_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
- 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>
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