Files
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- **App** (`app/`): unpublished application code with import prefix `app.*`.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files can silently become outdated.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

202 lines
7.0 KiB
Python

"""Memory API router for retrieving and managing global memory data."""
from fastapi import APIRouter
from pydantic import BaseModel, Field
from deerflow.agents.memory.updater import get_memory_data, reload_memory_data
from deerflow.config.memory_config import get_memory_config
router = APIRouter(prefix="/api", tags=["memory"])
class ContextSection(BaseModel):
"""Model for context sections (user and history)."""
summary: str = Field(default="", description="Summary content")
updatedAt: str = Field(default="", description="Last update timestamp")
class UserContext(BaseModel):
"""Model for user context."""
workContext: ContextSection = Field(default_factory=ContextSection)
personalContext: ContextSection = Field(default_factory=ContextSection)
topOfMind: ContextSection = Field(default_factory=ContextSection)
class HistoryContext(BaseModel):
"""Model for history context."""
recentMonths: ContextSection = Field(default_factory=ContextSection)
earlierContext: ContextSection = Field(default_factory=ContextSection)
longTermBackground: ContextSection = Field(default_factory=ContextSection)
class Fact(BaseModel):
"""Model for a memory fact."""
id: str = Field(..., description="Unique identifier for the fact")
content: str = Field(..., description="Fact content")
category: str = Field(default="context", description="Fact category")
confidence: float = Field(default=0.5, description="Confidence score (0-1)")
createdAt: str = Field(default="", description="Creation timestamp")
source: str = Field(default="unknown", description="Source thread ID")
class MemoryResponse(BaseModel):
"""Response model for memory data."""
version: str = Field(default="1.0", description="Memory schema version")
lastUpdated: str = Field(default="", description="Last update timestamp")
user: UserContext = Field(default_factory=UserContext)
history: HistoryContext = Field(default_factory=HistoryContext)
facts: list[Fact] = Field(default_factory=list)
class MemoryConfigResponse(BaseModel):
"""Response model for memory configuration."""
enabled: bool = Field(..., description="Whether memory is enabled")
storage_path: str = Field(..., description="Path to memory storage file")
debounce_seconds: int = Field(..., description="Debounce time for memory updates")
max_facts: int = Field(..., description="Maximum number of facts to store")
fact_confidence_threshold: float = Field(..., description="Minimum confidence threshold for facts")
injection_enabled: bool = Field(..., description="Whether memory injection is enabled")
max_injection_tokens: int = Field(..., description="Maximum tokens for memory injection")
class MemoryStatusResponse(BaseModel):
"""Response model for memory status."""
config: MemoryConfigResponse
data: MemoryResponse
@router.get(
"/memory",
response_model=MemoryResponse,
summary="Get Memory Data",
description="Retrieve the current global memory data including user context, history, and facts.",
)
async def get_memory() -> MemoryResponse:
"""Get the current global memory data.
Returns:
The current memory data with user context, history, and facts.
Example Response:
```json
{
"version": "1.0",
"lastUpdated": "2024-01-15T10:30:00Z",
"user": {
"workContext": {"summary": "Working on DeerFlow project", "updatedAt": "..."},
"personalContext": {"summary": "Prefers concise responses", "updatedAt": "..."},
"topOfMind": {"summary": "Building memory API", "updatedAt": "..."}
},
"history": {
"recentMonths": {"summary": "Recent development activities", "updatedAt": "..."},
"earlierContext": {"summary": "", "updatedAt": ""},
"longTermBackground": {"summary": "", "updatedAt": ""}
},
"facts": [
{
"id": "fact_abc123",
"content": "User prefers TypeScript over JavaScript",
"category": "preference",
"confidence": 0.9,
"createdAt": "2024-01-15T10:30:00Z",
"source": "thread_xyz"
}
]
}
```
"""
memory_data = get_memory_data()
return MemoryResponse(**memory_data)
@router.post(
"/memory/reload",
response_model=MemoryResponse,
summary="Reload Memory Data",
description="Reload memory data from the storage file, refreshing the in-memory cache.",
)
async def reload_memory() -> MemoryResponse:
"""Reload memory data from file.
This forces a reload of the memory data from the storage file,
useful when the file has been modified externally.
Returns:
The reloaded memory data.
"""
memory_data = reload_memory_data()
return MemoryResponse(**memory_data)
@router.get(
"/memory/config",
response_model=MemoryConfigResponse,
summary="Get Memory Configuration",
description="Retrieve the current memory system configuration.",
)
async def get_memory_config_endpoint() -> MemoryConfigResponse:
"""Get the memory system configuration.
Returns:
The current memory configuration settings.
Example Response:
```json
{
"enabled": true,
"storage_path": ".deer-flow/memory.json",
"debounce_seconds": 30,
"max_facts": 100,
"fact_confidence_threshold": 0.7,
"injection_enabled": true,
"max_injection_tokens": 2000
}
```
"""
config = get_memory_config()
return MemoryConfigResponse(
enabled=config.enabled,
storage_path=config.storage_path,
debounce_seconds=config.debounce_seconds,
max_facts=config.max_facts,
fact_confidence_threshold=config.fact_confidence_threshold,
injection_enabled=config.injection_enabled,
max_injection_tokens=config.max_injection_tokens,
)
@router.get(
"/memory/status",
response_model=MemoryStatusResponse,
summary="Get Memory Status",
description="Retrieve both memory configuration and current data in a single request.",
)
async def get_memory_status() -> MemoryStatusResponse:
"""Get the memory system status including configuration and data.
Returns:
Combined memory configuration and current data.
"""
config = get_memory_config()
memory_data = get_memory_data()
return MemoryStatusResponse(
config=MemoryConfigResponse(
enabled=config.enabled,
storage_path=config.storage_path,
debounce_seconds=config.debounce_seconds,
max_facts=config.max_facts,
fact_confidence_threshold=config.fact_confidence_threshold,
injection_enabled=config.injection_enabled,
max_injection_tokens=config.max_injection_tokens,
),
data=MemoryResponse(**memory_data),
)