Add another cloud-simple example

examples/runner-examples/cloud-simple-bot2.py

@@ -0,0 +1,165 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Pipecat Cloud-compatible bot example.
+
+Transports are Twilio or SmallWebRTC."""
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+from pipecat.runner.cloud import SmallWebRTCSessionArguments
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+
+try:
+    from pipecatcloud.agent import DailySessionArguments, WebSocketSessionArguments
+except ImportError:
+    raise ImportError(
+        "pipecatcloud package is required for cloud-compatible bots. "
+        "Install with: pip install pipecat-ai[pipecatcloud]"
+    )
+
+load_dotenv(override=True)
+
+# Check if we're running locally
+IS_LOCAL_RUN = os.environ.get("LOCAL_RUN", "0") == "1"
+
+
+async def run_bot(transport):
+    """Main bot logic that works with any transport."""
+    logger.info(f"Starting bot")
+
+    stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+    )
+
+    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            rtvi,
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info("Client connected")
+        messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."})
+        await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info("Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=False)
+    await runner.run(task)
+
+
+async def bot(
+    session_args: DailySessionArguments | SmallWebRTCSessionArguments | WebSocketSessionArguments,
+):
+    """Main bot entry point compatible with Pipecat Cloud."""
+
+    if isinstance(session_args, SmallWebRTCSessionArguments):
+        from pipecat.transports.base_transport import TransportParams
+        from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
+
+        transport = SmallWebRTCTransport(
+            params=TransportParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+            webrtc_connection=session_args.webrtc_connection,
+        )
+
+    elif isinstance(session_args, WebSocketSessionArguments):
+        # Use the utility to parse WebSocket data
+        from pipecat.runner.utils import parse_telephony_websocket
+
+        transport_type, stream_id, call_id = await parse_telephony_websocket(session_args.websocket)
+        logger.info(f"Auto-detected transport: {transport_type}")
+
+        # Create transport based on detected type
+        if transport_type == "twilio":
+            from pipecat.serializers.twilio import TwilioFrameSerializer
+
+            serializer = TwilioFrameSerializer(
+                stream_sid=stream_id,
+                call_sid=call_id,
+                account_sid=os.getenv("TWILIO_ACCOUNT_SID", ""),
+                auth_token=os.getenv("TWILIO_AUTH_TOKEN", ""),
+            )
+
+        else:
+            raise ValueError(f"Unsupported WebSocket transport type: {transport_type}")
+
+        # Create the transport
+        from pipecat.transports.network.fastapi_websocket import (
+            FastAPIWebsocketParams,
+            FastAPIWebsocketTransport,
+        )
+
+        transport = FastAPIWebsocketTransport(
+            websocket=session_args.websocket,
+            params=FastAPIWebsocketParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                add_wav_header=False,
+                vad_analyzer=SileroVADAnalyzer(),
+                serializer=serializer,
+            ),
+        )
+
+    await run_bot(transport)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.cloud import main
+
+    main()