- Move CONTAINER_REGISTRY.md and DATABASE_MODE.md to docs/
- Add comprehensive DEPLOYMENT.md with full deployment instructions
- Update README.md with documentation section linking to docs/
- Keep README.md at root for GitHub visibility
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Co-Authored-By: Claude <noreply@anthropic.com>
- Create interactive dashboard with company analysis page
- Add batch analysis with progress tracking and charts
- Include analytics page for historical data visualization
- Add system status monitoring
- Update requirements.txt with streamlit, plotly, pandas
- Document dashboard usage in README
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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
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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>
Implements a database mode that stores LLM prompts and responses in PostgreSQL
instead of making API calls. This enables:
- Testing without consuming API credits
- Collecting analytics on usage patterns
- Development and debugging workflows
Changes:
- Added DatabaseClient class for PostgreSQL operations
- Modified LLMAnalyzer to support database/API mode toggle
- Added USE_DATABASE config flag to switch between modes
- Included Docker Compose setup for PostgreSQL
- Added utility scripts for database init and analytics viewing
- Comprehensive documentation in DATABASE_MODE.md
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Co-Authored-By: Claude <noreply@anthropic.com>
- buildah requires user namespaces which aren't available in containers
- Use Docker CLI with host's Docker socket (already mounted by runner)
- Keep Alpine base and optimizations (git clone, sh shell)
- Simplest solution for containerized Kubernetes runners
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Co-Authored-By: Claude <noreply@anthropic.com>
- Switch from archived Kaniko to actively maintained buildah
- Use buildah from Alpine repos (no manual binary downloads)
- Replace bash syntax with POSIX sh (case instead of [[ ]])
- buildah works better in unprivileged containerized environments
- Simpler setup: just apk add buildah, no extra configuration
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Co-Authored-By: Claude <noreply@anthropic.com>
- Use sh (built into Alpine) instead of bash to avoid install errors
- Replace actions/checkout@v4 with direct git clone commands
- Add ca-certificates for HTTPS support
- Faster and more reliable for lightweight Alpine containers
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Replace Docker CLI with Kaniko executor for Kubernetes compatibility
- Combine build and push into single Kaniko step
- Remove Docker daemon dependency for better performance in containerized runners
- Reduce setup time with lighter dependencies (~14MB vs ~50MB+)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Remove docker/setup-buildx-action step which requires special
Docker daemon configuration. Use plain docker build commands
instead for better compatibility with Gitea Actions runner.
This simplifies the workflow and works with the standard
catthehacker/ubuntu:act-latest images that have Docker CLI
pre-installed.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add Gitea Actions workflow to automatically build and push Docker
images to Gitea container registry.
New files:
- .gitea/workflows/build.yaml: Automated Docker build workflow
- Triggers on push to main, tags, and manual dispatch
- Builds Docker image from Dockerfile
- Tags appropriately (commit SHA, tags, latest)
- Pushes to Gitea registry at 10.0.1.10
- CONTAINER_REGISTRY.md: Complete documentation for:
- Enabling Gitea container registry
- Setting up CI/CD with Gitea Actions
- Creating and using personal access tokens
- Pulling and pushing images
- Troubleshooting common issues
The workflow is compatible with the existing Dockerfile and provides
automated builds similar to the GitLab CI pipeline.
Prerequisites:
- Gitea container registry enabled
- GITEA_TOKEN secret configured with write:package scope
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Replace PS1 export with NIX_PROJECT_SHELL environment variable for
better integration with shell prompt configurations.
Also add trailing newline to flake.nix for proper formatting.
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Co-Authored-By: Claude <noreply@anthropic.com>
Update all user-facing documentation to reflect the migration from
Anthropic API to OpenRouter.
Changes:
- Update README.md to reference OpenRouter instead of Anthropic in:
- Features section
- Architecture diagram comments
- Configuration instructions
- API key acquisition links
- Update main.py docstring to use OPENROUTER_API_KEY
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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
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Co-Authored-By: Claude <noreply@anthropic.com>
Updated README.md with complete documentation:
- Project overview and features
- Architecture diagram
- Installation instructions (NixOS + manual)
- Configuration guide with API key setup
- Usage examples (basic + single patent)
- Testing instructions
- How it works explanation
- Updated roadmap with completed items
- Development guidelines
Makes the project immediately usable for other developers.
🤖 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.
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Co-Authored-By: Claude <noreply@anthropic.com>
Removed SPARC/patent_api.py as it contained duplicate implementations
of parse_patent_pdf, extract_section, and clean_patent_text functions
that are already present in SPARC/serp_api.py as static methods.
The serp_api.py implementation is actively used in main.py, while
patent_api.py was unused legacy code.
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Co-Authored-By: Claude <noreply@anthropic.com>
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