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https://gitee.com/wanwujie/deer-flow
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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 - **App** (`app/`): unpublished application code with import prefix `app.*`.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>
This commit is contained in:
DanielWalnut
113
backend/app/gateway/routers/models.py
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113
backend/app/gateway/routers/models.py
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel, Field
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from deerflow.config import get_app_config
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router = APIRouter(prefix="/api", tags=["models"])
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class ModelResponse(BaseModel):
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"""Response model for model information."""
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name: str = Field(..., description="Unique identifier for the model")
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display_name: str | None = Field(None, description="Human-readable name")
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description: str | None = Field(None, description="Model description")
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supports_thinking: bool = Field(default=False, description="Whether model supports thinking mode")
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supports_reasoning_effort: bool = Field(default=False, description="Whether model supports reasoning effort")
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class ModelsListResponse(BaseModel):
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"""Response model for listing all models."""
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models: list[ModelResponse]
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@router.get(
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"/models",
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response_model=ModelsListResponse,
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summary="List All Models",
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description="Retrieve a list of all available AI models configured in the system.",
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)
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async def list_models() -> ModelsListResponse:
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"""List all available models from configuration.
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Returns model information suitable for frontend display,
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excluding sensitive fields like API keys and internal configuration.
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Returns:
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A list of all configured models with their metadata.
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Example Response:
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```json
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{
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"models": [
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{
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"name": "gpt-4",
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"display_name": "GPT-4",
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"description": "OpenAI GPT-4 model",
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"supports_thinking": false
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},
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{
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"name": "claude-3-opus",
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"display_name": "Claude 3 Opus",
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"description": "Anthropic Claude 3 Opus model",
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"supports_thinking": true
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}
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]
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}
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```
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"""
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config = get_app_config()
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models = [
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ModelResponse(
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name=model.name,
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display_name=model.display_name,
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description=model.description,
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supports_thinking=model.supports_thinking,
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supports_reasoning_effort=model.supports_reasoning_effort,
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)
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for model in config.models
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]
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return ModelsListResponse(models=models)
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@router.get(
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"/models/{model_name}",
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response_model=ModelResponse,
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summary="Get Model Details",
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description="Retrieve detailed information about a specific AI model by its name.",
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)
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async def get_model(model_name: str) -> ModelResponse:
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"""Get a specific model by name.
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Args:
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model_name: The unique name of the model to retrieve.
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Returns:
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Model information if found.
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Raises:
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HTTPException: 404 if model not found.
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Example Response:
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```json
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{
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"name": "gpt-4",
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"display_name": "GPT-4",
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"description": "OpenAI GPT-4 model",
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"supports_thinking": false
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}
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```
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"""
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config = get_app_config()
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model = config.get_model_config(model_name)
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if model is None:
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raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
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return ModelResponse(
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name=model.name,
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display_name=model.display_name,
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description=model.description,
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supports_thinking=model.supports_thinking,
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supports_reasoning_effort=model.supports_reasoning_effort,
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)
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