how to implement RAG functionality in real time ap...
# ask-ai
a
how to implement RAG functionality in real time api just like what you do using RAGLookup in STT/LLM/TTS pipeline
t
Thanks for reaching out, maleek. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.
I'm happy to help you implement Retrieval-Augmented Generation (RAG) functionality in a real-time API, similar to RAGLookup in STT/LLM/TTS pipelines. Here are some approaches you might find useful: • Using `on_user_turn_completed`: This lifecycle hook triggers right after the user finishes speaking but before the agent responds. It’s a great spot to inject RAG-retrieved context directly into the conversation, perfect for keeping things low-latency. • Using Function Tools: You can define a function tool that performs RAG retrieval only when needed. This is especially handy if not every user query requires a RAG lookup or if you want to add some logic before fetching data. • Using
llm_node()
for Manual Context Injection:
This gives you full control over how you format prompts and manage context, which is fantastic for more complex RAG workflows. For some practical examples, I recommend checking out these resources: • LiveKit Docs RAG Example: Shows low-latency lookups using
on_user_turn_completed
. • LlamaIndex RAG Example: Demonstrates integration with LlamaIndex for advanced RAG workflows. If you have any questions or need a hand with the implementation, please don’t hesitate to reach out—I’m here to support you every step of the way! Sources: Pipeline nodes and hooks | LiveKit Docs | External data and RAG | LiveKit Docs | rag/README.md | examples/voice_agents/llamaindex-rag/retrieval.py | delay-handling/README.mdoc
a
for some reason, i don't think that the realtime api agent is quiet detecting on_user_turn_completed()
t
It looks like the
on_user_turn_completed
callback might not be detected in your real-time API agent for a few common reasons. Let’s walk through them together: • Turn Detection Configuration: Please double-check that turn detection is properly set up in your agent, such as using VAD or LiveKit's turn detector plugin. If turn detection is happening on the server side, this callback won’t be triggered. • Server-Side Turn Detection: When the realtime model manages turn detection server-side, the
on_user_turn_completed
callback won’t run. It’s important that turn detection happens within the agent for this callback to work. • Speech Interruption Settings: If your agent is currently generating speech and interruptions aren’t allowed, the callback might be skipped. • Speech Scheduling Paused: Also, if speech scheduling is paused, this callback won’t be executed. Could you please check your turn detection setup to make sure it’s managed by the agent? If you’d like, I’m here to help you review these settings or answer any questions you might have! Sources: Logs, metrics, and telemetry | LiveKit Docs | tests/test_agent_session.py | agents/src/metrics/base.ts | Docs::Agents | Pipeline nodes and hooks | LiveKit Docs
It seems like the
on_user_turn_completed
callback might not be detected in your real-time API agent for a few common reasons. Let’s walk through them together: • Turn Detection Configuration: It’s important to make sure turn detection is properly set up in your agent, such as using VAD or LiveKit’s turn detector plugin. If the realtime model handles turn detection on the server side, the callback won’t be triggered. • Server-Side Turn Detection: When server-side turn detection is enabled in the realtime model, the callback won’t run. For
on_user_turn_completed
to work, turn detection needs to happen within the agent itself. • Speech Interruption Settings: If your agent is generating speech and interruptions aren’t allowed, the callback might be skipped. • Speech Scheduling Paused: Also, if speech scheduling is paused, the callback won’t execute. Could you please double-check your agent’s turn detection setup to ensure it’s not relying on server-side detection? If you’d like, I’m here to help you review these settings or troubleshoot further—just let me know!