bot.py

import os
import asyncio
from fastapi import FastAPI, WebSocket
from dotenv import load_dotenv
from loguru import logger

from pipecat.audio.turn.smart_turn.local_smart_turn_v3 import (
    LocalSmartTurnAnalyzerV3,
)
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
from pipecat.frames.frames import LLMRunFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
    LLMContextAggregatorPair,
    LLMUserAggregatorParams,
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import parse_telephony_websocket
from pipecat.serializers.exotel import ExotelFrameSerializer
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport
from pipecat.transports.websocket.fastapi import (
    FastAPIWebsocketParams,
    FastAPIWebsocketTransport,
)
from pipecat.turns.user_stop import TurnAnalyzerUserTurnStopStrategy
from pipecat.turns.user_turn_strategies import UserTurnStrategies


# -------------------------------------------------------------------
# ENV
# -------------------------------------------------------------------

load_dotenv(override=True)

# -------------------------------------------------------------------
# FASTAPI APP
# -------------------------------------------------------------------

app = FastAPI()


@app.get("/health")
async def health():
    return {"status": "ok"}


# -------------------------------------------------------------------
# CORE BOT LOGIC (unchanged, just wrapped)
# -------------------------------------------------------------------

async def run_bot(transport: BaseTransport, handle_sigint: bool):
    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
    tts = CartesiaTTSService(
        api_key=os.getenv("CARTESIA_API_KEY"),
        voice_id="07bc462a-c644-49f1-baf7-82d5599131be",
    )

    messages = [
        {
            "role": "system",
            "content": """<YOUR FULL SYSTEM PROMPT EXACTLY AS YOU WROTE IT>""",
        }
    ]

    context = LLMContext(messages)

    user_agg, assistant_agg = LLMContextAggregatorPair(
        context,
        user_params=LLMUserAggregatorParams(
            user_turn_strategies=UserTurnStrategies(
                stop=[
                    TurnAnalyzerUserTurnStopStrategy(
                        turn_analyzer=LocalSmartTurnAnalyzerV3()
                    )
                ]
            ),
            vad_analyzer=SileroVADAnalyzer(
                params=VADParams(stop_secs=0.2)
            ),
        ),
    )

    pipeline = Pipeline(
        [
            transport.input(),
            stt,
            user_agg,
            llm,
            tts,
            transport.output(),
            assistant_agg,
        ]
    )

    task = PipelineTask(
        pipeline,
        params=PipelineParams(
            audio_in_sample_rate=8000,
            audio_out_sample_rate=8000,
            enable_metrics=True,
            enable_usage_metrics=True,
        ),
    )

    @transport.event_handler("on_client_connected")
    async def on_connect(transport, client):
        messages.append(
            {
                "role": "system",
                "content": "హలో, నేను స్పందనా స్ఫూర్తి నుంచి ఐషా మాట్లాడుతున్నాను. నేను ప్రజ్వల్ గారితో మాట్లాడుతున్నానా?",
            }
        )
        await task.queue_frames([LLMRunFrame()])

    @transport.event_handler("on_client_disconnected")
    async def on_disconnect(transport, client):
        await task.cancel()

    runner = PipelineRunner(handle_sigint=handle_sigint)
    await runner.run(task)


async def bot(runner_args: RunnerArguments):
    transport_type, call_data = await parse_telephony_websocket(
        runner_args.websocket
    )

    logger.info(f"Transport detected: {transport_type}")

    serializer = ExotelFrameSerializer(
        stream_sid=call_data["stream_id"],
        call_sid=call_data["call_id"],
    )

    transport = FastAPIWebsocketTransport(
        websocket=runner_args.websocket,
        params=FastAPIWebsocketParams(
            audio_in_enabled=True,
            audio_out_enabled=True,
            add_wav_header=False,
            serializer=serializer,
        ),
    )

    await run_bot(transport, handle_sigint=False)


# -------------------------------------------------------------------
# WEBSOCKET ENDPOINT (/media)
# -------------------------------------------------------------------

@app.websocket("/media")
async def media_ws(websocket: WebSocket):
    await websocket.accept()

    runner_args = RunnerArguments(
        websocket=websocket,
        handle_sigint=False,
    )

    await bot(runner_args)