Advice needed on a specific use case

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You can have a look at these posts to get some ideas on how to approach this using embeddings:

  1. Use embeddings to retrieve relevant context for AI assistant: This tutorial focuses on using embeddings to retrieve relevant context for an AI assistant, building upon a simple chat assistant tutorial with the Chat Completions API.

  2. Embedding past conversation data for context memory & retrieval: This post discusses different approaches for embedding past conversation data into a vector database for semantic query purposes, including fine-tuning or training embeddings models.

  3. Specialized Chatbot with GPT-3: This post breaks down the use of system prompts and embeddings-based retrieval to give a chatbot memory and the ability to provide contextually relevant responses.

  4. Infinity Memory implementation: This post discusses the use of embeddings and/or a vector database to retrieve relevant conversations and manage the indices of messages to remove from the message list to conserve tokens.

Feel free to follow up here if a question is not addressed by these posts.