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

from dotenv import load_dotenv from livekit.agents import Agent, AgentSession, JobContext, WorkerOptions, cli from livekit.plugins import openai # load environment variables (LIVEKIT_URL, API key/secret) load_dotenv() class ChatAgent(Agent): def __init__(self): super().__init__( instructions="You are a helpful text-only chat assistant.", llm=openai.LLM(model="gpt-4o-mini"), # your chosen LLM ) async def entrypoint(ctx: JobContext): # connect the agent to the LiveKit room await ctx.connect() # create the ChatAgent instance agent = ChatAgent() # create a text-only session session = AgentSession( llm=agent.llm, # only use the LLM stt=None, # no speech-to-text tts=None # no text-to-speech ) # start the agent session inside the room await session.start(agent=agent, room=ctx.room) def run(): cli.run_app( WorkerOptions( entrypoint_fnc=entrypoint, agent_name="chat-agent", # must match dispatch port=8084, # worker port ) ) if name == "__main__": run()export const connectChatAgent = asyncHandler(async (req: Request, res: Response) => { const { room_name } = req.body; await LiveKitService.createDispatch(room_name, "chat-agent", JSON.stringify({ some: "data" })); res.json({ room: room_name }); }); export const generateChatToken = asyncHandler(async (req: Request, res: Response) => { const { room_name, participant_name } = req.body; try { const jwt = await LiveKitService.createToken(room_name, participant_name); res.json({ token: jwt, room_name, url: LiveKitService.LIVEKIT_URL }); } catch (err) { console.error(err); res.status(500).json({ error: 'Token generation failed' }); } });

Thanks — I see your code for a text-only LiveKit agent (Python) plus two Node endpoints for dispatch and token creation. What would you like help with? A few common things I can assist with: • Debugging runtime errors (paste the error text and any stack trace). • Verifying agent registration / dispatch flow so the worker actually joins the room. • Troubleshooting token generation or authentication (include the LiveKitService/createToken implementation if possible). • Ensuring the agent connects to the right room and starts the session. • Making the session use only LLM (no STT/ TTS) and confirming message routing. • Deployment and networking issues (ports, env vars like LIVEKIT_URL, API key/secret). To help quickly, please share one of the following: • Any error messages or logs you’re seeing (worker logs, server logs, browser console). • The implementation of LiveKitService.createDispatch and createToken (or describe what they do). • The contents of relevant environment variables (redact secrets) and how you start the worker. • The exact behavior you expect vs. what actually happens (e.g., agent never joins, token denied, messages not delivered). If you don’t have errors and want a quick checklist to verify the flow, tell me and I’ll provide it.

{!chatRoomData ? ( <Button onClick={handleChatConnect}>Connect Chat</Button> ) : ( <div className="chat-container w-full h-96 border rounded-lg overflow-hidden"> <LiveKitRoom serverUrl={chatRoomData.url} token={chatRoomData.token} connect={true} data-lk-theme="default" > <Chat /> </LiveKitRoom> </div> )} </div> ntow gettin reply

Thanks — I’m here to help get your chat replies working. I’m responding to your last message which shows your frontend rendering the LiveKitRoom and Chat UI but says “not getting reply.” To diagnose, I need a few targeted details and logs so we can narrow the problem down quickly. Please provide the following: 1. What happens when you click “Connect Chat”? ◦ Does the Connect button disappear and the chat UI render (it looks like it does from your snippet)? ◦ Do you see the participant in the UI (your name) or any “connected” indicator? 1. Browser console logs (copy-paste any errors/warnings). ◦ Look for errors from LiveKit SDK or network failures (CORS, 401/403, WebSocket issues). 1. Frontend LiveKit SDK logs. ◦ If you can, enable debug logging in the browser (e.g., set log level) and paste the output around the connection and message-send time. 1. Agent/worker logs (the Python agent process). ◦ After you call

LiveKitService.createDispatch

, does the worker log show it received the dispatch, connected to the room, and started the session? Any error trace or warnings are important. 1. Confirmation the dispatch call succeeded. ◦ Did

LiveKitService.createDispatch(room_name, "chat-agent", ...)

return without error? Any response or exception from that call? 1. Do you see the agent as a participant in the room? ◦ Check the LiveKit dashboard or participant list. If the agent isn’t joining, that explains no replies. 1. How are messages sent from the user? ◦ Are you using the built-in Chat component from the LiveKit React SDK (which uses

localParticipant.sendText

) or a custom send? If custom, paste the send code. 1. Agent/room configuration snippets (if changed): ◦ Any RoomOptions/RoomInputOptions you set, or did you rely on defaults? Confirm dispatch name matches

agent_name="chat-agent"

in the worker and your createDispatch call uses

"chat-agent"

. 1. Versions you’re using: ◦ livekit-js (React SDK) version and livekit-agents package + Python SDK version. What I’ll check once you provide logs: • If the dispatch never reaches the worker, we’ll see that in your backend or agent logs. • If the worker receives the dispatch but the agent fails to join, the agent logs will show connection/auth errors. • If the agent joins but doesn’t reply, we’ll inspect agent lifecycle hooks and whether text input is enabled (text input is enabled by default, but confirm you didn’t disable it in session/room options). • If the frontend sends messages but they’re not delivered, the browser logs or network trace will show it. If you paste console logs and the relevant agent worker logs (just the lines around the time you press Connect and send a message), I’ll pinpoint the next steps and provide exact fixes.

Messages • *d94f6ab5-d47b-4f63-89ea-1cd0d0026be1-user*16:32hi • 16:35hi no reply

Thanks — I can see messages are reaching the room but the agent isn’t replying. I’ll help you narrow this down. I need a few targeted checks and small logs so we can identify where it’s failing. Please do the following and paste the results (or tell me what you see): 1. Confirm the agent joined the room ◦ In your app or LiveKit dashboard, do you see a participant for the agent (often named like your

agent_name

or the worker identity)? If you don’t see the agent as a participant, the agent never connected. 1. Agent / worker logs (most important) ◦ From the Python worker process that runs your ChatAgent, copy the logs for the timeframe when you clicked Connect and sent the two “hi” messages. Look for lines showing: ▪︎ Received dispatch or dispatch accepted ▪︎ Worker connecting to LiveKit (success or error) ▪︎ Session start or any exceptions ◦ Paste any error traces or warnings you find. 1. Frontend console logs and network status ◦ Open the browser console, click Connect, then send a chat message. Copy any console errors/warnings. ◦ In the browser devtools Network / WS tab, check the WebSocket connection to LiveKit — is it open (status 101) or closed/errored? Any HTTP 4xx/5xx responses when requesting the token or connecting? 1. Verify dispatch call returned success ◦ Did your backend call to

LiveKitService.createDispatch(room_name, "chat-agent", ...)

succeed (no exception)? Share the response or server log around that API call. 1. Confirm agent session config ◦ In your Python snippet you used: ▪︎

session = AgentSession(llm=agent.llm, stt=None, tts=None)

▪︎ Confirm

AgentSession.start(...)

completed without error in the worker logs. ◦ Also confirm the worker was started with

agent_name="chat-agent"

(your dispatch must match this exactly). 1. How messages are sent from the frontend ◦ Are you using the LiveKit React Chat component (the built-in

<Chat />

) or custom code to send messages? If custom, paste the send snippet (e.g., call to

localParticipant.sendText(...)

). What I’ll check once you paste logs or answers: • If there’s no agent participant, we’ll focus on dispatch/token/auth issues. • If the agent joined but logs show no incoming chat events, we’ll verify room input is enabled and the agent’s lifecycle hooks (entrypoint, on_user_turn) are running. • If the agent received messages but didn’t respond, I’ll help inspect the agent code/LLM call and confirm text output is being sent. If you paste: • The worker logs (around connect/dispatch), • A short copy of the browser console around connect/send, • And confirm whether the agent appears as a participant — I’ll give exact next steps and a likely fix.

from datetime import datetime import json import time from dotenv import load_dotenv from livekit import api from livekit.agents import Agent, JobContext, JobProcess, WorkerOptions, cli, function_tool from livekit.agents.voice import AgentSession from livekit.plugins import silero from agents.functions.function_builder import function_builder from agents.utils import get_llm_from_config, get_stt_from_config, get_tts_from_config, inactivity_handler from agents.utils import WELCOME_MESSAGE, OUTBOUND_MESSAGE, END_CALL_PROMPT from agents.utils import get_all_metadata, get_all_instructions, substitute_variables, get_interruption_params from agents.services.call_recording import CallRecordingService from agents.api import end_call from agents.rag import get_embed_model load_dotenv() def prewarm(proc: JobProcess): proc.userdata["vad"] = silero.VAD.load() proc.userdata["embedding_model"] = get_embed_model() class VoiceAgent(Agent): def __init__(self, ctx, meta_data, variables=None, call_metadata=None): self.ctx = ctx self.rag = meta_data['rag'] super().__init__( instructions=get_all_instructions(meta_data['agent'], variables), stt=get_stt_from_config(meta_data['stt']), llm=get_llm_from_config(meta_data['llm']), tts=get_tts_from_config(meta_data['tts']), tools=function_builder(meta_data['functions'], call_metadata) ) async def on_user_turn_completed(self, turn_ctx, new_message) -> None: if not self.rag: return query = new_message.text_content if not query or len(query) < 3: return rag_content = await self.rag.query(query) if rag_content: turn_ctx.add_message( role="assistant", content=f"[Knowledge Base Context]: {rag_content}" ) @function_tool(description=f"{END_CALL_PROMPT}") async def end_call_on_user_request(self) -> str: self.ctx.shutdown() return json.dumps({"status": "session shutdown initiated"}, indent=2) async def entrypoint(ctx: JobContext): meta_data = await get_all_metadata(ctx) dial_info = meta_data.get('dial_info', {}) to_number = dial_info.get('to_number') from_number = dial_info.get('from_number') sip_trunk_id = dial_info.get('sip_trunk_id') variables = dial_info.get('variables', {}) is_outbound = bool(to_number) if is_outbound: if not sip_trunk_id: ctx.shutdown() return try: await ctx.api.sip.create_sip_participant( api.CreateSIPParticipantRequest( room_name=ctx.room.name, sip_trunk_id=sip_trunk_id, sip_call_to=to_number, participant_identity=to_number, participant_name=f"Call to {to_number}", krisp_enabled=True, wait_until_answered=True, ) ) except api.TwirpError as e: ctx.shutdown() return is_telephony = True channel = "PHONE" else: await ctx.connect() is_telephony = False for participant in ctx.room.remote_participants.values(): if hasattr(participant, 'attributes') and participant.attributes: attrs = participant.attributes sip_phone = attrs.get('sip.phoneNumber') if sip_phone: from_number = sip_phone to_number = attrs.get('sip.trunkPhoneNumber') is_telephony = True break channel = "PHONE" if is_telephony else "WEB" call_metadata = { "from_number": from_number if is_telephony else None, "to_number": to_number if is_telephony else None, "call_type": channel, "direction": "OUTBOUND" if is_outbound else "INBOUND" if is_telephony else None, } agent = VoiceAgent(ctx, meta_data, variables, call_metadata) agent_data = meta_data['agent'] interruption_sensitivity = agent_data.get('interruption_sensitivity', 0.5) min_interruption_duration, false_interruption_timeout = get_interruption_params(interruption_sensitivity) session = AgentSession( vad=ctx.proc.userdata.get("vad"), preemptive_generation=False, min_interruption_duration=min_interruption_duration, false_interruption_timeout=false_interruption_timeout, ) inactivity_handler(session, ctx) start_time = datetime.now() recorder = CallRecordingService() await recorder.start_recording( room_name=ctx.room.name, filename=f"{ctx.room.name}_{int(time.time())}.ogg", ) await session.start(agent=agent, room=ctx.room) if is_telephony and is_outbound: greeting = agent_data.get('greeting_message', OUTBOUND_MESSAGE) else: greeting = agent_data.get('greeting_message', WELCOME_MESSAGE) greeting = substitute_variables(greeting, variables) await session.say(greeting) async def on_session_end(): recording_url = await recorder.stop_and_wait() end_call_data = { "session_id": ctx.job.id, "started_at": start_time.isoformat(), "ended_at": datetime.now().isoformat(), "transcript": json.dumps(session.history.to_dict() if hasattr(session, "history") else {"items": []}, indent=2), "agent_id": agent_data.get('id'), "client_id": agent_data.get('client_id'), "recording_url": recording_url, "direction": "OUTBOUND" if is_outbound else "INBOUND" if is_telephony else None, "channel": channel, "from_number": from_number if is_telephony else None, "to_number": to_number if is_telephony else None, } try: await end_call(end_call_data) except Exception as e: print(f"Error logging call: {e}") try: ctx.delete_room(ctx.room.name) except Exception as e: print(f"Error deleting room: {e}") ctx.add_shutdown_callback(on_session_end) def run(): cli.run_app( WorkerOptions( entrypoint_fnc=entrypoint, prewarm_fnc=prewarm, agent_name="voice-agent", port=8082, num_idle_processes=2, ) ) if name == "__main__": run() gve full code

Thanks — I can see you want a working, text-only LiveKit chat agent and that messages reach the room but the agent isn’t replying. I reviewed your agent code and the voice/voice-like agent you showed. Below I’ll: • Confirm what’s likely missing • Give a minimal, corrected text-only agent implementation (Python) • Show the frontend points you must check to send/receive text • List quick diagnostics to paste back if this still doesn’t work What’s likely happening • The agent process may not be starting in “text-only” room mode; audio is enabled by default and audio tracks can be processed even if

stt=None

/

tts=None

. That prevents the agent from being configured strictly as a text-only responder. • The frontend must send user chat messages on the

lk.chat

topic and the client must listen for the agent’s replies (which the SDK delivers via text streams such as

lk.transcription

). • Dispatch name and worker

agent_name

must match exactly so the worker actually joins the room. Minimal corrected text-only ChatAgent (Python) • This example explicitly disables audio and enables text I/O when starting the session.

from dotenv import load_dotenv
import logging
from livekit.agents import Agent, AgentSession, JobContext, WorkerOptions, cli, room_io
from livekit.plugins import openai

load_dotenv()

logger = logging.getLogger("chat-agent")
logger.setLevel(<http://logging.INFO|logging.INFO>)

class ChatAgent(Agent):
    def __init__(self):
        super().__init__(
            instructions="You are a helpful text-only chat assistant.",
            llm=openai.LLM(model="gpt-4o-mini"),
        )

async def entrypoint(ctx: JobContext):
    <http://logger.info|logger.info>(f"Entrypoint starting for room: {ctx.room.name}")
    await ctx.connect()

    agent = ChatAgent()

    session = AgentSession(
        llm=agent.llm,
        stt=None,   # no speech-to-text
        tts=None,   # no text-to-speech
    )

    # IMPORTANT: explicitly set RoomOptions for text-only
    await session.start(
        agent=agent,
        room=ctx.room,
        room_options=room_io.RoomOptions(
            audio_input=False,    # disable mic publishing
            audio_output=False,   # disable TTS/audio output
            text_input=True,      # enable text input
            text_output=True,     # enable text output
        ),
    )

    <http://logger.info|logger.info>("Text-only agent session started")

def run():
    cli.run_app(
        WorkerOptions(
            entrypoint_fnc=entrypoint,
            agent_name="chat-agent",  # must match createDispatch() target
            port=8084,
        )
    )

if __name__ == "__main__":
    run()

Frontend: send and receive text correctly • Sending text (example using livekit-js / room API):

// send a message to the room on the chat topic
await room.localParticipant.sendText("hi", { topic: "lk.chat" });

• Receiving agent replies (listen to transcription/text streams):

room.registerTextStreamHandler("lk.transcription", async (reader, participantInfo) => {
  const text = await reader.readAll();
  console.log("Agent reply:", text);
});

Important checks (quick) • Confirm your backend call to createDispatch uses the exact agent name:

"chat-agent"

. • Verify the worker logs: when you call createDispatch you should see the worker accept the dispatch and then log connection / "session started" messages. • Confirm the agent appears as a participant in the room (check participant list or LiveKit dashboard). • Confirm the frontend actually calls

sendText(..., { topic: "lk.chat" })

and not a different topic. • Ensure your client listens to

lk.transcription

(or registered text streams) to show the agent’s reply; the Playgrounds may not surface text-only replies. If it still doesn’t reply — what to paste here • The worker logs (lines around dispatch handling, session.start, and any exceptions). • A short browser console log around when you click Connect and send a chat (any errors or warnings). • Confirmation whether the agent shows up in the room participant list after dispatch. • The exact

createDispatch(...)

call or server log response. If you paste those logs I’ll pinpoint the failure (dispatch/auth, agent joining, text stream routing, or LLM error) and give exact next steps. Sources: Agent session | LiveKit Documentation | Text and transcriptions | LiveKit Documentation | How to Set Up Speech-to-Text Input with Text-Only Output in LiveKit Agents | How to build an agent with speech-to-text input and text-only output | Live...

{ "token": "eyJhbGciOiJIUzI1NiJ9.eyJuYW1lIjoiYTMyNWNhNzUtZGNkNy00YzBhLWFhZjktZDgzMjM1MDRhOTJjLXVzZXIiLCJ2aWRlbyI6eyJyb29tSm9pbiI6dHJ1ZSwicm9vbSI6IjVlM2RiMGNlLWUzZmUtNGZlMS04ZTJhLWIyY2E2ZjE2N2FkNiIsImNhblB1Ymxpc2giOnRydWUsImNhblN1YnNjcmliZSI6dHJ1ZX0sImlzcyI6IkFQSU5qTHJHSjhub3FqYSIsImV4cCI6MTc3MTI2MTg5MywibmJmIjowLCJzdWIiOiJhMzI1Y2E3NS1kY2Q3LTRjMGEtYWFmOS1kODMyMzUwNGE5MmMtdXNlciJ9.sHYlN0LUXJiyLP63rgMe6ZghEFapO-2dBb0rmc0B83Q", "room_name": "5e3db0ce-e3fe-4fe1-8e2a-b2ca6f167ad6", "url": "" }<div className="mt-6"> {!chatRoomData ? ( <Button onClick={handleChatConnect}>Connect Chat</Button> ) : ( <div className="chat-container w-full h-96 border rounded-lg overflow-hidden"> <LiveKitRoom serverUrl={chatRoomData.url} token={chatRoomData.token} connect={true} data-lk-theme="default" > <Chat > </Chat> </LiveKitRoom> </div> )} </div> nto worinhg

Thanks — I can see messages are reaching the room but the agent isn’t replying. You’ve given the agent code and frontend snippet, so here’s a focused checklist and a minimal, corrected text-only agent plus the exact frontend points you must verify. Quick summary of the likely cause • Setting

stt=None

and

tts=None

disables STT/TTS pipelines but does NOT automatically disable audio tracks. Audio is enabled by default and can keep the agent from operating as a pure text responder. You must explicitly disable audio input/output when starting the session. • The frontend must send text on the

lk.chat

topic (the Chat component does this) and must listen for agent replies (sent as text streams such as

lk.transcription

). • Dispatch name (createDispatch target) must exactly match the worker’s

agent_name

. Minimal corrected text-only ChatAgent (Python) • This explicitly disables audio and enables text I/O when starting the session.

from dotenv import load_dotenv
import logging
from livekit.agents import Agent, AgentSession, JobContext, WorkerOptions, cli, room_io
from livekit.plugins import openai

load_dotenv()
logger = logging.getLogger("chat-agent")
logger.setLevel(<http://logging.INFO|logging.INFO>)

class ChatAgent(Agent):
    def __init__(self):
        super().__init__(
            instructions="You are a helpful text-only chat assistant.",
            llm=openai.LLM(model="gpt-4o-mini"),
        )

async def entrypoint(ctx: JobContext):
    <http://logger.info|logger.info>(f"Entrypoint for room: {ctx.room.name}")
    await ctx.connect()

    agent = ChatAgent()

    session = AgentSession(
        llm=agent.llm,
        stt=None,
        tts=None,
    )

    # IMPORTANT: explicitly force text-only room options
    await session.start(
        agent=agent,
        room=ctx.room,
        room_options=room_io.RoomOptions(
            audio_input=False,   # disable publishing mic / STT path
            audio_output=False,  # disable TTS/audio output
            text_input=True,     # enable text input from users
            text_output=True,    # enable text output from agent
        ),
    )
    <http://logger.info|logger.info>("Text-only agent session started")

def run():
    cli.run_app(
        WorkerOptions(
            entrypoint_fnc=entrypoint,
            agent_name="chat-agent",  # must match createDispatch target
            port=8084,
        )
    )

if __name__ == "__main__":
    run()

Frontend: what to send and what to listen for • If you use the LiveKit React

Chat

component it will send user messages with topic

lk.chat

automatically. • If you send messages yourself, use: ◦ await room.localParticipant.sendText("hi", { topic: "lk.chat" }); • To receive agent replies, listen for the transcription/text stream (agent responses are published as text streams like

lk.transcription

):

room.registerTextStreamHandler("lk.transcription", async (reader, participantInfo) => {
  const text = await reader.readAll();
  console.log("Agent reply:", text);
});

Note: the LiveKit playground may not show text-only replies; use the React Chat component or a custom listener as above. Checklist / Diagnostics to run right now 1. Confirm your worker logs show the dispatch accepted and "Text-only agent session started". 2. Confirm the agent appears as a participant in the room after createDispatch. 3. Confirm your createDispatch call used the exact agent name

"chat-agent"

. 4. In browser console, confirm: ◦ token request succeeded (no 4xx/5xx) ◦ WebSocket to LiveKit is open (101) ◦ No CORS / auth errors 1. Confirm you can send text from the client: ◦ If using Chat component, type & send — check network or console to see a sendText event. ◦ If custom, ensure you call sendText(..., { topic: "lk.chat" }). 1. Paste these logs if it still fails: ◦ Worker log lines around dispatch & session.start ◦ Browser console logs around connect/send ◦ Whether the agent participant is visible in the room If you share the worker logs for the dispatch attempt and a short browser console capture when you press Connect and send “hi”, I’ll pinpoint whether the dispatch never reached the worker, the worker failed to join, the agent started but didn’t receive chat events, or the replies are being published but not shown by the frontend — and I’ll give exact next steps. Sources: How to build an agent with speech-to-text input and text-only output | Live... | Text and transcriptions | LiveKit Documentation