Files
deer-flow/backend/app/channels/store.py
DanielWalnut 76803b826f refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)
* refactor: extract shared utils to break harness→app cross-layer imports

Move _validate_skill_frontmatter to src/skills/validation.py and
CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py.
This eliminates the two reverse dependencies from client.py (harness layer)
into gateway/routers/ (app layer), preparing for the harness/app package split.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: split backend/src into harness (deerflow.*) and app (app.*)

Physically split the monolithic backend/src/ package into two layers:

- **Harness** (`packages/harness/deerflow/`): publishable agent framework
  package with import prefix `deerflow.*`. Contains agents, sandbox, tools,
  models, MCP, skills, config, and all core infrastructure.

- **App** (`app/`): unpublished application code with import prefix `app.*`.
  Contains gateway (FastAPI REST API) and channels (IM integrations).

Key changes:
- Move 13 harness modules to packages/harness/deerflow/ via git mv
- Move gateway + channels to app/ via git mv
- Rename all imports: src.* → deerflow.* (harness) / app.* (app layer)
- Set up uv workspace with deerflow-harness as workspace member
- Update langgraph.json, config.example.yaml, all scripts, Docker files
- Add build-system (hatchling) to harness pyproject.toml
- Add PYTHONPATH=. to gateway startup commands for app.* resolution
- Update ruff.toml with known-first-party for import sorting
- Update all documentation to reflect new directory structure

Boundary rule enforced: harness code never imports from app.
All 429 tests pass. Lint clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: add harness→app boundary check test and update docs

Add test_harness_boundary.py that scans all Python files in
packages/harness/deerflow/ and fails if any `from app.*` or
`import app.*` statement is found. This enforces the architectural
rule that the harness layer never depends on the app layer.

Update CLAUDE.md to document the harness/app split architecture,
import conventions, and the boundary enforcement test.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add config versioning with auto-upgrade on startup

When config.example.yaml schema changes, developers' local config.yaml
files can silently become outdated. This adds a config_version field and
auto-upgrade mechanism so breaking changes (like src.* → deerflow.*
renames) are applied automatically before services start.

- Add config_version: 1 to config.example.yaml
- Add startup version check warning in AppConfig.from_file()
- Add scripts/config-upgrade.sh with migration registry for value replacements
- Add `make config-upgrade` target
- Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services
- Add config error hints in service failure messages

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix comments

* fix: update src.* import in test_sandbox_tools_security to deerflow.*

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: handle empty config and search parent dirs for config.example.yaml

Address Copilot review comments on PR #1131:
- Guard against yaml.safe_load() returning None for empty config files
- Search parent directories for config.example.yaml instead of only
  looking next to config.yaml, fixing detection in common setups

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: correct skills root path depth and config_version type coercion

- loader.py: fix get_skills_root_path() to use 5 parent levels (was 3)
  after harness split, file lives at packages/harness/deerflow/skills/
  so parent×3 resolved to backend/packages/harness/ instead of backend/
- app_config.py: coerce config_version to int() before comparison in
  _check_config_version() to prevent TypeError when YAML stores value
  as string (e.g. config_version: "1")
- tests: add regression tests for both fixes

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: update test imports from src.* to deerflow.*/app.* after harness refactor

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-14 22:55:52 +08:00

154 lines
5.3 KiB
Python

"""ChannelStore — persists IM chat-to-DeerFlow thread mappings."""
from __future__ import annotations
import json
import logging
import tempfile
import threading
import time
from pathlib import Path
from typing import Any
logger = logging.getLogger(__name__)
class ChannelStore:
"""JSON-file-backed store that maps IM conversations to DeerFlow threads.
Data layout (on disk)::
{
"<channel_name>:<chat_id>": {
"thread_id": "<uuid>",
"user_id": "<platform_user>",
"created_at": 1700000000.0,
"updated_at": 1700000000.0
},
...
}
The store is intentionally simple — a single JSON file that is atomically
rewritten on every mutation. For production workloads with high concurrency,
this can be swapped for a proper database backend.
"""
def __init__(self, path: str | Path | None = None) -> None:
if path is None:
from deerflow.config.paths import get_paths
path = Path(get_paths().base_dir) / "channels" / "store.json"
self._path = Path(path)
self._path.parent.mkdir(parents=True, exist_ok=True)
self._data: dict[str, dict[str, Any]] = self._load()
self._lock = threading.Lock()
# -- persistence -------------------------------------------------------
def _load(self) -> dict[str, dict[str, Any]]:
if self._path.exists():
try:
return json.loads(self._path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, OSError):
logger.warning("Corrupt channel store at %s, starting fresh", self._path)
return {}
def _save(self) -> None:
fd = tempfile.NamedTemporaryFile(
mode="w",
dir=self._path.parent,
suffix=".tmp",
delete=False,
)
try:
json.dump(self._data, fd, indent=2)
fd.close()
Path(fd.name).replace(self._path)
except BaseException:
fd.close()
Path(fd.name).unlink(missing_ok=True)
raise
# -- key helpers -------------------------------------------------------
@staticmethod
def _key(channel_name: str, chat_id: str, topic_id: str | None = None) -> str:
if topic_id:
return f"{channel_name}:{chat_id}:{topic_id}"
return f"{channel_name}:{chat_id}"
# -- public API --------------------------------------------------------
def get_thread_id(self, channel_name: str, chat_id: str, topic_id: str | None = None) -> str | None:
"""Look up the DeerFlow thread_id for a given IM conversation/topic."""
entry = self._data.get(self._key(channel_name, chat_id, topic_id))
return entry["thread_id"] if entry else None
def set_thread_id(
self,
channel_name: str,
chat_id: str,
thread_id: str,
*,
topic_id: str | None = None,
user_id: str = "",
) -> None:
"""Create or update the mapping for an IM conversation/topic."""
with self._lock:
key = self._key(channel_name, chat_id, topic_id)
now = time.time()
existing = self._data.get(key)
self._data[key] = {
"thread_id": thread_id,
"user_id": user_id,
"created_at": existing["created_at"] if existing else now,
"updated_at": now,
}
self._save()
def remove(self, channel_name: str, chat_id: str, topic_id: str | None = None) -> bool:
"""Remove a mapping.
If ``topic_id`` is provided, only that specific conversation/topic mapping is removed.
If ``topic_id`` is omitted, all mappings whose key starts with
``"<channel_name>:<chat_id>"`` (including topic-specific ones) are removed.
Returns True if at least one mapping was removed.
"""
with self._lock:
# Remove a specific conversation/topic mapping.
if topic_id is not None:
key = self._key(channel_name, chat_id, topic_id)
if key in self._data:
del self._data[key]
self._save()
return True
return False
# Remove all mappings for this channel/chat_id (base and any topic-specific keys).
prefix = self._key(channel_name, chat_id)
keys_to_delete = [k for k in self._data if k == prefix or k.startswith(prefix + ":")]
if not keys_to_delete:
return False
for k in keys_to_delete:
del self._data[k]
self._save()
return True
def list_entries(self, channel_name: str | None = None) -> list[dict[str, Any]]:
"""List all stored mappings, optionally filtered by channel."""
results = []
for key, entry in self._data.items():
parts = key.split(":", 2)
ch = parts[0]
chat = parts[1] if len(parts) > 1 else ""
topic = parts[2] if len(parts) > 2 else None
if channel_name and ch != channel_name:
continue
item: dict[str, Any] = {"channel_name": ch, "chat_id": chat, **entry}
if topic is not None:
item["topic_id"] = topic
results.append(item)
return results