Does livekit provide knowledge base support or do ...
# ask-aic
creamy-tiger-14805
09/11/2025, 5:30 AMDoes livekit provide knowledge base support or do I have use a rag tool?
t
tall-airline-16756
09/11/2025, 5:30 AMThanks for reaching out, Subham. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
tall-airline-16756
09/11/2025, 5:31 AMThanks so much for reaching out! While LiveKit doesn’t have built-in knowledge base functionality just yet, the good news is that it does support adding this through Retrieval-Augmented Generation (RAG) tools. This means you can create a knowledge base for your LiveKit agents by setting up a vector database like Annoy or LlamaIndex and turning your knowledge content into embeddings.
If you'd like, I’m here to help walk you through implementing RAG or share some examples to get you started. Just let me know!
Sources: agent_extensions/agent_extensions/rag/handler.py | Repository Structure & Data Ingestion | livekit/livekit_composite | DeepWik... | Knowledge Management System | livekit/livekit_composite | DeepWiki | rag/rag_handler.py | External data and RAG | LiveKit Docs
tall-airline-16756
09/11/2025, 5:31 AMI understand you're looking to add knowledge base functionality with LiveKit. While LiveKit doesn’t have this feature built-in, the great news is that you can achieve it by using Retrieval-Augmented Generation (RAG) tools. This means developers can integrate RAG into LiveKit agents to help them pull information from a knowledge base and answer questions more effectively.
For instance, tools like Annoy or LlamaIndex come in handy for creating a vector database. You’d pre-process your knowledge content into embeddings and then connect a RAG handler into your agent’s logic. This setup offers a lot of flexibility for building knowledge-driven agents tailored to your needs.
If you’d like, I’m here to walk you through the details or provide examples to make the setup smoother. Just let me know how I can assist!
c
creamy-tiger-14805
09/11/2025, 5:32 AMCan you give me an example of integrating this into livekit?
t
tall-airline-16756
09/11/2025, 5:32 AMI'd love to help you integrate RAG (Retrieval-Augmented Generation) into LiveKit for your knowledge base! Here's a friendly step-by-step example using the LlamaIndex framework to get you started:
1. Prepare Your Knowledge Base:
◦ Collect all the content you'd like to include, such as documents or articles.
◦ Pre-process this content into embeddings using a tool like LlamaIndex to make it easier to search.
1. Set Up a Vector Database:
◦ Create a vector index, maybe with Annoy or LlamaIndex, to store those embeddings securely.
◦ Make sure this index is accessible by your LiveKit agent so it can retrieve information smoothly.
1. Integrate the RAG Handler:
◦ Build a RAG handler class that will take care of retrieval operations behind the scenes.
◦ This handler will query the vector database and pull out relevant context based on what users ask.
1. Connect to LiveKit Agent:
◦ Register your RAG handler with the LiveKit agent to link everything together.
◦ Configure the agent to use the retrieved context so it can generate helpful and accurate responses.
LiveKit also offers some great example implementations, like the LlamaIndex RAG example, which shows you exactly how to build and query a knowledge base. If you'd like, I’m here to provide more detailed guidance or share additional resources—just let me know!