-        [{"role": "user", "content": "first question"}],
-        runtime=loop.llm_runtime(),
-        session=session,
-        channel="websocket",
-        chat_id="temporary-follow-up",
-        session_key=key,
-        pending_queue=pending_queue,
-        tools=ToolRegistry(),
-    )
-
-    runtime_context_provider.assert_not_awaited()
-    assert "SECRET LOCAL PROJECT CONTEXT" not in str(messages)
-
-
-@pytest.mark.asyncio
-async def test_discarding_active_temporary_chat_does_not_create_durable_session(
-    tmp_path,
-) -> None:
-    provider_started = asyncio.Event()
-    provider = MagicMock()
-    provider.get_default_model.return_value = "test-model"
-    provider.generation = GenerationSettings()
-
-    async def block_provider(**_kwargs):
-        provider_started.set()
-        await asyncio.Event().wait()
-
-    provider.chat_with_retry = AsyncMock(side_effect=block_provider)
-    loop = AgentLoop(
-        bus=MessageBus(),
-        provider=provider,
-        workspace=tmp_path,
-        model="test-model",
-    )
-    key = "websocket:temporary-cancelled"
-    loop.sessions.get_or_create_transient(key)
-    message = InboundMessage(
-        channel="websocket",
-        sender_id="user",
-        chat_id="temporary-cancelled",
-        content="private",
-        session_key_override=key,
-        transient_session=True,
-    )
-    task = asyncio.create_task(loop._dispatch(message))
-    active_tasks = loop._active_tasks.setdefault(key, set())
-    active_tasks.add(task)
-    task.add_done_callback(active_tasks.discard)
-
-    await provider_started.wait()
-    assert loop.sessions.discard_transient(key)
-    assert await loop.cancel_active_turn(key) == 1
-
-    assert loop.sessions.get_cached(key) is None
-    assert loop.sessions.flush_all() == 0
-    assert loop.sessions.read_session_file(key) is None

tests/agent/test_unified_session.py

@@ -253,7 +253,7 @@ class TestCmdNewUnifiedSession:
         loop = SimpleNamespace(
             sessions=sessions,
             consolidator=SimpleNamespace(archive=AsyncMock(return_value=True)),
-            cancel_active_turn=AsyncMock(return_value=0),
+            _cancel_active_tasks=AsyncMock(return_value=0),
             llm_runtime=MagicMock(return_value=MagicMock()),
             schedule_background=lambda coro: asyncio.ensure_future(coro),
         )
@@ -301,7 +301,7 @@ class TestCmdNewUnifiedSession:
         loop = SimpleNamespace(
             sessions=sessions,
             consolidator=SimpleNamespace(archive=AsyncMock(return_value=True)),
-            cancel_active_turn=AsyncMock(return_value=0),
+            _cancel_active_tasks=AsyncMock(return_value=0),
             runtime_for_session=MagicMock(return_value=MagicMock()),
             schedule_background=lambda coro: asyncio.ensure_future(coro),
         )

tests/agent/tools/test_subagent_tools.py

@@ -504,7 +504,6 @@ async def test_drain_pending_blocks_while_subagents_running(tmp_path):
             usage={},
             had_injections=False,
             tools_used=[],
-            provider_state=None,
         )
 
     loop.runner.run = AsyncMock(side_effect=fake_runner_run)
@@ -590,7 +589,6 @@ async def test_drain_pending_no_block_when_no_subagents(tmp_path):
             usage={},
             had_injections=False,
             tools_used=[],
-            provider_state=None,
         )
 
     loop.runner.run = AsyncMock(side_effect=fake_runner_run)
@@ -640,7 +638,6 @@ async def test_drain_pending_timeout(tmp_path):
             usage={},
             had_injections=False,
             tools_used=[],
-            provider_state=None,
         )
 
     loop.runner.run = AsyncMock(side_effect=fake_runner_run)

tests/channels/test_base_channel.py

@@ -83,49 +83,6 @@ async def test_handle_message_dm_sends_pairing_code(monkeypatch) -> None:
     assert msg.metadata.get("_pairing_code") == "ABCD-EFGH"
 
 
-@pytest.mark.asyncio
-async def test_dm_during_transient_store_failure_keeps_approvals(
-    tmp_path, monkeypatch
-) -> None:
-    """An unapproved DM while pairing.json is unreadable must not wipe approvals.
-
-    The pairing store treated a transient OSError like corruption and returned
-    an empty store; the DM pairing path then persisted that empty view,
-    erasing every approved sender.
-    """
-    import builtins
-    from pathlib import Path
-
-    from nanobot.pairing import store
-
-    path = tmp_path / "pairing.json"
-    monkeypatch.setattr(store, "_store_path", lambda: path)
-    code = store.generate_code("dummy", "friend")
-    store.approve_code(code)
-
-    channel = _DummyChannel({"allowFrom": []}, MessageBus())
-
-    real_open = builtins.open
-
-    def flaky_open(file, mode="r", *args, **kwargs):
-        try:
-            same = Path(file) == path
-        except TypeError:
-            same = False
-        if same and "r" in mode and "+" not in mode:
-            raise PermissionError(13, "temporarily locked", str(path))
-        return real_open(file, mode, *args, **kwargs)
-
-    with monkeypatch.context() as m:
-        m.setattr(builtins, "open", flaky_open)
-        await channel._handle_message(
-            sender_id="stranger", chat_id="chat1", content="hello", is_dm=True
-        )
-
-    assert channel._sent == []
-    assert store.is_approved("dummy", "friend") is True
-
-
 @pytest.mark.asyncio
 async def test_handle_message_group_ignores_unknown() -> None:
     channel = _DummyChannel({"allowFrom": []}, MessageBus())

tests/channels/test_channel_plugins.py

@@ -2558,7 +2558,7 @@ def test_optional_dependency_metadata_for_enable():
     ):
         assert not any(dep.startswith(dep_name) for dep in required)
     for dependency in (
-        "tzdata>=2025.2",
+        "tzdata>=2025.2; sys_platform == 'win32'",
         "defusedxml>=0.7.1,<1.0.0",
         "pypdf>=5.0.0,<6.0.0",
         "python-docx>=1.1.0,<2.0.0",

tests/cli/test_commands.py

@@ -1160,63 +1160,6 @@ def test_config_falls_back_to_vllm_when_ollama_not_configured():
     assert config.get_api_base() == "http://localhost:8000"
 
 
-def test_config_cloud_nemotron_is_not_hijacked_by_unconfigured_ollama():
-    """`nvidia/nemotron-*` via a gateway must not route to Ollama when no
-    Ollama endpoint is configured. Ollama keeps "nemotron" in its keywords
-    for bare-model auto-routing (PR #1863), which previously hijacked
-    cloud-hosted nemotron variants and silently sent traffic to
-    http://localhost:11434/v1."""
-    config = Config.model_validate(
-        {
-            "agents": {
-                "defaults": {
-                    "provider": "auto",
-                    "model": "nvidia/nemotron-3-super-120b-a12b",
-                }
-            },
-            "providers": {"openrouter": {"apiKey": "sk-or-test"}},
-        }
-    )
-
-    assert config.get_provider_name() == "openrouter"
-    assert config.get_api_base() == "https://openrouter.ai/api/v1"
-
-
-def test_config_bare_nemotron_still_auto_routes_to_configured_ollama():
-    """Preserves PR #1863 intent: when the user has actually configured an
-    Ollama endpoint, a bare nemotron model still auto-routes there."""
-    config = Config.model_validate(
-        {
-            "agents": {"defaults": {"provider": "auto", "model": "nemotron-3-nano"}},
-            "providers": {"ollama": {"apiBase": "http://localhost:11434/v1"}},
-        }
-    )
-
-    assert config.get_provider_name() == "ollama"
-    assert config.get_api_base() == "http://localhost:11434/v1"
-
-
-def test_config_cloud_nemotron_is_not_hijacked_by_configured_ollama():
-    """An explicit cloud namespace takes precedence over local keywords."""
-    config = Config.model_validate(
-        {
-            "agents": {
-                "defaults": {
-                    "provider": "auto",
-                    "model": "nvidia/nemotron-3-super-120b-a12b",
-                }
-            },
-            "providers": {
-                "ollama": {"apiBase": "http://localhost:11434/v1"},
-                "openrouter": {"apiKey": "sk-or-test"},
-            },
-        }
-    )
-
-    assert config.get_provider_name() == "openrouter"
-    assert config.get_api_base() == "https://openrouter.ai/api/v1"
-
-
 def test_openai_compat_provider_passes_model_through():
     from nanobot.providers.openai_compat_provider import OpenAICompatProvider
 

tests/command/test_router_dispatchable.py

@@ -109,7 +109,7 @@ class TestMidTurnCommandDispatchedDirectly:
         loop.sessions.save = MagicMock()
         loop.sessions.invalidate = MagicMock()
         loop.schedule_background = MagicMock()
-        loop.cancel_active_turn = AsyncMock(return_value=0)
+        loop._cancel_active_tasks = AsyncMock(return_value=0)
         return loop
 
     @pytest.fixture()

tests/command/test_stop_pending_queue.py

@@ -1,5 +1,6 @@
 """Test cmd_stop drains pending queue to prevent mid-turn injection deadlock."""
 
+import asyncio
 from unittest.mock import AsyncMock, MagicMock
 
 import pytest
@@ -13,7 +14,13 @@ from nanobot.command.router import CommandContext
 async def test_cmd_stop_drains_pending_queue():
     """cmd_stop should drain pending queue in addition to cancelling active tasks."""
     mock_loop = MagicMock()
-    mock_loop.cancel_active_turn = AsyncMock(return_value=3)
+    mock_loop._cancel_active_tasks = AsyncMock(return_value=1)
+    mock_loop._pending_queues = {}
+
+    pending = asyncio.Queue()
+    await pending.put("msg1")
+    await pending.put("msg2")
+    mock_loop._pending_queues["test-session"] = pending
 
     ctx = CommandContext(
         msg=MagicMock(channel="websocket", chat_id="test-chat", metadata={}),
@@ -27,14 +34,18 @@ async def test_cmd_stop_drains_pending_queue():
 
     assert isinstance(result, OutboundMessage)
     assert "Stopped 3 task(s)" in result.content  # 1 cancelled + 2 drained
-    mock_loop.cancel_active_turn.assert_awaited_once_with("test-session")
+    assert "test-session" not in mock_loop._pending_queues
 
 
 @pytest.mark.asyncio
 async def test_cmd_stop_with_empty_pending_queue():
     """cmd_stop should work correctly when pending queue is empty."""
     mock_loop = MagicMock()
-    mock_loop.cancel_active_turn = AsyncMock(return_value=2)
+    mock_loop._cancel_active_tasks = AsyncMock(return_value=2)
+    mock_loop._pending_queues = {}
+
+    pending = asyncio.Queue()
+    mock_loop._pending_queues["test-session"] = pending
 
     ctx = CommandContext(
         msg=MagicMock(channel="websocket", chat_id="test-chat", metadata={}),
@@ -47,14 +58,15 @@ async def test_cmd_stop_with_empty_pending_queue():
     result = await cmd_stop(ctx)
 
     assert "Stopped 2 task(s)" in result.content
-    mock_loop.cancel_active_turn.assert_awaited_once_with("test-session")
+    assert "test-session" not in mock_loop._pending_queues
 
 
 @pytest.mark.asyncio
 async def test_cmd_stop_no_pending_queue():
     """cmd_stop should work when no pending queue exists."""
     mock_loop = MagicMock()
-    mock_loop.cancel_active_turn = AsyncMock(return_value=0)
+    mock_loop._cancel_active_tasks = AsyncMock(return_value=0)
+    mock_loop._pending_queues = {}
 
     ctx = CommandContext(
         msg=MagicMock(channel="websocket", chat_id="test-chat", metadata={}),

tests/config/test_model_presets.py

@@ -1,8 +1,4 @@
 import json
-import os
-import subprocess
-import sys
-import textwrap
 import warnings
 
 import pytest
@@ -46,32 +42,6 @@ def test_agent_timezone_rejects_unknown_iana_name() -> None:
         Config.model_validate({"agents": {"defaults": {"timezone": "Not/AZone"}}})
 
 
-def test_agent_timezones_use_packaged_data_without_system_database() -> None:
-    script = textwrap.dedent(
-        """\
-        from zoneinfo import TZPATH
-
-        from nanobot.config.schema import Config
-
-        assert not TZPATH
-        for name in ("UTC", "Asia/Shanghai"):
-            config = Config.model_validate({"agents": {"defaults": {"timezone": name}}})
-            serialized = config.model_dump(mode="json", by_alias=True)
-            restored = Config.model_validate(serialized)
-            assert restored.agents.defaults.timezone == name
-        """
-    )
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        env=os.environ | {"PYTHONTZPATH": ""},
-        capture_output=True,
-        text=True,
-        check=False,
-    )
-
-    assert result.returncode == 0, result.stderr
-
-
 def test_provider_api_type_accepts_exact_values_only() -> None:
     config = Config.model_validate({
         "providers": {

tests/cron/test_cron_service.py

@@ -600,117 +600,6 @@ async def test_run_job_preserves_running_service_state(tmp_path) -> None:
     service.stop()
 
 
-@pytest.mark.asyncio
-async def test_manual_run_persists_completion_when_callback_lists_jobs(tmp_path) -> None:
-    store_path = tmp_path / "cron" / "jobs.json"
-
-    async def on_job(_job) -> None:
-        service.list_jobs(include_disabled=True)
-        await asyncio.sleep(0)
-
-    service = CronService(store_path, on_job=on_job)
-    job = service.add_job(
-        name="manual",
-        schedule=CronSchedule(kind="every", every_ms=60_000),
-        message="hello",
-        **_bound_chat(),
-    )
-
-    assert await service.run_job(job.id) is True
-
-    state = json.loads(store_path.read_text())["jobs"][0]["state"]
-    assert state["lastStatus"] == "ok"
-    assert state["lastError"] is None
-    assert len(state["runHistory"]) == 1
-    assert state["runHistory"][0]["status"] == "ok"
-
-
-@pytest.mark.asyncio
-async def test_overlapping_manual_runs_preserve_stopped_service_state(tmp_path) -> None:
-    store_path = tmp_path / "cron" / "jobs.json"
-    entered = [asyncio.Event(), asyncio.Event()]
-    release = [asyncio.Event(), asyncio.Event()]
-    call_count = 0
-
-    async def on_job(_job) -> None:
-        nonlocal call_count
-        call_index = call_count
-        call_count += 1
-        entered[call_index].set()
-        await release[call_index].wait()
-
-    service = CronService(store_path, on_job=on_job)
-    jobs = [
-        service.add_job(
-            name=f"manual-{index}",
-            schedule=CronSchedule(kind="every", every_ms=60_000),
-            message="hello",
-            **_bound_chat(str(index)),
-        )
-        for index in range(2)
-    ]
-
-    first = asyncio.create_task(service.run_job(jobs[0].id))
-    await entered[0].wait()
-    second = asyncio.create_task(service.run_job(jobs[1].id))
-    try:
-        await entered[1].wait()
-        release[0].set()
-        assert await first is True
-        assert service._running is False
-
-        release[1].set()
-        assert await second is True
-        assert service._running is False
-        assert service._timer_task is None
-
-        states = {
-            item["name"]: item["state"]
-            for item in json.loads(store_path.read_text())["jobs"]
-        }
-        assert states["manual-0"]["lastStatus"] == "ok"
-        assert states["manual-1"]["lastStatus"] == "ok"
-    finally:
-        release[0].set()
-        release[1].set()
-        await asyncio.gather(first, second, return_exceptions=True)
-        service.stop()
-
-
-@pytest.mark.asyncio
-async def test_manual_run_does_not_restart_service_stopped_during_execution(tmp_path) -> None:
-    store_path = tmp_path / "cron" / "jobs.json"
-    entered = asyncio.Event()
-    release = asyncio.Event()
-
-    async def on_job(_job) -> None:
-        entered.set()
-        await release.wait()
-
-    service = CronService(store_path, on_job=on_job)
-    job = service.add_job(
-        name="manual-stop",
-        schedule=CronSchedule(kind="every", every_ms=60_000),
-        message="hello",
-        **_bound_chat(),
-    )
-    await service.start()
-
-    run = asyncio.create_task(service.run_job(job.id))
-    try:
-        await entered.wait()
-        service.stop()
-        release.set()
-
-        assert await run is True
-        assert service._running is False
-        assert service._timer_task is None
-    finally:
-        release.set()
-        await asyncio.gather(run, return_exceptions=True)
-        service.stop()
-
-
 @pytest.mark.asyncio
 async def test_running_service_honors_external_disable(tmp_path) -> None:
     store_path = tmp_path / "cron" / "jobs.json"

tests/pairing/test_store.py

@@ -323,66 +323,3 @@ def test_pending_gc_drops_malformed_entries(tmp_path, monkeypatch):
     )
     monkeypatch.setattr(store, "_store_path", lambda: path)
     assert store.list_pending() == []
-
-
-def _fail_reads_of(monkeypatch, path):
-    """Make reads of *path* raise like a transiently locked/busy file."""
-    import builtins
-    from pathlib import Path
-
-    real_open = builtins.open
-
-    def flaky_open(file, mode="r", *args, **kwargs):
-        try:
-            same = Path(file) == path
-        except TypeError:
-            same = False
-        if same and "r" in mode and "+" not in mode:
-            raise PermissionError(13, "temporarily locked", str(path))
-        return real_open(file, mode, *args, **kwargs)
-
-    monkeypatch.setattr(builtins, "open", flaky_open)
-
-
-class TestTransientReadFailure:
-    """A transient I/O failure is not corruption and must never wipe the store."""
-
-    def test_generate_code_does_not_wipe_approvals(self, tmp_path, monkeypatch):
-        """An unapproved DM during a read blip previously erased every approval.
-
-        _load treated OSError like corruption and returned an empty store;
-        generate_code then unconditionally saved it, overwriting pairing.json
-        with no approved senders.
-        """
-        code = store.generate_code("telegram", "123")
-        store.approve_code(code)
-
-        with monkeypatch.context() as m:
-            _fail_reads_of(m, store._store_path())
-            with pytest.raises(OSError):
-                store.generate_code("telegram", "stranger")
-
-        assert store.is_approved("telegram", "123") is True
-
-    def test_reads_fail_closed_without_crashing(self, tmp_path, monkeypatch):
-        code = store.generate_code("telegram", "123")
-        store.approve_code(code)
-
-        with monkeypatch.context() as m:
-            _fail_reads_of(m, store._store_path())
-            assert store.is_approved("telegram", "123") is False
-            assert store.list_pending() == []
-            assert store.get_approved("telegram") == []
-
-        assert store.is_approved("telegram", "123") is True
-
-    def test_approve_command_reports_store_unavailable(self, tmp_path, monkeypatch):
-        """/pairing approve must fail loudly instead of claiming the code is invalid."""
-        code = store.generate_code("telegram", "123")
-
-        with monkeypatch.context() as m:
-            _fail_reads_of(m, store._store_path())
-            reply = store.handle_pairing_command("telegram", f"approve {code}")
-
-        assert "unavailable" in reply.lower()
-        assert store.approve_code(code) == ("telegram", "123")

tests/providers/test_azure_openai_provider.py

@@ -11,7 +11,7 @@ from nanobot.providers.azure_openai_provider import (
     AzureOpenAIProvider,
     _AzureTokenProvider,
 )
-from nanobot.providers.base import LLMResponse, ProviderCallContext
+from nanobot.providers.base import LLMResponse
 
 # ---------------------------------------------------------------------------
 # Init & validation
@@ -234,7 +234,6 @@ def test_build_body_basic():
     assert body["max_output_tokens"] == 4096
     assert body["store"] is False
     assert "reasoning" not in body
-    assert "include" not in body
     # input should contain the converted user message only (system extracted)
     assert any(
         item.get("role") == "user"
@@ -242,30 +241,6 @@ def test_build_body_basic():
     )
 
 
-def test_build_body_enables_server_compaction():
-    provider = AzureOpenAIProvider(
-        api_key="k",
-        api_base="https://res.openai.azure.com",
-        default_model="gpt-5.6",
-    )
-
-    body = provider._build_body(
-        [{"role": "user", "content": "hello"}],
-        None,
-        None,
-        10_000,
-        0.1,
-        "high",
-        None,
-        provider_context=ProviderCallContext(context_window_tokens=200_000),
-    )
-
-    assert body["context_management"] == [{
-        "type": "compaction",
-        "compact_threshold": 180_000,
-    }]
-
-
 def test_build_body_max_tokens_minimum():
     """max_output_tokens should never be less than 1."""
     provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-4o")
@@ -383,38 +358,6 @@ async def test_chat_success():
     assert result.usage["prompt_tokens"] == 10
 
 
-@pytest.mark.asyncio
-async def test_chat_retries_without_unsupported_server_compaction():
-    provider = AzureOpenAIProvider(
-        api_key="test-key",
-        api_base="https://test.openai.azure.com",
-        default_model="gpt-5.6",
-    )
-
-    class UnsupportedCompactionError(Exception):
-        status_code = 400
-        body = {"error": {"message": "Unknown parameter: context_management"}}
-
-    provider._client.responses = MagicMock()
-    provider._client.responses.create = AsyncMock(side_effect=[
-        UnsupportedCompactionError(),
-        _make_sdk_response(content="compaction fallback"),
-    ])
-
-    result = await provider.chat(
-        [{"role": "user", "content": "Hi"}],
-        provider_context=ProviderCallContext(context_window_tokens=200_000),
-    )
-
-    create = provider._client.responses.create
-    assert result.content == "compaction fallback"
-    assert result.provider_state is not None
-    assert create.await_count == 2
-    assert "context_management" in create.call_args_list[0].kwargs
-    assert "context_management" not in create.call_args_list[1].kwargs
-    assert provider.supports_native_compaction() is False
-
-
 @pytest.mark.asyncio
 async def test_chat_uses_default_model():
     provider = AzureOpenAIProvider(
@@ -468,7 +411,6 @@ async def test_chat_with_tool_calls():
     assert len(result.tool_calls) == 1
     assert result.tool_calls[0].name == "get_weather"
     assert result.tool_calls[0].arguments == {"location": "SF"}
-    assert result.provider_state is not None
 
 
 @pytest.mark.asyncio
@@ -568,7 +510,6 @@ async def test_chat_stream_with_tool_calls():
     item_done.name = "get_weather"
     ev_item_done = MagicMock(type="response.output_item.done", item=item_done)
     resp_obj = MagicMock(status="completed")
-    resp_obj.model_dump.return_value = {"status": "completed", "output": []}
     ev_completed = MagicMock(type="response.completed", response=resp_obj)
 
     async def mock_stream():
@@ -586,7 +527,6 @@ async def test_chat_stream_with_tool_calls():
     assert len(result.tool_calls) == 1
     assert result.tool_calls[0].name == "get_weather"
     assert result.tool_calls[0].arguments == {"location": "SF"}
-    assert result.provider_state is not None
 
 
 @pytest.mark.asyncio

tests/providers/test_conversation_state.py

@@ -1,291 +0,0 @@
-"""Tests for provider-owned conversation-state lifecycle coordination."""
-
-from __future__ import annotations
-
-from unittest.mock import MagicMock
-
-import pytest
-
-from nanobot.providers.base import (
-    LLMProvider,
-    LLMResponse,
-    ProviderConversationState,
-    ToolCallRequest,
-)
-from nanobot.providers.conversation_state import (
-    ProviderConversationStateController,
-    allows_conversation_message_merge,
-)
-
-
-def _provider(*, resumable: bool = True, compact: bool = False) -> MagicMock:
-    provider = MagicMock(spec=LLMProvider)
-    provider.can_resume_conversation_state.return_value = resumable
-    provider.supports_native_compaction.return_value = compact
-    return provider
-
-
-def _state(label: str, *, pending: list[dict] | None = None) -> ProviderConversationState:
-    return ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={"items": [{"type": "reasoning", "encrypted_content": label}]},
-        pending_messages=pending or [],
-    )
-
-
-def test_controller_replays_only_messages_after_provider_output() -> None:
-    provider = _provider()
-    messages = [
-        {"role": "system", "content": "system"},
-        {"role": "user", "content": "run a tool"},
-    ]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-    )
-    state = _state("first")
-
-    controller.prepare_request(messages, context_window_tokens=200_000)
-    response = LLMResponse(content=None, provider_state=state)
-    controller.observe_response(response, messages)
-    assert allows_conversation_message_merge(messages[-1]) is False
-
-    messages.append(controller.project_response_message(
-        {
-            "role": "assistant",
-            "content": None,
-            "tool_calls": [{"id": "call_1", "type": "function"}],
-        },
-        response,
-    ))
-    tool_message = {
-        "role": "tool",
-        "tool_call_id": "call_1",
-        "content": "tool result",
-    }
-    messages.append(tool_message)
-
-    provider_context = controller.prepare_request(
-        messages,
-        context_window_tokens=200_000,
-    )
-
-    assert provider_context is not None
-    assert provider_context.conversation_state is not None
-    assert provider_context.conversation_state.payload == state.payload
-    assert provider_context.conversation_state.pending_messages == [tool_message]
-    assert controller.checkpoint(messages).pending_messages == [tool_message]
-
-
-def test_controller_uses_governed_messages_for_provider_state_delta() -> None:
-    provider = _provider()
-    messages = [
-        {"role": "user", "content": "run a tool"},
-    ]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-    )
-    state = _state("first")
-
-    controller.prepare_request(messages, context_window_tokens=200_000)
-    response = LLMResponse(content=None, provider_state=state)
-    controller.observe_response(response, messages)
-    messages.extend([
-        controller.project_response_message(
-            {
-                "role": "assistant",
-                "content": None,
-                "tool_calls": [{"id": "call_1", "type": "function"}],
-            },
-            response,
-        ),
-        {
-            "role": "tool",
-            "tool_call_id": "call_1",
-            "content": "raw oversized result",
-        },
-    ])
-    governed_messages = [
-        messages[0],
-        messages[1],
-        {
-            "role": "tool",
-            "tool_call_id": "call_1",
-            "content": "compacted result",
-        },
-    ]
-
-    provider_context = controller.prepare_request(
-        messages,
-        context_window_tokens=200_000,
-        model_messages=governed_messages,
-    )
-
-    assert provider_context is not None
-    assert provider_context.conversation_state is not None
-    assert provider_context.conversation_state.pending_messages == [{
-        "role": "tool",
-        "tool_call_id": "call_1",
-        "content": "compacted result",
-    }]
-    assert controller.checkpoint(messages).pending_messages[-1]["content"] == (
-        "raw oversized result"
-    )
-    governed_checkpoint = controller.checkpoint(
-        messages,
-        model_messages=governed_messages,
-    )
-    assert governed_checkpoint is not None
-    assert governed_checkpoint.pending_messages[-1]["content"] == "compacted result"
-
-
-def test_transient_response_preserves_only_durable_request_messages() -> None:
-    provider = _provider()
-    current_message = {"role": "user", "content": "continue"}
-    supplemental = {"role": "user", "content": "internal finalization retry"}
-    messages = [{"role": "system", "content": "system"}, current_message]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-        state=_state("saved", pending=[
-            {"role": "tool", "content": "prior"},
-            current_message,
-        ]),
-    )
-
-    provider_context = controller.prepare_request(
-        messages,
-        context_window_tokens=200_000,
-        supplemental_messages=[supplemental],
-    )
-    assert provider_context is not None
-    assert provider_context.conversation_state is not None
-    assert provider_context.conversation_state.pending_messages == [
-        {"role": "tool", "content": "prior"},
-        current_message,
-        supplemental,
-    ]
-
-    controller.observe_response(
-        LLMResponse(
-            content="temporary failure",
-            finish_reason="error",
-            error_kind="timeout",
-        ),
-        messages,
-    )
-    placeholder = {"role": "assistant", "content": "model error"}
-    messages.append(placeholder)
-
-    state = controller.finish(messages)
-    assert state is not None
-    assert state.pending_messages == [
-        {"role": "tool", "content": "prior"},
-        current_message,
-        placeholder,
-    ]
-
-
-def test_non_retryable_response_discards_saved_state() -> None:
-    provider = _provider()
-    messages = [{"role": "user", "content": "continue"}]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-        state=_state("saved"),
-    )
-
-    controller.prepare_request(messages, context_window_tokens=200_000)
-    controller.observe_response(
-        LLMResponse(
-            content="invalid request",
-            finish_reason="error",
-            error_status_code=400,
-            error_should_retry=False,
-        ),
-        messages,
-    )
-
-    assert controller.finish(messages) is None
-
-
-@pytest.mark.parametrize(
-    ("finish_reason", "exposes_tool_call"),
-    [
-        ("length", False),
-        ("length", True),
-        ("refusal", True),
-        ("content_filter", True),
-    ],
-)
-def test_terminal_response_discards_candidate_state(
-    finish_reason: str,
-    exposes_tool_call: bool,
-) -> None:
-    provider = _provider()
-    messages = [{"role": "user", "content": "continue"}]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-        state=_state("saved"),
-    )
-
-    controller.prepare_request(messages, context_window_tokens=200_000)
-    candidate = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload={
-            "items": [{
-                "type": "function_call",
-                "call_id": "call_1",
-                "name": "exec",
-                "arguments": "{}",
-            }],
-        },
-    )
-    response = LLMResponse(
-        content="terminal response",
-        tool_calls=(
-            [ToolCallRequest(id="call_1", name="exec", arguments={})]
-            if exposes_tool_call
-            else []
-        ),
-        finish_reason=finish_reason,
-        provider_state=candidate,
-    )
-    assert response.has_tool_calls is exposes_tool_call
-    assert response.should_execute_tools is False
-
-    controller.observe_response(response, messages)
-
-    assert controller.finish(messages) is None
-
-
-def test_independent_request_exposes_context_without_capability_check() -> None:
-    provider = _provider(compact=False)
-    messages = [{"role": "user", "content": "hello"}]
-    controller = ProviderConversationStateController(
-        provider=provider,
-        model="gpt-5.6",
-        messages=messages,
-        state=_state("saved"),
-    )
-
-    provider_context = controller.independent_request_context(
-        context_window_tokens=200_000,
-    )
-    assert provider_context is not None
-    assert provider_context.conversation_state is None
-    assert provider_context.context_window_tokens == 200_000
-    provider.supports_native_compaction.assert_not_called()

tests/providers/test_github_copilot_routing.py

@@ -10,7 +10,6 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from nanobot.providers.base import ProviderCallContext
 from nanobot.providers.openai_compat_provider import OpenAICompatProvider
 from nanobot.providers.registry import find_by_name
 
@@ -45,10 +44,8 @@ def test_build_responses_body_strips_github_copilot_prefix():
         temperature=0.1,
         reasoning_effort=None,
         tool_choice=None,
-        provider_context=ProviderCallContext(context_window_tokens=128_000),
     )
     assert body["model"] == "gpt-5.4-mini"
-    assert "context_management" not in body
 
 
 @pytest.mark.asyncio

tests/providers/test_litellm_kwargs.py

@@ -14,7 +14,6 @@ from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from nanobot.providers.base import ProviderCallContext
 from nanobot.providers.openai_compat_provider import OpenAICompatProvider
 from nanobot.providers.registry import find_by_name
 
@@ -680,7 +679,6 @@ async def test_direct_openai_gpt5_uses_responses_api() -> None:
     assert call_kwargs["max_output_tokens"] == 4096
     assert "input" in call_kwargs
     assert "messages" not in call_kwargs
-    assert call_kwargs["include"] == ["reasoning.encrypted_content"]
 
 
 @pytest.mark.asyncio
@@ -712,40 +710,6 @@ async def test_direct_openai_reasoning_prefers_responses_api() -> None:
     assert call_kwargs["include"] == ["reasoning.encrypted_content"]
 
 
-@pytest.mark.asyncio
-async def test_direct_openai_retries_without_unsupported_server_compaction() -> None:
-    mock_chat = AsyncMock(return_value=_fake_chat_response())
-    mock_responses = AsyncMock(side_effect=[
-        _FakeResponsesError(400, "Unknown parameter: context_management"),
-        _fake_responses_response("compaction fallback"),
-    ])
-    spec = find_by_name("openai")
-
-    with patch("nanobot.providers.openai_compat_provider.AsyncOpenAI") as mock_client_class:
-        client_instance = mock_client_class.return_value
-        client_instance.chat.completions.create = mock_chat
-        client_instance.responses.create = mock_responses
-        provider = OpenAICompatProvider(
-            api_key="sk-test-key",
-            default_model="gpt-5.6",
-            spec=spec,
-        )
-
-        result = await provider.chat_with_context(
-            messages=[{"role": "user", "content": "hello"}],
-            model="gpt-5.6",
-            provider_context=ProviderCallContext(context_window_tokens=200_000),
-        )
-
-    assert result.content == "compaction fallback"
-    assert result.provider_state is not None
-    assert mock_responses.await_count == 2
-    assert "context_management" in mock_responses.call_args_list[0].kwargs
-    assert "context_management" not in mock_responses.call_args_list[1].kwargs
-    assert provider.supports_native_compaction("gpt-5.6") is False
-    mock_chat.assert_not_awaited()
-
-
 @pytest.mark.asyncio
 async def test_direct_openai_gpt4o_stays_on_chat_completions() -> None:
     mock_chat = AsyncMock(return_value=_fake_chat_response())

tests/providers/test_openai_codex_provider.py

@@ -20,7 +20,6 @@ from nanobot.providers.openai_codex_provider import (
     _request_codex,
     _should_retry_status,
 )
-from nanobot.providers.openai_responses import build_responses_state
 from nanobot.providers.registry import find_by_name
 
 
@@ -116,48 +115,6 @@ async def test_codex_request_non_200_populates_http_metadata(monkeypatch) -> Non
     assert error.should_retry is True
 
 
-@pytest.mark.asyncio
-async def test_codex_request_marks_rejected_compaction_without_retaining_raw_body(
-    monkeypatch,
-) -> None:
-    original_client = httpx.AsyncClient
-    secret = "PRIVATE PROMPT MUST NOT BE RETAINED"
-
-    def handler(request: httpx.Request) -> httpx.Response:
-        return httpx.Response(
-            400,
-            json={
-                "error": {
-                    "message": f"Unknown input type compaction_trigger; {secret}",
-                },
-            },
-            request=request,
-        )
-
-    def fake_client(
-        *,
-        timeout: int,
-        verify: bool,
-        **_kwargs: object,
-    ) -> httpx.AsyncClient:
-        return original_client(transport=httpx.MockTransport(handler), timeout=timeout)
-
-    monkeypatch.setattr("nanobot.providers.openai_codex_provider.httpx.AsyncClient", fake_client)
-
-    with pytest.raises(_CodexHTTPError) as caught:
-        await _request_codex(
-            "https://codex.example/responses",
-            {},
-            {"input": [{"type": "compaction_trigger"}]},
-            verify=True,
-        )
-
-    error = caught.value
-    assert error.compaction_unsupported is True
-    assert secret not in str(error)
-    assert not hasattr(error, "body")
-
-
 @pytest.mark.asyncio
 async def test_codex_request_honors_stream_idle_timeout_env(monkeypatch) -> None:
     """NANOBOT_STREAM_IDLE_TIMEOUT_S overrides the default Codex stream timeout."""
@@ -235,7 +192,7 @@ async def test_codex_prompt_cache_key_uses_stable_conversation_prefix(monkeypatc
     ):
         _ = proxy, on_thinking_delta, on_tool_call_delta
         bodies.append(body)
-        return provider_base.LLMResponse(content="ok")
+        return "ok", [], "stop", {}, None
 
     monkeypatch.setattr("nanobot.providers.openai_codex_provider._request_codex", fake_request)
 
@@ -275,7 +232,7 @@ async def test_codex_provider_applies_extra_body_from_config(monkeypatch) -> Non
 
     async def fake_request(_url, _headers, body, **_kwargs):
         bodies.append(body)
-        return provider_base.LLMResponse(content="ok")
+        return "ok", [], "stop", {}, None
 
     monkeypatch.setattr("nanobot.providers.openai_codex_provider._request_codex", fake_request)
     config = Config.model_validate({
@@ -340,7 +297,7 @@ async def test_codex_provider_passes_proxy_to_oauth_and_response_request(monkeyp
     ):
         _ = url, headers, body, verify, on_content_delta, on_thinking_delta, on_tool_call_delta
         seen["request_proxy"] = proxy
-        return provider_base.LLMResponse(content="ok")
+        return "ok", [], "stop", {}, None
 
     monkeypatch.setattr("nanobot.providers.openai_codex_provider.get_codex_token", fake_token)
     monkeypatch.setattr("nanobot.providers.openai_codex_provider._request_codex", fake_request)
@@ -427,7 +384,7 @@ async def test_codex_retry_uses_structured_timeout_metadata(monkeypatch) -> None
         calls += 1
         if calls == 1:
             raise httpx.ReadTimeout("")
-        return provider_base.LLMResponse(content="ok")
+        return "ok", [], "stop", {}, None
 
     async def fake_sleep(delay: float) -> None:
         delays.append(delay)
@@ -576,254 +533,6 @@ def test_codex_reasoning_options_request_summary_without_forcing_effort() -> Non
     assert _build_reasoning_options("none") == {"effort": "none"}
 
 
-@pytest.mark.asyncio
-async def test_codex_replayed_tool_turn_omits_server_item_ids(monkeypatch) -> None:
-    _mock_codex_token(monkeypatch)
-    provider = OpenAICodexProvider(default_model="openai-codex/gpt-5.6-sol")
-    state = build_responses_state(
-        provider=provider._responses_state_provider(),
-        model="gpt-5.6-sol",
-        input_items=[{
-            "id": "msg_user",
-            "type": "message",
-            "role": "user",
-            "content": [{"type": "input_text", "text": "Check the weather"}],
-        }],
-        output_items=[
-            {
-                "id": "rs_reasoning",
-                "type": "reasoning",
-                "encrypted_content": "opaque reasoning",
-                "summary": [],
-            },
-            {
-                "id": "fc_read",
-                "type": "function_call",
-                "call_id": "call_read",
-                "name": "read_file",
-                "arguments": '{"path":"weather/SKILL.md"}',
-                "status": "completed",
-            },
-        ],
-    )
-    bodies: list[dict[str, Any]] = []
-
-    async def fake_request(
-        url,
-        headers,
-        body,
-        verify,
-        proxy=None,
-        on_content_delta=None,
-        on_thinking_delta=None,
-        on_tool_call_delta=None,
-    ):
-        bodies.append(body)
-        return provider_base.LLMResponse(content="done")
-
-    monkeypatch.setattr(
-        "nanobot.providers.openai_codex_provider._request_codex",
-        fake_request,
-    )
-
-    response = await provider.chat(
-        [{"role": "user", "content": "Check the weather"}],
-        provider_context=provider_base.ProviderCallContext(
-            conversation_state=state.with_pending_messages([{
-                "role": "tool",
-                "tool_call_id": "call_read|fc_read",
-                "content": "weather skill contents",
-            }]),
-        ),
-    )
-
-    assert response.content == "done"
-    assert len(bodies) == 1
-    input_items = bodies[0]["input"]
-    assert [item.get("type") for item in input_items] == [
-        "message",
-        "reasoning",
-        "function_call",
-        "function_call_output",
-    ]
-    assert all("id" not in item for item in input_items)
-    assert input_items[1]["encrypted_content"] == "opaque reasoning"
-    assert input_items[2]["call_id"] == "call_read"
-    assert input_items[3]["call_id"] == "call_read"
-
-
-@pytest.mark.asyncio
-async def test_codex_compacts_state_at_ninety_percent_before_next_request(
-    monkeypatch,
-) -> None:
-    _mock_codex_token(monkeypatch)
-    provider = OpenAICodexProvider(default_model="openai-codex/gpt-5.6-sol")
-    state_provider = provider._responses_state_provider()
-    state = build_responses_state(
-        provider=state_provider,
-        model="gpt-5.6-sol",
-        input_items=[{"type": "message", "role": "user", "content": "old question"}],
-        output_items=[
-            {"type": "reasoning", "encrypted_content": "old opaque reasoning"},
-            {
-                "type": "message",
-                "role": "assistant",
-                "content": [{"type": "output_text", "text": "old answer"}],
-            },
-        ],
-        usage={
-            "prompt_tokens": 90,
-            "completion_tokens": 5,
-            "total_tokens": 95,
-        },
-    )
-    bodies: list[dict[str, Any]] = []
-
-    async def fake_request(
-        url,
-        headers,
-        body,
-        verify,
-        proxy=None,
-        on_content_delta=None,
-        on_thinking_delta=None,
-        on_tool_call_delta=None,
-    ):
-        _ = (
-            url,
-            headers,
-            verify,
-            proxy,
-            on_content_delta,
-            on_thinking_delta,
-            on_tool_call_delta,
-        )
-        bodies.append(body)
-        if body["input"][-1].get("type") == "compaction_trigger":
-            compact_item = {
-                "type": "compaction",
-                "encrypted_content": "compacted opaque state",
-            }
-            return provider_base.LLMResponse(
-                content=None,
-                provider_state=build_responses_state(
-                    provider=state_provider,
-                    model="gpt-5.6-sol",
-                    input_items=body["input"],
-                    output_items=[compact_item],
-                    usage={
-                        "prompt_tokens": 95,
-                        "completion_tokens": 2,
-                        "total_tokens": 97,
-                    },
-                ),
-            )
-        return provider_base.LLMResponse(content="done")
-
-    monkeypatch.setattr(
-        "nanobot.providers.openai_codex_provider._request_codex",
-        fake_request,
-    )
-
-    response = await provider.chat_with_retry(
-        [
-            {"role": "system", "content": "system"},
-            {"role": "user", "content": "new question"},
-        ],
-        max_tokens=5,
-        provider_context=provider_base.ProviderCallContext(
-            conversation_state=state.with_pending_messages([
-                {"role": "user", "content": "new question"},
-            ]),
-            context_window_tokens=100,
-        ),
-    )
-
-    assert response.content == "done"
-    assert len(bodies) == 2
-    assert bodies[0]["input"][-1] == {"type": "compaction_trigger"}
-    assert bodies[1]["input"][-1] == {
-        "type": "compaction",
-        "encrypted_content": "compacted opaque state",
-    }
-    assert not any(
-        item.get("type") == "reasoning"
-        for item in bodies[1]["input"]
-    )
-    assert any(
-        item.get("role") == "user"
-        and "new question" in str(item.get("content"))
-        for item in bodies[1]["input"]
-    )
-
-
-@pytest.mark.asyncio
-async def test_codex_disables_unsupported_native_compaction_and_continues(
-    monkeypatch,
-) -> None:
-    _mock_codex_token(monkeypatch)
-    provider = OpenAICodexProvider(default_model="openai-codex/gpt-5.6-sol")
-    state_provider = provider._responses_state_provider()
-    state = build_responses_state(
-        provider=state_provider,
-        model="gpt-5.6-sol",
-        input_items=[{"type": "message", "role": "user", "content": "old"}],
-        output_items=[{"type": "reasoning", "encrypted_content": "opaque"}],
-        usage={"prompt_tokens": 90, "completion_tokens": 5, "total_tokens": 95},
-    )
-    bodies: list[dict[str, Any]] = []
-
-    async def fake_request(
-        url,
-        headers,
-        body,
-        verify,
-        proxy=None,
-        on_content_delta=None,
-        on_thinking_delta=None,
-        on_tool_call_delta=None,
-    ):
-        _ = (
-            url,
-            headers,
-            verify,
-            proxy,
-            on_content_delta,
-            on_thinking_delta,
-            on_tool_call_delta,
-        )
-        bodies.append(body)
-        if body["input"][-1].get("type") == "compaction_trigger":
-            raise _CodexHTTPError(
-                "HTTP 400: Codex API request failed",
-                status_code=400,
-                compaction_unsupported=True,
-            )
-        return provider_base.LLMResponse(content="done")
-
-    monkeypatch.setattr(
-        "nanobot.providers.openai_codex_provider._request_codex",
-        fake_request,
-    )
-
-    response = await provider.chat(
-        [{"role": "user", "content": "new"}],
-        max_tokens=5,
-        provider_context=provider_base.ProviderCallContext(
-            conversation_state=state.with_pending_messages([
-                {"role": "user", "content": "new"},
-            ]),
-            context_window_tokens=100,
-        ),
-    )
-
-    assert response.content == "done"
-    assert len(bodies) == 2
-    assert bodies[0]["input"][-1] == {"type": "compaction_trigger"}
-    assert bodies[1]["input"][-1] != {"type": "compaction_trigger"}
-    assert provider.supports_native_compaction() is False
-
-
 @pytest.mark.asyncio
 async def test_codex_stream_surfaces_reasoning_summary(monkeypatch) -> None:
     def fake_token(**_kwargs):
@@ -850,12 +559,7 @@ async def test_codex_stream_surfaces_reasoning_summary(monkeypatch) -> None:
             await on_content_delta("answer")
         if on_thinking_delta:
             await on_thinking_delta("summary")
-        return provider_base.LLMResponse(
-            content="answer",
-            finish_reason="stop",
-            usage={"prompt_tokens": 10, "completion_tokens": 5},
-            reasoning_content="summary",
-        )
+        return "answer", [], "stop", {"prompt_tokens": 10, "completion_tokens": 5}, "summary"
 
     monkeypatch.setattr("nanobot.providers.openai_codex_provider._request_codex", fake_request)
 

tests/providers/test_openai_responses.py

@@ -1,11 +1,9 @@
 """Tests for the shared openai_responses converters and parsers."""
 
 import json
-from io import StringIO
 from unittest.mock import MagicMock, patch
 
 import pytest
-from loguru import logger
 
 from nanobot.providers.openai_responses.converters import (
     convert_messages,
@@ -14,22 +12,12 @@ from nanobot.providers.openai_responses.converters import (
     split_tool_call_id,
 )
 from nanobot.providers.openai_responses.parsing import (
-    ResponsesStreamCapture,
     consume_sdk_stream,
     consume_sse,
     consume_sse_with_reasoning,
-    is_replayable_finish_reason,
     map_finish_reason,
     parse_response_output,
 )
-from nanobot.providers.openai_responses.state import (
-    build_responses_state,
-    is_compaction_compatibility_error,
-    prepare_responses_input,
-    resolve_compact_threshold,
-    responses_state_context_tokens,
-    responses_state_items,
-)
 
 # ======================================================================
 # converters - split_tool_call_id
@@ -150,22 +138,6 @@ class TestConvertMessages:
         assert items[0]["content"][0]["type"] == "output_text"
         assert items[0]["content"][0]["text"] == "I'll help"
 
-    def test_preserves_deepseek_reasoning_content(self):
-        _, items = convert_messages([
-            {"role": "assistant", "reasoning_content": "think first", "content": "answer"},
-        ], preserve_reasoning=True)
-
-        assert items == [
-            {"type": "reasoning", "content": "think first"},
-            {
-                "type": "message",
-                "role": "assistant",
-                "content": [{"type": "output_text", "text": "answer"}],
-                "status": "completed",
-                "id": "msg_0",
-            },
-        ]
-
     def test_assistant_empty_content_skipped(self):
         _, items = convert_messages([{"role": "assistant", "content": ""}])
         assert len(items) == 0
@@ -426,17 +398,6 @@ class TestMapFinishReason:
     def test_unknown_defaults_to_stop(self):
         assert map_finish_reason("some_new_status") == "stop"
 
-    @pytest.mark.parametrize("finish_reason", ["stop", "tool_calls", "function_call"])
-    def test_replayable_finish_reasons(self, finish_reason):
-        assert is_replayable_finish_reason(finish_reason) is True
-
-    @pytest.mark.parametrize(
-        "finish_reason",
-        ["length", "refusal", "content_filter", "error"],
-    )
-    def test_non_replayable_finish_reasons(self, finish_reason):
-        assert is_replayable_finish_reason(finish_reason) is False
-
 
 # ======================================================================
 # parsing - parse_response_output
@@ -457,29 +418,6 @@ class TestParseResponseOutput:
         assert result.usage == {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
         assert result.tool_calls == []
 
-    def test_refusal_response_surfaces_text_without_advancing_state(self):
-        refusal = "I can’t help with that request."
-        resp = {
-            "output": [{
-                "type": "message",
-                "role": "assistant",
-                "content": [{"type": "refusal", "refusal": refusal}],
-            }],
-            "status": "completed",
-            "usage": {},
-        }
-
-        result = parse_response_output(
-            resp,
-            state_provider="openai:test",
-            state_model="gpt-5.6",
-            state_input_items=[{"role": "user", "content": "request"}],
-        )
-
-        assert result.content == refusal
-        assert result.finish_reason == "refusal"
-        assert result.provider_state is None
-
     def test_tool_call_response(self):
         resp = {
             "output": [{
@@ -491,18 +429,12 @@ class TestParseResponseOutput:
             "status": "completed",
             "usage": {},
         }
-        result = parse_response_output(
-            resp,
-            state_provider="openai:test",
-            state_model="gpt-5.6",
-            state_input_items=[{"role": "user", "content": "weather?"}],
-        )
+        result = parse_response_output(resp)
         assert result.content is None
         assert len(result.tool_calls) == 1
         assert result.tool_calls[0].name == "get_weather"
         assert result.tool_calls[0].arguments == {"city": "SF"}
         assert result.tool_calls[0].id == "call_1|fc_1"
-        assert result.provider_state is not None
 
     def test_malformed_tool_arguments_logged(self):
         """Malformed JSON arguments should log a warning and remain non-object."""
@@ -555,61 +487,16 @@ class TestParseResponseOutput:
         assert result.content == "42"
         assert result.reasoning_content == "I think therefore I am."
 
-    def test_deepseek_reasoning_content_extracted(self):
-        resp = {
-            "output": [
-                {"type": "reasoning", "content": "think first"},
-                {"type": "message", "content": [
-                    {"type": "output_text", "text": "answer"},
-                ]},
-            ],
-            "status": "completed", "usage": {},
-        }
-
-        result = parse_response_output(resp)
-
-        assert result.content == "answer"
-        assert result.reasoning_content == "think first"
-
     def test_empty_output(self):
         resp = {"output": [], "status": "completed", "usage": {}}
         result = parse_response_output(resp)
         assert result.content is None
         assert result.tool_calls == []
 
-    @pytest.mark.parametrize(
-        ("reason", "expected_finish_reason"),
-        [
-            ("max_output_tokens", "length"),
-            ("content_filter", "content_filter"),
-        ],
-    )
-    def test_incomplete_status(self, reason, expected_finish_reason):
-        resp = {
-            "output": [],
-            "status": "incomplete",
-            "incomplete_details": {"reason": reason},
-            "usage": {},
-        }
-        result = parse_response_output(
-            resp,
-            state_provider="openai:test",
-            state_model="gpt-5.6",
-            state_input_items=[{"role": "user", "content": "prompt"}],
-        )
-        assert result.finish_reason == expected_finish_reason
-        assert result.provider_state is None
-
-    def test_unknown_status_does_not_advance_provider_state(self):
-        result = parse_response_output(
-            {"output": [], "status": "future_terminal_status", "usage": {}},
-            state_provider="openai:test",
-            state_model="gpt-5.6",
-            state_input_items=[{"role": "user", "content": "prompt"}],
-        )
-
-        assert result.finish_reason == "stop"
-        assert result.provider_state is None
+    def test_incomplete_status(self):
+        resp = {"output": [], "status": "incomplete", "usage": {}}
+        result = parse_response_output(resp)
+        assert result.finish_reason == "length"
 
     def test_sdk_model_object(self):
         """parse_response_output should handle SDK objects with model_dump()."""
@@ -636,194 +523,6 @@ class TestParseResponseOutput:
         assert result.usage["completion_tokens"] == 50
         assert result.usage["total_tokens"] == 150
 
-    def test_preserves_every_output_item_as_opaque_state(self):
-        input_items = [{"role": "user", "content": "inspect the repo"}]
-        output = [
-            {
-                "id": "rs_1",
-                "type": "reasoning",
-                "encrypted_content": "opaque-secret",
-                "summary": [],
-            },
-            {
-                "id": "future_1",
-                "type": "future_item_type",
-                "provider_field": {"nested": True},
-            },
-            {
-                "id": "msg_1",
-                "type": "message",
-                "role": "assistant",
-                "status": "completed",
-                "content": [{"type": "output_text", "text": "done"}],
-            },
-        ]
-
-        result = parse_response_output(
-            {"output": output, "status": "completed", "usage": {}},
-            state_provider="openai:test",
-            state_model="gpt-5.6",
-            state_input_items=input_items,
-        )
-
-        assert result.provider_state is not None
-        assert responses_state_items(result.provider_state) == [*input_items, *output]
-
-
-class TestResponsesConversationState:
-    def test_server_compaction_prunes_superseded_prefix(self):
-        state = build_responses_state(
-            provider="openai:test",
-            model="gpt-5.6",
-            input_items=[
-                {"type": "message", "role": "user", "content": "old"},
-                {"type": "reasoning", "encrypted_content": "old-reasoning"},
-            ],
-            output_items=[
-                {"type": "compaction", "encrypted_content": "compact"},
-                {"type": "message", "role": "assistant", "content": "new"},
-            ],
-            usage={
-                "prompt_tokens": 90,
-                "completion_tokens": 10,
-                "total_tokens": 100,
-            },
-        )
-
-        assert responses_state_items(state) == [
-            {"type": "compaction", "encrypted_content": "compact"},
-            {"type": "message", "role": "assistant", "content": "new"},
-        ]
-        assert responses_state_context_tokens(state) == 100
-
-    def test_existing_compaction_keeps_canonical_retained_prefix(self):
-        canonical_input = [
-            {"type": "message", "role": "user", "content": "retained"},
-            {"type": "compaction", "encrypted_content": "compact"},
-        ]
-        output = [{"type": "message", "role": "assistant", "content": "new"}]
-
-        state = build_responses_state(
-            provider="openai:test",
-            model="gpt-5.6",
-            input_items=canonical_input,
-            output_items=output,
-        )
-
-        assert responses_state_items(state) == [*canonical_input, *output]
-
-    @pytest.mark.parametrize(
-        ("context_window", "max_output", "expected"),
-        [
-            (200_000, 20_000, 180_000),
-            (100_000, 30_000, 70_000),
-            (0, 4_096, None),
-        ],
-    )
-    def test_compact_threshold_reserves_codex_style_headroom(
-        self,
-        context_window,
-        max_output,
-        expected,
-    ):
-        assert resolve_compact_threshold(context_window, max_output) == expected
-
-    def test_compaction_compatibility_recognizes_old_sdk_signature_error(self):
-        error = TypeError("create() got an unexpected keyword argument 'context_management'")
-        assert is_compaction_compatibility_error(error) is True
-        assert is_compaction_compatibility_error(TypeError("unrelated argument")) is False
-
-    def test_state_observability_logs_counts_without_opaque_content(self):
-        secret = "opaque-secret-that-must-not-be-logged"
-        state = build_responses_state(
-            provider=f"openai:https://example.test/?key={secret}",
-            model=f"secret-model-{secret}",
-            input_items=[{"role": "user", "content": secret}],
-            output_items=[{"type": "reasoning", "encrypted_content": secret}],
-        ).with_pending_messages([{"role": "user", "content": secret}])
-        sink = StringIO()
-        sink_id = logger.add(sink, level="DEBUG", format="{message}")
-        try:
-            prepare_responses_input(
-                [{"role": "user", "content": secret}],
-                state=state,
-                provider=state.provider,
-                model=state.model,
-            )
-            build_responses_state(
-                provider=state.provider,
-                model=state.model,
-                input_items=[
-                    {"role": "user", "content": secret},
-                    {"type": "reasoning", "encrypted_content": secret},
-                ],
-                output_items=[
-                    {"type": "compaction", "encrypted_content": secret},
-                ],
-            )
-        finally:
-            logger.remove(sink_id)
-
-        log_text = sink.getvalue()
-        assert "prior_items=2" in log_text
-        assert "pending_messages=1" in log_text
-        assert "dropped_items=2" in log_text
-        assert secret not in log_text
-
-    def test_replays_exact_items_then_only_pending_and_new_messages(self):
-        prior_items = [
-            {"role": "user", "content": "first"},
-            {
-                "type": "reasoning",
-                "id": "rs_1",
-                "encrypted_content": "opaque-secret",
-            },
-            {
-                "type": "function_call",
-                "id": "fc_1",
-                "call_id": "call_1",
-                "name": "read_file",
-                "arguments": '{"path":"a.py"}',
-            },
-        ]
-        state = build_responses_state(
-            provider="openai:test",
-            model="gpt-5.6",
-            input_items=prior_items[:1],
-            output_items=prior_items[1:],
-        ).with_pending_messages([
-            {
-                "role": "tool",
-                "tool_call_id": "call_1|fc_1",
-                "content": "file contents",
-            },
-            {"role": "user", "content": "continue"},
-        ])
-
-        instructions, items, replayed = prepare_responses_input(
-            [
-                {"role": "system", "content": "current instructions"},
-                {"role": "user", "content": "a lossy public transcript"},
-            ],
-            state=state,
-            provider="openai:test",
-            model="gpt-5.6",
-        )
-
-        assert instructions == "current instructions"
-        assert replayed is True
-        assert items[:3] == prior_items
-        assert items[3] == {
-            "type": "function_call_output",
-            "call_id": "call_1",
-            "output": "file contents",
-        }
-        assert items[4] == {
-            "role": "user",
-            "content": [{"type": "input_text", "text": "continue"}],
-        }
-        assert "lossy public transcript" not in str(items)
-
 
 # ======================================================================
 # parsing - consume_sse
@@ -854,122 +553,6 @@ class TestConsumeSse:
         assert tool_calls == []
         assert finish_reason == "stop"
 
-    @pytest.mark.asyncio
-    async def test_refusal_events_reconcile_parts_and_terminal_output(self):
-        refusal = "First and second sentence. Done-only. Terminal suffix."
-        terminal_response = {
-            "status": "completed",
-            "output": [{
-                "type": "message",
-                "id": "msg_2",
-                "role": "assistant",
-                "content": [{"type": "refusal", "refusal": refusal}],
-            }],
-        }
-        response = _SseResponse([
-            {
-                "type": "response.refusal.delta",
-                "item_id": "msg_1",
-                "content_index": 0,
-                "delta": "First",
-            },
-            {
-                "type": "response.refusal.delta",
-                "item_id": "msg_1",
-                "content_index": 1,
-                "delta": " and second",
-            },
-            {
-                "type": "response.refusal.done",
-                "item_id": "msg_1",
-                "content_index": 0,
-                "refusal": "First",
-            },
-            {
-                "type": "response.refusal.done",
-                "item_id": "msg_1",
-                "content_index": 1,
-                "refusal": " and second sentence.",
-            },
-            {
-                "type": "response.refusal.done",
-                "item_id": "msg_2",
-                "content_index": 0,
-                "refusal": " Done-only.",
-            },
-            {
-                "type": "response.refusal.delta",
-                "item_id": "msg_2",
-                "content_index": 1,
-                "delta": " Terminal",
-            },
-            {"type": "response.completed", "response": terminal_response},
-        ])
-        capture = ResponsesStreamCapture()
-        deltas: list[str] = []
-
-        async def on_content(delta: str) -> None:
-            deltas.append(delta)
-
-        content, _, finish_reason, _, _ = await consume_sse_with_reasoning(
-            response,
-            on_content_delta=on_content,
-            capture=capture,
-        )
-
-        assert content == refusal
-        assert deltas == [
-            "First",
-            " and second",
-            " sentence.",
-            " Done-only.",
-            " Terminal",
-            " suffix.",
-        ]
-        assert finish_reason == "refusal"
-        assert capture.completed is True
-        assert is_replayable_finish_reason(finish_reason) is False
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize("source", ["events", "terminal"])
-    async def test_refusal_without_deltas_has_non_replayable_finish(self, source: str):
-        refusal = "I can’t help with that request."
-        terminal_response = {
-            "status": "completed",
-            "output": [{
-                "type": "message",
-                "id": "msg_1",
-                "role": "assistant",
-                "content": [{"type": "refusal", "refusal": refusal}],
-            }],
-        }
-        events = (
-            [
-                {"type": "response.refusal.done", "refusal": refusal},
-                {"type": "response.completed", "response": {"status": "completed"}},
-            ]
-            if source == "events"
-            else [{"type": "response.completed", "response": terminal_response}]
-        )
-        response = _SseResponse(events)
-        capture = ResponsesStreamCapture()
-        deltas: list[str] = []
-
-        async def on_content(delta: str) -> None:
-            deltas.append(delta)
-
-        content, _, finish_reason, _, _ = await consume_sse_with_reasoning(
-            response,
-            on_content_delta=on_content,
-            capture=capture,
-        )
-
-        assert content == refusal
-        assert deltas == [refusal]
-        assert finish_reason == "refusal"
-        assert capture.completed is True
-        assert is_replayable_finish_reason(finish_reason) is False
-
     @pytest.mark.asyncio
     async def test_reasoning_summary_delta_extracted(self):
         response = _SseResponse([
@@ -1016,139 +599,6 @@ class TestConsumeSse:
 
         assert reasoning == "cached summary"
 
-    @pytest.mark.asyncio
-    async def test_capture_commits_exact_items_only_after_completed_event(self):
-        output = [
-            {
-                "type": "reasoning",
-                "id": "rs_1",
-                "encrypted_content": "opaque-secret",
-            },
-            {"type": "future_item_type", "id": "future_1", "value": 7},
-        ]
-        capture = ResponsesStreamCapture()
-        response = _SseResponse([
-            {
-                "type": "response.output_item.done",
-                "output_index": 0,
-                "item": output[0],
-            },
-            {
-                "type": "response.output_item.done",
-                "output_index": 1,
-                "item": output[1],
-            },
-            {
-                "type": "response.completed",
-                "response": {"status": "completed", "output": output},
-            },
-        ])
-
-        await consume_sse_with_reasoning(response, capture=capture)
-
-        assert capture.completed is True
-        assert capture.output_items == output
-
-    @pytest.mark.asyncio
-    async def test_capture_keeps_done_items_when_completed_output_is_empty(self):
-        output = [
-            {
-                "type": "reasoning",
-                "id": "rs_1",
-                "encrypted_content": "opaque-secret",
-                "summary": [],
-            },
-            {
-                "type": "function_call",
-                "id": "fc_1",
-                "call_id": "call_1",
-                "name": "read_file",
-                "arguments": '{"path":"weather/SKILL.md"}',
-            },
-        ]
-        capture = ResponsesStreamCapture()
-        response = _SseResponse([
-            {
-                "type": "response.output_item.done",
-                "output_index": index,
-                "item": item,
-            }
-            for index, item in enumerate(output)
-        ] + [{
-            "type": "response.completed",
-            "response": {"status": "completed", "output": []},
-        }])
-
-        await consume_sse_with_reasoning(response, capture=capture)
-
-        assert capture.completed is True
-        assert capture.output_items == output
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize(
-        ("reason", "expected_finish_reason"),
-        [
-            ("max_output_tokens", "length"),
-            ("content_filter", "content_filter"),
-        ],
-    )
-    async def test_incomplete_event_commits_capture_usage(
-        self,
-        reason,
-        expected_finish_reason,
-    ):
-        output = [
-            {
-                "type": "message",
-                "id": "msg_1",
-                "status": "incomplete",
-                "content": [{"type": "output_text", "text": "partial"}],
-            },
-        ]
-        terminal_response = {
-            "id": "resp_1",
-            "status": "incomplete",
-            "incomplete_details": {"reason": reason},
-            "output": output,
-            "usage": {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15},
-        }
-        capture = ResponsesStreamCapture()
-        response = _SseResponse([
-            {"type": "response.output_text.delta", "delta": "partial"},
-            {"type": "response.incomplete", "response": terminal_response},
-        ])
-
-        content, _, finish_reason, usage, _ = await consume_sse_with_reasoning(
-            response,
-            capture=capture,
-        )
-
-        assert content == "partial"
-        assert finish_reason == expected_finish_reason
-        assert usage == {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
-        assert capture.completed is True
-        assert capture.response == terminal_response
-        assert capture.output_items == output
-
-    @pytest.mark.asyncio
-    async def test_capture_does_not_commit_interrupted_stream(self):
-        capture = ResponsesStreamCapture()
-        response = _SseResponse([
-            {
-                "type": "response.output_item.done",
-                "output_index": 0,
-                "item": {
-                    "type": "reasoning",
-                    "id": "rs_1",
-                    "encrypted_content": "opaque-secret",
-                },
-            },
-        ])
-
-        await consume_sse_with_reasoning(response, capture=capture)
-
-        assert capture.completed is False
-
     @pytest.mark.asyncio
     async def test_reasoning_summary_from_done_item(self):
         response = _SseResponse([
@@ -1305,131 +755,6 @@ class TestConsumeSdkStream:
         assert tool_calls == []
         assert finish_reason == "stop"
 
-    @pytest.mark.asyncio
-    async def test_refusal_events_reconcile_parts_and_terminal_output(self):
-        refusal = "First and second sentence. Done-only. Terminal suffix."
-        terminal_response = {
-            "status": "completed",
-            "output": [{
-                "type": "message",
-                "id": "msg_2",
-                "role": "assistant",
-                "content": [{"type": "refusal", "refusal": refusal}],
-            }],
-        }
-        resp_obj = MagicMock(status="completed", usage=None, output=[])
-        resp_obj.model_dump.return_value = terminal_response
-        events = [
-            MagicMock(
-                type="response.refusal.delta",
-                item_id="msg_1",
-                content_index=0,
-                delta="First",
-            ),
-            MagicMock(
-                type="response.refusal.delta",
-                item_id="msg_1",
-                content_index=1,
-                delta=" and second",
-            ),
-            MagicMock(
-                type="response.refusal.done",
-                item_id="msg_1",
-                content_index=0,
-                refusal="First",
-            ),
-            MagicMock(
-                type="response.refusal.done",
-                item_id="msg_1",
-                content_index=1,
-                refusal=" and second sentence.",
-            ),
-            MagicMock(
-                type="response.refusal.done",
-                item_id="msg_2",
-                content_index=0,
-                refusal=" Done-only.",
-            ),
-            MagicMock(
-                type="response.refusal.delta",
-                item_id="msg_2",
-                content_index=1,
-                delta=" Terminal",
-            ),
-            MagicMock(type="response.completed", response=resp_obj),
-        ]
-        capture = ResponsesStreamCapture()
-        deltas: list[str] = []
-
-        async def on_content(delta: str) -> None:
-            deltas.append(delta)
-
-        async def stream():
-            for event in events:
-                yield event
-
-        content, _, finish_reason, _, _ = await consume_sdk_stream(
-            stream(),
-            on_content_delta=on_content,
-            capture=capture,
-        )
-
-        assert content == refusal
-        assert deltas == [
-            "First",
-            " and second",
-            " sentence.",
-            " Done-only.",
-            " Terminal",
-            " suffix.",
-        ]
-        assert finish_reason == "refusal"
-        assert capture.completed is True
-        assert is_replayable_finish_reason(finish_reason) is False
-
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize("source", ["events", "terminal"])
-    async def test_refusal_without_deltas_has_non_replayable_finish(self, source: str):
-        refusal = "I can’t help with that request."
-        terminal_response = {
-            "status": "completed",
-            "output": [{
-                "type": "message",
-                "id": "msg_1",
-                "role": "assistant",
-                "content": [{"type": "refusal", "refusal": refusal}],
-            }],
-        }
-        resp_obj = MagicMock(status="completed", usage=None, output=[])
-        resp_obj.model_dump.return_value = terminal_response
-        capture = ResponsesStreamCapture()
-        deltas: list[str] = []
-
-        async def on_content(delta: str) -> None:
-            deltas.append(delta)
-
-        async def stream():
-            if source == "events":
-                yield MagicMock(type="response.refusal.done", refusal=refusal)
-                yield MagicMock(
-                    type="response.completed",
-                    response={"status": "completed"},
-                )
-            else:
-                yield MagicMock(type="response.completed", response=resp_obj)
-
-        content, _, finish_reason, _, _ = await consume_sdk_stream(
-            stream(),
-            on_content_delta=on_content,
-            capture=capture,
-        )
-
-        assert content == refusal
-        assert deltas == [refusal]
-        assert finish_reason == "refusal"
-        assert capture.completed is True
-        assert is_replayable_finish_reason(finish_reason) is False
-
     @pytest.mark.asyncio
     async def test_on_content_delta_called(self):
         ev1 = MagicMock(type="response.output_text.delta", delta="hi")
@@ -1594,64 +919,6 @@ class TestConsumeSdkStream:
         _, _, _, usage, _ = await consume_sdk_stream(stream())
         assert usage == {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
 
-    @pytest.mark.asyncio
-    @pytest.mark.parametrize(
-        ("reason", "expected_finish_reason"),
-        [
-            ("max_output_tokens", "length"),
-            ("content_filter", "content_filter"),
-        ],
-    )
-    async def test_incomplete_event_commits_capture_usage(
-        self,
-        reason,
-        expected_finish_reason,
-    ):
-        output = [
-            {
-                "type": "message",
-                "id": "msg_1",
-                "status": "incomplete",
-                "content": [{"type": "output_text", "text": "partial"}],
-            },
-        ]
-        usage_obj = MagicMock(input_tokens=10, output_tokens=5, total_tokens=15)
-        output_item = MagicMock(type="message")
-        terminal_response = {
-            "id": "resp_1",
-            "status": "incomplete",
-            "incomplete_details": {"reason": reason},
-            "output": output,
-            "usage": {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15},
-        }
-        resp_obj = MagicMock(
-            status="incomplete",
-            usage=usage_obj,
-            output=[output_item],
-        )
-        resp_obj.model_dump.return_value = terminal_response
-        events = [
-            MagicMock(type="response.output_text.delta", delta="partial"),
-            MagicMock(type="response.incomplete", response=resp_obj),
-        ]
-        capture = ResponsesStreamCapture()
-
-        async def stream():
-            for event in events:
-                yield event
-
-        content, _, finish_reason, usage, _ = await consume_sdk_stream(
-            stream(),
-            capture=capture,
-        )
-
-        assert content == "partial"
-        assert finish_reason == expected_finish_reason
-        assert usage == {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}
-        assert capture.completed is True
-        assert capture.response == terminal_response
-        assert capture.output_items == output
-
     @pytest.mark.asyncio
     async def test_reasoning_extracted(self):
         summary_item = MagicMock(type="summary_text", text="thinking...")
@@ -1665,30 +932,6 @@ class TestConsumeSdkStream:
         _, _, _, _, reasoning = await consume_sdk_stream(stream())
         assert reasoning == "thinking..."
 
-    @pytest.mark.asyncio
-    async def test_deepseek_reasoning_text_streamed(self):
-        events = [
-            MagicMock(type="response.reasoning_text.delta", delta="step 1 "),
-            MagicMock(type="response.reasoning_text.delta", delta="step 2"),
-            MagicMock(type="response.reasoning_text.done", text="step 1 step 2"),
-        ]
-        emitted: list[str] = []
-
-        async def stream():
-            for event in events:
-                yield event
-
-        async def on_reasoning_delta(delta: str) -> None:
-            emitted.append(delta)
-
-        _, _, _, _, reasoning = await consume_sdk_stream(
-            stream(),
-            on_reasoning_delta=on_reasoning_delta,
-        )
-
-        assert reasoning == "step 1 step 2"
-        assert emitted == ["step 1 ", "step 2"]
-
     @pytest.mark.asyncio
     async def test_error_event_raises(self):
         ev = MagicMock(type="error", error="rate_limit_exceeded")

tests/providers/test_provider_retry.py

@@ -3,14 +3,7 @@ import copy
 
 import pytest
 
-from nanobot.providers.base import (
-    RETRY_AFTER_BUFFER,
-    GenerationSettings,
-    LLMProvider,
-    LLMResponse,
-    ProviderCallContext,
-    ProviderConversationState,
-)
+from nanobot.providers.base import RETRY_AFTER_BUFFER, GenerationSettings, LLMProvider, LLMResponse
 
 
 class ScriptedProvider(LLMProvider):
@@ -337,79 +330,6 @@ async def test_successful_image_retry_mutates_original_messages_in_place() -> No
     assert any("not delivered" in (block.get("text") or "").lower() for block in content)
 
 
-@pytest.mark.asyncio
-@pytest.mark.parametrize(
-    ("messages", "payload", "pending_messages"),
-    [
-        (_IMAGE_MSG, {}, _IMAGE_MSG),
-        (
-            [{"role": "user", "content": "continue"}],
-            {
-                "items": [
-                    {
-                        "type": "message",
-                        "role": "user",
-                        "content": [
-                            {
-                                "type": "input_image",
-                                "image_url": "data:image/png;base64,abc",
-                            }
-                        ],
-                    }
-                ]
-            },
-            [],
-        ),
-    ],
-    ids=["pending-image", "opaque-payload-image"],
-)
-async def test_image_retry_discards_provider_state_with_images(
-    messages,
-    payload,
-    pending_messages,
-) -> None:
-    class ContextScriptedProvider(ScriptedProvider):
-        def __init__(self, responses):
-            super().__init__(responses)
-            self.contexts: list[ProviderCallContext] = []
-
-        async def chat_with_context(
-            self,
-            *,
-            provider_context: ProviderCallContext,
-            **kwargs,
-        ) -> LLMResponse:
-            self.contexts.append(provider_context)
-            return await self.chat(**kwargs)
-
-    provider = ContextScriptedProvider([
-        LLMResponse(content="model does not support images", finish_reason="error"),
-        LLMResponse(content="ok, no image"),
-    ])
-    messages = copy.deepcopy(messages)
-    state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="gpt-5.6",
-        version=1,
-        payload=copy.deepcopy(payload),
-        pending_messages=copy.deepcopy(pending_messages),
-    )
-
-    response = await provider.chat_with_retry(
-        messages=messages,
-        provider_context=ProviderCallContext(conversation_state=state),
-    )
-
-    assert response.content == "ok, no image"
-    retry_context = provider.contexts[-1]
-    assert isinstance(retry_context, ProviderCallContext)
-    assert retry_context.conversation_state is None
-    public_content = messages[0]["content"]
-    if isinstance(public_content, list):
-        assert all(block.get("type") != "image_url" for block in public_content)
-
-
 @pytest.mark.asyncio
 async def test_non_transient_error_without_images_no_retry() -> None:
     """Non-transient errors without image content are returned immediately."""

tests/providers/test_responses_circuit_breaker.py

@@ -4,7 +4,6 @@ import time
 
 import pytest
 
-from nanobot.providers.base import ProviderCallContext
 from nanobot.providers.openai_compat_provider import (
     _RESPONSES_FAILURE_THRESHOLD,
     _RESPONSES_PROBE_INTERVAL_S,
@@ -29,52 +28,6 @@ def test_responses_api_available_by_default(provider):
     assert provider._should_use_responses_api("gpt-5", None) is True
 
 
-def test_deepseek_v4_flash_uses_responses_by_model(provider):
-    provider._spec = type("Spec", (), {
-        "name": "deepseek",
-        "responses_models": ("deepseek-v4-flash",),
-        "strip_model_prefix": False,
-        "strip_model_prefixes": (),
-    })()
-    provider._effective_base = "https://api.deepseek.com"
-    provider.default_model = "deepseek-v4-flash"
-
-    assert provider._should_use_responses_api("deepseek-v4-flash", None) is True
-    assert provider._should_use_responses_api("deepseek-v4-pro", None) is False
-
-
-def test_deepseek_v4_flash_matches_provider_prefixed_model(provider):
-    provider._spec = type("Spec", (), {
-        "name": "deepseek",
-        "responses_models": ("deepseek-v4-flash",),
-        "strip_model_prefix": False,
-        "strip_model_prefixes": (),
-    })()
-    provider._effective_base = "https://api.deepseek.com"
-
-    assert provider._should_use_responses_api("deepseek/deepseek-v4-flash", None) is True
-
-
-def test_direct_openai_enables_server_compaction(provider):
-    provider._extra_body = {}
-
-    body = provider._build_responses_body(
-        messages=[{"role": "user", "content": "hello"}],
-        tools=None,
-        model="gpt-5.6",
-        max_tokens=30_000,
-        temperature=0.1,
-        reasoning_effort="high",
-        tool_choice=None,
-        provider_context=ProviderCallContext(context_window_tokens=100_000),
-    )
-
-    assert body["context_management"] == [{
-        "type": "compaction",
-        "compact_threshold": 70_000,
-    }]
-
-
 def test_api_type_chat_completions_disables_responses(provider):
     provider._api_type = "chat_completions"
     assert provider._should_use_responses_api("gpt-5", None) is False

tests/security/test_security_network.py

@@ -9,9 +9,12 @@ from unittest.mock import patch
 import pytest
 
 from nanobot.security.network import (
+    Httpx2PinnedDNSAsyncTransport,
+    PinnedDNSAsyncTransport,
     configure_ssrf_whitelist,
     contains_internal_url,
     env_proxy_applies_to_url,
+    httpx2_env_proxy_mounts,
     httpx_env_proxy_mounts,
     is_loopback_host,
     pin_resolved_url_dns,
@@ -264,6 +267,17 @@ def test_env_proxy_helpers_respect_no_proxy(monkeypatch):
     assert any(transport is None for transport in mounts.values())
     assert any(transport is not None for transport in mounts.values())
 
+    httpx2_mounts = httpx2_env_proxy_mounts()
+    assert any(transport is None for transport in httpx2_mounts.values())
+    assert any(transport is not None for transport in httpx2_mounts.values())
+
+
+def test_httpx_transports_share_global_dns_pin_lock():
+    assert (
+        Httpx2PinnedDNSAsyncTransport._resolver_lock
+        is PinnedDNSAsyncTransport._resolver_lock
+    )
+
 
 # ---------------------------------------------------------------------------
 # contains_internal_url — shell command scanning

tests/session/test_session_cache.py

@@ -73,23 +73,3 @@ def test_flush_all_includes_live_sessions_outside_strong_cache(tmp_path, monkeyp
 
     assert manager.flush_all() == 2
     assert set(saved) == {("test:active", True), ("test:other", True)}
-
-
-def test_transient_session_never_reaches_store(tmp_path) -> None:
-    manager = SessionManager(tmp_path)
-    session = manager.get_or_create_transient("websocket:temporary-test")
-    session.add_message("user", "private")
-
-    manager.save(session, fsync=True)
-
-    assert manager.get_cached(session.key) is session
-    assert manager.read_session_file(session.key) is None
-
-
-def test_transient_session_becomes_inactive_when_discarded(tmp_path) -> None:
-    manager = SessionManager(tmp_path)
-    session = manager.get_or_create_transient("websocket:temporary-test")
-
-    assert manager.discard_transient(session.key) is True
-    assert manager.is_transient_active(session.key) is False
-    assert manager.get_cached(session.key) is None

tests/tools/test_exec_session_tools.py

@@ -16,13 +16,9 @@ from nanobot.agent import context as agent_context
 from nanobot.agent.loop import AgentLoop
 from nanobot.agent.tools.context import RequestContext, bind_request_context, reset_request_context
 from nanobot.agent.tools.exec_session import (
-    MAX_OUTPUT_CHARS,
     ExecSessionManager,
     ListExecSessionsTool,
     WriteStdinTool,
-    _BoundedOutputBuffer,
-    _SessionPoll,
-    _truncate_output,
 )
 from nanobot.agent.tools.registry import is_tool_error_result
 from nanobot.agent.tools.shell import ExecTool
@@ -147,134 +143,6 @@ def test_exec_session_accepts_max_output_tokens_alias(tmp_path):
     assert "Exit code: 0" in result
 
 
-def test_bounded_output_buffer_keeps_head_tail_and_exact_drop_count():
-    buffer = _BoundedOutputBuffer(10)
-
-    buffer.append("012345")
-    buffer.append("6789ABCDEF")
-
-    assert buffer.retained_chars == 10
-    assert buffer.drain() == ("01234BCDEF", 6)
-    assert buffer.retained_chars == 0
-
-
-def test_exec_session_bounds_unpolled_stdout_and_stderr(tmp_path):
-    async def run() -> tuple[int, int, str, int]:
-        manager = ExecSessionManager()
-        tool = ExecTool(working_dir=str(tmp_path), timeout=5, session_manager=manager)
-        command = _python_command(
-            "import sys,time; time.sleep(0.05); "
-            "sys.stdout.write('OUT_HEAD' + 'o' * 200000 + 'OUT_TAIL'); "
-            "sys.stderr.write('ERR_HEAD' + 'e' * 200000 + 'ERR_TAIL')"
-        )
-
-        initial = await tool.execute(
-            command=command,
-            yield_time_ms=0,
-            max_output_chars=1000,
-        )
-        sid = _session_id(initial)
-        session = manager._sessions[sid]
-        await asyncio.wait_for(session.process.wait(), timeout=5)
-        await asyncio.wait_for(
-            asyncio.gather(session._stdout_task, session._stderr_task),
-            timeout=5,
-        )
-        retained_stdout = session._stdout.retained_chars
-        retained_stderr = session._stderr.retained_chars
-        poll = await manager.write(
-            session_id=sid,
-            chars=None,
-            close_stdin=False,
-            terminate=False,
-            yield_time_ms=0,
-            max_output_chars=1000,
-        )
-        return retained_stdout, retained_stderr, poll.output, poll.truncated_chars
-
-    retained_stdout, retained_stderr, output, truncated_chars = asyncio.run(run())
-
-    assert retained_stdout == 50000
-    assert retained_stderr == 50000
-    assert output.startswith("OUT_HEAD")
-    assert output.endswith("ERR_TAIL")
-    assert truncated_chars > 390000
-
-
-def test_write_stdin_wait_for_keeps_aggregate_within_output_budget():
-    async def run() -> str:
-        manager = SimpleNamespace(
-            write=AsyncMock(side_effect=[
-                _SessionPoll(output="HEAD" + "a" * 596, done=False, exit_code=None),
-                _SessionPoll(output="b" * 600, done=False, exit_code=None),
-                _SessionPoll(output="c" * 590 + "TARGET", done=False, exit_code=None),
-            ])
-        )
-        tool = WriteStdinTool(manager=manager)
-        return await tool._wait_for_output(
-            session_id="session",
-            chars=None,
-            close_stdin=False,
-            terminate=False,
-            wait_for="TARGET",
-            wait_timeout_ms=1000,
-            max_output_chars=1000,
-        )
-
-    result = asyncio.run(run())
-
-    assert result.startswith("HEAD")
-    assert "TARGET" in result
-    assert "(796 chars truncated from output)" in result
-    assert len(result) < 1100
-
-
-def test_write_stdin_wait_for_searches_before_response_truncation():
-    async def run() -> tuple[str, list[int]]:
-        output = "A" * 1500 + "TARGET" + "B" * 1500
-        observed_limits: list[int] = []
-
-        async def write(
-            *,
-            session_id: str,
-            chars: str | None,
-            close_stdin: bool,
-            terminate: bool,
-            yield_time_ms: int,
-            max_output_chars: int,
-            owner_session_key: str | None,
-        ) -> _SessionPoll:
-            del session_id, chars, close_stdin, terminate, yield_time_ms, owner_session_key
-            observed_limits.append(max_output_chars)
-            visible, truncated = _truncate_output(output, max_output_chars)
-            return _SessionPoll(
-                output=visible,
-                done=True,
-                exit_code=0,
-                truncated_chars=truncated,
-            )
-
-        manager = SimpleNamespace(write=AsyncMock(side_effect=write))
-        tool = WriteStdinTool(manager=manager)
-        result = await tool._wait_for_output(
-            session_id="session",
-            chars=None,
-            close_stdin=False,
-            terminate=False,
-            wait_for="TARGET",
-            wait_timeout_ms=1000,
-            max_output_chars=1000,
-        )
-        return result, observed_limits
-
-    result, observed_limits = asyncio.run(run())
-
-    assert observed_limits == [MAX_OUTPUT_CHARS]
-    assert "Wait target not observed" not in result
-    assert "(2,006 chars truncated from output)" in result
-    assert len(result) < 1100
-
-
 def test_exec_one_shot_accepts_max_output_tokens_alias(tmp_path):
     async def run() -> str:
         tool = ExecTool(working_dir=str(tmp_path), timeout=5)

tests/tools/test_mcp_tool.py

@@ -7,7 +7,7 @@ from contextlib import asynccontextmanager
 from pathlib import Path
 from types import ModuleType, SimpleNamespace
 
-import httpx
+import httpx2 as httpx
 import pytest
 
 import nanobot.agent.tools.mcp as mcp_mod
@@ -52,7 +52,7 @@ class _FakeBlobResourceContents:
 class _FakeImageContent:
     def __init__(self, data: str, mime_type: str = "image/png") -> None:
         self.data = data
-        self.mimeType = mime_type
+        self.mime_type = mime_type
 
 
 @pytest.fixture
@@ -111,7 +111,7 @@ def _fake_mcp_module(
 
     @asynccontextmanager
     async def _fake_streamable_http_client(_url: str, http_client=None):
-        yield object(), object(), object()
+        yield object(), object()
 
     mod.ClientSession = _FakeClientSession
     mod.StdioServerParameters = _FakeStdioServerParameters
@@ -133,12 +133,13 @@ def _fake_mcp_module(
     shared_mod = ModuleType("mcp.shared")
     exc_mod = ModuleType("mcp.shared.exceptions")
 
-    class _FakeMcpError(Exception):
+    class _FakeMCPError(Exception):
         def __init__(self, code: int = -1, message: str = "error"):
             self.error = SimpleNamespace(code=code, message=message)
             super().__init__(message)
 
-    exc_mod.McpError = _FakeMcpError
+    mod.MCPError = _FakeMCPError
+    exc_mod.MCPError = _FakeMCPError
     monkeypatch.setitem(sys.modules, "mcp.shared", shared_mod)
     monkeypatch.setitem(sys.modules, "mcp.shared.exceptions", exc_mod)
 
@@ -147,7 +148,7 @@ def _make_wrapper(session: object, *, timeout: float = 0.1) -> MCPToolWrapper:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
     return MCPToolWrapper(session, "test", tool_def, tool_timeout=timeout)
 
@@ -185,7 +186,7 @@ def test_wrapper_preserves_non_nullable_unions() -> None:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "value": {
@@ -207,7 +208,7 @@ def test_wrapper_normalizes_nullable_property_type_union() -> None:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "name": {"type": ["string", "null"]},
@@ -224,7 +225,7 @@ def test_wrapper_normalizes_nullable_property_anyof() -> None:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "name": {
@@ -249,7 +250,7 @@ def test_wrapper_hoists_recursive_local_refs_into_defs() -> None:
     tool_def = SimpleNamespace(
         name="search_dataset",
         description="search tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "filter": {
@@ -282,7 +283,7 @@ def test_wrapper_hoists_root_self_ref_into_defs() -> None:
     tool_def = SimpleNamespace(
         name="tree",
         description="tree tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "children": {"type": "array", "items": {"$ref": "#"}},
@@ -304,7 +305,7 @@ def test_wrapper_preserves_existing_defs_refs() -> None:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "$defs": {"value": {"type": "string"}},
             "properties": {"value": {"$ref": "#/$defs/value"}},
@@ -321,7 +322,7 @@ def test_wrapper_resolves_uri_encoded_json_pointer() -> None:
     tool_def = SimpleNamespace(
         name="demo",
         description="demo tool",
-        inputSchema={
+        input_schema={
             "type": "object",
             "properties": {
                 "space name/value": {"type": "string"},
@@ -449,7 +450,7 @@ async def test_execute_wraps_mcp_is_error_result() -> None:
     async def call_tool(_name: str, arguments: dict) -> object:
         return SimpleNamespace(
             content=[_FakeTextContent("Error: server-side MCP failure")],
-            isError=True,
+            is_error=True,
         )
 
     wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
@@ -494,7 +495,7 @@ async def test_execute_preserves_success_text_that_starts_with_error() -> None:
     async def call_tool(_name: str, arguments: dict) -> object:
         return SimpleNamespace(
             content=[_FakeTextContent("Error: generated report successfully")],
-            isError=False,
+            is_error=False,
         )
 
     wrapper = _make_wrapper(SimpleNamespace(call_tool=call_tool))
@@ -622,7 +623,7 @@ def _make_tool_def(name: str) -> SimpleNamespace:
     return SimpleNamespace(
         name=name,
         description=f"{name} tool",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
 
 
@@ -936,7 +937,7 @@ async def test_connect_mcp_servers_env_proxy_adds_proxy_mounts_and_keeps_pinned_
     @asynccontextmanager
     async def _capturing_streamable_http_client(_url: str, http_client=None):
         assert http_client is not None
-        yield object(), object(), object()
+        yield object(), object()
 
     monkeypatch.setenv("HTTPS_PROXY", "http://proxy.example:8080")
     monkeypatch.setenv("NO_PROXY", "localhost,127.0.0.1,::1")
@@ -944,11 +945,11 @@ async def test_connect_mcp_servers_env_proxy_adds_proxy_mounts_and_keeps_pinned_
     monkeypatch.setattr(mcp_mod, "_probe_http_url", _reachable)
     monkeypatch.setattr(
         mcp_mod,
-        "PinnedDNSAsyncTransport",
+        "Httpx2PinnedDNSAsyncTransport",
         lambda: httpx.MockTransport(lambda request: httpx.Response(200, request=request)),
     )
     monkeypatch.setattr(
-        "nanobot.security.network.httpx.AsyncHTTPTransport",
+        "nanobot.security.network.httpx2.AsyncHTTPTransport",
         lambda **_kwargs: httpx.MockTransport(
             lambda request: httpx.Response(200, request=request)
         ),
@@ -976,11 +977,11 @@ def test_mcp_http_clients_no_proxy_env_keeps_pinned_direct_route(monkeypatch):
     monkeypatch.setenv("NO_PROXY", "mcp.example.com")
     monkeypatch.setattr(
         mcp_mod,
-        "PinnedDNSAsyncTransport",
+        "Httpx2PinnedDNSAsyncTransport",
         lambda: httpx.MockTransport(lambda request: httpx.Response(200, request=request)),
     )
     monkeypatch.setattr(
-        "nanobot.security.network.httpx.AsyncHTTPTransport",
+        "nanobot.security.network.httpx2.AsyncHTTPTransport",
         lambda **_kwargs: httpx.MockTransport(
             lambda request: httpx.Response(200, request=request)
         ),
@@ -1050,13 +1051,15 @@ async def test_connect_mcp_servers_http_clients_reject_unsafe_redirect_targets(
         assert http_client is not None
         used_transports.append("streamableHttp")
         await http_client.get("https://example.com/start")
-        yield object(), object(), object()
+        yield object(), object()
 
     monkeypatch.setattr(mcp_mod, "validate_url_target", _validate)
     monkeypatch.setattr(mcp_mod, "_probe_http_url", _reachable)
+    # Keep the redirect exercise isolated from host-level proxy settings.
+    monkeypatch.setattr(mcp_mod, "httpx2_env_proxy_mounts", lambda: {})
     monkeypatch.setattr(
         mcp_mod,
-        "PinnedDNSAsyncTransport",
+        "Httpx2PinnedDNSAsyncTransport",
         lambda **_kwargs: httpx.MockTransport(_handler),
     )
     monkeypatch.setattr(mcp_mod.httpx, "AsyncClient", _async_client_with_mock_transport)
@@ -1138,13 +1141,13 @@ async def test_connect_mcp_servers_streamable_http_uses_finite_timeout(
     @asynccontextmanager
     async def _capturing_streamable_http_client(_url: str, http_client=None):
         captured["timeout"] = http_client.timeout
-        yield object(), object(), object()
+        yield object(), object()
 
     monkeypatch.setattr(mcp_mod, "validate_url_target", _validate)
     monkeypatch.setattr(mcp_mod, "_probe_http_url", _reachable)
     monkeypatch.setattr(
         mcp_mod,
-        "PinnedDNSAsyncTransport",
+        "Httpx2PinnedDNSAsyncTransport",
         lambda: httpx.MockTransport(lambda request: httpx.Response(200, request=request)),
     )
     monkeypatch.setattr(
@@ -1385,10 +1388,10 @@ async def test_prompt_wrapper_execute_handles_timeout() -> None:
 
 @pytest.mark.asyncio
 async def test_prompt_wrapper_execute_handles_mcp_error() -> None:
-    from mcp.shared.exceptions import McpError
+    from mcp import MCPError
 
     async def get_prompt(name: str, arguments: dict | None = None) -> object:
-        raise McpError(code=42, message="invalid argument")
+        raise MCPError(code=42, message="invalid argument")
 
     wrapper = _make_prompt_wrapper(SimpleNamespace(get_prompt=get_prompt))
     result = await wrapper.execute()
@@ -1510,7 +1513,7 @@ def test_tool_wrapper_sanitizes_name() -> None:
     tool_def = SimpleNamespace(
         name="My Tool",
         description="tool with spaces",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
     wrapper = MCPToolWrapper(SimpleNamespace(call_tool=None), "srv", tool_def)
     assert wrapper.name == "mcp_srv_My_Tool"
@@ -1541,7 +1544,7 @@ def test_tool_wrapper_preserves_original_name_for_mcp_call() -> None:
     tool_def = SimpleNamespace(
         name="My Tool",
         description="tool with spaces",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
     wrapper = MCPToolWrapper(SimpleNamespace(call_tool=None), "srv", tool_def)
     # The sanitized API-facing name differs from the original MCP name
@@ -1619,12 +1622,12 @@ def test_long_server_name_tools_are_matched_by_server_name() -> None:
     tool_def = SimpleNamespace(
         name="search",
         description="search tool",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
     other_tool_def = SimpleNamespace(
         name="search",
         description="other search tool",
-        inputSchema={"type": "object", "properties": {}},
+        input_schema={"type": "object", "properties": {}},
     )
     wrapper = MCPToolWrapper(SimpleNamespace(call_tool=None), server_name, tool_def)
     other_wrapper = MCPToolWrapper(SimpleNamespace(call_tool=None), "other", other_tool_def)

tests/utils/test_gitstore.py

@@ -310,25 +310,3 @@ class TestNestedRepoProtection:
 
         assert result is False
         assert not (workspace / ".git").exists()
-
-
-class TestCommitIdEncoding:
-    """Commit ids must be usable with git, not hex-of-hex."""
-
-    def test_auto_commit_returns_the_real_short_sha(self, git, tmp_path):
-        (tmp_path / "MEMORY.md").write_text("- a fact\n", encoding="utf-8")
-        sha = git.auto_commit("memory update")
-        expected = subprocess.run(
-            ["git", "-C", str(tmp_path), "log", "-1", "--format=%h", "--abbrev=8"],
-            capture_output=True, text=True, check=True,
-        ).stdout.strip()
-        assert sha == expected
-
-    def test_a_real_git_sha_resolves(self, git, tmp_path):
-        (tmp_path / "MEMORY.md").write_text("- a fact\n", encoding="utf-8")
-        git.auto_commit("memory update")
-        real = subprocess.run(
-            ["git", "-C", str(tmp_path), "log", "-1", "--format=%h", "--abbrev=8"],
-            capture_output=True, text=True, check=True,
-        ).stdout.strip()
-        assert git._resolve_sha(real) is not None

tests/utils/test_webui_transcript.py

@@ -696,42 +696,6 @@ def test_replay_preserves_local_trigger_source_metadata(tmp_path, monkeypatch) -
     assert msgs[0]["source"] == {"kind": "local_trigger", "label": "PR review"}
 
 
-def test_replay_preserves_automation_source_metadata_on_streamed_reply(
-    tmp_path,
-    monkeypatch,
-) -> None:
-    monkeypatch.setattr("nanobot.config.paths.get_data_dir", lambda: tmp_path)
-    key = "websocket:t-streamed-cron-source"
-    source = {"kind": "cron", "label": "Repo check"}
-
-    for record in (
-        {
-            "event": "delta",
-            "chat_id": "t-streamed-cron-source",
-            "text": "Repo ",
-            "source": source,
-        },
-        {
-            "event": "delta",
-            "chat_id": "t-streamed-cron-source",
-            "text": "clean.",
-            "source": source,
-        },
-        {
-            "event": "stream_end",
-            "chat_id": "t-streamed-cron-source",
-            "source": source,
-        },
-        {"event": "turn_end", "chat_id": "t-streamed-cron-source"},
-    ):
-        append_transcript_object(key, record)
-
-    msgs = replay_transcript_to_ui_messages(read_transcript_lines(key))
-
-    assert msgs[0]["content"] == "Repo clean."
-    assert msgs[0]["source"] == source
-
-
 def test_replay_preserves_legacy_trigger_source_metadata(tmp_path, monkeypatch) -> None:
     monkeypatch.setattr("nanobot.config.paths.get_data_dir", lambda: tmp_path)
     key = "websocket:t-trigger-source"

tests/webui/test_session_list_index.py

@@ -8,7 +8,6 @@ import pytest
 
 import nanobot.webui.session_list_index as session_list_index
 from nanobot.cron.session_turns import CRON_HISTORY_META
-from nanobot.providers.base import ProviderConversationState
 from nanobot.session.automation_turns import AUTOMATION_HISTORY_META
 from nanobot.session.history_visibility import HIDDEN_HISTORY_META
 from nanobot.session.manager import SessionManager
@@ -86,26 +85,6 @@ def test_webui_session_list_rescans_only_changed_file(tmp_path: Path, monkeypatc
     assert {row["preview"] for row in rows} == {"first", "second after"}
 
 
-def test_webui_session_list_skips_provider_state_before_preview_budget(
-    tmp_path: Path,
-    monkeypatch,
-) -> None:
-    monkeypatch.setattr(session_list_index, "_SESSION_LIST_PREVIEW_MAX_CHARS", 100)
-    manager = SessionManager(tmp_path)
-    session = manager.get_or_create("websocket:private-state")
-    session.provider_state = ProviderConversationState(
-        kind="openai_responses",
-        provider="openai:test",
-        model="test-model",
-        version=1,
-        payload={"items": [{"encrypted_content": "x" * 200}]},
-    )
-    session.add_message("user", "visible preview")
-    manager.save(session)
-
-    assert list_webui_sessions(manager)[0]["preview"] == "visible preview"
-
-
 def test_webui_session_list_drops_deleted_index_rows(tmp_path: Path) -> None:
     manager = SessionManager(tmp_path)
     session = manager.get_or_create("websocket:deleted")

tests/webui/test_token_usage.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import json
 from datetime import datetime, timezone
 from types import SimpleNamespace
 
@@ -15,60 +14,6 @@ from nanobot.webui.token_usage import (
 )
 
 
-def _write_state(tmp_path, days: dict) -> None:
-    state_dir = tmp_path / "webui"
-    state_dir.mkdir(parents=True, exist_ok=True)
-    (state_dir / "token-usage.json").write_text(
-        json.dumps({"days": days}), encoding="utf-8"
-    )
-
-
-def test_payload_tolerates_malformed_persisted_day_keys(tmp_path, monkeypatch) -> None:
-    """Day keys that are not real dates must not break settings payloads.
-
-    normalize_token_usage_state only length-checks day keys, so a hand-edited
-    10-char key survives reads and atomic rewrites; token_usage_payload then
-    parsed it with an unguarded fromisoformat, failing every /api/settings and
-    /api/settings/usage request until the file was fixed by hand.
-    """
-    monkeypatch.setattr("nanobot.webui.token_usage.get_webui_dir", lambda: tmp_path / "webui")
-    _write_state(tmp_path, {
-        "not-a-dat3": {"total_tokens": 7, "requests": 1},
-        "2026-13-01": {"total_tokens": 9, "requests": 1},
-        "2026-06-02": {"total_tokens": 5, "requests": 1},
-    })
-
-    payload = token_usage_payload(
-        timezone_name="UTC",
-        now=datetime(2026, 6, 3, 12, 0, tzinfo=timezone.utc),
-    )
-
-    assert payload["total_tokens"] == 5
-    assert payload["total_tokens_30d"] == 5
-    assert payload["requests_30d"] == 1
-    assert payload["active_days_30d"] == 1
-
-
-def test_record_scrubs_malformed_day_keys(tmp_path, monkeypatch) -> None:
-    """Rewrites drop malformed day keys instead of persisting them forever."""
-    monkeypatch.setattr("nanobot.webui.token_usage.get_webui_dir", lambda: tmp_path / "webui")
-    _write_state(tmp_path, {
-        "not-a-dat3": {"total_tokens": 7, "requests": 1},
-        "2026-06-02": {"total_tokens": 5, "requests": 1},
-    })
-
-    record_token_usage(
-        {"prompt_tokens": 1, "completion_tokens": 1},
-        timezone_name="UTC",
-        now=datetime(2026, 6, 3, 12, 0, tzinfo=timezone.utc),
-    )
-
-    raw = json.loads((tmp_path / "webui" / "token-usage.json").read_text(encoding="utf-8"))
-    assert "not-a-dat3" not in raw["days"]
-    assert "2026-06-02" in raw["days"]
-    assert "2026-06-03" in raw["days"]
-
-
 def test_record_token_usage_aggregates_by_local_day(tmp_path, monkeypatch) -> None:
     monkeypatch.setattr("nanobot.webui.token_usage.get_webui_dir", lambda: tmp_path / "webui")
 

webui/src/App.tsx

@@ -8,7 +8,7 @@ import {
   useState,
   type ReactNode,
 } from "react";
-import { Ghost, Moon, PanelLeft, ShieldCheck, Sun, X } from "lucide-react";
+import { Moon, PanelLeft, ShieldCheck, Sun, X } from "lucide-react";
 import { useTranslation } from "react-i18next";
 import { channelUiPresentation } from "@/channel-plugins/registry";
 import { Sidebar } from "@/components/Sidebar";
@@ -37,13 +37,6 @@ import {
 import { displayTitle } from "@/lib/chat-groups";
 import { deriveTitle } from "@/lib/format";
 import { NanobotClient } from "@/lib/nanobot-client";
-import {
-  createTemporaryChatSession,
-  isQuickChatKey,
-  QUICK_CHAT_ID,
-  QUICK_CHAT_KEY,
-  quickChatSession,
-} from "@/lib/quick-chat";
 import { ClientProvider, useClient } from "@/providers/ClientProvider";
 import type {
   BootstrapResponse,
@@ -232,9 +225,6 @@ function readShellRoute(): ShellRoute {
   if (path === "/skills") {
     return { view: "skills", activeKey, settingsSection: "skills" };
   }
-  if (path === "/quick-chat") {
-    return { view: "chat", activeKey: QUICK_CHAT_KEY, settingsSection: "overview" };
-  }
   if (path.startsWith("/chat/")) {
     const encoded = path.slice("/chat/".length);
     try {
@@ -251,7 +241,6 @@ function readShellRoute(): ShellRoute {
 
 function shellRouteHash(route: ShellRoute): string {
   if (route.view === "chat") {
-    if (isQuickChatKey(route.activeKey)) return "#/quick-chat";
     return route.activeKey
       ? `#/chat/${encodeURIComponent(route.activeKey)}`
       : "#/new";
@@ -958,24 +947,14 @@ function Shell({
     deleteChat,
     getSessionAutomations,
   } = useSessions();
-  const regularSessions = useMemo(
-    () => sessions.filter((session) => !isQuickChatKey(session.key)),
-    [sessions],
-  );
-  const quickSession = useMemo(
-    () => quickChatSession(sessions.find((session) => isQuickChatKey(session.key))),
-    [sessions],
-  );
   const { state: sidebarState, update: updateSidebarState } =
-    useSidebarState(regularSessions, !loading);
+    useSidebarState(sessions, !loading);
   const initialRouteRef = useRef<ShellRoute | null>(null);
   if (!initialRouteRef.current) initialRouteRef.current = readShellRoute();
   const [activeKey, setActiveKey] = useState<string | null>(
     initialRouteRef.current.activeKey,
   );
   const [view, setView] = useState<ShellView>(initialRouteRef.current.view);
-  const [temporarySession, setTemporarySession] = useState<ChatSummary | null>(null);
-  const temporarySessionRef = useRef<ChatSummary | null>(null);
   const [settingsInitialSection, setSettingsInitialSection] =
     useState<SettingsSectionKey>(initialRouteRef.current.settingsSection);
   const [hostSidebarOpen, setHostSidebarOpen] =
@@ -1025,33 +1004,19 @@ function Shell({
   const showHostChrome = effectiveRuntimeSurface === "native";
   const showMainSidebar = view !== "settings";
 
-  const discardTemporaryChat = useCallback(() => {
-    const current = temporarySessionRef.current;
-    if (!current) return;
-    temporarySessionRef.current = null;
-    client.discardTemporaryChat(current.chatId);
-    setTemporarySession(null);
-  }, [client]);
-
   const navigate = useCallback(
     (route: ShellRoute, options?: { replace?: boolean }) => {
-      if (route.view !== "chat" || route.activeKey !== QUICK_CHAT_KEY) {
-        discardTemporaryChat();
-      }
       setActiveKey(route.activeKey);
       setView(route.view);
       setSettingsInitialSection(route.settingsSection);
       writeShellRoute(route, options?.replace);
     },
-    [discardTemporaryChat],
+    [],
   );
 
   useEffect(() => {
     const applyRoute = () => {
       const route = readShellRoute();
-      if (route.view !== "chat" || route.activeKey !== QUICK_CHAT_KEY) {
-        discardTemporaryChat();
-      }
       setActiveKey(route.activeKey);
       setView(route.view);
       setSettingsInitialSection(route.settingsSection);
@@ -1062,15 +1027,7 @@ function Shell({
     };
     window.addEventListener("hashchange", applyRoute);
     return () => window.removeEventListener("hashchange", applyRoute);
-  }, [discardTemporaryChat]);
-
-  useEffect(() => {
-    return client.onStatus((status) => {
-      if (status !== "open") discardTemporaryChat();
-    });
-  }, [client, discardTemporaryChat]);
-
-  useEffect(() => () => discardTemporaryChat(), [discardTemporaryChat]);
+  }, []);
 
   useEffect(() => {
     let cancelled = false;
@@ -1157,11 +1114,8 @@ function Shell({
 
   const activeSession = useMemo<ChatSummary | null>(() => {
     if (!activeKey) return null;
-    if (isQuickChatKey(activeKey)) return temporarySession ?? quickSession;
     return sessions.find((s) => s.key === activeKey) ?? null;
-  }, [sessions, activeKey, quickSession, temporarySession]);
-  const quickChatActive = isQuickChatKey(activeKey);
-  const temporaryChatActive = quickChatActive && temporarySession !== null;
+  }, [sessions, activeKey]);
   const runningChatIdList = useMemo(() => Array.from(runningChatIds), [runningChatIds]);
   const updatedChatIdList = useMemo(() => Array.from(updatedChatIds), [updatedChatIds]);
   const activeChatId = activeSession?.chatId ?? null;
@@ -1176,12 +1130,6 @@ function Shell({
     });
   }, [activeChatId]);
   const activeWorkspaceScope = useMemo<WorkspaceScopePayload | null>(() => {
-    if (temporaryChatActive) {
-      return null;
-    }
-    if (quickChatActive) {
-      return workspaces?.default_scope ?? null;
-    }
     if (activeChatId && workspaceOverrides[activeChatId]) {
       return workspaceOverrides[activeChatId];
     }
@@ -1193,8 +1141,6 @@ function Shell({
     activeChatId,
     activeSession?.workspaceScope,
     draftWorkspaceScope,
-    quickChatActive,
-    temporaryChatActive,
     workspaceOverrides,
     workspaces?.default_scope,
   ]);
@@ -1215,10 +1161,7 @@ function Shell({
 
   useEffect(() => {
     if (loading) return;
-    const knownChatIds = new Set([
-      QUICK_CHAT_ID,
-      ...sessions.map((session) => session.chatId),
-    ]);
+    const knownChatIds = new Set(sessions.map((session) => session.chatId));
     setUpdatedChatIds((current) => {
       const next = new Set(
         Array.from(current).filter((chatId) => knownChatIds.has(chatId)),
@@ -1233,7 +1176,6 @@ function Shell({
 
   useEffect(() => {
     if (loading || !activeKey) return;
-    if (isQuickChatKey(activeKey)) return;
     if (sessions.some((session) => session.key === activeKey)) return;
     const currentRoute = readShellRoute();
     navigate(
@@ -1475,28 +1417,6 @@ function Shell({
     setMobileSidebarOpen(false);
   }, [navigate]);
 
-  const onOpenQuickChat = useCallback(() => {
-    setDraftWorkspaceScope(null);
-    setWorkspaceError(null);
-    setSessionSearchOpen(false);
-    navigate({
-      view: "chat",
-      activeKey: QUICK_CHAT_KEY,
-      settingsSection: "overview",
-    });
-    setMobileSidebarOpen(false);
-  }, [navigate]);
-
-  const onToggleTemporaryChat = useCallback(() => {
-    if (temporarySessionRef.current) {
-      discardTemporaryChat();
-      return;
-    }
-    const session = createTemporaryChatSession();
-    temporarySessionRef.current = session;
-    setTemporarySession(session);
-  }, [discardTemporaryChat]);
-
   const onNewChatInProject = useCallback(
     (projectPath: string, projectName: string) => {
       const base = workspaces?.default_scope ?? activeWorkspaceScope;
@@ -1762,7 +1682,6 @@ function Shell({
     setMobileSidebarOpen(false);
     const nextKey = (() => {
       if (!activeKey) return null;
-      if (isQuickChatKey(activeKey)) return activeKey;
       if (sessions.some((session) => session.key === activeKey)) return activeKey;
       return sessions[0]?.key ?? null;
     })();
@@ -1854,10 +1773,7 @@ function Shell({
     });
   }, [client, t]);
 
-  const onTurnEnd = useDeferredTitleRefresh(
-    quickChatActive ? null : activeSession,
-    refresh,
-  );
+  const onTurnEnd = useDeferredTitleRefresh(activeSession, refresh);
 
   const onConfirmDelete = useCallback(async () => {
     if (!pendingDelete) return;
@@ -1947,39 +1863,11 @@ function Shell({
     });
   }, []);
 
-  const headerTitle = temporaryChatActive
-    ? t("quickChat.temporary.title")
-    : quickChatActive
-      ? t("sidebar.quickChat")
-    : activeSession
+  const headerTitle = activeSession
     ? sidebarState.title_overrides[activeSession.key] ||
       activeSession.title ||
       deriveTitle(activeSession.preview, t("chat.newChat"))
-      : t("app.brand");
-
-  const temporaryChatAction = quickChatActive ? (
-    <Button
-      type="button"
-      size="sm"
-      variant="ghost"
-      aria-pressed={temporaryChatActive}
-      aria-label={
-        temporaryChatActive
-          ? t("quickChat.temporary.exit")
-          : t("quickChat.temporary.enter")
-      }
-      onClick={onToggleTemporaryChat}
-      className={cn(
-        "host-no-drag h-8 rounded-full px-2.5 text-xs text-muted-foreground",
-        temporaryChatActive && "bg-foreground text-background hover:bg-foreground/90 hover:text-background",
-      )}
-    >
-      <Ghost className="mr-1.5 h-3.5 w-3.5" />
-      {temporaryChatActive
-        ? t("quickChat.temporary.active")
-        : t("quickChat.temporary.enter")}
-    </Button>
-  ) : undefined;
+    : t("app.brand");
 
   useEffect(() => {
     if (view === "settings") {
@@ -2012,12 +1900,9 @@ function Shell({
   }, [activeSession, headerTitle, i18n.resolvedLanguage, t, view]);
 
   const sidebarProps = {
-    sessions: regularSessions,
-    activeKey: view === "chat" ? activeKey : null,
+    sessions,
+    activeKey,
     loading,
-    quickChatActive: view === "chat" && quickChatActive,
-    newChatActive: view === "chat" && activeKey === null,
-    onOpenQuickChat,
     onNewChat,
     onSelect: onSelectChat,
     onRequestDelete,
@@ -2180,7 +2065,7 @@ function Shell({
               <SessionSearchDialog
                 open
                 onOpenChange={setSessionSearchOpen}
-                sessions={regularSessions}
+                sessions={sessions}
                 activeKey={activeKey}
                 loading={loading}
                 titleOverrides={sidebarState.title_overrides}
@@ -2205,7 +2090,7 @@ function Shell({
                 onToggleSidebar={toggleSidebar}
                 onNewChat={onNewChat}
                 onCreateChat={onCreateChat}
-                onForkChat={quickChatActive ? undefined : onForkChat}
+                onForkChat={onForkChat}
                 onTurnEnd={onTurnEnd}
                 theme={theme}
                 onToggleTheme={toggle}
@@ -2213,34 +2098,14 @@ function Shell({
                 hostChromeTitleInset={hostSidebarCollapsed}
                 hideHeader={false}
                 workspaceScope={activeWorkspaceScope}
-                workspaceDefaultScope={
-                  temporaryChatActive ? null : workspaces?.default_scope ?? null
-                }
-                workspaceControls={
-                  quickChatActive ? null : (workspaces?.controls ?? null)
-                }
+                workspaceDefaultScope={workspaces?.default_scope ?? null}
+                workspaceControls={workspaces?.controls ?? null}
                 workspaceScopeDisabled={activeChatRunning}
                 workspaceError={workspaceError}
                 onWorkspaceScopeChange={applyWorkspaceScope}
                 settingsSnapshot={settingsSnapshot}
                 onOpenModelSettings={onOpenModelSettings}
                 skills={skills}
-                allowConversationReset={!quickChatActive}
-                showSessionInfo={!quickChatActive}
-                emptyStateGreeting={
-                  temporaryChatActive
-                    ? t("quickChat.temporary.greeting")
-                    : quickChatActive
-                      ? t("quickChat.greeting")
-                      : undefined
-                }
-                emptyStateDescription={
-                  temporaryChatActive
-                    ? t("quickChat.temporary.description")
-                    : undefined
-                }
-                temporary={temporaryChatActive}
-                headerAction={temporaryChatAction}
               />
             </div>
             {view !== "chat" && (

webui/src/components/ChatList.tsx

@@ -1,6 +1,7 @@
 import {
   memo,
   useEffect,
+  useLayoutEffect,
   useMemo,
   useRef,
   useState,
@@ -24,10 +25,6 @@ import {
   DropdownMenuItem,
   DropdownMenuTrigger,
 } from "@/components/ui/dropdown-menu";
-import {
-  SIDEBAR_SELECTION_ITEM_CLASS,
-  SidebarSelectionHighlight,
-} from "@/components/SidebarSelectionHighlight";
 import { deriveTitle, relativeTime, visibleSessionPreview } from "@/lib/format";
 import {
   COLLAPSED_CHATS_VISIBLE_COUNT,
@@ -107,7 +104,11 @@ export const ChatList = memo(function ChatList({
 }: ChatListProps) {
   const { t } = useTranslation();
   const [visibleLimit, setVisibleLimit] = useState(INITIAL_VISIBLE_SESSIONS);
+  const listContentRef = useRef<HTMLDivElement>(null);
   const activeRowRef = useRef<HTMLDivElement>(null);
+  const activeHighlightRef = useRef<HTMLDivElement>(null);
+  const activeHighlightSurfaceRef = useRef<HTMLDivElement>(null);
+  const highlightVisibleRef = useRef(false);
   const labels = useMemo<ChatGroupLabels>(() => ({
     pinned: t("chat.groups.pinned"),
     all: t("chat.groups.all"),
@@ -162,6 +163,74 @@ export const ChatList = memo(function ChatList({
     setVisibleLimit(INITIAL_VISIBLE_SESSIONS);
   }, [showArchived, sort]);
 
+  useLayoutEffect(() => {
+    let resetTransitionFrame: number | null = null;
+
+    const updateHighlight = () => {
+      const content = listContentRef.current;
+      const row = activeRowRef.current;
+      const highlight = activeHighlightRef.current;
+      const surface = activeHighlightSurfaceRef.current;
+
+      if (!highlight || !surface) return;
+      if (!content || !row) {
+        surface.style.opacity = "0";
+        surface.style.transform = "scale(0.97)";
+        highlightVisibleRef.current = false;
+        return;
+      }
+
+      const shouldFloatIn = !highlightVisibleRef.current;
+      if (shouldFloatIn) {
+        highlight.style.transitionProperty = "none";
+      }
+
+      const contentRect = content.getBoundingClientRect();
+      const rowRect = row.getBoundingClientRect();
+      highlight.style.width = `${rowRect.width}px`;
+      highlight.style.height = `${rowRect.height}px`;
+      highlight.style.transform = `translate3d(${rowRect.left - contentRect.left}px, ${
+        rowRect.top - contentRect.top
+      }px, 0)`;
+
+      if (shouldFloatIn) {
+        void highlight.offsetWidth;
+      }
+
+      surface.style.opacity = "1";
+      surface.style.transform = "scale(1)";
+      highlightVisibleRef.current = true;
+
+      if (shouldFloatIn) {
+        resetTransitionFrame = window.requestAnimationFrame(() => {
+          highlight.style.removeProperty("transition-property");
+          resetTransitionFrame = null;
+        });
+      }
+    };
+
+    updateHighlight();
+
+    const resizeObserver =
+      typeof ResizeObserver === "undefined"
+        ? null
+        : new ResizeObserver(updateHighlight);
+    if (resizeObserver) {
+      if (listContentRef.current) resizeObserver.observe(listContentRef.current);
+      if (activeRowRef.current) resizeObserver.observe(activeRowRef.current);
+    }
+    window.addEventListener("resize", updateHighlight);
+
+    return () => {
+      if (resetTransitionFrame !== null) {
+        window.cancelAnimationFrame(resetTransitionFrame);
+      }
+      activeHighlightRef.current?.style.removeProperty("transition-property");
+      resizeObserver?.disconnect();
+      window.removeEventListener("resize", updateHighlight);
+    };
+  }, [activeKey, density, limitedGroups, showPreviews, showTimestamps]);
+
   if (loading && sessions.length === 0) {
     return (
       <div className="px-3 py-6 text-[12px] text-muted-foreground">
@@ -187,10 +256,8 @@ export const ChatList = memo(function ChatList({
 
   return (
     <div className="h-full min-h-0 min-w-0 overflow-x-hidden overflow-y-auto overscroll-contain scrollbar-thin scrollbar-track-transparent">
-      <SidebarSelectionHighlight
-        targetRef={activeRowRef}
-        activeId={activeKey}
-        scope="sessions"
+      <div
+        ref={listContentRef}
         data-chat-list-content
         className="relative min-w-0 space-y-3 px-2 py-1.5"
       >
@@ -266,8 +333,7 @@ export const ChatList = memo(function ChatList({
                           ref={active ? activeRowRef : undefined}
                           data-chat-row={s.key}
                           className={cn(
-                            "group flex min-w-0 max-w-full items-center gap-2 rounded-xl px-2 text-[13px]",
-                            SIDEBAR_SELECTION_ITEM_CLASS,
+                            "group flex min-w-0 max-w-full items-center gap-2 rounded-xl px-2 text-[13px] transition-colors",
                             compact ? "min-h-7" : "min-h-8",
                             active
                               ? "text-sidebar-accent-foreground"
@@ -409,7 +475,19 @@ export const ChatList = memo(function ChatList({
             </button>
           </div>
         ) : null}
-      </SidebarSelectionHighlight>
+        <div
+          ref={activeHighlightRef}
+          data-testid="active-chat-highlight"
+          aria-hidden="true"
+          className="pointer-events-none absolute left-0 top-0 z-0 !mt-0 transition-[transform,width,height] duration-300 ease-out will-change-transform motion-reduce:transition-none"
+        >
+          <div
+            ref={activeHighlightSurfaceRef}
+            data-testid="active-chat-highlight-surface"
+            className="h-full w-full scale-[0.97] rounded-xl bg-sidebar-foreground/[0.055] opacity-0 transition-[opacity,transform] duration-200 ease-out motion-reduce:transition-none dark:bg-white/[0.07]"
+          />
+        </div>
+      </div>
     </div>
   );
 });

webui/src/components/Sidebar.tsx

@@ -1,14 +1,8 @@
-import {
-  type ReactNode,
-  type RefObject,
-  useRef,
-  useState,
-} from "react";
+import { useState, type ReactNode } from "react";
 import {
   Archive,
   Brain,
   CalendarClock,
-  MessageCircle,
   Menu,
   Search,
   Settings,
@@ -19,10 +13,6 @@ import { useTranslation } from "react-i18next";
 
 import { ChatList } from "@/components/ChatList";
 import { ConnectionBadge } from "@/components/ConnectionBadge";
-import {
-  SIDEBAR_SELECTION_ACTION_ITEM_CLASS,
-  SidebarSelectionHighlight,
-} from "@/components/SidebarSelectionHighlight";
 import { Button } from "@/components/ui/button";
 import type {
   ChatSummary,
@@ -34,9 +24,6 @@ interface SidebarProps {
   sessions: ChatSummary[];
   activeKey: string | null;
   loading: boolean;
-  quickChatActive: boolean;
-  newChatActive: boolean;
-  onOpenQuickChat: () => void;
   onNewChat: () => void;
   onSelect: (key: string) => void;
   onRequestDelete: (key: string, label: string) => void;
@@ -95,14 +82,6 @@ export function Sidebar(props: SidebarProps) {
   const collapsed = Boolean(props.collapsed);
   const toggleLabel = t("thread.header.toggleSidebar");
   const newChatShortcut = newChatShortcutLabel();
-  const activeActionRef = useRef<HTMLButtonElement>(null);
-  const activeActionId = props.quickChatActive
-    ? "quick-chat"
-    : props.newChatActive
-      ? "new-chat"
-      : props.activeUtility
-        ? `utility:${props.activeUtility}`
-        : null;
 
   return (
     <nav
@@ -154,29 +133,16 @@ export function Sidebar(props: SidebarProps) {
         )}
       </div>
 
-      <SidebarSelectionHighlight
-        targetRef={activeActionRef}
-        activeId={activeActionId}
-        scope="actions"
+      <div
         className={cn(
-          "relative space-y-1.5 px-2 pb-2",
+          "space-y-1.5 px-2 pb-2",
           collapsed && "flex w-14 flex-col items-center px-0",
         )}
       >
-        <SidebarActionButton
-          collapsed={collapsed}
-          label={t("sidebar.quickChat")}
-          onClick={props.onOpenQuickChat}
-          active={props.quickChatActive}
-          selectionRef={activeActionRef}
-          icon={<MessageCircle className="h-4 w-4" />}
-        />
         <SidebarActionButton
           collapsed={collapsed}
           label={t("sidebar.newChat")}
           onClick={props.onNewChat}
-          active={props.newChatActive}
-          selectionRef={activeActionRef}
           icon={<SquarePen className="h-4 w-4" />}
           shortcut={newChatShortcut}
           ariaKeyShortcuts="Meta+Shift+O Control+Shift+O"
@@ -193,7 +159,6 @@ export function Sidebar(props: SidebarProps) {
           onClick={props.onOpenApps}
           onIntent={props.onSettingsIntent}
           active={props.activeUtility === "apps"}
-          selectionRef={activeActionRef}
           icon={<Blocks className="h-4 w-4" />}
         />
         <SidebarActionButton
@@ -202,7 +167,6 @@ export function Sidebar(props: SidebarProps) {
           onClick={props.onOpenSkills}
           onIntent={props.onSettingsIntent}
           active={props.activeUtility === "skills"}
-          selectionRef={activeActionRef}
           icon={<Brain className="h-4 w-4" />}
         />
         <SidebarActionButton
@@ -211,7 +175,6 @@ export function Sidebar(props: SidebarProps) {
           onClick={props.onOpenAutomations}
           onIntent={props.onSettingsIntent}
           active={props.activeUtility === "automations"}
-          selectionRef={activeActionRef}
           icon={<CalendarClock className="h-4 w-4" />}
         />
         {props.archivedCount ? (
@@ -222,7 +185,7 @@ export function Sidebar(props: SidebarProps) {
             icon={<Archive className="h-4 w-4" />}
           />
         ) : null}
-      </SidebarSelectionHighlight>
+      </div>
       <div
         className={cn(
           "flex min-h-0 min-w-0 flex-1 flex-col overflow-hidden transition-opacity duration-200",
@@ -292,7 +255,6 @@ function SidebarActionButton({
   shortcut,
   ariaKeyShortcuts,
   onIntent,
-  selectionRef,
 }: {
   collapsed: boolean;
   label: string;
@@ -303,15 +265,13 @@ function SidebarActionButton({
   shortcut?: string;
   ariaKeyShortcuts?: string;
   onIntent?: () => void;
-  selectionRef?: RefObject<HTMLButtonElement>;
 }) {
   const title = shortcut ? `${label} (${shortcut})` : collapsed ? label : undefined;
 
   return (
     <Button
-      ref={active ? selectionRef : undefined}
       type="button"
-      variant={null}
+      variant="ghost"
       aria-label={label}
       aria-current={active ? "page" : undefined}
       aria-keyshortcuts={ariaKeyShortcuts}
@@ -320,14 +280,12 @@ function SidebarActionButton({
       onFocus={onIntent}
       onPointerEnter={onIntent}
       className={cn(
-        "touch-target group h-8 min-w-0 gap-2 overflow-hidden rounded-xl font-medium",
-        SIDEBAR_SELECTION_ACTION_ITEM_CLASS,
+        "touch-target group h-8 min-w-0 gap-2 overflow-hidden rounded-full font-medium text-sidebar-foreground/85 hover:bg-sidebar-accent/75 hover:text-sidebar-foreground",
+        "transition-[width,padding,border-radius,color,background-color] duration-300 ease-out",
         collapsed
-          ? "w-9 justify-center gap-0 px-0"
+          ? "w-9 justify-center gap-0 rounded-xl px-0"
           : "w-full justify-start gap-2 px-3 text-[12.5px]",
-        active
-          ? "text-sidebar-accent-foreground"
-          : "text-sidebar-foreground/85 hover:bg-sidebar-foreground/[0.035] hover:text-sidebar-foreground dark:hover:bg-white/[0.05]",
+        active && "bg-sidebar-accent text-sidebar-foreground shadow-[inset_0_0_0_1px_hsl(var(--sidebar-border)/0.55)]",
         className,
       )}
     >

webui/src/components/SidebarSelectionHighlight.tsx

@@ -1,101 +0,0 @@
-import {
-  type HTMLAttributes,
-  type RefObject,
-  useLayoutEffect,
-  useRef,
-} from "react";
-
-interface SidebarSelectionHighlightProps extends HTMLAttributes<HTMLDivElement> {
-  targetRef: RefObject<HTMLElement>;
-  activeId: string | null;
-  scope: string;
-}
-
-export const SIDEBAR_SELECTION_ITEM_CLASS =
-  "relative z-[1] transition-[color] duration-150 ease-out motion-reduce:transition-none";
-
-export const SIDEBAR_SELECTION_ACTION_ITEM_CLASS =
-  "relative z-[1] transition-[width,padding,color] [transition-duration:300ms,300ms,150ms] ease-out motion-reduce:transition-none";
-
-export function SidebarSelectionHighlight({
-  targetRef,
-  activeId,
-  scope,
-  children,
-  ...containerProps
-}: SidebarSelectionHighlightProps) {
-  const containerRef = useRef<HTMLDivElement>(null);
-  const highlightRef = useRef<HTMLDivElement>(null);
-  const positionedRef = useRef(false);
-
-  useLayoutEffect(() => {
-    const highlight = highlightRef.current;
-    const container = containerRef.current;
-    const target = targetRef.current;
-    if (!highlight) return;
-    if (!activeId || !container || !target) {
-      highlight.style.opacity = "0";
-      positionedRef.current = false;
-      return;
-    }
-
-    let restoreTransitionFrame: number | null = null;
-
-    const position = () => {
-      const containerRect = container.getBoundingClientRect();
-      const targetRect = target.getBoundingClientRect();
-      if (targetRect.width === 0 || targetRect.height === 0) {
-        highlight.style.opacity = "0";
-        positionedRef.current = false;
-        return;
-      }
-
-      const firstPosition = !positionedRef.current;
-      if (firstPosition) highlight.style.transitionProperty = "none";
-
-      highlight.style.width = `${targetRect.width}px`;
-      highlight.style.height = `${targetRect.height}px`;
-      highlight.style.transform = `translate3d(${targetRect.left - containerRect.left}px, ${
-        targetRect.top - containerRect.top
-      }px, 0)`;
-      highlight.style.opacity = "1";
-      positionedRef.current = true;
-
-      if (firstPosition) {
-        restoreTransitionFrame = window.requestAnimationFrame(() => {
-          highlight.style.removeProperty("transition-property");
-          restoreTransitionFrame = null;
-        });
-      }
-    };
-
-    position();
-    const resizeObserver =
-      typeof ResizeObserver === "undefined" ? null : new ResizeObserver(position);
-    resizeObserver?.observe(container);
-    resizeObserver?.observe(target);
-    window.addEventListener("resize", position);
-
-    return () => {
-      if (restoreTransitionFrame !== null) {
-        window.cancelAnimationFrame(restoreTransitionFrame);
-      }
-      highlight?.style.removeProperty("transition-property");
-      resizeObserver?.disconnect();
-      window.removeEventListener("resize", position);
-    };
-  });
-
-  return (
-    <div {...containerProps} ref={containerRef}>
-      {children}
-      <div
-        ref={highlightRef}
-        data-testid={`${scope}-selection-highlight`}
-        data-active-id={activeId ?? undefined}
-        aria-hidden="true"
-        className="pointer-events-none absolute left-0 top-0 z-0 !mt-0 rounded-xl bg-sidebar-foreground/[0.055] opacity-0 transition-[transform,width,height] duration-300 ease-out will-change-transform motion-reduce:transition-none dark:bg-white/[0.07]"
-      />
-    </div>
-  );
-}

webui/src/components/settings/SettingsView.tsx

@@ -65,10 +65,6 @@ import { useTranslation } from "react-i18next";
 
 import { channelUiPresentation } from "@/channel-plugins/registry";
 import { LanguageSwitcher } from "@/components/LanguageSwitcher";
-import {
-  SIDEBAR_SELECTION_ITEM_CLASS,
-  SidebarSelectionHighlight,
-} from "@/components/SidebarSelectionHighlight";
 import { SkillsCatalogSettings } from "@/components/settings/SkillsCatalogSettings";
 import { TokenUsageHeatmap } from "@/components/settings/TokenUsageHeatmap";
 import { ToggleButton } from "@/components/settings/ToggleButton";
@@ -2501,7 +2497,6 @@ function SettingsSidebar({
   hostChromeInset?: boolean;
 }) {
   const { t } = useTranslation();
-  const activeNavItemRef = useRef<HTMLButtonElement>(null);
   const activeItem = SETTINGS_NAV_ITEMS.find((item) => item.key === activeSection)
     ?? SETTINGS_NAV_ITEMS[0];
   const ActiveIcon = activeItem.icon;
@@ -2574,26 +2569,19 @@ function SettingsSidebar({
           </DropdownMenuContent>
         </DropdownMenu>
 
-        <SidebarSelectionHighlight
-          targetRef={activeNavItemRef}
-          activeId={activeSection}
-          scope="settings"
-          className="relative hidden space-y-1 lg:block"
-        >
+        <div className="hidden space-y-1 lg:block">
           {SETTINGS_NAV_ITEMS.map(({ key, icon: Icon, fallback }) => {
             const active = key === activeSection;
             return (
               <button
-                ref={active ? activeNavItemRef : undefined}
                 key={key}
                 type="button"
                 aria-current={active ? "page" : undefined}
                 onClick={() => onSelectSection(key)}
                 className={cn(
-                  "touch-target flex h-9 w-full items-center gap-2 rounded-xl px-2.5 text-left text-[13px] font-medium",
-                  SIDEBAR_SELECTION_ITEM_CLASS,
+                  "touch-target flex h-9 w-full items-center gap-2 rounded-[10px] px-2.5 text-left text-[13px] font-medium transition-colors",
                   active
-                    ? "text-sidebar-accent-foreground"
+                    ? "bg-sidebar-accent text-foreground"
                     : "text-muted-foreground/78 hover:bg-muted/45 hover:text-foreground",
                 )}
               >
@@ -2604,7 +2592,7 @@ function SettingsSidebar({
               </button>
             );
           })}
-        </SidebarSelectionHighlight>
+        </div>
       </nav>
 
       <div className="hidden lg:mt-auto lg:block lg:pt-4">

webui/src/components/thread/ThreadComposer.tsx

@@ -202,7 +202,6 @@ interface ThreadComposerProps {
   quotedContext?: string | null;
   focusRequest?: number;
   onQuotedContextChange?: (text: string | null) => void;
-  allowAttachments?: boolean;
 }
 
 const COMMAND_ICONS: Record<string, LucideIcon> = {
@@ -851,7 +850,6 @@ export function ThreadComposer({
   quotedContext = null,
   focusRequest = 0,
   onQuotedContextChange,
-  allowAttachments = true,
 }: ThreadComposerProps) {
   const { t } = useTranslation();
   const [value, setValue] = useState("");
@@ -915,10 +913,6 @@ export function ThreadComposer({
   const { images, enqueue, remove, clear, restoreReadyImages, encoding, full } =
     useAttachedImages({ ingressLimits });
 
-  useEffect(() => {
-    if (!allowAttachments) clear();
-  }, [allowAttachments, clear]);
-
   const formatRejection = useCallback(
     (reason: AttachmentError): string => {
       const key = `thread.composer.imageRejected.${reason}`;
@@ -948,7 +942,6 @@ export function ThreadComposer({
 
   const addFiles = useCallback(
     (files: File[]) => {
-      if (!allowAttachments) return;
       if (files.length === 0) return;
       secondEnterPromptIdRef.current = null;
       const { rejected } = enqueue(files);
@@ -958,7 +951,7 @@ export function ThreadComposer({
         setInlineError(null);
       }
     },
-    [allowAttachments, enqueue, formatRejection],
+    [enqueue, formatRejection],
   );
 
   const {
@@ -1881,10 +1874,10 @@ export function ThreadComposer({
         e.preventDefault();
         submit();
       }}
-      onDragEnter={allowAttachments ? onDragEnter : undefined}
-      onDragOver={allowAttachments ? onDragOver : undefined}
-      onDragLeave={allowAttachments ? onDragLeave : undefined}
-      onDrop={allowAttachments ? onDrop : undefined}
+      onDragEnter={onDragEnter}
+      onDragOver={onDragOver}
+      onDragLeave={onDragLeave}
+      onDrop={onDrop}
       className={cn("relative w-full", isHero ? "px-0" : "px-1 pb-1.5 pt-1 sm:px-0")}
     >
       {showSlashMenu ? (
@@ -1914,9 +1907,7 @@ export function ThreadComposer({
             ? "max-w-[58rem] rounded-[28px] bg-muted/30 focus-within:bg-muted/50 dark:bg-card dark:focus-within:bg-white/[0.06]"
             : "max-w-[49.5rem] rounded-[22px] bg-muted/30 focus-within:bg-muted/50 dark:bg-card dark:focus-within:bg-white/[0.06]",
           disabled && "opacity-60",
-          allowAttachments
-            && isDragging
-            && "ring-2 ring-primary/40 motion-reduce:ring-0 motion-reduce:border-primary",
+          isDragging && "ring-2 ring-primary/40 motion-reduce:ring-0 motion-reduce:border-primary",
           goalState?.active &&
             "goal-shell-glow ring-1 ring-sky-400/35 motion-reduce:ring-sky-400/25 dark:ring-sky-400/45",
         )}
@@ -2023,7 +2014,7 @@ export function ThreadComposer({
             onKeyUp={(e) => setCursorPosition(e.currentTarget.selectionStart ?? e.currentTarget.value.length)}
             onSelect={(e) => setCursorPosition(e.currentTarget.selectionStart ?? e.currentTarget.value.length)}
             onClick={(e) => setCursorPosition(e.currentTarget.selectionStart ?? e.currentTarget.value.length)}
-            onPaste={allowAttachments ? onPaste : undefined}
+            onPaste={onPaste}
             rows={1}
             placeholder={resolvedPlaceholder}
             disabled={disabled}
@@ -2066,34 +2057,30 @@ export function ThreadComposer({
               isHero ? "gap-1.5" : "gap-2",
             )}
           >
-            {allowAttachments ? (
-              <>
-                <input
-                  ref={fileInputRef}
-                  type="file"
-                  accept={ACCEPT_ATTR}
-                  multiple
-                  hidden
-                  onChange={onFilePick}
-                />
-                <Button
-                  type="button"
-                  size="icon"
-                  variant="ghost"
-                  disabled={attachButtonDisabled}
-                  aria-label={t("thread.composer.attachImage")}
-                  onClick={() => fileInputRef.current?.click()}
-                  className={cn(
-                    "thread-composer-action touch-target rounded-full text-muted-foreground hover:text-foreground",
-                    isHero
-                      ? "h-8 w-8 border border-border/55 bg-card shadow-[0_2px_8px_rgba(15,23,42,0.05)] hover:bg-card"
-                      : "h-9 w-9 border border-border/55 bg-card shadow-[0_2px_8px_rgba(15,23,42,0.05)] hover:bg-card",
-                  )}
-                >
-                  <Plus className={cn(isHero ? "h-[18px] w-[18px]" : "h-4 w-4")} />
-                </Button>
-              </>
-            ) : null}
+            <input
+              ref={fileInputRef}
+              type="file"
+              accept={ACCEPT_ATTR}
+              multiple
+              hidden
+              onChange={onFilePick}
+            />
+            <Button
+              type="button"
+              size="icon"
+              variant="ghost"
+              disabled={attachButtonDisabled}
+              aria-label={t("thread.composer.attachImage")}
+              onClick={() => fileInputRef.current?.click()}
+              className={cn(
+                "thread-composer-action touch-target rounded-full text-muted-foreground hover:text-foreground",
+                isHero
+                  ? "h-8 w-8 border border-border/55 bg-card shadow-[0_2px_8px_rgba(15,23,42,0.05)] hover:bg-card"
+                  : "h-9 w-9 border border-border/55 bg-card shadow-[0_2px_8px_rgba(15,23,42,0.05)] hover:bg-card",
+              )}
+            >
+              <Plus className={cn(isHero ? "h-[18px] w-[18px]" : "h-4 w-4")} />
+            </Button>
             {voiceRecorder.isRecording ? (
               <VoiceRecordingMeter
                 ariaLabel={voiceRecordingStatusLabel}

webui/src/components/thread/ThreadHeader.tsx

@@ -16,7 +16,6 @@ interface ThreadHeaderProps {
   minimal?: boolean;
   promptNavigatorAction?: ReactNode;
   sessionInfoAction?: ReactNode;
-  headerAction?: ReactNode;
 }
 
 export function ThreadHeader({
@@ -30,7 +29,6 @@ export function ThreadHeader({
   minimal = false,
   promptNavigatorAction,
   sessionInfoAction,
-  headerAction,
 }: ThreadHeaderProps) {
   const { t } = useTranslation();
 
@@ -63,7 +61,6 @@ export function ThreadHeader({
       </div>
 
       <div className="ml-auto flex shrink-0 items-center gap-1">
-        {headerAction}
         {sessionInfoAction}
         {promptNavigatorAction}
         {!hideThemeButton ? (

webui/src/components/thread/ThreadShell.tsx

@@ -1,5 +1,5 @@
 import { useCallback, useEffect, useLayoutEffect, useMemo, useRef, useState } from "react";
-import type { PointerEvent as ReactPointerEvent, ReactNode } from "react";
+import type { PointerEvent as ReactPointerEvent } from "react";
 import { useTranslation } from "react-i18next";
 
 import { FilePreviewAvailabilityProvider } from "@/components/FilePreviewAvailabilityContext";
@@ -33,7 +33,6 @@ import {
 } from "@/lib/mcp-preset-events";
 import type { CanonicalRunSnapshot, StreamError } from "@/lib/nanobot-client";
 import { inferProviderFromModelName, providerDisplayLabel } from "@/lib/provider-brand";
-import { TEMPORARY_CHAT_ID_PREFIX } from "@/lib/quick-chat";
 import type {
   ChatSummary,
   SettingsPayload,
@@ -316,12 +315,6 @@ interface ThreadShellProps {
   settingsSnapshot?: SettingsPayload | null;
   onOpenModelSettings?: () => void;
   skills?: SkillSummary[];
-  allowConversationReset?: boolean;
-  showSessionInfo?: boolean;
-  emptyStateGreeting?: string;
-  emptyStateDescription?: string;
-  temporary?: boolean;
-  headerAction?: ReactNode;
 }
 
 function toModelBadgeLabel(modelName: string | null): string | null {
@@ -604,16 +597,10 @@ export function ThreadShell({
   settingsSnapshot = null,
   onOpenModelSettings,
   skills = [],
-  allowConversationReset = true,
-  showSessionInfo = true,
-  emptyStateGreeting,
-  emptyStateDescription,
-  temporary = false,
-  headerAction,
 }: ThreadShellProps) {
   const { t } = useTranslation();
   const chatId = session?.chatId ?? null;
-  const historyKey = temporary ? null : session?.key ?? null;
+  const historyKey = session?.key ?? null;
   const {
     messages: historical,
     loading,
@@ -635,16 +622,6 @@ export function ThreadShell({
   const [fallbackModelName, setFallbackModelName] = useState<string | null>(null);
   const [booting, setBooting] = useState(false);
   const [slashCommands, setSlashCommands] = useState<SlashCommand[]>([]);
-  const availableSlashCommands = useMemo(
-    () => temporary
-      ? slashCommands.filter((command) =>
-          command.command === "/model" || command.command === "/stop",
-        )
-      : allowConversationReset
-        ? slashCommands
-        : slashCommands.filter((command) => command.command !== "/new"),
-    [allowConversationReset, slashCommands, temporary],
-  );
   const cliApps = useInstalledSettingItems({
     getToken,
     eventName: CLI_APPS_CHANGED_EVENT,
@@ -692,9 +669,8 @@ export function ThreadShell({
 
   const initial = useMemo(() => {
     if (!chatId) return historical;
-    if (temporary) return historical;
     return messageCacheRef.current.get(chatId) ?? historical;
-  }, [chatId, historical, temporary]);
+  }, [chatId, historical]);
   const handleTurnEnd = useCallback(() => {
     if (chatId) activeViewportTurnByChatIdRef.current.delete(chatId);
     setSubmittedViewportTurnId(null);
@@ -714,13 +690,7 @@ export function ThreadShell({
     setMessages,
     streamError,
     dismissStreamError,
-  } = useNanobotStream(
-    chatId,
-    initial,
-    hasPendingToolCalls,
-    handleTurnEnd,
-    { temporary },
-  );
+  } = useNanobotStream(chatId, initial, hasPendingToolCalls, handleTurnEnd);
 
   useLayoutEffect(() => {
     if (currentUiMessagesRef.current === messages) return;
@@ -849,12 +819,9 @@ export function ThreadShell({
   const handleModelPresetChange = useCallback((name: string) => {
     setLocalModelPreset(name);
     if (chatId) {
-      const request = temporary
-        ? client.sendSystemCommand(chatId, `/model ${name}`, 5_000, { temporary: true })
-        : client.sendSystemCommand(chatId, `/model ${name}`);
-      void request.catch(() => {});
+      void client.sendSystemCommand(chatId, `/model ${name}`).catch(() => {});
     }
-  }, [chatId, client, temporary]);
+  }, [chatId, client]);
   const modelPresetOptions = useMemo(
     () => modelPresetOptionsFromSettings(settings),
     [settings],
@@ -875,16 +842,13 @@ export function ThreadShell({
 
   const withWorkspaceScope = useCallback(
     (options?: SendOptions): SendOptions | undefined => {
-      if (temporary) {
-        return { ...(options ?? {}), temporary: true };
-      }
       if (!workspaceScope) return options;
       return {
         ...(options ?? {}),
         workspaceScope,
       };
     },
-    [temporary, workspaceScope],
+    [workspaceScope],
   );
 
   const refreshModelSettings = useCallback(async () => {
@@ -918,11 +882,11 @@ export function ThreadShell({
     return client.onChat(chatId, (event) => {
       if (event.event !== "turn_model_updated") return;
       setFallbackModelName(event.model_name);
-    }, { temporary });
-  }, [chatId, client, temporary]);
+    });
+  }, [chatId, client]);
 
   useEffect(() => {
-    if (!chatId || loading || temporary) return;
+    if (!chatId || loading) return;
     const cached = messageCacheRef.current.get(chatId);
     const pendingCanonicalHydrate = pendingCanonicalHydrateRef.current.get(chatId);
     const hasNewCanonicalHistory = (
@@ -1052,7 +1016,6 @@ export function ThreadShell({
     historyLineage,
     historyActiveTurnId,
     hasPendingToolCalls,
-    temporary,
   ]);
 
   useLayoutEffect(() => {
@@ -1104,7 +1067,7 @@ export function ThreadShell({
   }, [chatId, hasPendingToolCalls, historyVersion, messages, reconcileTurnComplete]);
 
   const refreshCanonicalHistory = useCallback(() => {
-    if (!chatId || temporary) return;
+    if (!chatId) return;
     pendingCanonicalHydrateRef.current.set(chatId, {
       historyLineage,
       historyVersion,
@@ -1114,7 +1077,7 @@ export function ThreadShell({
       uiRevision: uiRevisionRef.current,
     });
     refreshHistory();
-  }, [chatId, client, historyLineage, historyVersion, refreshHistory, temporary]);
+  }, [chatId, client, historyLineage, historyVersion, refreshHistory]);
 
   useEffect(() => {
     if (!chatId) return;
@@ -1181,22 +1144,16 @@ export function ThreadShell({
     if (chatId) {
       const prev = prevChatIdForCacheRef.current;
       if (prev && prev !== chatId) {
-        if (prev.startsWith(TEMPORARY_CHAT_ID_PREFIX)) {
-          messageCacheRef.current.delete(prev);
-        } else {
-          messageCacheRef.current.set(prev, displayMessages);
-        }
+        messageCacheRef.current.set(prev, displayMessages);
         skipLayoutCacheRef.current = true;
       }
       prevChatIdForCacheRef.current = chatId;
     } else {
       if (prevChatIdForCacheRef.current) {
-        const prev = prevChatIdForCacheRef.current;
-        if (prev.startsWith(TEMPORARY_CHAT_ID_PREFIX)) {
-          messageCacheRef.current.delete(prev);
-        } else {
-          messageCacheRef.current.set(prev, displayMessages);
-        }
+        messageCacheRef.current.set(
+          prevChatIdForCacheRef.current,
+          displayMessages,
+        );
         skipLayoutCacheRef.current = true;
       }
       prevChatIdForCacheRef.current = null;
@@ -1207,7 +1164,7 @@ export function ThreadShell({
   // ``useEffect`` reset has flushed; ``skipLayoutCacheRef`` drops the first run that still
   // sees the *previous* chat's ``messages`` (avoids stale rows leaking across sessions).
   useEffect(() => {
-    if (!chatId || temporary) {
+    if (!chatId) {
       return;
     }
     if (skipLayoutCacheRef.current) {
@@ -1218,7 +1175,7 @@ export function ThreadShell({
       return;
     }
     messageCacheRef.current.set(chatId, displayMessages);
-  }, [chatId, displayMessages, loading, temporary]);
+  }, [chatId, displayMessages, loading]);
 
   // The landing composer queues the first message while `new_chat` is in flight.
   // Only the chat created for that send may consume it; selecting another chat
@@ -1417,12 +1374,12 @@ export function ThreadShell({
           fallbackModelName={fallbackModelName}
           onModelBadgeClick={modelBadge.needsSetup ? onOpenModelSettings : undefined}
           variant={showHeroComposer ? "hero" : "thread"}
-          slashCommands={availableSlashCommands}
-          cliApps={temporary ? [] : cliApps}
-          mcpPresets={temporary ? [] : mcpPresets}
-          skills={temporary ? [] : skills}
+          slashCommands={slashCommands}
+          cliApps={cliApps}
+          mcpPresets={mcpPresets}
+          skills={skills}
           onStop={stop}
-          onTranscribeAudio={temporary ? undefined : transcribeAudio}
+          onTranscribeAudio={transcribeAudio}
           runStartedAt={currentRunStartedAt}
           goalState={currentGoalState}
           workspaceScope={workspaceScope}
@@ -1437,7 +1394,6 @@ export function ThreadShell({
           quotedContext={quotedContext}
           focusRequest={composerFocusSignal}
           onQuotedContextChange={setQuotedContext}
-          allowAttachments={!temporary}
         />
       ) : (
         <ThreadComposer
@@ -1460,7 +1416,7 @@ export function ThreadShell({
           fallbackModelName={fallbackModelName}
           onModelBadgeClick={modelBadge.needsSetup ? onOpenModelSettings : undefined}
           variant="hero"
-          slashCommands={availableSlashCommands}
+          slashCommands={slashCommands}
           cliApps={cliApps}
           mcpPresets={mcpPresets}
           skills={skills}
@@ -1486,15 +1442,10 @@ export function ThreadShell({
     </div>
   ) : (
     <div className="flex w-full flex-col items-center text-center animate-in fade-in-0 slide-in-from-bottom-2 duration-500">
-      <HeroGreeting text={emptyStateGreeting ?? t(heroGreetingKey)} />
-      {emptyStateDescription ? (
-        <p className="mt-3 max-w-xl text-sm text-muted-foreground">
-          {emptyStateDescription}
-        </p>
-      ) : null}
+      <HeroGreeting text={t(heroGreetingKey)} />
     </div>
   );
-  const sessionInfoAction = historyKey && showSessionInfo ? (
+  const sessionInfoAction = historyKey ? (
     <SessionInfoPopover sessionKey={historyKey} token={token} title={title} />
   ) : undefined;
   const promptNavigatorAction = historyKey ? (
@@ -1519,7 +1470,6 @@ export function ThreadShell({
             minimal={!session && !loading}
             promptNavigatorAction={promptNavigatorAction}
             sessionInfoAction={sessionInfoAction}
-            headerAction={headerAction}
           />
         ) : null}
         <FilePreviewAvailabilityProvider
@@ -1536,17 +1486,17 @@ export function ThreadShell({
             conversationKey={historyKey}
             conversationReady={messagesReady}
             showScrollToBottomButton={!!session}
-            cliApps={temporary ? [] : cliApps}
-            mcpPresets={temporary ? [] : mcpPresets}
-            slashCommands={availableSlashCommands}
+            cliApps={cliApps}
+            mcpPresets={mcpPresets}
+            slashCommands={slashCommands}
             forkBoundaryMessageCount={forkBoundaryMessageCount}
             hasMoreBefore={hasMoreBefore}
             loadingOlder={loadingOlder}
             userMessageOffset={userMessageOffset}
             onLoadOlder={loadOlder}
             onOpenFilePreview={historyKey ? handleOpenFilePreview : undefined}
-            onForkFromMessage={!temporary && onForkChat ? handleForkFromMessage : undefined}
-            onQuoteSelection={session && !temporary ? handleQuoteSelection : undefined}
+            onForkFromMessage={onForkChat ? handleForkFromMessage : undefined}
+            onQuoteSelection={session ? handleQuoteSelection : undefined}
           />
         </FilePreviewAvailabilityProvider>
       </div>

webui/src/components/thread/ThreadViewport.tsx

@@ -542,7 +542,7 @@ export const ThreadViewport = forwardRef<ThreadViewportHandle, ThreadViewportPro
       const distance = el.scrollHeight - el.scrollTop - el.clientHeight;
       const near = distance < NEAR_BOTTOM_PX;
       const owner = threadMotionRef.current?.observeScroll(near) ?? "automatic";
-      const logicallyAtBottom = owner === "automatic" || (owner === "navigation" && near);
+      const logicallyAtBottom = owner === "automatic" || near;
       setAtBottom((current) =>
         current === logicallyAtBottom ? current : logicallyAtBottom,
       );
@@ -557,7 +557,6 @@ export const ThreadViewport = forwardRef<ThreadViewportHandle, ThreadViewportPro
       if (!direction) return;
       threadMotionRef.current?.handleUserScrollIntent(
         canScrollInDirection(el, direction),
-        direction === "forward",
       );
     };
     const handleWheel = (event: WheelEvent) => {
@@ -573,21 +572,20 @@ export const ThreadViewport = forwardRef<ThreadViewportHandle, ThreadViewportPro
     const handlePointerDown = (event: PointerEvent) => {
       if (event.button === 0 && event.target === el) yieldCameraToUser();
     };
-    let lastTouchY: number | null = null;
+    let touchStartY: number | null = null;
     const handleTouchStart = (event: TouchEvent) => {
-      lastTouchY = event.touches[0]?.clientY ?? null;
+      touchStartY = event.touches[0]?.clientY ?? null;
     };
     const handleTouchMove = (event: TouchEvent) => {
       const currentY = event.touches[0]?.clientY;
       const scrollDeltaY =
-        lastTouchY !== null && currentY !== undefined
-          ? lastTouchY - currentY
+        touchStartY !== null && currentY !== undefined
+          ? touchStartY - currentY
           : 0;
-      lastTouchY = currentY ?? null;
       handleDirectionalInput(directionFromDelta(scrollDeltaY));
     };
     const handleTouchEnd = () => {
-      lastTouchY = null;
+      touchStartY = null;
     };
     const handleKeyDown = (event: KeyboardEvent) => {
       if (