Thanks — I understand you want the agent (using LiveKit Python + telephony) to transfer the caller to a human but stay in the room, continue listening to the conversation, and produce a summary. Below is a concise, practical plan and example code patterns to implement that behavior. What to do (high level) • Do not close or remove the agent participant from the room when you initiate transfer. Let the agent remain connected as a participant so it can keep receiving audio/transcripts and room events. • Use a cold SIP transfer (SIP REFER) to move the PSTN caller to a human. The transfer will redirect the caller while your agent stays in-room. • Continue collecting transcripts and/or recorded audio from the room after transfer so you can build a final call summary. • When you want the summary, aggregate the collected transcripts/audio and send them to your LLM/summary service. Key implementation steps (with example patterns) 1) Identify and transfer the SIP participant (cold transfer) • Find the SIP participant in the room and call the SIP transfer API. This issues a SIP REFER to your trunk provider and transfers the caller to the target phone number. The agent does not leave the room. Example pattern:

# find SIP participant
sip_participant = None
for p in job_ctx.room.remote_participants.values():
    if p.kind == rtc.ParticipantKind.PARTICIPANT_KIND_SIP:
        sip_participant = p
        break

if not sip_participant:
    return "No SIP caller found to transfer."

# request cold transfer (tel: format)
await job_ctx.api.sip.transfer_sip_participant(
    api.TransferSIPParticipantRequest(
        room_name=job_ctx.room.name,
        participant_identity=sip_participant.identity,
        transfer_to=f"tel:{human_phone}",
    )
)
# agent remains in the room after this call

Notes: • Ensure your SIP trunk/provider supports SIP REFER (some trunks require an explicit setting like “Enable PSTN Transfer”). 2) Keep the agent connected and listening • Do not call session close/shutdown after transfer. Keep background listeners for events active. • Subscribe to transcript events and track events so the agent keeps receiving speech-to-text and notifications when the human joins. Example event handlers:

@session.on("user_input_transcribed")
async def on_transcript(transcript):
    if transcript.is_final:
        call_history.append(transcript.transcript)

@session.on("track_published")
def on_track_published(track, participant):
    if participant.kind == rtc.ParticipantKind.PARTICIPANT_KIND_STANDARD:
        # human has joined — you can start special monitoring if needed
        print(f"Human agent {participant.identity} joined")

3) Collect conversation data for the summary • Maintain a running buffer (call_history) of final transcripts and optionally store audio samples or recordings if you need higher quality for the summary. • Include timestamps and participant identities if you want more structured summaries. 4) Generate the call summary with an LLM • When appropriate (e.g., after some inactivity or when the human signals handoff complete), aggregate the transcripts and request a summary from your LLM. Example pattern:

async def generate_call_summary():
    full_transcript = "\n".join(call_history)
    response = await ctx.llm.chat(
        chat_ctx=[{"role": "user", "content": f"Summarize this call:\n{full_transcript}"}]
    )
    return response.choices[0].message.content

5) Optional: agent publishes audio or interjects • If you want the agent to speak (e.g., announce that it will summarize), keep it publishing an audio track and use TTS to interject into the room. Checklist and gotchas • Do not call

session.close()

or

ctx.shutdown()

if you want the agent to remain and listen. • Confirm your SIP trunk/provider supports SIP REFER / PSTN transfer features. • If you rely on transcripts, ensure your session is configured to receive

user_input_transcribed

events or the appropriate STT stream. • If you need verbatim accuracy, capture and store audio recordings in addition to transcripts. If you want, I can: • Show a full minimal example file wiring up the session lifecycle, transfer call, transcript collection, and summary generation. • Help design how to detect "transfer complete" or when to trigger summary generation (e.g., inactivity timeout, explicit human signal, or a webhook). Which would you like next: the full example code, or help deciding the best trigger to generate the summary? Sources: Agents (Python) | livekit/livekit_composite | DeepWiki | Agents telephony integration | LiveKit Documentation | Agent session | LiveKit Documentation | Company directory phone assistant | LiveKit Documentation