how to access vector files stored in openai dashboard in livekit

Thanks for reaching out, Harsh. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

i want the agent to use the information stored in vector db and files of openai

I'm glad you're interested in enabling a LiveKit agent to use information stored in a vector database and OpenAI files! A great way to achieve this is by implementing a Retrieval-Augmented Generation (RAG) system. Here's a friendly overview of how it works: 1. Generating Embeddings: You can use OpenAI's

create_embeddings

API to transform your text into high-dimensional vectors, which helps the agent understand the content better. 2. Building a Vector Database: These embeddings are then stored in a vector database, like Annoy, along with metadata to make retrieval smooth and efficient. 3. Runtime Integration: During the agent's operation, you can query this vector database in real time to fetch relevant context. This can be done using function tools or by injecting the retrieved context directly into the agent's system instructions. 4. Enhancing User Experience: Tools such as

RAGHandler

can be really helpful to manage any response delays and keep users informed while the retrieval is happening. If you'd like, I’d be more than happy to walk you through any specific part of this setup—whether it’s generating embeddings, building the database, or integrating everything at runtime. Just let me know how I can assist you best! Sources: examples/voice_agents/llamaindex-rag/query_engine.py | OpenAI LLM integration guide | LiveKit Docs | agent_extensions/agent_extensions/rag/builder.py | rag/rag_handler.py