Update file permissions and add documentation for LLM integration

cline_docs/activeContext.md

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+# Active Context
+Last Updated: 2024-12-27
+
+## Current Focus
+Integrating LLM capabilities into the existing Discord bot while maintaining the unique "personality" of each server's Markov-based responses.
+
+### Active Issues
+1. Response Generation
+   - Need to implement hybrid Markov-LLM response system
+   - Must maintain response speed within acceptable limits
+   - Need to handle API rate limiting gracefully
+
+2. Data Management
+   - Implement efficient storage for embeddings
+   - Design context window management
+   - Handle conversation threading
+
+3. Integration Points
+   - Modify generateResponse function to support LLM
+   - Add embedding generation pipeline
+   - Implement context tracking
+
+## Recent Changes
+- Analyzed current codebase structure
+- Identified integration points for LLM
+- Documented system architecture
+- Created implementation plan
+
+## Active Files
+
+### Core Implementation
+- src/index.ts
+  - Main bot logic
+  - Message handling
+  - Command processing
+
+- src/entity/
+  - Database schema
+  - Need to add embedding and context tables
+
+- src/train.ts
+  - Training pipeline
+  - Need to add embedding generation
+
+### New Files Needed
+- src/llm/
+  - provider.ts (LLM service integration)
+  - embedding.ts (Embedding generation)
+  - context.ts (Context management)
+
+- src/entity/
+  - MessageEmbedding.ts
+  - ConversationContext.ts
+
+## Next Steps
+
+### Immediate Tasks
+1. Create database migrations
+   - Add embedding table
+   - Add context table
+   - Update existing message schema
+
+2. Implement LLM integration
+   - Set up OpenAI client
+   - Create response generation service
+   - Add fallback mechanisms
+
+3. Add embedding pipeline
+   - Implement background processing
+   - Set up batch operations
+   - Add storage management
+
+### Short-term Goals
+1. Test hybrid response system
+   - Benchmark response times
+   - Measure coherence
+   - Validate context usage
+
+2. Optimize performance
+   - Implement caching
+   - Add rate limiting
+   - Tune batch sizes
+
+3. Update documentation
+   - Add LLM configuration guide
+   - Update deployment instructions
+   - Document new commands
+
+### Dependencies
+- OpenAI API access
+- Additional storage capacity
+- Updated environment configuration
+
+## Implementation Strategy
+
+### Phase 1: Foundation
+1. Database schema updates
+2. Basic LLM integration
+3. Simple context tracking
+
+### Phase 2: Enhancement
+1. Hybrid response system
+2. Advanced context management
+3. Performance optimization
+
+### Phase 3: Refinement
+1. User feedback integration
+2. Response quality metrics
+3. Fine-tuning capabilities
+
+## Notes
+- Keep existing Markov system as fallback
+- Monitor API usage and costs
+- Consider implementing local LLM option
+- Need to update help documentation
+- Consider adding configuration commands