- Add LLM_BACKEND to environment configuration
- Implement detailed debug logging for LLM request/response cycles
- Add missing llama-index dependencies for embeddings and chroma
- Update prompt constraints to prevent lore redundancy
- Enable CUDA for transcription and set logging to DEBUG level
- Add entry point for running the orchestrator directly
- Cleanup unused comment in TUI context updates
- Add RAG capabilities using LlamaIndex and ChromaDB
- Implement RAGManager for PHB indexing and retrieval
- Integrate RAG pipeline into orchestrator to trigger queries based on extracted entities
- Update TUI to include a 3-column layout with a real-time Context Pane
- Define ContextUpdate data models in src/llm/models.py
- Update requirements.txt with new dependencies
Implement a sliding window audio buffer and update the transcriber to
use WhisperX for transcription, alignment, and speaker identification.
Update the pipeline to handle and store speaker-attributed transcripts.
Additionally, update the LLM processor's reasoning parameter to
"enable_thinking".