feat: implement Multi-Agent Foundation (tool reranking, rejection, metrics) - #8
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- Delete requirements.txt and requirements-dev.txt - Dependencies managed via pyproject.toml
- Remove extensive Python/IDE-specific patterns - Keep essential entries: venvs, __pycache__, .egg-info, OS files - Ensure .vscode/ is properly ignored
- Add success_score, trajectory_id, and step_number parameters to log_execution - Extend docstrings with detailed parameter descriptions - Implement data dict structure for flexible event logging - Add comprehensive tests for new metric fields and aggregation - Enable foundation for agent performance analysis and optimization
- Add ToolReranker class with success history and context relevance scoring - Implement ToolRejectionHandler with 7 distinct rejection reasons - Introduce confidence threshold filtering for tool selection - Provide alternative tool suggestions on rejection - Add RejectionReason enum for structured error handling - Include comprehensive test suite with 20+ test cases - Enable smarter tool selection and error recovery for agents
- Mark Tasks 1.1.1, 1.1.2, and 1.4.1 as completed (✅) - Update sprint timeline with actual Sprint 1 deliverables - Translate success criteria to Russian and mark Phase 1 progress - Remove all 'Phase 1', 'Phase 2', 'Task' tags from content - Reflect current architecture state post-implementation - Add detailed next steps for Sprints 2-9
- Add Sprint 1 completion status (metrics, reranking, rejection) - Update Quick Start with Poetry installation instructions - Document new metrics CLI commands (trajectory, success-rate) - Update Architecture diagram with tool_management.py - Add reference to HOLOBIONT_ROADMAP.md
- Translate HOLOBIONT_ROADMAP.md from Russian to English - Add metrics.jsonl to .gitignore to prevent committing runtime data - Remove metrics.jsonl from repository
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Code Review
This pull request introduces the foundation for the HolobiontLLM multi-agent system, specifically focusing on Sprint 1 deliverables: tool reranking, rejection handling, and extended metrics for trajectory tracking. While the new logic is implemented in core/tool_management.py and core/metrics.py with accompanying tests, the reviewer noted that the new tool management components are not yet integrated into the core execution loop. Additionally, several formatting issues were identified in the .gitignore and README.md files, and there is an opportunity to optimize the history tracking logic using collections.deque.
…ject.toml - Explicitly define pytest, pytest-cov, pytest-timeout, flake8, mypy in dev extras - Resolves CI failure where 'pip install -e .[dev]' installed no dev tools
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Summary
This PR implements Multi-Agent Foundation, laying the groundwork for the HolobiontLLM architecture. Key enhancements include:
success_score,trajectory_id, andstep_numberto enable future agent performance analysis and self-learning loops.tool_management.py) featuring:requirements.txt) in favor ofpyproject.toml.HOLOBIONT_ROADMAP.md) to English.metrics.jsonlto.gitignore.These changes transform RawLLM from a simple executor into a multi-agent ready platform with basic introspection capabilities.
Type of change
Checklist
flake8passes)pytest tests/ --cov=core --cov-fail-under=90passes locallyREADME.md, docstrings,HOLOBIONT_ROADMAP.md)dev)Manual Verification:
rawllm metrics success-rateto verify new aggregation logic.ToolRejectionHandlerin action.ToolRerankersorts tools correctly when history data is present.Automated Tests:
ToolRerankerscoring factors andToolRejectionHandlerreason detection.coremodule.Migration Notes:
requirements.txtandrequirements-dev.txthave been removed. Users must now install viapoetry installorpip install -e ..metrics.jsonl) are now ignored by default; ensure you backup existing logs if needed before pulling.