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185f5649dd
* feat(persistence): add SQLAlchemy 2.0 async ORM scaffold Introduce a unified database configuration (DatabaseConfig) that controls both the LangGraph checkpointer and the DeerFlow application persistence layer from a single `database:` config section. New modules: - deerflow.config.database_config — Pydantic config with memory/sqlite/postgres backends - deerflow.persistence — async engine lifecycle, DeclarativeBase with to_dict mixin, Alembic skeleton - deerflow.runtime.runs.store — RunStore ABC + MemoryRunStore implementation Gateway integration initializes/tears down the persistence engine in the existing langgraph_runtime() context manager. Legacy checkpointer config is preserved for backward compatibility. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add RunEventStore ABC + MemoryRunEventStore Phase 2-A prerequisite for event storage: adds the unified run event stream interface (RunEventStore) with an in-memory implementation, RunEventsConfig, gateway integration, and comprehensive tests (27 cases). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add ORM models, repositories, DB/JSONL event stores, RunJournal, and API endpoints Phase 2-B: run persistence + event storage + token tracking. - ORM models: RunRow (with token fields), ThreadMetaRow, RunEventRow - RunRepository implements RunStore ABC via SQLAlchemy ORM - ThreadMetaRepository with owner access control - DbRunEventStore with trace content truncation and cursor pagination - JsonlRunEventStore with per-run files and seq recovery from disk - RunJournal (BaseCallbackHandler) captures LLM/tool/lifecycle events, accumulates token usage by caller type, buffers and flushes to store - RunManager now accepts optional RunStore for persistent backing - Worker creates RunJournal, writes human_message, injects callbacks - Gateway deps use factory functions (RunRepository when DB available) - New endpoints: messages, run messages, run events, token-usage - ThreadCreateRequest gains assistant_id field - 92 tests pass (33 new), zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(persistence): add user feedback + follow-up run association Phase 2-C: feedback and follow-up tracking. - FeedbackRow ORM model (rating +1/-1, optional message_id, comment) - FeedbackRepository with CRUD, list_by_run/thread, aggregate stats - Feedback API endpoints: create, list, stats, delete - follow_up_to_run_id in RunCreateRequest (explicit or auto-detected from latest successful run on the thread) - Worker writes follow_up_to_run_id into human_message event metadata - Gateway deps: feedback_repo factory + getter - 17 new tests (14 FeedbackRepository + 3 follow-up association) - 109 total tests pass, zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test+config: comprehensive Phase 2 test coverage + deprecate checkpointer config - config.example.yaml: deprecate standalone checkpointer section, activate unified database:sqlite as default (drives both checkpointer + app data) - New: test_thread_meta_repo.py (14 tests) — full ThreadMetaRepository coverage including check_access owner logic, list_by_owner pagination - Extended test_run_repository.py (+4 tests) — completion preserves fields, list ordering desc, limit, owner_none returns all - Extended test_run_journal.py (+8 tests) — on_chain_error, track_tokens=false, middleware no ai_message, unknown caller tokens, convenience fields, tool_error, non-summarization custom event - Extended test_run_event_store.py (+7 tests) — DB batch seq continuity, make_run_event_store factory (memory/db/jsonl/fallback/unknown) - Extended test_phase2b_integration.py (+4 tests) — create_or_reject persists, follow-up metadata, summarization in history, full DB-backed lifecycle - Fixed DB integration test to use proper fake objects (not MagicMock) for JSON-serializable metadata - 157 total Phase 2 tests pass, zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * config: move default sqlite_dir to .deer-flow/data Keep SQLite databases alongside other DeerFlow-managed data (threads, memory) under the .deer-flow/ directory instead of a top-level ./data folder. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(persistence): remove UTFJSON, use engine-level json_serializer + datetime.now() - Replace custom UTFJSON type with standard sqlalchemy.JSON in all ORM models. Add json_serializer=json.dumps(ensure_ascii=False) to all create_async_engine calls so non-ASCII text (Chinese etc.) is stored as-is in both SQLite and Postgres. - Change ORM datetime defaults from datetime.now(UTC) to datetime.now(), remove UTC imports. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): simplify deps.py with getter factory + inline repos - Replace 6 identical getter functions with _require() factory. - Inline 3 _make_*_repo() factories into langgraph_runtime(), call get_session_factory() once instead of 3 times. - Add thread_meta upsert in start_run (services.py). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(docker): add UV_EXTRAS build arg for optional dependencies Support installing optional dependency groups (e.g. postgres) at Docker build time via UV_EXTRAS build arg: UV_EXTRAS=postgres docker compose build Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(journal): fix flush, token tracking, and consolidate tests RunJournal fixes: - _flush_sync: retain events in buffer when no event loop instead of dropping them; worker's finally block flushes via async flush(). - on_llm_end: add tool_calls filter and caller=="lead_agent" guard for ai_message events; mark message IDs for dedup with record_llm_usage. - worker.py: persist completion data (tokens, message count) to RunStore in finally block. Model factory: - Auto-inject stream_usage=True for BaseChatOpenAI subclasses with custom api_base, so usage_metadata is populated in streaming responses. Test consolidation: - Delete test_phase2b_integration.py (redundant with existing tests). - Move DB-backed lifecycle test into test_run_journal.py. - Add tests for stream_usage injection in test_model_factory.py. - Clean up executor/task_tool dead journal references. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): widen content type to str|dict in all store backends Allow event content to be a dict (for structured OpenAI-format messages) in addition to plain strings. Dict values are JSON-serialized for the DB backend and deserialized on read; memory and JSONL backends handle dicts natively. Trace truncation now serializes dicts to JSON before measuring. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(events): use metadata flag instead of heuristic for dict content detection Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(converters): add LangChain-to-OpenAI message format converters Pure functions langchain_to_openai_message, langchain_to_openai_completion, langchain_messages_to_openai, and _infer_finish_reason for converting LangChain BaseMessage objects to OpenAI Chat Completions format, used by RunJournal for event storage. 15 unit tests added. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(converters): handle empty list content as null, clean up test Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): human_message content uses OpenAI user message format Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): ai_message uses OpenAI format, add ai_tool_call message event - ai_message content now uses {"role": "assistant", "content": "..."} format - New ai_tool_call message event emitted when lead_agent LLM responds with tool_calls - ai_tool_call uses langchain_to_openai_message converter for consistent format - Both events include finish_reason in metadata ("stop" or "tool_calls") Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): add tool_result message event with OpenAI tool message format Cache tool_call_id from on_tool_start keyed by run_id as fallback for on_tool_end, then emit a tool_result message event (role=tool, tool_call_id, content) after each successful tool completion. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): summary content uses OpenAI system message format Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): replace llm_start/llm_end with llm_request/llm_response in OpenAI format Add on_chat_model_start to capture structured prompt messages as llm_request events. Replace llm_end trace events with llm_response using OpenAI Chat Completions format. Track llm_call_index to pair request/response events. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(events): add record_middleware method for middleware trace events Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test(events): add full run sequence integration test for OpenAI content format Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(events): align message events with checkpoint format and add middleware tag injection - Message events (ai_message, ai_tool_call, tool_result, human_message) now use BaseMessage.model_dump() format, matching LangGraph checkpoint values.messages - on_tool_end extracts tool_call_id/name/status from ToolMessage objects - on_tool_error now emits tool_result message events with error status - record_middleware uses middleware:{tag} event_type and middleware category - Summarization custom events use middleware:summarize category - TitleMiddleware injects middleware:title tag via get_config() inheritance - SummarizationMiddleware model bound with middleware:summarize tag - Worker writes human_message using HumanMessage.model_dump() Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(threads): switch search endpoint to threads_meta table and sync title - POST /api/threads/search now queries threads_meta table directly, removing the two-phase Store + Checkpointer scan approach - Add ThreadMetaRepository.search() with metadata/status filters - Add ThreadMetaRepository.update_display_name() for title sync - Worker syncs checkpoint title to threads_meta.display_name on run completion - Map display_name to values.title in search response for API compatibility Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat(threads): history endpoint reads messages from event store - POST /api/threads/{thread_id}/history now combines two data sources: checkpointer for checkpoint_id, metadata, title, thread_data; event store for messages (complete history, not truncated by summarization) - Strip internal LangGraph metadata keys from response - Remove full channel_values serialization in favor of selective fields Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: remove duplicate optional-dependencies header in pyproject.toml Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(middleware): pass tagged config to TitleMiddleware ainvoke call Without the config, the middleware:title tag was not injected, causing the LLM response to be recorded as a lead_agent ai_message in run_events. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: resolve merge conflict in .env.example Keep both DATABASE_URL (from persistence-scaffold) and WECOM credentials (from main) after the merge. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address review feedback on PR #1851 - Fix naive datetime.now() → datetime.now(UTC) in all ORM models - Fix seq race condition in DbRunEventStore.put() with FOR UPDATE and UNIQUE(thread_id, seq) constraint - Encapsulate _store access in RunManager.update_run_completion() - Deduplicate _store.put() logic in RunManager via _persist_to_store() - Add update_run_completion to RunStore ABC + MemoryRunStore - Wire follow_up_to_run_id through the full create path - Add error recovery to RunJournal._flush_sync() lost-event scenario - Add migration note for search_threads breaking change - Fix test_checkpointer_none_fix mock to set database=None Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: update uv.lock Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address 22 review comments from CodeQL, Copilot, and Code Quality Bug fixes: - Sanitize log params to prevent log injection (CodeQL) - Reset threads_meta.status to idle/error when run completes - Attach messages only to latest checkpoint in /history response - Write threads_meta on POST /threads so new threads appear in search Lint fixes: - Remove unused imports (journal.py, migrations/env.py, test_converters.py) - Convert lambda to named function (engine.py, Ruff E731) - Remove unused logger definitions in repos (Ruff F841) - Add logging to JSONL decode errors and empty except blocks - Separate assert side-effects in tests (CodeQL) - Remove unused local variables in tests (Ruff F841) - Fix max_trace_content truncation to use byte length, not char length Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: apply ruff format to persistence and runtime files Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Potential fix for pull request finding 'Statement has no effect' Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> * refactor(runtime): introduce RunContext to reduce run_agent parameter bloat Extract checkpointer, store, event_store, run_events_config, thread_meta_repo, and follow_up_to_run_id into a frozen RunContext dataclass. Add get_run_context() in deps.py to build the base context from app.state singletons. start_run() uses dataclasses.replace() to enrich per-run fields before passing ctx to run_agent. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): move sanitize_log_param to app/gateway/utils.py Extract the log-injection sanitizer from routers/threads.py into a shared utils module and rename to sanitize_log_param (public API). Eliminates the reverse service → router import in services.py. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * perf: use SQL aggregation for feedback stats and thread token usage Replace Python-side counting in FeedbackRepository.aggregate_by_run with a single SELECT COUNT/SUM query. Add RunStore.aggregate_tokens_by_thread abstract method with SQL GROUP BY implementation in RunRepository and Python fallback in MemoryRunStore. Simplify the thread_token_usage endpoint to delegate to the new method, eliminating the limit=10000 truncation risk. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: annotate DbRunEventStore.put() as low-frequency path Add docstring clarifying that put() opens a per-call transaction with FOR UPDATE and should only be used for infrequent writes (currently just the initial human_message event). High-throughput callers should use put_batch() instead. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(threads): fall back to Store search when ThreadMetaRepository is unavailable When database.backend=memory (default) or no SQL session factory is configured, search_threads now queries the LangGraph Store instead of returning 503. Returns empty list if neither Store nor repo is available. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(persistence): introduce ThreadMetaStore ABC for backend-agnostic thread metadata Add ThreadMetaStore abstract base class with create/get/search/update/delete interface. ThreadMetaRepository (SQL) now inherits from it. New MemoryThreadMetaStore wraps LangGraph BaseStore for memory-mode deployments. deps.py now always provides a non-None thread_meta_repo, eliminating all `if thread_meta_repo is not None` guards in services.py, worker.py, and routers/threads.py. search_threads no longer needs a Store fallback branch. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(history): read messages from checkpointer instead of RunEventStore The /history endpoint now reads messages directly from the checkpointer's channel_values (the authoritative source) instead of querying RunEventStore.list_messages(). The RunEventStore API is preserved for other consumers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(persistence): address new Copilot review comments - feedback.py: validate thread_id/run_id before deleting feedback - jsonl.py: add path traversal protection with ID validation - run_repo.py: parse `before` to datetime for PostgreSQL compat - thread_meta_repo.py: fix pagination when metadata filter is active - database_config.py: use resolve_path for sqlite_dir consistency Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Implement skill self-evolution and skill_manage flow (#1874) * chore: ignore .worktrees directory * Add skill_manage self-evolution flow * Fix CI regressions for skill_manage * Address PR review feedback for skill evolution * fix(skill-evolution): preserve history on delete * fix(skill-evolution): tighten scanner fallbacks * docs: add skill_manage e2e evidence screenshot * fix(skill-manage): avoid blocking fs ops in session runtime --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com> * fix(config): resolve sqlite_dir relative to CWD, not Paths.base_dir resolve_path() resolves relative to Paths.base_dir (.deer-flow), which double-nested the path to .deer-flow/.deer-flow/data/app.db. Use Path.resolve() (CWD-relative) instead. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * Feature/feishu receive file (#1608) * feat(feishu): add channel file materialization hook for inbound messages - Introduce Channel.receive_file(msg, thread_id) as a base method for file materialization; default is no-op. - Implement FeishuChannel.receive_file to download files/images from Feishu messages, save to sandbox, and inject virtual paths into msg.text. - Update ChannelManager to call receive_file for any channel if msg.files is present, enabling downstream model access to user-uploaded files. - No impact on Slack/Telegram or other channels (they inherit the default no-op). * style(backend): format code with ruff for lint compliance - Auto-formatted packages/harness/deerflow/agents/factory.py and tests/test_create_deerflow_agent.py using `ruff format` - Ensured both files conform to project linting standards - Fixes CI lint check failures caused by code style issues * fix(feishu): handle file write operation asynchronously to prevent blocking * fix(feishu): rename GetMessageResourceRequest to _GetMessageResourceRequest and remove redundant code * test(feishu): add tests for receive_file method and placeholder replacement * fix(manager): remove unnecessary type casting for channel retrieval * fix(feishu): update logging messages to reflect resource handling instead of image * fix(feishu): sanitize filename by replacing invalid characters in file uploads * fix(feishu): improve filename sanitization and reorder image key handling in message processing * fix(feishu): add thread lock to prevent filename conflicts during file downloads * fix(test): correct bad merge in test_feishu_parser.py * chore: run ruff and apply formatting cleanup fix(feishu): preserve rich-text attachment order and improve fallback filename handling * fix(docker): restore gateway env vars and fix langgraph empty arg issue (#1915) Two production docker-compose.yaml bugs prevent `make up` from working: 1. Gateway missing DEER_FLOW_CONFIG_PATH and DEER_FLOW_EXTENSIONS_CONFIG_PATH environment overrides. Added infb2d99f(#1836) but accidentally reverted byca2fb95(#1847). Without them, gateway reads host paths from .env via env_file, causing FileNotFoundError inside the container. 2. Langgraph command fails when LANGGRAPH_ALLOW_BLOCKING is unset (default). Empty $${allow_blocking} inserts a bare space between flags, causing ' --no-reload' to be parsed as unexpected extra argument. Fix by building args string first and conditionally appending --allow-blocking. Co-authored-by: cooper <cooperfu@tencent.com> * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities (#1904) * fix(frontend): resolve invalid HTML nesting and tabnabbing vulnerabilities Fix `<button>` inside `<a>` invalid HTML in artifact components and add missing `noopener,noreferrer` to `window.open` calls to prevent reverse tabnabbing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(frontend): address Copilot review on tabnabbing and double-tab-open Remove redundant parent onClick on web_fetch ChainOfThoughtStep to prevent opening two tabs on link click, and explicitly null out window.opener after window.open() for defensive tabnabbing hardening. --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * refactor(persistence): organize entities into per-entity directories Restructure the persistence layer from horizontal "models/ + repositories/" split into vertical entity-aligned directories. Each entity (thread_meta, run, feedback) now owns its ORM model, abstract interface (where applicable), and concrete implementations under a single directory with an aggregating __init__.py for one-line imports. Layout: persistence/thread_meta/{base,model,sql,memory}.py persistence/run/{model,sql}.py persistence/feedback/{model,sql}.py models/__init__.py is kept as a facade so Alembic autogenerate continues to discover all ORM tables via Base.metadata. RunEventRow remains under models/run_event.py because its storage implementation lives in runtime/events/store/db.py and has no matching repository directory. The repositories/ directory is removed entirely. All call sites in gateway/deps.py and tests are updated to import from the new entity packages, e.g.: from deerflow.persistence.thread_meta import ThreadMetaRepository from deerflow.persistence.run import RunRepository from deerflow.persistence.feedback import FeedbackRepository Full test suite passes (1690 passed, 14 skipped). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix(gateway): sync thread rename and delete through ThreadMetaStore The POST /threads/{id}/state endpoint previously synced title changes only to the LangGraph Store via _store_upsert. In sqlite mode the search endpoint reads from the ThreadMetaRepository SQL table, so renames never appeared in /threads/search until the next agent run completed (worker.py syncs title from checkpoint to thread_meta in its finally block). Likewise the DELETE /threads/{id} endpoint cleaned up the filesystem, Store, and checkpointer but left the threads_meta row orphaned in sqlite, so deleted threads kept appearing in /threads/search. Fix both endpoints by routing through the ThreadMetaStore abstraction which already has the correct sqlite/memory implementations wired up by deps.py. The rename path now calls update_display_name() and the delete path calls delete() — both work uniformly across backends. Verified end-to-end with curl in gateway mode against sqlite backend. Existing test suite (1690 passed) and focused router/repo tests pass. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * refactor(gateway): route all thread metadata access through ThreadMetaStore Following the rename/delete bug fix in PR1, migrate the remaining direct LangGraph Store reads/writes in the threads router and services to the ThreadMetaStore abstraction so that the sqlite and memory backends behave identically and the legacy dual-write paths can be removed. Migrated endpoints (threads.py): - create_thread: idempotency check + write now use thread_meta_repo.get/create instead of dual-writing the LangGraph Store and the SQL row. - get_thread: reads from thread_meta_repo.get; the checkpoint-only fallback for legacy threads is preserved. - patch_thread: replaced _store_get/_store_put with thread_meta_repo.update_metadata. - delete_thread_data: dropped the legacy store.adelete; thread_meta_repo.delete already covers it. Removed dead code (services.py): - _upsert_thread_in_store — redundant with the immediately following thread_meta_repo.create() call. - _sync_thread_title_after_run — worker.py's finally block already syncs the title via thread_meta_repo.update_display_name() after each run. Removed dead code (threads.py): - _store_get / _store_put / _store_upsert helpers (no remaining callers). - THREADS_NS constant. - get_store import (router no longer touches the LangGraph Store directly). New abstract method: - ThreadMetaStore.update_metadata(thread_id, metadata) merges metadata into the thread's metadata field. Implemented in both ThreadMetaRepository (SQL, read-modify-write inside one session) and MemoryThreadMetaStore. Three new unit tests cover merge / empty / nonexistent behaviour. Net change: -134 lines. Full test suite: 1693 passed, 14 skipped. Verified end-to-end with curl in gateway mode against sqlite backend (create / patch / get / rename / search / delete). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> Co-authored-by: DanielWalnut <45447813+hetaoBackend@users.noreply.github.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: JilongSun <965640067@qq.com> Co-authored-by: jie <49781832+stan-fu@users.noreply.github.com> Co-authored-by: cooper <cooperfu@tencent.com> Co-authored-by: yangzheli <43645580+yangzheli@users.noreply.github.com>
316 lines
13 KiB
Python
316 lines
13 KiB
Python
"""Runs endpoints — create, stream, wait, cancel.
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Implements the LangGraph Platform runs API on top of
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:class:`deerflow.agents.runs.RunManager` and
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:class:`deerflow.agents.stream_bridge.StreamBridge`.
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SSE format is aligned with the LangGraph Platform protocol so that
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the ``useStream`` React hook from ``@langchain/langgraph-sdk/react``
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works without modification.
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"""
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from __future__ import annotations
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import asyncio
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import logging
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from typing import Any, Literal
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from fastapi import APIRouter, HTTPException, Query, Request
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from fastapi.responses import Response, StreamingResponse
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from pydantic import BaseModel, Field
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from app.gateway.deps import get_checkpointer, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
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from app.gateway.services import sse_consumer, start_run
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from deerflow.runtime import RunRecord, serialize_channel_values
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/threads", tags=["runs"])
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# ---------------------------------------------------------------------------
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# Request / response models
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# ---------------------------------------------------------------------------
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class RunCreateRequest(BaseModel):
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assistant_id: str | None = Field(default=None, description="Agent / assistant to use")
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input: dict[str, Any] | None = Field(default=None, description="Graph input (e.g. {messages: [...]})")
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command: dict[str, Any] | None = Field(default=None, description="LangGraph Command")
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metadata: dict[str, Any] | None = Field(default=None, description="Run metadata")
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config: dict[str, Any] | None = Field(default=None, description="RunnableConfig overrides")
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context: dict[str, Any] | None = Field(default=None, description="DeerFlow context overrides (model_name, thinking_enabled, etc.)")
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webhook: str | None = Field(default=None, description="Completion callback URL")
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checkpoint_id: str | None = Field(default=None, description="Resume from checkpoint")
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checkpoint: dict[str, Any] | None = Field(default=None, description="Full checkpoint object")
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interrupt_before: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt before")
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interrupt_after: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt after")
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stream_mode: list[str] | str | None = Field(default=None, description="Stream mode(s)")
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stream_subgraphs: bool = Field(default=False, description="Include subgraph events")
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stream_resumable: bool | None = Field(default=None, description="SSE resumable mode")
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on_disconnect: Literal["cancel", "continue"] = Field(default="cancel", description="Behaviour on SSE disconnect")
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on_completion: Literal["delete", "keep"] = Field(default="keep", description="Delete temp thread on completion")
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multitask_strategy: Literal["reject", "rollback", "interrupt", "enqueue"] = Field(default="reject", description="Concurrency strategy")
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after_seconds: float | None = Field(default=None, description="Delayed execution")
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if_not_exists: Literal["reject", "create"] = Field(default="create", description="Thread creation policy")
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feedback_keys: list[str] | None = Field(default=None, description="LangSmith feedback keys")
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follow_up_to_run_id: str | None = Field(default=None, description="Run ID this message follows up on. Auto-detected from latest successful run if not provided.")
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class RunResponse(BaseModel):
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run_id: str
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thread_id: str
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assistant_id: str | None = None
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status: str
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metadata: dict[str, Any] = Field(default_factory=dict)
|
|
kwargs: dict[str, Any] = Field(default_factory=dict)
|
|
multitask_strategy: str = "reject"
|
|
created_at: str = ""
|
|
updated_at: str = ""
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Helpers
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
def _record_to_response(record: RunRecord) -> RunResponse:
|
|
return RunResponse(
|
|
run_id=record.run_id,
|
|
thread_id=record.thread_id,
|
|
assistant_id=record.assistant_id,
|
|
status=record.status.value,
|
|
metadata=record.metadata,
|
|
kwargs=record.kwargs,
|
|
multitask_strategy=record.multitask_strategy,
|
|
created_at=record.created_at,
|
|
updated_at=record.updated_at,
|
|
)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Endpoints
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
@router.post("/{thread_id}/runs", response_model=RunResponse)
|
|
async def create_run(thread_id: str, body: RunCreateRequest, request: Request) -> RunResponse:
|
|
"""Create a background run (returns immediately)."""
|
|
record = await start_run(body, thread_id, request)
|
|
return _record_to_response(record)
|
|
|
|
|
|
@router.post("/{thread_id}/runs/stream")
|
|
async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -> StreamingResponse:
|
|
"""Create a run and stream events via SSE.
|
|
|
|
The response includes a ``Content-Location`` header with the run's
|
|
resource URL, matching the LangGraph Platform protocol. The
|
|
``useStream`` React hook uses this to extract run metadata.
|
|
"""
|
|
bridge = get_stream_bridge(request)
|
|
run_mgr = get_run_manager(request)
|
|
record = await start_run(body, thread_id, request)
|
|
|
|
return StreamingResponse(
|
|
sse_consumer(bridge, record, request, run_mgr),
|
|
media_type="text/event-stream",
|
|
headers={
|
|
"Cache-Control": "no-cache",
|
|
"Connection": "keep-alive",
|
|
"X-Accel-Buffering": "no",
|
|
# LangGraph Platform includes run metadata in this header.
|
|
# The SDK uses a greedy regex to extract the run id from this path,
|
|
# so it must point at the canonical run resource without extra suffixes.
|
|
"Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}",
|
|
},
|
|
)
|
|
|
|
|
|
@router.post("/{thread_id}/runs/wait", response_model=dict)
|
|
async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) -> dict:
|
|
"""Create a run and block until it completes, returning the final state."""
|
|
record = await start_run(body, thread_id, request)
|
|
|
|
if record.task is not None:
|
|
try:
|
|
await record.task
|
|
except asyncio.CancelledError:
|
|
pass
|
|
|
|
checkpointer = get_checkpointer(request)
|
|
config = {"configurable": {"thread_id": thread_id}}
|
|
try:
|
|
checkpoint_tuple = await checkpointer.aget_tuple(config)
|
|
if checkpoint_tuple is not None:
|
|
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
|
|
channel_values = checkpoint.get("channel_values", {})
|
|
return serialize_channel_values(channel_values)
|
|
except Exception:
|
|
logger.exception("Failed to fetch final state for run %s", record.run_id)
|
|
|
|
return {"status": record.status.value, "error": record.error}
|
|
|
|
|
|
@router.get("/{thread_id}/runs", response_model=list[RunResponse])
|
|
async def list_runs(thread_id: str, request: Request) -> list[RunResponse]:
|
|
"""List all runs for a thread."""
|
|
run_mgr = get_run_manager(request)
|
|
records = await run_mgr.list_by_thread(thread_id)
|
|
return [_record_to_response(r) for r in records]
|
|
|
|
|
|
@router.get("/{thread_id}/runs/{run_id}", response_model=RunResponse)
|
|
async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
|
|
"""Get details of a specific run."""
|
|
run_mgr = get_run_manager(request)
|
|
record = run_mgr.get(run_id)
|
|
if record is None or record.thread_id != thread_id:
|
|
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
|
|
return _record_to_response(record)
|
|
|
|
|
|
@router.post("/{thread_id}/runs/{run_id}/cancel")
|
|
async def cancel_run(
|
|
thread_id: str,
|
|
run_id: str,
|
|
request: Request,
|
|
wait: bool = Query(default=False, description="Block until run completes after cancel"),
|
|
action: Literal["interrupt", "rollback"] = Query(default="interrupt", description="Cancel action"),
|
|
) -> Response:
|
|
"""Cancel a running or pending run.
|
|
|
|
- action=interrupt: Stop execution, keep current checkpoint (can be resumed)
|
|
- action=rollback: Stop execution, revert to pre-run checkpoint state
|
|
- wait=true: Block until the run fully stops, return 204
|
|
- wait=false: Return immediately with 202
|
|
"""
|
|
run_mgr = get_run_manager(request)
|
|
record = run_mgr.get(run_id)
|
|
if record is None or record.thread_id != thread_id:
|
|
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
|
|
|
|
cancelled = await run_mgr.cancel(run_id, action=action)
|
|
if not cancelled:
|
|
raise HTTPException(
|
|
status_code=409,
|
|
detail=f"Run {run_id} is not cancellable (status: {record.status.value})",
|
|
)
|
|
|
|
if wait and record.task is not None:
|
|
try:
|
|
await record.task
|
|
except asyncio.CancelledError:
|
|
pass
|
|
return Response(status_code=204)
|
|
|
|
return Response(status_code=202)
|
|
|
|
|
|
@router.get("/{thread_id}/runs/{run_id}/join")
|
|
async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingResponse:
|
|
"""Join an existing run's SSE stream."""
|
|
bridge = get_stream_bridge(request)
|
|
run_mgr = get_run_manager(request)
|
|
record = run_mgr.get(run_id)
|
|
if record is None or record.thread_id != thread_id:
|
|
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
|
|
|
|
return StreamingResponse(
|
|
sse_consumer(bridge, record, request, run_mgr),
|
|
media_type="text/event-stream",
|
|
headers={
|
|
"Cache-Control": "no-cache",
|
|
"Connection": "keep-alive",
|
|
"X-Accel-Buffering": "no",
|
|
},
|
|
)
|
|
|
|
|
|
@router.api_route("/{thread_id}/runs/{run_id}/stream", methods=["GET", "POST"], response_model=None)
|
|
async def stream_existing_run(
|
|
thread_id: str,
|
|
run_id: str,
|
|
request: Request,
|
|
action: Literal["interrupt", "rollback"] | None = Query(default=None, description="Cancel action"),
|
|
wait: int = Query(default=0, description="Block until cancelled (1) or return immediately (0)"),
|
|
):
|
|
"""Join an existing run's SSE stream (GET), or cancel-then-stream (POST).
|
|
|
|
The LangGraph SDK's ``joinStream`` and ``useStream`` stop button both use
|
|
``POST`` to this endpoint. When ``action=interrupt`` or ``action=rollback``
|
|
is present the run is cancelled first; the response then streams any
|
|
remaining buffered events so the client observes a clean shutdown.
|
|
"""
|
|
run_mgr = get_run_manager(request)
|
|
record = run_mgr.get(run_id)
|
|
if record is None or record.thread_id != thread_id:
|
|
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
|
|
|
|
# Cancel if an action was requested (stop-button / interrupt flow)
|
|
if action is not None:
|
|
cancelled = await run_mgr.cancel(run_id, action=action)
|
|
if cancelled and wait and record.task is not None:
|
|
try:
|
|
await record.task
|
|
except (asyncio.CancelledError, Exception):
|
|
pass
|
|
return Response(status_code=204)
|
|
|
|
bridge = get_stream_bridge(request)
|
|
return StreamingResponse(
|
|
sse_consumer(bridge, record, request, run_mgr),
|
|
media_type="text/event-stream",
|
|
headers={
|
|
"Cache-Control": "no-cache",
|
|
"Connection": "keep-alive",
|
|
"X-Accel-Buffering": "no",
|
|
},
|
|
)
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Messages / Events / Token usage endpoints
|
|
# ---------------------------------------------------------------------------
|
|
|
|
|
|
@router.get("/{thread_id}/messages")
|
|
async def list_thread_messages(
|
|
thread_id: str,
|
|
request: Request,
|
|
limit: int = Query(default=50, le=200),
|
|
before_seq: int | None = Query(default=None),
|
|
after_seq: int | None = Query(default=None),
|
|
) -> list[dict]:
|
|
"""Return displayable messages for a thread (across all runs)."""
|
|
event_store = get_run_event_store(request)
|
|
return await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq)
|
|
|
|
|
|
@router.get("/{thread_id}/runs/{run_id}/messages")
|
|
async def list_run_messages(thread_id: str, run_id: str, request: Request) -> list[dict]:
|
|
"""Return displayable messages for a specific run."""
|
|
event_store = get_run_event_store(request)
|
|
return await event_store.list_messages_by_run(thread_id, run_id)
|
|
|
|
|
|
@router.get("/{thread_id}/runs/{run_id}/events")
|
|
async def list_run_events(
|
|
thread_id: str,
|
|
run_id: str,
|
|
request: Request,
|
|
event_types: str | None = Query(default=None),
|
|
limit: int = Query(default=500, le=2000),
|
|
) -> list[dict]:
|
|
"""Return the full event stream for a run (debug/audit)."""
|
|
event_store = get_run_event_store(request)
|
|
types = event_types.split(",") if event_types else None
|
|
return await event_store.list_events(thread_id, run_id, event_types=types, limit=limit)
|
|
|
|
|
|
@router.get("/{thread_id}/token-usage")
|
|
async def thread_token_usage(thread_id: str, request: Request) -> dict:
|
|
"""Thread-level token usage aggregation."""
|
|
run_store = get_run_store(request)
|
|
agg = await run_store.aggregate_tokens_by_thread(thread_id)
|
|
return {"thread_id": thread_id, **agg}
|