Resolves conflicts after main landed the state-machine turn refactor
and the test_runner.py 9-file split:
- nanobot/agent/loop.py: take main's `_state_build`/`_persist_user_message_early`
flow; restore the `reasoning: bool` parameter on `_build_bus_progress_callback`
so the loop hook can mark progress as reasoning-channel without coupling to
the answer stream.
- nanobot/cli/stream.py: keep main's configurable `bot_name`/`bot_icon` header
while preserving the PR's `transient=True` Live + `self._console` routing
+ `_renderable()` final-render path that fixed TUI duplication.
- tests/agent/test_runner.py was deleted on main and split into 9 focused
files; relocated all 6 reasoning tests into a new `test_runner_reasoning.py`
matching the new layout, deduplicated the per-test `ReasoningHook` boilerplate
through a shared `_RecordingHook` helper.
Co-authored-by: Cursor <cursoragent@cursor.com>
Reasoning surfacing was split across three branches in runner.py plus
two separate streaming buffers (loop hook and runner progress stream),
with three independent display-side gates in the CLI. This collapsed
the policy into one source of truth and fixed two real bugs:
- Structured `reasoning_content` was suppressed whenever the answer was
streamed, because the runner gated emission on `streamed_content`.
Providers don't stream `reasoning_content`; it only arrives on the
final response, so the answer stream and the reasoning channel are
independent. Added `streamed_reasoning` to `AgentHookContext` to track
the right bit.
- `channels.showReasoning` was subordinated to `sendProgress`. They are
orthogonal — turning off progress streaming shouldn't silence
reasoning. Reworked the CLI gates accordingly.
Single-helper consolidation:
- `extract_reasoning(reasoning_content, thinking_blocks, content)`
returns `(reasoning_text, cleaned_content)` with a defined fallback
order: dedicated field → Anthropic thinking_blocks → inline
`<think>`/`<thought>` tags. Models that expose none of these
short-circuit to `(None, content)` — zero overhead.
- `IncrementalThinkExtractor` replaces the ad-hoc `emit_incremental_think`
function and its hand-rolled "emitted cursor" state in both the loop
hook and the runner progress stream.
Also documented the new `showReasoning` channel option in
docs/configuration.md and noted its independence from sendProgress.
Co-authored-by: Cursor <cursoragent@cursor.com>
Remove unused code confirmed dead via vulture scan, grep verification,
and coverage analysis:
- _get_bridge_dir (cli/commands.py): 82-line function with zero callers
- add_assistant_message (agent/context.py): method body never executed,
also removed now-unused build_assistant_message import
- _tool_parameters_schema (agent/tools/base.py): redundant copy of schema
already exposed via the `parameters` property
- MSTEAMS_REF_TTL_S (channels/msteams.py): unused constant (production
uses config.ref_ttl_days directly); inlined in test
- MESSAGE_TYPE_USER (channels/weixin.py): unused constant
- Add `ModelPresetConfig` schema for named model presets
- Add `model_presets` dict to `Config` and `model_preset` field to `AgentDefaults`
- Add `resolve_preset()` to return effective model params from preset or defaults
- Add `@model_validator` to reject unknown preset names
- Update `_match_provider()` to use resolved preset model/provider
- Update `make_provider()` and `provider_signature()` to use `resolve_preset()`
- Add `model_preset` property to `AgentLoop` for atomic runtime switching
- Update `AgentLoop.from_config()` to inject a runtime `default` preset
- Wire self-tool to inspect/clear preset state
- Update CLI display strings to show active preset
Both StreamRenderer instantiations in the agent command (single-message
mode and interactive mode) now read bot_name and bot_icon from
config.agents.defaults and forward them to the renderer.
This is the wiring step that makes the schema fields actually take
effect at runtime. With safe defaults of "nanobot" and "🐈", existing
users see no change.
Add show_reasoning config (default: False) to display model
thinking/reasoning content in the TUI during streaming. Reasoning
is emitted via a new emit_reasoning hook on AgentHook, gated by the
channels config. Display uses ✻ prefix with dim italic styling.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Route progress output through the Live's render hook to fix cursor
misalignment that caused content duplication. The root cause was that
progress/reasoning output used a separate Console instance, bypassing
Rich Live's process_renderables hook. Also fixes pre-existing issue
where multiple headers printed per agent turn.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Pop model and context_window_tokens from extra kwargs before
forwarding to __init__, allowing callers like _run_gateway to
pass snapshot-derived values instead of config defaults
- _run_gateway now explicitly passes model/context_window_tokens
from provider_snapshot to preserve pre-refactor behavior
Extract duplicated bus/provider/loop initialization from CLI commands
(serve, _run_gateway, agent) and Nanobot facade into a single
AgentLoop.from_config() classmethod.
- Remove _make_provider() from cli/commands.py and nanobot.py
- Remove inline provider creation in all three CLI entry points
- AgentLoop.from_config() creates MessageBus, calls make_provider(),
and assembles AgentLoop with all standard config-derived parameters
- Supports **extra overrides for callers that need custom args
(e.g. cron_service, session_manager, provider_snapshot_loader)
- Update tests to mock make_provider at nanobot.providers.factory
and add from_config classmethod to _FakeAgentLoop fixtures
This is PR 1/4 of the model-preset feature decomposition.
On Windows, prompt_toolkit produces lone surrogate code points (e.g.
🐈) for emoji input. These propagate through the message bus
and crash at json.dumps() / file write time because surrogates cannot
be encoded as UTF-8.
Extract _sanitize_surrogates() that round-trips through UTF-16 to
reconstruct paired surrogates into real characters (e.g. 🐈
→ 🐈), replacing unpaired surrogates with U+FFFD. Apply it at the CLI
input path and reuse in SafeFileHistory.
The config field was added but never passed from config to AgentLoop.
The value was always falling back to the default (40) regardless of
what was set in config.json.
Now passes tool_hint_max_length through all AgentLoop() call sites:
- nanobot/nanobot.py (main bot)
- nanobot/cli/commands.py (CLI agent, dev, webui commands)
Also adds documentation in docs/configuration.md.
Logout previously claimed to support github-copilot in --help text but had
no registered handler, so `provider logout github-copilot` failed with
"Logout not implemented". Add the handler, sharing token deletion with the
codex flow via `_delete_oauth_files`. Tighten handler-table types, fix the
codex test fixture filename, and cover github-copilot plus the unknown
provider path.
- Implement \
anobot provider logout <provider>\ to clear OAuth credentials.
- Add \_LOGOUT_HANDLERS\ registration mechanism mirroring login.
- Implement logout for \openai-codex\ by deleting local \oauth-cli-kit\ token and lock files.
- Fallback gracefully when attempting to logout from providers lacking local credentials or implementations.
- Fixes#2665
Keep provider retry wait messages on the interactive progress path so they do not fall through as assistant responses.
Co-authored-by: Cursor <cursoragent@cursor.com>
The max_messages config field in AgentDefaults was accepted by the
schema but never threaded through to the actual get_history() calls
in the agent loop. Both call sites in _process_message hardcoded the
default, so sessions with slow or local models accumulated unbounded
history that inflated prompt tokens and caused LLM timeouts.
Changes:
- Add max_messages field to AgentDefaults (default 0 = use built-in
constant, any positive value caps history replay)
- Store the value on AgentLoop and pass it to get_history() when
non-zero
- Wire the config through all three AgentLoop construction sites in
commands.py (gateway, API server, CLI chat)
- 14 focused tests covering schema validation, init storage, history
slicing, boundary alignment, integration wiring, and the
zero/default path
Three failure modes addressed:
1. Model reflects HEARTBEAT.md instructions back as output instead of
executing them ("HEARTBEAT.md has active tasks listed...")
2. Model narrates decision logic ("Best judgment call: stay quiet")
3. Model produces empty output for silence, runner treats it as failure,
finalization retry generates "couldn't produce a final answer" which
gets delivered to the user
Changes:
- Add _is_deliverable() pre-filter in HeartbeatService._tick() that catches
finalization fallback messages and leaked reasoning patterns before they
reach the evaluator
- Wrap Phase 2 task input with a delivery-awareness preamble telling the
model its output goes directly to the user's messaging app
- Add meta-reasoning suppression criterion to evaluator template
No changes to agent/loop.py, runner.py, providers, or config schema.
The old prompt framed cron firing as a "task triggered" status report,
which led the agent to reply with things like "Done ✅ 已提醒
U0AV8BJPV8D 喝水" — exposing the user id and reading like a system log
instead of a friendly reminder. Reword it to instruct the agent to
speak directly to the user and forbid status-style language.
Made-with: Cursor
Capture Slack thread metadata for cron and message-tool deliveries so replies stay in the originating thread, and hydrate first thread mentions with recent Slack context.
Made-with: Cursor
Only mark message-tool deliveries for channel-session recording while cron jobs are running, avoiding duplicate session writes during normal user turns.
Made-with: Cursor
Route heartbeat, cron, and message-tool deliveries through one gateway helper so user-visible proactive messages are available when the channel replies.
Made-with: Cursor
When heartbeat delivers output to a channel (e.g. Telegram), the message
is a raw OutboundMessage that bypasses the channel's session. If the user
replies, their reply enters a different session with no context about the
heartbeat message, so the agent cannot follow through.
This change injects the delivered heartbeat message as an assistant turn
into the target channel's session before publishing the outbound. When
the user replies, the channel session has conversational context.
Handles unified_session mode by resolving to UNIFIED_SESSION_KEY when
enabled, matching the agent loop's own session routing.
No changes to agent/loop.py, session/manager.py, channels, providers,
or config schema — uses existing add_message() and save() APIs.
Extend the existing on_progress callback to carry structured tool-event
payloads alongside the plain-text hint, so channels can render rich
tool execution state (start/finish/error, arguments, results, file
attachments) rather than only the pre-formatted hint string.
Changes
-------
- AgentLoop._tool_event_start_payload() — builds a version-1 start
payload from a ToolCallRequest
- AgentLoop._tool_event_result_extras() — extracts files/embeds from a
tool result dict
- AgentLoop._tool_event_finish_payloads() — maps tool_calls +
tool_results + tool_events from AgentHookContext into finish payloads
- _LoopHook.before_execute_tools() — passes tool_events=[...] to
on_progress together with the existing tool_hint flag
- _LoopHook.after_iteration() — emits a second on_progress call with
the finish payloads once tool results are available
- _bus_progress() — forwards tool_events as _tool_events in OutboundMessage
metadata so channel implementations can read them
- on_progress type widened to Callable[..., Awaitable[None]] on all
public entry points; _cli_progress updated to accept and ignore
tool_events
The contract is additive: callers that only accept (content, *, tool_hint)
continue to work unchanged. Callers that also accept tool_events receive
the structured data.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
On filesystems with write-back caching (rclone VFS, NFS, FUSE mounts)
the OS page cache may buffer recent session writes. If the process is
killed before the cache flushes, the most recent conversation turns are
silently lost — causing the agent to "forget" recent context and
respond to stale history on the next startup.
Changes:
- session/manager.py: add fsync=True option to save() that flushes the
file and its parent directory to durable storage. Add flush_all() that
re-saves every cached session with fsync. Default save() behavior is
unchanged (no fsync) to avoid performance regression in normal
operation.
- cli/commands.py: call agent.sessions.flush_all() in the gateway
shutdown finally block, after stopping heartbeat/cron/channels.
- tests/session/test_session_fsync.py: 8 tests covering fsync flag
behavior, flush_all with empty/multiple/errored sessions, and
data survival across simulated process restart.
- tests/cli/test_commands.py: add sessions attribute to _FakeAgentLoop
so the gateway health endpoint test passes with the new shutdown
flush.
Cron jobs now pass on_progress=_silent to process_direct, matching
the heartbeat pattern. Previously, tool hints and streaming deltas
were published to the user channel via bus during execution, but the
final response could be rejected by evaluate_response — leaving users
with confusing partial output and no conclusion.
Closes#3319
Follow-up to #3212, fully backward compatible:
- Extract the 14-day staleness threshold as `_STALE_THRESHOLD_DAYS` module
constant and pass it into the Phase 1 prompt template as
`{{ stale_threshold_days }}`. The number lived in three places before
(code threshold, prompt instruction, docstring); now there is one.
- Add `DreamConfig.annotate_line_ages` (default True = current behavior)
and propagate it through `Dream.__init__` and the gateway wiring in
cli/commands.py. Gives users a knob to disable the feature without a
code patch if an LLM reacts poorly to the `← Nd` suffix.
- Harden `_annotate_with_ages` against dirty working trees: when HEAD
blob line count disagrees with the working-tree content length, skip
annotation entirely instead of assigning ages to the wrong lines. The
previous `i >= len(ages)` guard only handled one direction of the
mismatch.
- Inline-comment the `max_iterations` 10→15 bump with a pointer to
exp002 so future blame has context.
- Add 4 regression tests: end-to-end `← 30d` reaches prompt, 14/15
threshold boundary, `annotate_line_ages=False` bypasses git entirely
(verified via `assert_not_called`), length-mismatch defense, and
template-var rendering.
Made-with: Cursor
Add a built-in tool that lets the agent inspect and modify its own
runtime state (model, iterations, context window, etc.).
Key features:
- inspect: view current config, usage stats, and subagent status
- modify: adjust parameters at runtime (protected by type/range validation)
- Subagent observability: inspect running subagent tasks (phase,
iteration, tool events, errors) — subagents are no longer a black box
- Watchdog corrects out-of-bounds values on each iteration
- Enabled by default in read-only mode (self_modify: false)
- All changes are in-memory only; restart restores defaults
- Comprehensive test suite (90 tests)
Includes a self-awareness skill (always-on) with progressive disclosure:
SKILL.md for core rules, references/examples.md for detailed scenarios.
Bind the gateway health listener to localhost by default and reduce the probe response to a minimal status payload so accidental public exposure leaks less information.
Made-with: Cursor
Keep the gateway health endpoint patch current with the latest gateway runtime changes, and lock the new HTTP routes in with CLI regression coverage and README guidance.
Made-with: Cursor
