Nan Gao 4fcb4bc366
feat(subagents): persist and display subagent step history (#3779) (#3845)
* feat(subagents): persist and display subagent step history (#3779)

Capture both assistant turns and tool outputs during subagent execution,
stream them in task_running events, and persist them as subagent.* run
events so the subtask card's step timeline survives a reload.

Backend:
- step_events.py: pure layer (capture_step_message, build_subagent_step,
  subagent_run_event) shared by streaming and persistence
- executor.py: capture ToolMessage outputs, not just AIMessage turns
- worker.py: persist task_* custom events to RunEventStore (category
  "subagent" keeps them out of the thread feed; list_events backfills)

Frontend:
- core/tasks/steps.ts + api.ts: SubtaskStep model, messageToStep,
  eventsToSteps, mergeSteps, fetchSubtaskSteps
- subtask card accumulates live steps and backfills on expand
- carry run_id onto history content messages for the events endpoint

* fix(subagents): show AI turns in subtask card + paginate step backfill (#3779)

Two follow-ups to the subagent step-history feature:

Problem 1 — reload backfill could silently truncate the step timeline because
list_events capped at 500 events (seq-ASC) across the whole run. Add task_id
filtering + an after_seq forward cursor to list_events (all three stores +
abstract base + the /events route), and make fetchSubtaskSteps page through one
task's subagent.step events until a short page. No schema migration: the DB
filter rides the existing run-scoped index via event_metadata["task_id"].

Problem 2 — the card only rendered tool steps, so persisted AI turns were never
shown. Replace toolStepsForDisplay with stepsForDisplay: interleave AI reasoning
turns (with text) and tool steps by message_index, drop blank-text AI turns, and
drop the trailing final-answer AI turn when completed (already shown as result).
Card renders AI steps as muted clamped markdown with a sparkles icon.

Tests: store task_id/after_seq filtering + pagination across memory/db/jsonl,
the /events route forwarding, stepsForDisplay rules, and fetchSubtaskSteps
pagination. Docs updated in both AGENTS.md.

* make format

* fix(subagents): capture full multi-tool step tail, batch step persistence, cap tool-call args (#3779)

Address PR review findings on the subagent step-history feature:

1. executor.py streamed on stream_mode="values" and captured only
   messages[-1] per chunk, so a multi-tool-call turn (ToolNode appends
   one ToolMessage per call in a single super-step) lost all but the last
   tool output in both the live task_running stream and the persisted
   history. Replace with capture_new_step_messages, which walks the
   newly-appended tail (and still re-checks the trailing message on
   no-growth chunks so id-less in-place replacements survive).

2. worker.py persisted each step with the store's low-frequency put()
   (a per-thread advisory lock per call); a deep subagent (max_turns=150)
   emits hundreds of steps on the hot stream loop. Replace with
   _SubagentEventBuffer, which batches via put_batch (flush on terminal
   subagent.end, at FLUSH_THRESHOLD, and in the worker finally).

3. build_subagent_step capped only text; tool_calls[].args were copied
   verbatim, so a large write_file/bash payload produced an unbounded
   subagent.step row. Cap each call's serialized args at
   SUBAGENT_STEP_MAX_CHARS, flagged args_truncated.

Tests updated/added for all three; AGENTS.md refreshed.

* fix(subagents): merge backfill into latest subtask state; reuse message_content_to_text (#3779)

Address the remaining two PR review findings:

4. subtask-card's fetchSubtaskSteps().then(updateSubtask) closed over a
   stale tasks snapshot: a late-resolving backfill wrote setTasks({...stale}),
   clobbering SSE steps/status and sibling subtasks that arrived during the
   fetch. useUpdateSubtask now reads/writes through a tasksRef mirroring the
   latest state (ref-to-latest), and the pure per-subtask transition is
   extracted to core/tasks/subtask-update.ts::computeNextSubtask (unit-tested).

5. step_events._content_to_text duplicated deerflow.utils.messages.
   message_content_to_text; call the shared helper instead (guarding None
   content with 'or ""' so a tool-call-only turn still renders as "").

Tests added for computeNextSubtask and the None-content case; AGENTS.md docs updated.
2026-07-02 07:43:09 +08:00

116 lines
4.0 KiB
Python

"""Abstract interface for run event storage.
RunEventStore is the unified storage interface for run event streams.
Messages (frontend display) and execution traces (debugging/audit) go
through the same interface, distinguished by the ``category`` field.
Implementations:
- MemoryRunEventStore: in-memory dict (development, tests)
- Future: DB-backed store (SQLAlchemy ORM), JSONL file store
"""
from __future__ import annotations
import abc
class RunEventStore(abc.ABC):
"""Run event stream storage interface.
All implementations must guarantee:
1. put() events are retrievable in subsequent queries
2. seq is strictly increasing within the same thread
3. list_messages() only returns category="message" events
4. list_events() returns all events for the specified run
5. Returned dicts match the RunEvent field structure
"""
@abc.abstractmethod
async def put(
self,
*,
thread_id: str,
run_id: str,
event_type: str,
category: str,
content: str | dict = "",
metadata: dict | None = None,
created_at: str | None = None,
) -> dict:
"""Write an event, auto-assign seq, return the complete record."""
@abc.abstractmethod
async def put_batch(self, events: list[dict]) -> list[dict]:
"""Batch-write events. Used by RunJournal flush buffer.
Each dict's keys match put()'s keyword arguments.
Returns complete records with seq assigned.
"""
@abc.abstractmethod
async def list_messages(
self,
thread_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict]:
"""Return displayable messages (category=message) for a thread, ordered by seq ascending.
Supports bidirectional cursor pagination:
- before_seq: return the last ``limit`` records with seq < before_seq (ascending)
- after_seq: return the first ``limit`` records with seq > after_seq (ascending)
- neither: return the latest ``limit`` records (ascending)
"""
@abc.abstractmethod
async def list_events(
self,
thread_id: str,
run_id: str,
*,
event_types: list[str] | None = None,
task_id: str | None = None,
limit: int = 500,
after_seq: int | None = None,
) -> list[dict]:
"""Return the full event stream for a run, ordered by seq ascending.
Optionally filter by ``event_types`` and/or ``task_id`` (matched against
``metadata["task_id"]``). ``after_seq`` is a forward cursor returning the
first ``limit`` records with seq > after_seq, so callers can page through
a single subagent task's events without the run-wide ``limit`` truncating
the tail (#3779).
"""
@abc.abstractmethod
async def list_messages_by_run(
self,
thread_id: str,
run_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict]:
"""Return displayable messages (category=message) for a specific run, ordered by seq ascending.
Supports bidirectional cursor pagination:
- after_seq: return the first ``limit`` records with seq > after_seq (ascending)
- before_seq: return the last ``limit`` records with seq < before_seq (ascending)
- neither: return the latest ``limit`` records (ascending)
"""
@abc.abstractmethod
async def count_messages(self, thread_id: str) -> int:
"""Count displayable messages (category=message) in a thread."""
@abc.abstractmethod
async def delete_by_thread(self, thread_id: str) -> int:
"""Delete all events for a thread. Return the number of deleted events."""
@abc.abstractmethod
async def delete_by_run(self, thread_id: str, run_id: str) -> int:
"""Delete all events for a specific run. Return the number of deleted events."""