mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-05-23 08:25:57 +00:00
feat(persistence): add unified persistence layer with event store, token tracking, and feedback (#1930)
* 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>
This commit is contained in:
rayhpeng
@@ -0,0 +1,13 @@
|
||||
"""DeerFlow application persistence layer (SQLAlchemy 2.0 async ORM).
|
||||
|
||||
This module manages DeerFlow's own application data -- runs metadata,
|
||||
thread ownership, cron jobs, users. It is completely separate from
|
||||
LangGraph's checkpointer, which manages graph execution state.
|
||||
|
||||
Usage:
|
||||
from deerflow.persistence import init_engine, close_engine, get_session_factory
|
||||
"""
|
||||
|
||||
from deerflow.persistence.engine import close_engine, get_engine, get_session_factory, init_engine
|
||||
|
||||
__all__ = ["close_engine", "get_engine", "get_session_factory", "init_engine"]
|
||||
@@ -0,0 +1,40 @@
|
||||
"""SQLAlchemy declarative base with automatic to_dict support.
|
||||
|
||||
All DeerFlow ORM models inherit from this Base. It provides a generic
|
||||
to_dict() method via SQLAlchemy's inspect() so individual models don't
|
||||
need to write their own serialization logic.
|
||||
|
||||
LangGraph's checkpointer tables are NOT managed by this Base.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from sqlalchemy import inspect as sa_inspect
|
||||
from sqlalchemy.orm import DeclarativeBase
|
||||
|
||||
|
||||
class Base(DeclarativeBase):
|
||||
"""Base class for all DeerFlow ORM models.
|
||||
|
||||
Provides:
|
||||
- Automatic to_dict() via SQLAlchemy column inspection.
|
||||
- Standard __repr__() showing all column values.
|
||||
"""
|
||||
|
||||
def to_dict(self, *, exclude: set[str] | None = None) -> dict:
|
||||
"""Convert ORM instance to plain dict.
|
||||
|
||||
Uses SQLAlchemy's inspect() to iterate mapped column attributes.
|
||||
|
||||
Args:
|
||||
exclude: Optional set of column keys to omit.
|
||||
|
||||
Returns:
|
||||
Dict of {column_key: value} for all mapped columns.
|
||||
"""
|
||||
exclude = exclude or set()
|
||||
return {c.key: getattr(self, c.key) for c in sa_inspect(type(self)).mapper.column_attrs if c.key not in exclude}
|
||||
|
||||
def __repr__(self) -> str:
|
||||
cols = ", ".join(f"{c.key}={getattr(self, c.key)!r}" for c in sa_inspect(type(self)).mapper.column_attrs)
|
||||
return f"{type(self).__name__}({cols})"
|
||||
@@ -0,0 +1,166 @@
|
||||
"""Async SQLAlchemy engine lifecycle management.
|
||||
|
||||
Initializes at Gateway startup, provides session factory for
|
||||
repositories, disposes at shutdown.
|
||||
|
||||
When database.backend="memory", init_engine is a no-op and
|
||||
get_session_factory() returns None. Repositories must check for
|
||||
None and fall back to in-memory implementations.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
|
||||
from sqlalchemy.ext.asyncio import AsyncEngine, AsyncSession, async_sessionmaker, create_async_engine
|
||||
|
||||
|
||||
def _json_serializer(obj: object) -> str:
|
||||
"""JSON serializer with ensure_ascii=False for Chinese character support."""
|
||||
return json.dumps(obj, ensure_ascii=False)
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_engine: AsyncEngine | None = None
|
||||
_session_factory: async_sessionmaker[AsyncSession] | None = None
|
||||
|
||||
|
||||
async def _auto_create_postgres_db(url: str) -> None:
|
||||
"""Connect to the ``postgres`` maintenance DB and CREATE DATABASE.
|
||||
|
||||
The target database name is extracted from *url*. The connection is
|
||||
made to the default ``postgres`` database on the same server using
|
||||
``AUTOCOMMIT`` isolation (CREATE DATABASE cannot run inside a
|
||||
transaction).
|
||||
"""
|
||||
from sqlalchemy import text
|
||||
from sqlalchemy.engine.url import make_url
|
||||
|
||||
parsed = make_url(url)
|
||||
db_name = parsed.database
|
||||
if not db_name:
|
||||
raise ValueError("Cannot auto-create database: no database name in URL")
|
||||
|
||||
# Connect to the default 'postgres' database to issue CREATE DATABASE
|
||||
maint_url = parsed.set(database="postgres")
|
||||
maint_engine = create_async_engine(maint_url, isolation_level="AUTOCOMMIT")
|
||||
try:
|
||||
async with maint_engine.connect() as conn:
|
||||
await conn.execute(text(f'CREATE DATABASE "{db_name}"'))
|
||||
logger.info("Auto-created PostgreSQL database: %s", db_name)
|
||||
finally:
|
||||
await maint_engine.dispose()
|
||||
|
||||
|
||||
async def init_engine(
|
||||
backend: str,
|
||||
*,
|
||||
url: str = "",
|
||||
echo: bool = False,
|
||||
pool_size: int = 5,
|
||||
sqlite_dir: str = "",
|
||||
) -> None:
|
||||
"""Create the async engine and session factory, then auto-create tables.
|
||||
|
||||
Args:
|
||||
backend: "memory", "sqlite", or "postgres".
|
||||
url: SQLAlchemy async URL (for sqlite/postgres).
|
||||
echo: Echo SQL to log.
|
||||
pool_size: Postgres connection pool size.
|
||||
sqlite_dir: Directory to create for SQLite (ensured to exist).
|
||||
"""
|
||||
global _engine, _session_factory
|
||||
|
||||
if backend == "memory":
|
||||
logger.info("Persistence backend=memory -- ORM engine not initialized")
|
||||
return
|
||||
|
||||
if backend == "postgres":
|
||||
try:
|
||||
import asyncpg # noqa: F401
|
||||
except ImportError:
|
||||
raise ImportError("database.backend is set to 'postgres' but asyncpg is not installed.\nInstall it with:\n uv sync --extra postgres\nOr switch to backend: sqlite in config.yaml for single-node deployment.") from None
|
||||
|
||||
if backend == "sqlite":
|
||||
import os
|
||||
|
||||
os.makedirs(sqlite_dir or ".", exist_ok=True)
|
||||
_engine = create_async_engine(url, echo=echo, json_serializer=_json_serializer)
|
||||
elif backend == "postgres":
|
||||
_engine = create_async_engine(
|
||||
url,
|
||||
echo=echo,
|
||||
pool_size=pool_size,
|
||||
pool_pre_ping=True,
|
||||
json_serializer=_json_serializer,
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"Unknown persistence backend: {backend!r}")
|
||||
|
||||
_session_factory = async_sessionmaker(_engine, expire_on_commit=False)
|
||||
|
||||
# Auto-create tables (dev convenience). Production should use Alembic.
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
# Import all models so Base.metadata discovers them.
|
||||
# When no models exist yet (scaffolding phase), this is a no-op.
|
||||
try:
|
||||
import deerflow.persistence.models # noqa: F401
|
||||
except ImportError:
|
||||
# Models package not yet available — tables won't be auto-created.
|
||||
# This is expected during initial scaffolding or minimal installs.
|
||||
logger.debug("deerflow.persistence.models not found; skipping auto-create tables")
|
||||
|
||||
try:
|
||||
async with _engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
except Exception as exc:
|
||||
if backend == "postgres" and "does not exist" in str(exc):
|
||||
# Database not yet created — attempt to auto-create it, then retry.
|
||||
await _auto_create_postgres_db(url)
|
||||
# Rebuild engine against the now-existing database
|
||||
await _engine.dispose()
|
||||
_engine = create_async_engine(url, echo=echo, pool_size=pool_size, pool_pre_ping=True, json_serializer=_json_serializer)
|
||||
_session_factory = async_sessionmaker(_engine, expire_on_commit=False)
|
||||
async with _engine.begin() as conn:
|
||||
await conn.run_sync(Base.metadata.create_all)
|
||||
else:
|
||||
raise
|
||||
|
||||
logger.info("Persistence engine initialized: backend=%s", backend)
|
||||
|
||||
|
||||
async def init_engine_from_config(config) -> None:
|
||||
"""Convenience: init engine from a DatabaseConfig object."""
|
||||
if config.backend == "memory":
|
||||
await init_engine("memory")
|
||||
return
|
||||
await init_engine(
|
||||
backend=config.backend,
|
||||
url=config.app_sqlalchemy_url,
|
||||
echo=config.echo_sql,
|
||||
pool_size=config.pool_size,
|
||||
sqlite_dir=config.sqlite_dir if config.backend == "sqlite" else "",
|
||||
)
|
||||
|
||||
|
||||
def get_session_factory() -> async_sessionmaker[AsyncSession] | None:
|
||||
"""Return the async session factory, or None if backend=memory."""
|
||||
return _session_factory
|
||||
|
||||
|
||||
def get_engine() -> AsyncEngine | None:
|
||||
"""Return the async engine, or None if not initialized."""
|
||||
return _engine
|
||||
|
||||
|
||||
async def close_engine() -> None:
|
||||
"""Dispose the engine, release all connections."""
|
||||
global _engine, _session_factory
|
||||
if _engine is not None:
|
||||
await _engine.dispose()
|
||||
logger.info("Persistence engine closed")
|
||||
_engine = None
|
||||
_session_factory = None
|
||||
@@ -0,0 +1,6 @@
|
||||
"""Feedback persistence — ORM and SQL repository."""
|
||||
|
||||
from deerflow.persistence.feedback.model import FeedbackRow
|
||||
from deerflow.persistence.feedback.sql import FeedbackRepository
|
||||
|
||||
__all__ = ["FeedbackRepository", "FeedbackRow"]
|
||||
@@ -0,0 +1,30 @@
|
||||
"""ORM model for user feedback on runs."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from sqlalchemy import DateTime, String, Text
|
||||
from sqlalchemy.orm import Mapped, mapped_column
|
||||
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
|
||||
class FeedbackRow(Base):
|
||||
__tablename__ = "feedback"
|
||||
|
||||
feedback_id: Mapped[str] = mapped_column(String(64), primary_key=True)
|
||||
run_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
|
||||
thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
|
||||
owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
|
||||
message_id: Mapped[str | None] = mapped_column(String(64))
|
||||
# message_id is an optional RunEventStore event identifier —
|
||||
# allows feedback to target a specific message or the entire run
|
||||
|
||||
rating: Mapped[int] = mapped_column(nullable=False)
|
||||
# +1 (thumbs-up) or -1 (thumbs-down)
|
||||
|
||||
comment: Mapped[str | None] = mapped_column(Text)
|
||||
# Optional text feedback from the user
|
||||
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
|
||||
@@ -0,0 +1,98 @@
|
||||
"""SQLAlchemy-backed feedback storage.
|
||||
|
||||
Each method acquires its own short-lived session.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from sqlalchemy import case, func, select
|
||||
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
|
||||
|
||||
from deerflow.persistence.feedback.model import FeedbackRow
|
||||
|
||||
|
||||
class FeedbackRepository:
|
||||
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
|
||||
self._sf = session_factory
|
||||
|
||||
@staticmethod
|
||||
def _row_to_dict(row: FeedbackRow) -> dict:
|
||||
d = row.to_dict()
|
||||
val = d.get("created_at")
|
||||
if isinstance(val, datetime):
|
||||
d["created_at"] = val.isoformat()
|
||||
return d
|
||||
|
||||
async def create(
|
||||
self,
|
||||
*,
|
||||
run_id: str,
|
||||
thread_id: str,
|
||||
rating: int,
|
||||
owner_id: str | None = None,
|
||||
message_id: str | None = None,
|
||||
comment: str | None = None,
|
||||
) -> dict:
|
||||
"""Create a feedback record. rating must be +1 or -1."""
|
||||
if rating not in (1, -1):
|
||||
raise ValueError(f"rating must be +1 or -1, got {rating}")
|
||||
row = FeedbackRow(
|
||||
feedback_id=str(uuid.uuid4()),
|
||||
run_id=run_id,
|
||||
thread_id=thread_id,
|
||||
owner_id=owner_id,
|
||||
message_id=message_id,
|
||||
rating=rating,
|
||||
comment=comment,
|
||||
created_at=datetime.now(UTC),
|
||||
)
|
||||
async with self._sf() as session:
|
||||
session.add(row)
|
||||
await session.commit()
|
||||
await session.refresh(row)
|
||||
return self._row_to_dict(row)
|
||||
|
||||
async def get(self, feedback_id: str) -> dict | None:
|
||||
async with self._sf() as session:
|
||||
row = await session.get(FeedbackRow, feedback_id)
|
||||
return self._row_to_dict(row) if row else None
|
||||
|
||||
async def list_by_run(self, thread_id: str, run_id: str, *, limit: int = 100) -> list[dict]:
|
||||
stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id, FeedbackRow.run_id == run_id).order_by(FeedbackRow.created_at.asc()).limit(limit)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def list_by_thread(self, thread_id: str, *, limit: int = 100) -> list[dict]:
|
||||
stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id).order_by(FeedbackRow.created_at.asc()).limit(limit)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def delete(self, feedback_id: str) -> bool:
|
||||
async with self._sf() as session:
|
||||
row = await session.get(FeedbackRow, feedback_id)
|
||||
if row is None:
|
||||
return False
|
||||
await session.delete(row)
|
||||
await session.commit()
|
||||
return True
|
||||
|
||||
async def aggregate_by_run(self, thread_id: str, run_id: str) -> dict:
|
||||
"""Aggregate feedback stats for a run using database-side counting."""
|
||||
stmt = select(
|
||||
func.count().label("total"),
|
||||
func.coalesce(func.sum(case((FeedbackRow.rating == 1, 1), else_=0)), 0).label("positive"),
|
||||
func.coalesce(func.sum(case((FeedbackRow.rating == -1, 1), else_=0)), 0).label("negative"),
|
||||
).where(FeedbackRow.thread_id == thread_id, FeedbackRow.run_id == run_id)
|
||||
async with self._sf() as session:
|
||||
row = (await session.execute(stmt)).one()
|
||||
return {
|
||||
"run_id": run_id,
|
||||
"total": row.total,
|
||||
"positive": row.positive,
|
||||
"negative": row.negative,
|
||||
}
|
||||
@@ -0,0 +1,38 @@
|
||||
[alembic]
|
||||
script_location = %(here)s
|
||||
# Default URL for offline mode / autogenerate.
|
||||
# Runtime uses engine from DeerFlow config.
|
||||
sqlalchemy.url = sqlite+aiosqlite:///./data/app.db
|
||||
|
||||
[loggers]
|
||||
keys = root,sqlalchemy,alembic
|
||||
|
||||
[handlers]
|
||||
keys = console
|
||||
|
||||
[formatters]
|
||||
keys = generic
|
||||
|
||||
[logger_root]
|
||||
level = WARN
|
||||
handlers = console
|
||||
|
||||
[logger_sqlalchemy]
|
||||
level = WARN
|
||||
handlers =
|
||||
qualname = sqlalchemy.engine
|
||||
|
||||
[logger_alembic]
|
||||
level = INFO
|
||||
handlers =
|
||||
qualname = alembic
|
||||
|
||||
[handler_console]
|
||||
class = StreamHandler
|
||||
args = (sys.stderr,)
|
||||
level = NOTSET
|
||||
formatter = generic
|
||||
|
||||
[formatter_generic]
|
||||
format = %(levelname)-5.5s [%(name)s] %(message)s
|
||||
datefmt = %H:%M:%S
|
||||
@@ -0,0 +1,65 @@
|
||||
"""Alembic environment for DeerFlow application tables.
|
||||
|
||||
ONLY manages DeerFlow's tables (runs, threads_meta, cron_jobs, users).
|
||||
LangGraph's checkpointer tables are managed by LangGraph itself -- they
|
||||
have their own schema lifecycle and must not be touched by Alembic.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
from logging.config import fileConfig
|
||||
|
||||
from alembic import context
|
||||
from sqlalchemy.ext.asyncio import create_async_engine
|
||||
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
# Import all models so metadata is populated.
|
||||
try:
|
||||
import deerflow.persistence.models # noqa: F401 — register ORM models with Base.metadata
|
||||
except ImportError:
|
||||
# Models not available — migration will work with existing metadata only.
|
||||
logging.getLogger(__name__).warning("Could not import deerflow.persistence.models; Alembic may not detect all tables")
|
||||
|
||||
config = context.config
|
||||
if config.config_file_name is not None:
|
||||
fileConfig(config.config_file_name)
|
||||
|
||||
target_metadata = Base.metadata
|
||||
|
||||
|
||||
def run_migrations_offline() -> None:
|
||||
url = config.get_main_option("sqlalchemy.url")
|
||||
context.configure(
|
||||
url=url,
|
||||
target_metadata=target_metadata,
|
||||
literal_binds=True,
|
||||
render_as_batch=True,
|
||||
)
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
def do_run_migrations(connection):
|
||||
context.configure(
|
||||
connection=connection,
|
||||
target_metadata=target_metadata,
|
||||
render_as_batch=True, # Required for SQLite ALTER TABLE support
|
||||
)
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
async def run_migrations_online() -> None:
|
||||
connectable = create_async_engine(config.get_main_option("sqlalchemy.url"))
|
||||
async with connectable.connect() as connection:
|
||||
await connection.run_sync(do_run_migrations)
|
||||
await connectable.dispose()
|
||||
|
||||
|
||||
if context.is_offline_mode():
|
||||
run_migrations_offline()
|
||||
else:
|
||||
asyncio.run(run_migrations_online())
|
||||
@@ -0,0 +1,21 @@
|
||||
"""ORM model registration entry point.
|
||||
|
||||
Importing this module ensures all ORM models are registered with
|
||||
``Base.metadata`` so Alembic autogenerate detects every table.
|
||||
|
||||
The actual ORM classes have moved to entity-specific subpackages:
|
||||
- ``deerflow.persistence.thread_meta``
|
||||
- ``deerflow.persistence.run``
|
||||
- ``deerflow.persistence.feedback``
|
||||
|
||||
``RunEventRow`` remains in ``deerflow.persistence.models.run_event`` because
|
||||
its storage implementation lives in ``deerflow.runtime.events.store.db`` and
|
||||
there is no matching entity directory.
|
||||
"""
|
||||
|
||||
from deerflow.persistence.feedback.model import FeedbackRow
|
||||
from deerflow.persistence.models.run_event import RunEventRow
|
||||
from deerflow.persistence.run.model import RunRow
|
||||
from deerflow.persistence.thread_meta.model import ThreadMetaRow
|
||||
|
||||
__all__ = ["FeedbackRow", "RunEventRow", "RunRow", "ThreadMetaRow"]
|
||||
@@ -0,0 +1,31 @@
|
||||
"""ORM model for run events."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from sqlalchemy import JSON, DateTime, Index, String, Text, UniqueConstraint
|
||||
from sqlalchemy.orm import Mapped, mapped_column
|
||||
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
|
||||
class RunEventRow(Base):
|
||||
__tablename__ = "run_events"
|
||||
|
||||
id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
|
||||
thread_id: Mapped[str] = mapped_column(String(64), nullable=False)
|
||||
run_id: Mapped[str] = mapped_column(String(64), nullable=False)
|
||||
event_type: Mapped[str] = mapped_column(String(32), nullable=False)
|
||||
category: Mapped[str] = mapped_column(String(16), nullable=False)
|
||||
# "message" | "trace" | "lifecycle"
|
||||
content: Mapped[str] = mapped_column(Text, default="")
|
||||
event_metadata: Mapped[dict] = mapped_column(JSON, default=dict)
|
||||
seq: Mapped[int] = mapped_column(nullable=False)
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
|
||||
|
||||
__table_args__ = (
|
||||
UniqueConstraint("thread_id", "seq", name="uq_events_thread_seq"),
|
||||
Index("ix_events_thread_cat_seq", "thread_id", "category", "seq"),
|
||||
Index("ix_events_run", "thread_id", "run_id", "seq"),
|
||||
)
|
||||
@@ -0,0 +1,6 @@
|
||||
"""Run metadata persistence — ORM and SQL repository."""
|
||||
|
||||
from deerflow.persistence.run.model import RunRow
|
||||
from deerflow.persistence.run.sql import RunRepository
|
||||
|
||||
__all__ = ["RunRepository", "RunRow"]
|
||||
@@ -0,0 +1,49 @@
|
||||
"""ORM model for run metadata."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from sqlalchemy import JSON, DateTime, Index, String, Text
|
||||
from sqlalchemy.orm import Mapped, mapped_column
|
||||
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
|
||||
class RunRow(Base):
|
||||
__tablename__ = "runs"
|
||||
|
||||
run_id: Mapped[str] = mapped_column(String(64), primary_key=True)
|
||||
thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
|
||||
assistant_id: Mapped[str | None] = mapped_column(String(128))
|
||||
owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
|
||||
status: Mapped[str] = mapped_column(String(20), default="pending")
|
||||
# "pending" | "running" | "success" | "error" | "timeout" | "interrupted"
|
||||
|
||||
model_name: Mapped[str | None] = mapped_column(String(128))
|
||||
multitask_strategy: Mapped[str] = mapped_column(String(20), default="reject")
|
||||
metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
|
||||
kwargs_json: Mapped[dict] = mapped_column(JSON, default=dict)
|
||||
error: Mapped[str | None] = mapped_column(Text)
|
||||
|
||||
# Convenience fields (for listing pages without querying RunEventStore)
|
||||
message_count: Mapped[int] = mapped_column(default=0)
|
||||
first_human_message: Mapped[str | None] = mapped_column(Text)
|
||||
last_ai_message: Mapped[str | None] = mapped_column(Text)
|
||||
|
||||
# Token usage (accumulated in-memory by RunJournal, written on run completion)
|
||||
total_input_tokens: Mapped[int] = mapped_column(default=0)
|
||||
total_output_tokens: Mapped[int] = mapped_column(default=0)
|
||||
total_tokens: Mapped[int] = mapped_column(default=0)
|
||||
llm_call_count: Mapped[int] = mapped_column(default=0)
|
||||
lead_agent_tokens: Mapped[int] = mapped_column(default=0)
|
||||
subagent_tokens: Mapped[int] = mapped_column(default=0)
|
||||
middleware_tokens: Mapped[int] = mapped_column(default=0)
|
||||
|
||||
# Follow-up association
|
||||
follow_up_to_run_id: Mapped[str | None] = mapped_column(String(64))
|
||||
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
|
||||
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
|
||||
|
||||
__table_args__ = (Index("ix_runs_thread_status", "thread_id", "status"),)
|
||||
@@ -0,0 +1,227 @@
|
||||
"""SQLAlchemy-backed RunStore implementation.
|
||||
|
||||
Each method acquires and releases its own short-lived session.
|
||||
Run status updates happen from background workers that may live
|
||||
minutes -- we don't hold connections across long execution.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any
|
||||
|
||||
from sqlalchemy import func, select, update
|
||||
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
|
||||
|
||||
from deerflow.persistence.run.model import RunRow
|
||||
from deerflow.runtime.runs.store.base import RunStore
|
||||
|
||||
|
||||
class RunRepository(RunStore):
|
||||
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
|
||||
self._sf = session_factory
|
||||
|
||||
@staticmethod
|
||||
def _safe_json(obj: Any) -> Any:
|
||||
"""Ensure obj is JSON-serializable. Falls back to model_dump() or str()."""
|
||||
if obj is None:
|
||||
return None
|
||||
if isinstance(obj, (str, int, float, bool)):
|
||||
return obj
|
||||
if isinstance(obj, dict):
|
||||
return {k: RunRepository._safe_json(v) for k, v in obj.items()}
|
||||
if isinstance(obj, (list, tuple)):
|
||||
return [RunRepository._safe_json(v) for v in obj]
|
||||
if hasattr(obj, "model_dump"):
|
||||
try:
|
||||
return obj.model_dump()
|
||||
except Exception:
|
||||
pass
|
||||
if hasattr(obj, "dict"):
|
||||
try:
|
||||
return obj.dict()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
json.dumps(obj)
|
||||
return obj
|
||||
except (TypeError, ValueError):
|
||||
return str(obj)
|
||||
|
||||
@staticmethod
|
||||
def _row_to_dict(row: RunRow) -> dict[str, Any]:
|
||||
d = row.to_dict()
|
||||
# Remap JSON columns to match RunStore interface
|
||||
d["metadata"] = d.pop("metadata_json", {})
|
||||
d["kwargs"] = d.pop("kwargs_json", {})
|
||||
# Convert datetime to ISO string for consistency with MemoryRunStore
|
||||
for key in ("created_at", "updated_at"):
|
||||
val = d.get(key)
|
||||
if isinstance(val, datetime):
|
||||
d[key] = val.isoformat()
|
||||
return d
|
||||
|
||||
async def put(
|
||||
self,
|
||||
run_id,
|
||||
*,
|
||||
thread_id,
|
||||
assistant_id=None,
|
||||
owner_id=None,
|
||||
status="pending",
|
||||
multitask_strategy="reject",
|
||||
metadata=None,
|
||||
kwargs=None,
|
||||
error=None,
|
||||
created_at=None,
|
||||
follow_up_to_run_id=None,
|
||||
):
|
||||
now = datetime.now(UTC)
|
||||
row = RunRow(
|
||||
run_id=run_id,
|
||||
thread_id=thread_id,
|
||||
assistant_id=assistant_id,
|
||||
owner_id=owner_id,
|
||||
status=status,
|
||||
multitask_strategy=multitask_strategy,
|
||||
metadata_json=self._safe_json(metadata) or {},
|
||||
kwargs_json=self._safe_json(kwargs) or {},
|
||||
error=error,
|
||||
follow_up_to_run_id=follow_up_to_run_id,
|
||||
created_at=datetime.fromisoformat(created_at) if created_at else now,
|
||||
updated_at=now,
|
||||
)
|
||||
async with self._sf() as session:
|
||||
session.add(row)
|
||||
await session.commit()
|
||||
|
||||
async def get(self, run_id):
|
||||
async with self._sf() as session:
|
||||
row = await session.get(RunRow, run_id)
|
||||
return self._row_to_dict(row) if row else None
|
||||
|
||||
async def list_by_thread(self, thread_id, *, owner_id=None, limit=100):
|
||||
stmt = select(RunRow).where(RunRow.thread_id == thread_id)
|
||||
if owner_id is not None:
|
||||
stmt = stmt.where(RunRow.owner_id == owner_id)
|
||||
stmt = stmt.order_by(RunRow.created_at.desc()).limit(limit)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def update_status(self, run_id, status, *, error=None):
|
||||
values: dict[str, Any] = {"status": status, "updated_at": datetime.now(UTC)}
|
||||
if error is not None:
|
||||
values["error"] = error
|
||||
async with self._sf() as session:
|
||||
await session.execute(update(RunRow).where(RunRow.run_id == run_id).values(**values))
|
||||
await session.commit()
|
||||
|
||||
async def delete(self, run_id):
|
||||
async with self._sf() as session:
|
||||
row = await session.get(RunRow, run_id)
|
||||
if row is not None:
|
||||
await session.delete(row)
|
||||
await session.commit()
|
||||
|
||||
async def list_pending(self, *, before=None):
|
||||
if before is None:
|
||||
before_dt = datetime.now(UTC)
|
||||
elif isinstance(before, datetime):
|
||||
before_dt = before
|
||||
else:
|
||||
before_dt = datetime.fromisoformat(before)
|
||||
stmt = select(RunRow).where(RunRow.status == "pending", RunRow.created_at <= before_dt).order_by(RunRow.created_at.asc())
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def update_run_completion(
|
||||
self,
|
||||
run_id: str,
|
||||
*,
|
||||
status: str,
|
||||
total_input_tokens: int = 0,
|
||||
total_output_tokens: int = 0,
|
||||
total_tokens: int = 0,
|
||||
llm_call_count: int = 0,
|
||||
lead_agent_tokens: int = 0,
|
||||
subagent_tokens: int = 0,
|
||||
middleware_tokens: int = 0,
|
||||
message_count: int = 0,
|
||||
last_ai_message: str | None = None,
|
||||
first_human_message: str | None = None,
|
||||
error: str | None = None,
|
||||
) -> None:
|
||||
"""Update status + token usage + convenience fields on run completion."""
|
||||
values: dict[str, Any] = {
|
||||
"status": status,
|
||||
"total_input_tokens": total_input_tokens,
|
||||
"total_output_tokens": total_output_tokens,
|
||||
"total_tokens": total_tokens,
|
||||
"llm_call_count": llm_call_count,
|
||||
"lead_agent_tokens": lead_agent_tokens,
|
||||
"subagent_tokens": subagent_tokens,
|
||||
"middleware_tokens": middleware_tokens,
|
||||
"message_count": message_count,
|
||||
"updated_at": datetime.now(UTC),
|
||||
}
|
||||
if last_ai_message is not None:
|
||||
values["last_ai_message"] = last_ai_message[:2000]
|
||||
if first_human_message is not None:
|
||||
values["first_human_message"] = first_human_message[:2000]
|
||||
if error is not None:
|
||||
values["error"] = error
|
||||
async with self._sf() as session:
|
||||
await session.execute(update(RunRow).where(RunRow.run_id == run_id).values(**values))
|
||||
await session.commit()
|
||||
|
||||
async def aggregate_tokens_by_thread(self, thread_id: str) -> dict[str, Any]:
|
||||
"""Aggregate token usage via a single SQL GROUP BY query."""
|
||||
_completed = RunRow.status.in_(("success", "error"))
|
||||
_thread = RunRow.thread_id == thread_id
|
||||
|
||||
stmt = (
|
||||
select(
|
||||
func.coalesce(RunRow.model_name, "unknown").label("model"),
|
||||
func.count().label("runs"),
|
||||
func.coalesce(func.sum(RunRow.total_tokens), 0).label("total_tokens"),
|
||||
func.coalesce(func.sum(RunRow.total_input_tokens), 0).label("total_input_tokens"),
|
||||
func.coalesce(func.sum(RunRow.total_output_tokens), 0).label("total_output_tokens"),
|
||||
func.coalesce(func.sum(RunRow.lead_agent_tokens), 0).label("lead_agent"),
|
||||
func.coalesce(func.sum(RunRow.subagent_tokens), 0).label("subagent"),
|
||||
func.coalesce(func.sum(RunRow.middleware_tokens), 0).label("middleware"),
|
||||
)
|
||||
.where(_thread, _completed)
|
||||
.group_by(func.coalesce(RunRow.model_name, "unknown"))
|
||||
)
|
||||
|
||||
async with self._sf() as session:
|
||||
rows = (await session.execute(stmt)).all()
|
||||
|
||||
total_tokens = total_input = total_output = total_runs = 0
|
||||
lead_agent = subagent = middleware = 0
|
||||
by_model: dict[str, dict] = {}
|
||||
for r in rows:
|
||||
by_model[r.model] = {"tokens": r.total_tokens, "runs": r.runs}
|
||||
total_tokens += r.total_tokens
|
||||
total_input += r.total_input_tokens
|
||||
total_output += r.total_output_tokens
|
||||
total_runs += r.runs
|
||||
lead_agent += r.lead_agent
|
||||
subagent += r.subagent
|
||||
middleware += r.middleware
|
||||
|
||||
return {
|
||||
"total_tokens": total_tokens,
|
||||
"total_input_tokens": total_input,
|
||||
"total_output_tokens": total_output,
|
||||
"total_runs": total_runs,
|
||||
"by_model": by_model,
|
||||
"by_caller": {
|
||||
"lead_agent": lead_agent,
|
||||
"subagent": subagent,
|
||||
"middleware": middleware,
|
||||
},
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
"""Thread metadata persistence — ORM, abstract store, and concrete implementations."""
|
||||
|
||||
from deerflow.persistence.thread_meta.base import ThreadMetaStore
|
||||
from deerflow.persistence.thread_meta.memory import MemoryThreadMetaStore
|
||||
from deerflow.persistence.thread_meta.model import ThreadMetaRow
|
||||
from deerflow.persistence.thread_meta.sql import ThreadMetaRepository
|
||||
|
||||
__all__ = [
|
||||
"MemoryThreadMetaStore",
|
||||
"ThreadMetaRepository",
|
||||
"ThreadMetaRow",
|
||||
"ThreadMetaStore",
|
||||
]
|
||||
@@ -0,0 +1,60 @@
|
||||
"""Abstract interface for thread metadata storage.
|
||||
|
||||
Implementations:
|
||||
- ThreadMetaRepository: SQL-backed (sqlite / postgres via SQLAlchemy)
|
||||
- MemoryThreadMetaStore: wraps LangGraph BaseStore (memory mode)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import abc
|
||||
|
||||
|
||||
class ThreadMetaStore(abc.ABC):
|
||||
@abc.abstractmethod
|
||||
async def create(
|
||||
self,
|
||||
thread_id: str,
|
||||
*,
|
||||
assistant_id: str | None = None,
|
||||
owner_id: str | None = None,
|
||||
display_name: str | None = None,
|
||||
metadata: dict | None = None,
|
||||
) -> dict:
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def get(self, thread_id: str) -> dict | None:
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def search(
|
||||
self,
|
||||
*,
|
||||
metadata: dict | None = None,
|
||||
status: str | None = None,
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
) -> list[dict]:
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def update_display_name(self, thread_id: str, display_name: str) -> None:
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def update_status(self, thread_id: str, status: str) -> None:
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def update_metadata(self, thread_id: str, metadata: dict) -> None:
|
||||
"""Merge ``metadata`` into the thread's metadata field.
|
||||
|
||||
Existing keys are overwritten by the new values; keys absent from
|
||||
``metadata`` are preserved. No-op if the thread does not exist.
|
||||
"""
|
||||
pass
|
||||
|
||||
@abc.abstractmethod
|
||||
async def delete(self, thread_id: str) -> None:
|
||||
pass
|
||||
@@ -0,0 +1,120 @@
|
||||
"""In-memory ThreadMetaStore backed by LangGraph BaseStore.
|
||||
|
||||
Used when database.backend=memory. Delegates to the LangGraph Store's
|
||||
``("threads",)`` namespace — the same namespace used by the Gateway
|
||||
router for thread records.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
from langgraph.store.base import BaseStore
|
||||
|
||||
from deerflow.persistence.thread_meta.base import ThreadMetaStore
|
||||
|
||||
THREADS_NS: tuple[str, ...] = ("threads",)
|
||||
|
||||
|
||||
class MemoryThreadMetaStore(ThreadMetaStore):
|
||||
def __init__(self, store: BaseStore) -> None:
|
||||
self._store = store
|
||||
|
||||
async def create(
|
||||
self,
|
||||
thread_id: str,
|
||||
*,
|
||||
assistant_id: str | None = None,
|
||||
owner_id: str | None = None,
|
||||
display_name: str | None = None,
|
||||
metadata: dict | None = None,
|
||||
) -> dict:
|
||||
now = time.time()
|
||||
record: dict[str, Any] = {
|
||||
"thread_id": thread_id,
|
||||
"assistant_id": assistant_id,
|
||||
"owner_id": owner_id,
|
||||
"display_name": display_name,
|
||||
"status": "idle",
|
||||
"metadata": metadata or {},
|
||||
"values": {},
|
||||
"created_at": now,
|
||||
"updated_at": now,
|
||||
}
|
||||
await self._store.aput(THREADS_NS, thread_id, record)
|
||||
return record
|
||||
|
||||
async def get(self, thread_id: str) -> dict | None:
|
||||
item = await self._store.aget(THREADS_NS, thread_id)
|
||||
return item.value if item is not None else None
|
||||
|
||||
async def search(
|
||||
self,
|
||||
*,
|
||||
metadata: dict | None = None,
|
||||
status: str | None = None,
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
) -> list[dict]:
|
||||
filter_dict: dict[str, Any] = {}
|
||||
if metadata:
|
||||
filter_dict.update(metadata)
|
||||
if status:
|
||||
filter_dict["status"] = status
|
||||
|
||||
items = await self._store.asearch(
|
||||
THREADS_NS,
|
||||
filter=filter_dict or None,
|
||||
limit=limit,
|
||||
offset=offset,
|
||||
)
|
||||
return [self._item_to_dict(item) for item in items]
|
||||
|
||||
async def update_display_name(self, thread_id: str, display_name: str) -> None:
|
||||
item = await self._store.aget(THREADS_NS, thread_id)
|
||||
if item is None:
|
||||
return
|
||||
record = dict(item.value)
|
||||
record["display_name"] = display_name
|
||||
record["updated_at"] = time.time()
|
||||
await self._store.aput(THREADS_NS, thread_id, record)
|
||||
|
||||
async def update_status(self, thread_id: str, status: str) -> None:
|
||||
item = await self._store.aget(THREADS_NS, thread_id)
|
||||
if item is None:
|
||||
return
|
||||
record = dict(item.value)
|
||||
record["status"] = status
|
||||
record["updated_at"] = time.time()
|
||||
await self._store.aput(THREADS_NS, thread_id, record)
|
||||
|
||||
async def update_metadata(self, thread_id: str, metadata: dict) -> None:
|
||||
"""Merge ``metadata`` into the in-memory record. No-op if absent."""
|
||||
item = await self._store.aget(THREADS_NS, thread_id)
|
||||
if item is None:
|
||||
return
|
||||
record = dict(item.value)
|
||||
merged = dict(record.get("metadata") or {})
|
||||
merged.update(metadata)
|
||||
record["metadata"] = merged
|
||||
record["updated_at"] = time.time()
|
||||
await self._store.aput(THREADS_NS, thread_id, record)
|
||||
|
||||
async def delete(self, thread_id: str) -> None:
|
||||
await self._store.adelete(THREADS_NS, thread_id)
|
||||
|
||||
@staticmethod
|
||||
def _item_to_dict(item) -> dict[str, Any]:
|
||||
"""Convert a Store SearchItem to the dict format expected by callers."""
|
||||
val = item.value
|
||||
return {
|
||||
"thread_id": item.key,
|
||||
"assistant_id": val.get("assistant_id"),
|
||||
"owner_id": val.get("owner_id"),
|
||||
"display_name": val.get("display_name"),
|
||||
"status": val.get("status", "idle"),
|
||||
"metadata": val.get("metadata", {}),
|
||||
"created_at": str(val.get("created_at", "")),
|
||||
"updated_at": str(val.get("updated_at", "")),
|
||||
}
|
||||
@@ -0,0 +1,23 @@
|
||||
"""ORM model for thread metadata."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
|
||||
from sqlalchemy import JSON, DateTime, String
|
||||
from sqlalchemy.orm import Mapped, mapped_column
|
||||
|
||||
from deerflow.persistence.base import Base
|
||||
|
||||
|
||||
class ThreadMetaRow(Base):
|
||||
__tablename__ = "threads_meta"
|
||||
|
||||
thread_id: Mapped[str] = mapped_column(String(64), primary_key=True)
|
||||
assistant_id: Mapped[str | None] = mapped_column(String(128), index=True)
|
||||
owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
|
||||
display_name: Mapped[str | None] = mapped_column(String(256))
|
||||
status: Mapped[str] = mapped_column(String(20), default="idle")
|
||||
metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
|
||||
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
|
||||
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
|
||||
@@ -0,0 +1,140 @@
|
||||
"""SQLAlchemy-backed thread metadata repository."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import UTC, datetime
|
||||
from typing import Any
|
||||
|
||||
from sqlalchemy import select, update
|
||||
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
|
||||
|
||||
from deerflow.persistence.thread_meta.base import ThreadMetaStore
|
||||
from deerflow.persistence.thread_meta.model import ThreadMetaRow
|
||||
|
||||
|
||||
class ThreadMetaRepository(ThreadMetaStore):
|
||||
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
|
||||
self._sf = session_factory
|
||||
|
||||
@staticmethod
|
||||
def _row_to_dict(row: ThreadMetaRow) -> dict[str, Any]:
|
||||
d = row.to_dict()
|
||||
d["metadata"] = d.pop("metadata_json", {})
|
||||
for key in ("created_at", "updated_at"):
|
||||
val = d.get(key)
|
||||
if isinstance(val, datetime):
|
||||
d[key] = val.isoformat()
|
||||
return d
|
||||
|
||||
async def create(
|
||||
self,
|
||||
thread_id: str,
|
||||
*,
|
||||
assistant_id: str | None = None,
|
||||
owner_id: str | None = None,
|
||||
display_name: str | None = None,
|
||||
metadata: dict | None = None,
|
||||
) -> dict:
|
||||
now = datetime.now(UTC)
|
||||
row = ThreadMetaRow(
|
||||
thread_id=thread_id,
|
||||
assistant_id=assistant_id,
|
||||
owner_id=owner_id,
|
||||
display_name=display_name,
|
||||
metadata_json=metadata or {},
|
||||
created_at=now,
|
||||
updated_at=now,
|
||||
)
|
||||
async with self._sf() as session:
|
||||
session.add(row)
|
||||
await session.commit()
|
||||
await session.refresh(row)
|
||||
return self._row_to_dict(row)
|
||||
|
||||
async def get(self, thread_id: str) -> dict | None:
|
||||
async with self._sf() as session:
|
||||
row = await session.get(ThreadMetaRow, thread_id)
|
||||
return self._row_to_dict(row) if row else None
|
||||
|
||||
async def list_by_owner(self, owner_id: str, *, limit: int = 100, offset: int = 0) -> list[dict]:
|
||||
stmt = select(ThreadMetaRow).where(ThreadMetaRow.owner_id == owner_id).order_by(ThreadMetaRow.updated_at.desc()).limit(limit).offset(offset)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def check_access(self, thread_id: str, owner_id: str) -> bool:
|
||||
"""Check if owner_id has access to thread_id.
|
||||
|
||||
Returns True if: row doesn't exist (untracked thread), owner_id
|
||||
is None on the row (shared thread), or owner_id matches.
|
||||
"""
|
||||
async with self._sf() as session:
|
||||
row = await session.get(ThreadMetaRow, thread_id)
|
||||
if row is None:
|
||||
return True
|
||||
if row.owner_id is None:
|
||||
return True
|
||||
return row.owner_id == owner_id
|
||||
|
||||
async def search(
|
||||
self,
|
||||
*,
|
||||
metadata: dict | None = None,
|
||||
status: str | None = None,
|
||||
limit: int = 100,
|
||||
offset: int = 0,
|
||||
) -> list[dict]:
|
||||
"""Search threads with optional metadata and status filters."""
|
||||
stmt = select(ThreadMetaRow).order_by(ThreadMetaRow.updated_at.desc())
|
||||
if status:
|
||||
stmt = stmt.where(ThreadMetaRow.status == status)
|
||||
|
||||
if metadata:
|
||||
# When metadata filter is active, fetch a larger window and filter
|
||||
# in Python. TODO(Phase 2): use JSON DB operators (Postgres @>,
|
||||
# SQLite json_extract) for server-side filtering.
|
||||
stmt = stmt.limit(limit * 5 + offset)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
rows = [self._row_to_dict(r) for r in result.scalars()]
|
||||
rows = [r for r in rows if all(r.get("metadata", {}).get(k) == v for k, v in metadata.items())]
|
||||
return rows[offset : offset + limit]
|
||||
else:
|
||||
stmt = stmt.limit(limit).offset(offset)
|
||||
async with self._sf() as session:
|
||||
result = await session.execute(stmt)
|
||||
return [self._row_to_dict(r) for r in result.scalars()]
|
||||
|
||||
async def update_display_name(self, thread_id: str, display_name: str) -> None:
|
||||
"""Update the display_name (title) for a thread."""
|
||||
async with self._sf() as session:
|
||||
await session.execute(update(ThreadMetaRow).where(ThreadMetaRow.thread_id == thread_id).values(display_name=display_name, updated_at=datetime.now(UTC)))
|
||||
await session.commit()
|
||||
|
||||
async def update_status(self, thread_id: str, status: str) -> None:
|
||||
async with self._sf() as session:
|
||||
await session.execute(update(ThreadMetaRow).where(ThreadMetaRow.thread_id == thread_id).values(status=status, updated_at=datetime.now(UTC)))
|
||||
await session.commit()
|
||||
|
||||
async def update_metadata(self, thread_id: str, metadata: dict) -> None:
|
||||
"""Merge ``metadata`` into ``metadata_json``.
|
||||
|
||||
Read-modify-write inside a single session/transaction so concurrent
|
||||
callers see consistent state. No-op if the row does not exist.
|
||||
"""
|
||||
async with self._sf() as session:
|
||||
row = await session.get(ThreadMetaRow, thread_id)
|
||||
if row is None:
|
||||
return
|
||||
merged = dict(row.metadata_json or {})
|
||||
merged.update(metadata)
|
||||
row.metadata_json = merged
|
||||
row.updated_at = datetime.now(UTC)
|
||||
await session.commit()
|
||||
|
||||
async def delete(self, thread_id: str) -> None:
|
||||
async with self._sf() as session:
|
||||
row = await session.get(ThreadMetaRow, thread_id)
|
||||
if row is not None:
|
||||
await session.delete(row)
|
||||
await session.commit()
|
||||
Reference in New Issue
Block a user