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* 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 - **App** (`app/`): unpublished application code with import prefix `app.*`.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on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated.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>
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Setup Guide
Quick setup instructions for DeerFlow.
Configuration Setup
DeerFlow uses a YAML configuration file that should be placed in the project root directory.
Steps
-
Navigate to project root:
cd /path/to/deer-flow -
Copy example configuration:
cp config.example.yaml config.yaml -
Edit configuration:
# Option A: Set environment variables (recommended) export OPENAI_API_KEY="your-key-here" # Option B: Edit config.yaml directly vim config.yaml # or your preferred editor -
Verify configuration:
cd backend python -c "from deerflow.config import get_app_config; print('✓ Config loaded:', get_app_config().models[0].name)"
Important Notes
- Location:
config.yamlshould be indeer-flow/(project root), notdeer-flow/backend/ - Git:
config.yamlis automatically ignored by git (contains secrets) - Priority: If both
backend/config.yamland../config.yamlexist, backend version takes precedence
Configuration File Locations
The backend searches for config.yaml in this order:
DEER_FLOW_CONFIG_PATHenvironment variable (if set)backend/config.yaml(current directory when running from backend/)deer-flow/config.yaml(parent directory - recommended location)
Recommended: Place config.yaml in project root (deer-flow/config.yaml).
Sandbox Setup (Optional but Recommended)
If you plan to use Docker/Container-based sandbox (configured in config.yaml under sandbox.use: deerflow.community.aio_sandbox:AioSandboxProvider), it's highly recommended to pre-pull the container image:
# From project root
make setup-sandbox
Why pre-pull?
- The sandbox image (~500MB+) is pulled on first use, causing a long wait
- Pre-pulling provides clear progress indication
- Avoids confusion when first using the agent
If you skip this step, the image will be automatically pulled on first agent execution, which may take several minutes depending on your network speed.
Troubleshooting
Config file not found
# Check where the backend is looking
cd deer-flow/backend
python -c "from deerflow.config.app_config import AppConfig; print(AppConfig.resolve_config_path())"
If it can't find the config:
- Ensure you've copied
config.example.yamltoconfig.yaml - Verify you're in the correct directory
- Check the file exists:
ls -la ../config.yaml
Permission denied
chmod 600 ../config.yaml # Protect sensitive configuration
See Also
- Configuration Guide - Detailed configuration options
- Architecture Overview - System architecture