chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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"""Minimal FastAPI server for handling OpenAI Realtime SIP calls with Twilio."""
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from __future__ import annotations
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import asyncio
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import logging
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import os
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import websockets
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from fastapi import FastAPI, HTTPException, Request, Response
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from openai import APIStatusError, AsyncOpenAI, InvalidWebhookSignatureError
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from agents.realtime.config import RealtimeSessionModelSettings
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from agents.realtime.items import (
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AssistantAudio,
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AssistantMessageItem,
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AssistantText,
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InputText,
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UserMessageItem,
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)
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from agents.realtime.model_inputs import RealtimeModelSendRawMessage
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from agents.realtime.openai_realtime import OpenAIRealtimeSIPModel
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from agents.realtime.runner import RealtimeRunner
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from .agents import WELCOME_MESSAGE, get_starting_agent
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger("twilio_sip_example")
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def _get_env(name: str) -> str:
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value = os.getenv(name)
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if not value:
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raise RuntimeError(f"Missing environment variable: {name}")
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return value
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OPENAI_API_KEY = _get_env("OPENAI_API_KEY")
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OPENAI_WEBHOOK_SECRET = _get_env("OPENAI_WEBHOOK_SECRET")
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client = AsyncOpenAI(api_key=OPENAI_API_KEY, webhook_secret=OPENAI_WEBHOOK_SECRET)
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# Build the multi-agent graph (triage + specialist agents) from agents.py.
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assistant_agent = get_starting_agent()
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app = FastAPI()
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# Track background tasks so repeated webhooks do not spawn duplicates.
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active_call_tasks: dict[str, asyncio.Task[None]] = {}
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async def accept_call(call_id: str) -> None:
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"""Accept the incoming SIP call and configure the realtime session."""
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# The starting agent uses static instructions, so we can forward them directly to the accept
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# call payload. If someone swaps in a dynamic prompt, fall back to a sensible default.
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instructions_payload = (
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assistant_agent.instructions
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if isinstance(assistant_agent.instructions, str)
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else "You are a helpful triage agent for ABC customer service."
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)
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try:
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# AsyncOpenAI does not yet expose high-level helpers like client.realtime.calls.accept, so
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# we call the REST endpoint directly via client.post(). Keep this until the SDK grows an
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# async helper.
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await client.post(
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f"/realtime/calls/{call_id}/accept",
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body={
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"type": "realtime",
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"model": "gpt-realtime-2.1",
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"instructions": instructions_payload,
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},
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cast_to=dict,
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)
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except APIStatusError as exc:
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if exc.status_code == 404:
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# Twilio occasionally retries webhooks after the caller hangs up; treat as a no-op so
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# the webhook still returns 200.
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logger.warning(
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"Call %s no longer exists when attempting accept (404). Skipping.", call_id
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)
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return
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detail = exc.message
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if exc.response is not None:
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try:
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detail = exc.response.text
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except Exception: # noqa: BLE001
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detail = str(exc.response)
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logger.error("Failed to accept call %s: %s %s", call_id, exc.status_code, detail)
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raise HTTPException(status_code=500, detail="Failed to accept call") from exc
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logger.info("Accepted call %s", call_id)
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async def observe_call(call_id: str) -> None:
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"""Attach to the realtime session and log conversation events."""
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runner = RealtimeRunner(assistant_agent, model=OpenAIRealtimeSIPModel())
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try:
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initial_model_settings: RealtimeSessionModelSettings = {
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"turn_detection": {
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"type": "semantic_vad",
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"interrupt_response": True,
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}
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}
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async with await runner.run(
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model_config={
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"call_id": call_id,
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"initial_model_settings": initial_model_settings,
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}
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) as session:
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# Trigger an initial greeting so callers hear the agent right away.
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# Issue a response.create immediately after the WebSocket attaches so the model speaks
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# before the caller says anything. Using the raw client message ensures zero latency
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# and avoids threading the greeting through history.
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await session.model.send_event(
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RealtimeModelSendRawMessage(
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message={
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"type": "response.create",
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"other_data": {
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"response": {
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"instructions": (
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"Say exactly '"
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f"{WELCOME_MESSAGE}"
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"' now before continuing the conversation."
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)
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}
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},
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}
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)
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)
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async for event in session:
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if event.type == "history_added":
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item = event.item
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if isinstance(item, UserMessageItem):
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for user_content in item.content:
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if isinstance(user_content, InputText) and user_content.text:
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logger.info("Caller: %s", user_content.text)
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elif isinstance(item, AssistantMessageItem):
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for assistant_content in item.content:
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if (
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isinstance(assistant_content, AssistantText)
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and assistant_content.text
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):
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logger.info("Assistant (text): %s", assistant_content.text)
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elif (
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isinstance(assistant_content, AssistantAudio)
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and assistant_content.transcript
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):
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logger.info(
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"Assistant (audio transcript): %s",
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assistant_content.transcript,
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)
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elif event.type == "error":
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logger.error("Realtime session error: %s", event.error)
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except websockets.exceptions.ConnectionClosedError:
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# Callers hanging up causes the WebSocket to close without a frame; log at info level so it
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# does not surface as an error.
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logger.info("Realtime WebSocket closed for call %s", call_id)
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except Exception as exc: # noqa: BLE001 - demo logging only
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logger.exception("Error while observing call %s", call_id, exc_info=exc)
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finally:
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logger.info("Call %s ended", call_id)
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active_call_tasks.pop(call_id, None)
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def _track_call_task(call_id: str) -> None:
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existing = active_call_tasks.get(call_id)
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if existing:
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if not existing.done():
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logger.info(
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"Call %s already has an active observer; ignoring duplicate webhook delivery.",
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call_id,
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)
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return
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# Remove completed tasks so a new observer can start for a fresh call.
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active_call_tasks.pop(call_id, None)
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task = asyncio.create_task(observe_call(call_id))
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active_call_tasks[call_id] = task
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@app.post("/openai/webhook")
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async def openai_webhook(request: Request) -> Response:
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body = await request.body()
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try:
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event = client.webhooks.unwrap(body, request.headers)
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except InvalidWebhookSignatureError as exc:
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raise HTTPException(status_code=400, detail="Invalid webhook signature") from exc
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if event.type == "realtime.call.incoming":
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call_id = event.data.call_id
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await accept_call(call_id)
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_track_call_task(call_id)
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return Response(status_code=200)
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# Ignore other webhook event types for brevity.
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return Response(status_code=200)
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@app.get("/")
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async def healthcheck() -> dict[str, str]:
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return {"status": "ok"}
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