Enhance follow-up detection logic in RecommendationService - Added checks to differentiate between follow-up queries and new primary artist queries based on current and previous artist mentions. Updated context handling rules in ContextAwareIntentAnalyzer to clarify follow-up criteria and improve intent management. This update aims to refine user experience by ensuring accurate query handling and maintaining session context effectively.

Merge pull request #2 from SulmanK/refactor/production-refinement

Remove obsolete phase completion summaries and demo test scripts - Deleted `PHASE1_COMPLETION_SUMMARY.md`, `PHASE2_COMPLETION_SUMMARY.md`, `PHASE3_COMPLETION_SUMMARY.md`, and associated demo test scripts to streamline the codebase and eliminate unused documentation. This cleanup supports ongoing refactoring efforts and enhances overall project maintainability.

Implement Phase 3 enhancements for candidate pool persistence in recommendation agents - Introduced `SessionManagerService` to support candidate pool generation and retrieval across `UnifiedCandidateGenerator`, `DiscoveryAgent`, `JudgeAgent`, and `GenreMoodAgent`. Updated agent initialization to accept session manager, enabling efficient follow-up query handling and improved user experience. Added methods for generating and persisting large candidate pools, as well as retrieving candidates from persisted pools, ensuring better performance and responsiveness in music recommendations. This update aims to streamline agent logic and enhance the overall recommendation system.

Enhance intent management and context handling in the recommendation system - Introduced `SessionManagerService` and `IntentOrchestrationService` to centralize intent processing and improve follow-up query handling. Refactored `EnhancedRecommendationService` to integrate these new services, ensuring agents receive a clear "effective intent" for better decision-making. Updated scoring logic in `ComprehensiveQualityScorer` for improved robustness. This update aims to streamline agent logic, enhance user experience with follow-ups, and support ongoing refactoring efforts.

feat: implement LLM fallback system for unknown intents - Add LLMFallbackService with Gemini Flash 2.0 integration - Implement fallback trigger detection in chat interface - Add response formatter support for fallback disclaimers - Include comprehensive test coverage for fallback scenarios

Add autopep8 as a dependency for code formatting - Updated pyproject.toml to include autopep8 version 2.3.2 for improved code style consistency. Modified uv.lock to reflect the new dependency and its requirements. This update aims to enhance code maintainability and adherence to style guidelines.

Enhance intent-aware recommendation system design and scoring logic - Updated the design document to introduce a new query type for "by artist" intent, detailing user goals, scoring strategies, and agent workflows. Refactored scoring logic in the quality scorer and ranking logic to accommodate exploration preferences and artist alias handling. Improved candidate generation for artist-specific queries and refined genre filtering methods to support hybrid queries. This update aims to better align system behavior with user intent and enhance overall recommendation accuracy.

Update configuration files and remove obsolete test scripts - Increased line length limit in `pyproject.toml`, `test_hybrid_intent_final.py`, `test_hybrid_intent_fix.py`, `test_hybrid_subtypes.py`, `test_intent_fix.py`, `test_quick_hybrid.py`, `test_ui_improvements.py` to enhance code formatting flexibility. Deleted unused test files to streamline the codebase and improve maintainability. This cleanup supports ongoing refactoring efforts and enhances overall project structure.

Update .gitignore and remove obsolete cleanup documentation - Added `.gradio` and `tests/data/cache` to `.gitignore` to prevent unnecessary file tracking. Deleted outdated cleanup documentation files (`AGENT_CLEANUP_COMPLETION.md` and `CLEANUP_PLAN.md`) to streamline the codebase and remove obsolete references. This cleanup supports ongoing refactoring efforts and enhances overall project maintainability.

Remove obsolete test files and enhance agent initialization - Deleted unused test files `test_backend_fixes.py` and `test_query_fix.py` to streamline the codebase. Updated agent initialization in `EnhancedRecommendationService` to include rate limiting for improved API management and performance. This cleanup supports ongoing refactoring efforts and enhances the overall structure of the project.

Remove obsolete test files and refactor agent imports - Deleted unused test files for `test_fix.py` and `test_smart_context.py`. Updated agent imports in `__init__.py` and other files to streamline the codebase and improve maintainability. This cleanup supports ongoing refactoring efforts and enhances the overall structure of the project.

Enhance UnifiedTrackMetadata and Services Module - Added recommendation-specific fields and audio features to UnifiedTrackMetadata for improved track metadata handling. Updated services module to include enhanced API and recommendation services, streamlining workflows and maintaining backward compatibility.

Enhance PlannerAgent with entity recognition and coordination strategies - Implemented enhanced entity recognition and intent analysis in the PlannerAgent, allowing for improved query processing and coordination strategies. Updated the MusicRecommenderState model to include new fields for extracted entities, intent analysis, and conversation context. Enhanced logging and reasoning steps for better traceability during planning. Revised design documentation to reflect these changes and outline future enhancements.

Update dependencies and enhance logging and configuration - Added google-generativeai to pyproject.toml and uv.lock, improved logging in main.py, and updated environment variable loading for better configuration management. Also, refined the .gitignore to include .gradio directory.

Phase 3 Frontend Implementation Complete

Phase 2.3: Update Design Documents and pyproject.toml - Revised design documents to reflect implementation details for JudgeAgent and PlannerAgent, including evaluation framework and diversity targets. Increased line length limit in pyproject.toml for code formatting consistency.

Phase 2.1: Core Agent Infrastructure Complete - PlannerAgent with strategic planning, Pydantic models, BaseAgent class, comprehensive tests (11/11 passing, 90% coverage)

feat: Complete Phase 1 - Foundation and API clients