- Add jobs table to database schema (job_id, status, progress, result_json, etc.)
- Add DatabaseClient methods: create_job, update_job, get_job, list_jobs
- Add mark_stale_jobs_failed() called at startup to handle interrupted jobs
- Refactor _run_batch_job and job endpoints to read/write from PostgreSQL
- Remove in-memory _jobs dict; job state now survives API restarts
- Update init_database.py to list all tables in output
Closesleeworks-agents/SPARC#8
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Add check_jwt_secret() that refuses default JWT secret when APP_ENV != development
- Make CORS origins configurable via CORS_ORIGINS env var (comma-separated)
- Replace hardcoded postgres credentials in docker-compose.yml with env var references
- Add APP_ENV and cors_origins to config.py
- Update .env.example with all required variables and documentation
- Add tests for JWT startup guard and CORS configuration
Closesleeworks-agents/SPARC#4Closesleeworks-agents/SPARC#5Closesleeworks-agents/SPARC#6
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
_analyze_company_safe was calling SERP.query directly, bypassing the
SERP query cache in analyze_company. Now delegates fully to
analyze_company() and reads patent_count from the serp_queries cache.
- Add TestSingleQueryBugFix: verify SERP.query called once per analysis
- Add TestPatentCaching: DB cache hit/miss, SERP query cache hit/miss
- Add TestDynamicDateRange: rolling window, days_back param
- Add TestFilesystemPDFCaching: skip download, redownload empty files
- Add autouse mock_db fixture to prevent real DB connections in all tests
Rename database mode tests to cache mode to reflect new architecture:
- Replace USE_DATABASE with USE_CACHE references
- Update test assertions for cache behavior
- Maintain backward compatibility testing
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Create REST API with endpoints for single and batch analysis
- Add async job support for long-running batch operations
- Implement job status tracking and listing endpoints
- Add 9 tests for API endpoints
- Update requirements.txt with fastapi, uvicorn, httpx
- Document API usage in README
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add CompanyAnalysisResult and BatchAnalysisResult dataclasses
- Implement analyze_companies() for concurrent batch analysis
- Implement analyze_companies_sequential() for rate-limited scenarios
- Add progress callback support for monitoring batch jobs
- Include 5 new tests for batch processing functionality
- Fix pre-existing test mock issue in test_llm.py
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Replace direct Anthropic API integration with OpenRouter to enable
more flexible LLM provider access while maintaining Claude 3.5 Sonnet.
Changes:
- Replace anthropic package with openai in requirements.txt
- Update config to use OPENROUTER_API_KEY instead of ANTHROPIC_API_KEY
- Migrate LLMAnalyzer from Anthropic client to OpenAI client with
OpenRouter base URL (https://openrouter.ai/api/v1)
- Update model identifier to OpenRouter format: anthropic/claude-3.5-sonnet
- Convert API calls from messages.create() to chat.completions.create()
- Update response parsing to match OpenAI format
- Rename API key parameter in CompanyAnalyzer from anthropic_api_key
to openrouter_api_key
- Update all tests to mock OpenAI client instead of Anthropic
- Fix client initialization to accept direct API key parameter
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Created CompanyAnalyzer class that orchestrates the complete pipeline:
1. Retrieves patents via SERP API
2. Downloads and parses PDFs
3. Minimizes content (removes bloat)
4. Analyzes portfolio with LLM
5. Returns performance estimation
Features:
- Full company portfolio analysis
- Single patent analysis support
- Robust error handling (continues on partial failures)
- Progress logging for user visibility
Updated main.py with clean example usage demonstrating the high-level API.
Added comprehensive test suite (7 tests) covering:
- Full pipeline integration
- Error handling at each stage
- Single patent analysis
- Edge cases (no patents, all failures)
All 26 tests passing.
This completes the core functionality for patent-based company
performance estimation.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implemented LLMAnalyzer class using Anthropic's Claude API for:
- Single patent content analysis
- Portfolio-wide analysis across multiple patents
- Configurable API key management via environment variables
Key features:
- Uses Claude 3.5 Sonnet for high-quality analysis
- Structured prompts for innovation assessment
- Token limits optimized per use case (1024 for single, 2048 for portfolio)
- Analyzes: innovation quality, market potential, strategic direction
Updated config.py to support ANTHROPIC_API_KEY environment variable.
Added comprehensive test suite (6 tests) covering:
- Initialization from config and direct API key
- Single patent analysis
- Portfolio analysis
- Token limit validation
All 19 tests passing.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added pytest and pytest-mock to requirements.txt for testing infrastructure.
Created tests/ directory with comprehensive test coverage for:
- Text cleaning functions (figure references, whitespace, line numbers)
- Section extraction logic (abstract, claims, case sensitivity)
All 8 tests passing. This provides a foundation for test-driven
development as we continue building the LLM integration.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
AI-Manager
agent-company
0xWheatyz