* refactor(agent): defer transcript assembly to runner
Keep persisted history and the fresh turn as explicit inputs until the Runner assembles the provider transcript. Preserve ContextBuilder and direct AgentRunner compatibility while making the save boundary structural.
Refs NAN-81.
* fix(providers): preserve mixed adjacent user content
* refactor(agent): decouple loop from message tool state
* refactor(agent): scope message delivery tracking per run
* refactor(agent): clarify message delivery scope name
This commit implements a progressive refactoring of the tool system to support
plugin discovery, scoped loading, and protocol-driven runtime context injection.
Key changes:
- Add Tool ABC metadata (tool_name, _scopes) and ToolContext dataclass for
dependency injection.
- Introduce ToolLoader with pkgutil-based builtin discovery and
entry_points-based third-party plugin loading.
- Add scope filtering (core/subagent/memory) so different contexts load
appropriate tool sets.
- Introduce ContextAware protocol and RequestContext dataclass to replace
hardcoded per-tool context injection in AgentLoop.
- Add RuntimeState / MutableRuntimeState protocols to decouple MyTool from
AgentLoop.
- Migrate all built-in tools to declare scopes and implement create()/enabled()
hooks.
- Migrate MessageTool, SpawnTool, CronTool, and MyTool to ContextAware.
- Refactor AgentLoop to use ToolLoader and protocol-driven context injection.
- Refactor SubagentManager to use ToolLoader(scope="subagent") with per-run
FileStates isolation.
- Register all built-in tools via pyproject.toml entry_points.
- Add comprehensive tests for loader scopes, entry_points, ContextAware,
subagent tools, and runtime state sync.
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>
* feat(agent): add mid-turn message injection for responsive follow-ups
Allow user messages sent during an active agent turn to be injected
into the running LLM context instead of being queued behind a
per-session lock. Inspired by Claude Code's mid-turn queue drain
mechanism (query.ts:1547-1643).
Key design decisions:
- Messages are injected as natural user messages between iterations,
no tool cancellation or special system prompt needed
- Two drain checkpoints: after tool execution and after final LLM
response ("last-mile" to prevent dropping late arrivals)
- Bounded by MAX_INJECTION_CYCLES (5) to prevent consuming the
iteration budget on rapid follow-ups
- had_injections flag bypasses _sent_in_turn suppression so follow-up
responses are always delivered
Closes#1609
* fix(agent): harden mid-turn injection with streaming fix, bounded queue, and message safety
- Fix streaming protocol violation: Checkpoint 2 now checks for injections
BEFORE calling on_stream_end, passing resuming=True when injections found
so streaming channels (Feishu) don't prematurely finalize the card
- Bound pending queue to maxsize=20 with QueueFull handling
- Add warning log when injection batch exceeds _MAX_INJECTIONS_PER_TURN
- Re-publish leftover queue messages to bus in _dispatch finally block to
prevent silent message loss on early exit (max_iterations, tool_error, cancel)
- Fix PEP 8 blank line before dataclass and logger.info indentation
- Add 12 new tests covering drain, checkpoints, cycle cap, queue routing,
cleanup, and leftover re-publish
When the LLM returns an error (e.g. 429 quota exceeded, stream timeout),
streaming channels silently drop the error message because `_streamed=True`
is set in metadata even though no content was actually streamed.
This change:
- Skips setting `_streamed` when stop_reason is "error", so error messages
go through the normal channel.send() path and reach the user
- Stops appending error content to session history, preventing error
messages from polluting subsequent conversation context
- Exposes stop_reason from _run_agent_loop to enable the above check
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