Create an AI Knowledge Assistant with RAG and RLHF via Telegram

The workflow consists of two main components: document ingestion and indexing, and a Telegram chat interface with RLHF. The first component imports product documentation from Google Docs, splits it into manageable chunks, and embeds these chunks using OpenAI embeddings. These embeddings are stored in MongoDB Atlas to enable semantic search. The second component listens for user messages via a Telegram bot, retrieves relevant documentation using vector similarity search, generates responses with OpenAI's model, and sends them back to the user. User feedback is captured and used to refine future responses, ensuring continuous improvement.