NameError: name 'TextInputEvent' is not defined

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

i am trying to create a custom callback for text_input_cb async def on_user_text_message(self, sess: AgentSession, ev: TextInputEvent, turn_ctx: ChatContext) -> None: """Executed after the user's text input is received.""" print("on_user_text_message called.", flush=True) # Debugging print(f"New message received: {ev.text}", flush=True) # Debugging new message user_query = ev.text or "" sess.interrupt() try: retriever = self.index.as_retriever() nodes = await retriever.aretrieve(user_query) retrieved_context = "\n\n".join( node.get_content(metadata_mode=MetadataMode.LLM) for node in nodes ) # Update the agent's instructions dynamically instructions = ( f"Context that might help answer the user's question:\n\n{retrieved_context}\n\n" "You must only use this context to answer the user's query. " "If the query is inconsistent with the context, politely correct the user." ) # Update the agent's instructions print("Updating agent instructions with retrieved context...", flush=True) turn_ctx.add_message( role="assistant", content=f"{instructions}" ) print("Agent instructions updated successfully.", flush=True) # Debugging success await self.update_chat_ctx(turn_ctx) sess.generate_reply(user_input=user_query, allow_interruptions=True) except Exception as error: print(f"Error retrieving context: {error}", flush=True)

It looks like the 'TextInputEvent' class or type isn't defined in your code right now. No worries—let's figure this out together! Could you help me understand a bit more by answering a few questions? • Did you expect 'TextInputEvent' to be a class or type included in LiveKit's SDK or API? • Have you had a chance to import all the necessary modules or dependencies in your code? • Are you working with a specific version of the LiveKit SDK, or perhaps a custom implementation?

i dont know i am new to livekit what i am trying to do is when someone sends a message to agent it should have rag context before it replies to participant so in my entry function i am doing this await session.start( agent=agent, room=ctx.room, room_output_options=RoomOutputOptions( transcription_enabled=True, sync_transcription=False ), room_input_options=RoomInputOptions( noise_cancellation=noise_cancellation.BVC(), text_enabled=True, text_input_cb=agent.on_user_text_message, # Callback for text input ), ) and then to create the rag if there is some other way of doing this i am open to that

I'm glad you're exploring how to implement RAG (Retrieval-Augmented Generation) context in LiveKit with text input callbacks! A great way to do this is by using the

on_user_turn_completed

lifecycle hook. This lets you fetch and add relevant context right before the LLM generates its response. Here's a simple example to guide you:

async def on_user_turn_completed(self, turn_ctx: ChatContext, new_message: ChatMessage) -> None:
    # Perform RAG lookup using the user's message
    rag_content = await my_rag_lookup(new_message.text_content())

    # Add retrieved content to chat context
    turn_ctx.add_message(
        role="assistant",
        content=f"Additional information relevant to the user's next message: {rag_content}"
    )

    # Persist context changes
    await self.update_chat_ctx(turn_ctx)

This method helps ensure that the extra context is smoothly included in the conversation right before the agent replies, making interactions more meaningful. If you're coming from an older LiveKit version, you might also consider using the

llm_node

method. Just let me know if you'd like me to walk you through that or if you need any assistance setting up your RAG system—I’m here to help! Sources: agents/src/voice/room_io/room_io.ts | Pipeline nodes and hooks | LiveKit Docs | rag/rag_handler.py | delay-handling/agent.py | livekit-agents/livekit/agents/voice/room_io/room_io.py

but this function does not work for chat message out of the box i am sending the chat using lk.chat topic from frontend

I'm happy to help you manage chat messages sent using the

lk.chat

topic with LiveKit's text stream API. Here's a simple way to handle this: Sending Chat Messages:

const text = 'Hello, how are you today?';
const info = await room.localParticipant.sendText(text, {
  topic: 'lk.chat',
});

Receiving Chat Messages:

room.registerTextStreamHandler('lk.chat', async (reader, participantInfo) => {
  const message = await reader.readAll();
  console.log(`New message from ${participantInfo.identity}: ${message}`);
});

If you're using LiveKit Agents, they’ll automatically keep an eye on the

lk.chat

topic for any incoming messages and can handle them smoothly. Please feel free to reach out if you'd like assistance integrating this with your RAG setup or if you want to customize the behavior even more—I’m here to help! Sources: Agents v0.x migration guide - Node.js | LiveKit Docs | packages/react/src/hooks/useDataChannel.ts | Text and transcriptions | LiveKit Docs | Text and transcriptions | LiveKit Docs