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feat: implement HFInferenceJudgeHandler for free-tier AI analysis
Replace MockJudgeHandler with real AI analysis using HuggingFace Inference API: - Add HFInferenceJudgeHandler with chat_completion API - Model fallback chain: Llama 3.1 → Mistral → Zephyr (ungated) - Robust JSON extraction (handles markdown blocks, nested braces) - Tenacity retry with exponential backoff for rate limits - Fix app.py to use HF Inference when no paid API keys present Priority: User API key → Env API key → HF Inference (free) Hackathon judges now get real AI analysis without needing API keys. Set HF_TOKEN as Space secret for best model (Llama 3.1).7fab6d4
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fix(report): add explicit JSON structure guidance in prompt
The LLM was returning incorrect JSON structures: - hypotheses_tested: dict instead of list - references: string URLs instead of list of dicts Added explicit format examples in SYSTEM_PROMPT to guide the LLM to produce valid structured output that passes Pydantic validation. This fixes the full_stack_demo ReportAgent validation errors.d01e70d -
fix: apply lazy init pattern and pydantic-ai fixes to ReportAgent (#12)
Applies the same fixes as Phase 7 HypothesisAgent: - Lazy initialization via _get_agent() to avoid API key requirement at import - Use output_type instead of result_type (pydantic-ai API) - Use result.output instead of result.data - Fix line length issues in tests - Proper mocking of get_model in tests3139749 -
feat(phase7): implement Hypothesis Agent for mechanistic reasoning
Add HypothesisAgent that generates Drug → Target → Pathway → Effect hypotheses based on collected evidence. Key features: Models: - MechanismHypothesis: structured hypothesis with confidence scoring - HypothesisAssessment: container for hypotheses with knowledge gaps Utilities: - MMR (Maximal Marginal Relevance) for diverse evidence selection - Sentence-aware truncation for clean text processing Agent: - HypothesisAgent generates 2-4 testable hypotheses per query - Integrated with EmbeddingService for semantic evidence selection Orchestrator: - Refactored MagenticOrchestrator into smaller methods - Added "hypothesizing" event type for UI feedback - Workflow: Search → Hypothesize → Targeted Search → Judge Tests: 53/53 passing, mypy clean, ruff cleanc690006 -
fix: add type ignore comment for Agent instantiation in JudgeHandler
Updated the Agent instantiation in JudgeHandler to include a type ignore comment, addressing type-checking issues while maintaining functionality.9760706 -
feat(phase3): implement judge slice (LLM Judge, Prompts, Models)
Implemented LLM-based Judge Agent with PydanticAI for structured output. Includes 100% test coverage and fallback mechanisms.d7e5abb -
feat(phase1): Foundation & Tooling complete
* feat: initialize deepcritical project structure with core configuration and main functionality - Added initial project files including `.python-version`, `pyproject.toml`, and main application logic in `main.py`. - Implemented application configuration using Pydantic in `src/utils/config.py` with environment variable support. - Created directory structure for source code and tests, including placeholders for agents, prompts, tools, and utilities. - Added unit tests for configuration loading and validation in `tests/unit/utils/test_config.py`. Review Score: 100/100 (Ironclad Gucci Banger Edition) * feat(phase1): complete foundation with Python 3.11, tests, and tooling - Fix Python version to 3.11 for HuggingFace Spaces compatibility - Add config.py with pydantic-settings for typed configuration - Add exceptions.py with custom exception hierarchy - Add conftest.py with test fixtures (sample_evidence deferred to Phase 2) - Add .env.example and .pre-commit-config.yaml - Remove refere…069f0a0
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adds scaffolding
Joseph Pollack1465eef