Implement efficiency improvements: HF endpoint monitoring optimization, Redis connection pooling, API request caching, session management optimization, async processing, model validation caching, and config singleton pattern

Enhanced system initialization, context awareness, and debug information

Implemented timestamp injection at multiple levels to ensure AI always has access to current date/time

Implement hierarchical multi-model conversation architecture with HF as authoritative layer

Adjust Redis connection logic for SSL-first approach, add Hugging Face provider debugging, and update requirements

Fix Redis SSL connection issues and Hugging Face provider deprecated parameters

Fix critical issues: Redis host/port parsing, Ollama URL sanitization, and Hugging Face provider initialization

Fix critical deployment issues: Redis connection, Ollama URL sanitization, Hugging Face provider, config validation, and enhanced error handling

Implement Core LLM Factory Module with provider abstraction and factory pattern