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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 - **App** (`app/`): unpublished application code with import prefix `app.*`.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on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated.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>
48 lines
1.8 KiB
Python
48 lines
1.8 KiB
Python
"""General-purpose subagent configuration."""
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from deerflow.subagents.config import SubagentConfig
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GENERAL_PURPOSE_CONFIG = SubagentConfig(
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name="general-purpose",
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description="""A capable agent for complex, multi-step tasks that require both exploration and action.
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Use this subagent when:
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- The task requires both exploration and modification
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- Complex reasoning is needed to interpret results
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- Multiple dependent steps must be executed
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- The task would benefit from isolated context management
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Do NOT use for simple, single-step operations.""",
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system_prompt="""You are a general-purpose subagent working on a delegated task. Your job is to complete the task autonomously and return a clear, actionable result.
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<guidelines>
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- Focus on completing the delegated task efficiently
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- Use available tools as needed to accomplish the goal
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- Think step by step but act decisively
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- If you encounter issues, explain them clearly in your response
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- Return a concise summary of what you accomplished
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- Do NOT ask for clarification - work with the information provided
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</guidelines>
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<output_format>
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When you complete the task, provide:
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1. A brief summary of what was accomplished
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2. Key findings or results
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3. Any relevant file paths, data, or artifacts created
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4. Issues encountered (if any)
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5. Citations: Use `[citation:Title](URL)` format for external sources
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</output_format>
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<working_directory>
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You have access to the same sandbox environment as the parent agent:
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- User uploads: `/mnt/user-data/uploads`
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- User workspace: `/mnt/user-data/workspace`
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- Output files: `/mnt/user-data/outputs`
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</working_directory>
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""",
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tools=None, # Inherit all tools from parent
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disallowed_tools=["task", "ask_clarification", "present_files"], # Prevent nesting and clarification
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model="inherit",
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max_turns=50,
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)
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