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- Add FastAPI application with /github/input-repos endpoint - Support dynamic repository URLs in API requests - Add Pydantic models for request/response validation - Add GitHub service for SHA validation against repositories - Add repository import scripts (Python, Shell, YAML config) - Add sample Python files for testing - Update requirements.txt with FastAPI dependencies - Add comprehensive documentation and test scripts Features: - POST /github/input-repos: Process 3 GitHub SHAs with repo URLs - Dynamic repository validation (no config file needed) - Comprehensive error handling and validation - Automatic API documentation (Swagger UI) - Repository import utilities for data folder
- Remove original engine/ directory and core functionality - Remove web/ directory and Next.js application - Remove server/ directory and API server - Remove mcp-server/ directory and TypeScript server - Remove debug/ and test directories - Remove schemas/ and .github/workflows/ - Remove original sample data directories - Remove patch files and test scripts - Remove documentation files (ADAPTER_REMOVAL_SUMMARY.md, AI_DIRECT_REBASE.md) - Remove master_prompt and other configuration files - Keep only FastAPI integration and essential files Repository now contains only: - FastAPI application (api/, main.py, test_api.py) - Repository import scripts (scripts/) - Sample data (data/sample/) - Configuration (config/repos.yaml) - Essential files (LICENSE, README.md, requirements.txt, pyproject.toml)
- Restore .github/workflows/ci.yml - Keep GitHub Actions CI configuration intact - Maintain repository's GitHub integration
- Add pytest-based test suite with unit and integration tests - Add test fixtures and configuration (conftest.py, pytest.ini) - Add unit tests for Pydantic models (test_models.py) - Add unit tests for GitHub service (test_services.py) - Add integration tests for API endpoints (test_api_endpoints.py) - Add manual tests for running server (test_api.py) - Add test runner script (run_tests.py) - Add testing dependencies to requirements.txt - Add comprehensive FastAPI documentation (README_FASTAPI.md) Testing Features: - Unit tests with mocked dependencies - Integration tests with FastAPI TestClient - Manual tests for running server instances - Comprehensive error handling tests - Input validation tests - Service layer tests - API endpoint tests Test Coverage: - Models validation and serialization - Service business logic - API endpoint behavior - Error handling scenarios - Input validation edge cases
- Fix Python compatibility issue: Change tuple[str, str] to Tuple[str, str] for Python < 3.9 - Fix router import in main.py: Import router directly instead of module - Remove duplicate dependencies in requirements.txt (pytest, httpx) - Add Tuple import to github_service.py All files now compile and import successfully. FastAPI app creates successfully with all expected routes.
- Restore simple standalone test script in root directory - This provides easy manual testing: python test_api.py - Different from tests/test_api.py which is pytest-based - Both serve different purposes: - Root test_api.py: Quick manual testing - tests/test_api.py: Pytest-based manual tests Usage: - Quick test: python test_api.py - Pytest tests: python run_tests.py - Manual pytest: python tests/test_api.py
…ractices - Remove test_api.py from root directory (not best practice) - Enhance tests/test_api.py with simple manual testing functionality - Update run_tests.py with 'simple' option for easy manual testing - Update documentation to reflect proper test structure Best Practices Followed: - All test files in tests/ directory - Proper Python project structure - Tool compatibility (pytest, CI/CD) - Maintainable organization Usage Options: - Automated tests: python run_tests.py - Manual tests: python run_tests.py manual - Simple tests: python run_tests.py simple - Direct: python tests/test_api.py
- Create AutoRebase core module (api/autorebase/core.py) - AutoRebase class for repository processing - Repository cloning functionality with git commands - Placeholder autorebase method (to be implemented in next steps) - Complete process: clone repositories and run autorebase - Add AutoRebase models (api/models/autorebase_models.py) - AutoRebaseRequest: Input validation for repository URLs and SHAs - AutoRebaseResponse: Complete response with cloning and autorebase results - CloneResult: Individual repository cloning results - AutoRebaseResult: Autorebase operation results - Add AutoRebase service (api/services/autorebase_service.py) - AutoRebaseService: Business logic for autorebase operations - Process repositories: clone and run autorebase - Error handling and response formatting - Add AutoRebase router (api/routers/autorebase_router.py) - POST /autorebase/process: Main autorebase endpoint - GET /autorebase/health: Health check - GET /autorebase/: Root endpoint with API info - Update main FastAPI app - Include autorebase router - New routes: /autorebase/process, /autorebase/health, /autorebase/ - Add comprehensive tests (tests/test_autorebase.py) - Unit tests for models, core, and service - Integration tests for API endpoints - Mocked dependencies for reliable testing - Update test infrastructure - Include autorebase tests in test runner - Add autorebase testing to manual tests Features: - Repository cloning with specific SHA checkout - Working directory management - Comprehensive error handling - Async/await support - Input validation - Detailed response structure - Health monitoring - Full test coverage Ready for Step 3: Implement actual autorebase logic
- Remove separate AutoRebase API endpoints (not needed for now) - Integrate AutoRebase process into GitHub service - AutoRebase now runs automatically after SHA validation - Update GitHub router documentation to reflect integration - Fix test data to use valid SHA patterns (hex only) - Fix async mock issues in tests - Remove obsolete AutoRebase endpoint tests - Update test assertions for Pydantic v2 error messages Architecture: - Single endpoint: POST /github/input-repos - Validates SHAs → Clones repos → Runs AutoRebase - All in one seamless workflow - Future: Can expose AutoRebase as separate API if needed
- Add DiffPatchManager class for handling diff generation and patch application - Implement simplified AutoRebase process: apply base_0->feature_0 patches to base_1 files - Create f1 files in feature-5.1 directory instead of modifying original files - Handle patch failures with .orig/.rej file preservation and process_3way_merge() calls - Add comprehensive test script (test_autorebase_sample.py) for validation - Clean up temporary test files and artifacts - Update naming convention: f2 -> f1, feature-5.1 directory structure Key features: - Finds common files between base_0 and feature_0 directories - Generates git diff patches for base_0->feature_0 and base_0->base_1 - Applies patches to create new f1 files in feature-5.1 directory - Maintains changelog with processing details and failure tracking - Preserves .orig backup files and .rej reject files for failed patches
- Add OpenAI integration for intelligent conflict resolution - Implement file_conflict_resolver.py with requirements-based AI prompting - Update diff_patch.py to use AI resolution when patches fail - Fix patch command interactive behavior with --batch flag - Add comprehensive conflict analysis and validation - Update test_autorebase_sample.py to test AI resolution - Add .env file support for OpenAI API key - Maintain backward compatibility with fallback behavior The system now automatically resolves conflicts using AI when: - Patches fail and generate .rej files - Requirements are found in requirements_map.yaml - OpenAI API key is available Falls back gracefully when AI resolution fails or requirements missing.
- Resolved conflicts by removing old files that were replaced by fastapi structure - Removed sample-base-sw_1.1 and sample-feature-sw_5.0 directories - Removed old scripts (resolve_conflict.py, run_auto_rebase.sh) - Updated requirements_map.yaml from main branch - FastAPI structure now replaces the old autorebase implementation
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