Update memory bank with API testing implementation details

.note/current_focus.md

@@ -1,4 +1,4 @@
-# Current Focus: FastAPI Implementation, LLM-Based Query Classification, and Progressive Report Generation
+# Current Focus: FastAPI Implementation, API Testing, and Progressive Report Generation
 
 ## Active Work
 
@@ -14,6 +14,15 @@
 - ✅ Implemented JWT-based authentication
 - ✅ Added OpenAPI documentation endpoints
 
+### API Testing
+- ✅ Created comprehensive test suite for the API using pytest
+- ✅ Implemented test fixtures for database initialization and user authentication
+- ✅ Added tests for authentication, query processing, search execution, and report generation
+- ✅ Created a test runner script with options for verbosity, coverage reporting, and test selection
+- ✅ Implemented a manual testing script using curl commands
+- ✅ Added test documentation with instructions for running tests and troubleshooting
+- ✅ Set up test database isolation to avoid affecting production data
+
 ### LLM-Based Query Domain Classification
 - ✅ Implemented LLM-based query domain classification to replace keyword-based approach
 - ✅ Added `classify_query_domain` method to `LLMInterface` class
@@ -58,6 +67,15 @@
 
 ## Recent Changes
 
+### API Testing Implementation
+- Created comprehensive test suite for the API using pytest
+- Implemented test fixtures for database initialization and user authentication
+- Added tests for authentication, query processing, search execution, and report generation
+- Created a test runner script with options for verbosity, coverage reporting, and test selection
+- Implemented a manual testing script using curl commands
+- Added test documentation with instructions for running tests and troubleshooting
+- Set up test database isolation to avoid affecting production data
+
 ### FastAPI Implementation
 - Created a new `sim-search-api` directory for the FastAPI application
 - Implemented a layered architecture with API, service, and data layers
@@ -97,15 +115,16 @@
 
 ## Next Steps
 
-1. Test the FastAPI implementation to ensure it works correctly with the existing sim-search functionality
-2. Create a React frontend to consume the FastAPI backend
-3. Implement user management in the frontend
-4. Add search history and report management to the frontend
-5. Implement real-time progress tracking for report generation in the frontend
-6. Add visualization components for reports in the frontend
-7. Run comprehensive tests to ensure all functionality works with the new API
-8. Update any remaining documentation to reflect the new API
-9. Consider adding more API endpoints for additional functionality
+1. Run the API tests to verify that the API is working correctly
+2. Fix any issues found during testing
+3. Add more specific tests for edge cases and error handling
+4. Integrate the tests into a CI/CD pipeline
+5. Create a React frontend to consume the FastAPI backend
+6. Implement user management in the frontend
+7. Add search history and report management in the frontend
+8. Implement real-time progress tracking for report generation in the frontend
+9. Add visualization components for reports in the frontend
+10. Consider adding more API endpoints for additional functionality
 
 ### Future Enhancements
 
@@ -147,21 +166,27 @@
 
 ### Current Tasks
 
-1. **Report Generation Module Implementation (Phase 4)**:
+1. **API Testing**:
+   - Run the API tests to verify that the API is working correctly
+   - Fix any issues found during testing
+   - Add more specific tests for edge cases and error handling
+   - Integrate the tests into a CI/CD pipeline
+
+2. **Report Generation Module Implementation (Phase 4)**:
    - Implementing support for alternative models with larger context windows
    - Implementing progressive report generation for very large research tasks
    - Creating visualization components for data mentioned in reports
    - Adding interactive elements to the generated reports
    - Implementing report versioning and comparison
 
-2. **Integration with UI**:
+3. **Integration with UI**:
    - ✅ Adding report generation options to the UI
    - ✅ Implementing progress indicators for document scraping and report generation
    - ✅ Adding query type selection to the UI
    - Creating visualization components for generated reports
    - Adding options to customize report generation parameters
 
-3. **Performance Optimization**:
+4. **Performance Optimization**:
    - Optimizing token usage for more efficient LLM utilization
    - Implementing caching strategies for document scraping and LLM calls
    - Parallelizing document scraping and processing
@@ -201,3 +226,9 @@
   - Set up database migrations with Alembic
   - Added comprehensive documentation for the API
   - Implemented OpenAPI documentation endpoints
+- Created comprehensive testing framework for the API:
+  - Implemented automated tests with pytest for all API endpoints
+  - Created a test runner script with options for verbosity and coverage reporting
+  - Implemented a manual testing script using curl commands
+  - Added test documentation with instructions for running tests and troubleshooting
+  - Set up test database isolation to avoid affecting production data

.note/session_log.md

@@ -1,5 +1,53 @@
 # Session Log
 
+## Session: 2025-03-20 - API Testing Implementation
+
+### Overview
+Created a comprehensive testing framework for the sim-search API, including automated tests with pytest, a test runner script, and a manual testing script using curl commands.
+
+### Key Activities
+1. **Created Automated API Tests**:
+   - Implemented `test_api.py` with pytest to test all API endpoints
+   - Created tests for authentication, query processing, search execution, and report generation
+   - Set up test fixtures for database initialization and user authentication
+   - Implemented test database isolation to avoid affecting production data
+
+2. **Developed Test Runner Script**:
+   - Created `run_tests.py` to simplify running the tests
+   - Added command-line options for verbosity, coverage reporting, and test selection
+   - Implemented clear output formatting for test results
+
+3. **Created Manual Testing Script**:
+   - Implemented `test_api_curl.sh` for manual testing with curl commands
+   - Added tests for all API endpoints with proper authentication
+   - Implemented colorized output for better readability
+   - Added error handling and dependency checks between tests
+
+4. **Added Test Documentation**:
+   - Created a README.md file for the tests directory
+   - Documented how to run the tests using different methods
+   - Added troubleshooting information for common issues
+
+### Insights
+- The FastAPI TestClient provides a convenient way to test API endpoints without starting a server
+- Using a separate test database ensures that tests don't affect production data
+- Pytest fixtures are useful for setting up and tearing down test environments
+- Manual testing with curl commands is useful for debugging and understanding the API
+
+### Challenges
+- Ensuring proper authentication for all API endpoints
+- Managing dependencies between tests (e.g., needing a search ID to generate a report)
+- Setting up a clean test environment for each test run
+- Handling asynchronous operations in tests
+
+### Next Steps
+1. Run the tests to verify that the API is working correctly
+2. Fix any issues found during testing
+3. Add more specific tests for edge cases and error handling
+4. Integrate the tests into a CI/CD pipeline
+5. Add performance tests for the API
+6. Consider adding integration tests with the frontend
+
 ## Session: 2025-03-20 - FastAPI Backend Implementation
 
 ### Overview