Add quickstart examples

examples/quickstart/README.md

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+## Quickstart
+
+### Setup
+
+1. Set up a venv
+
+2. Install packages
+
+pip install "pipecat-ai[webrtc,deepgram,openai,cartesia,silero]" \
+ "pipecat-ai-small-webrtc-prebuilt" \
+ "python-dotenv"
+
+3. Configure environment variables
+
+Create a `.env` file:
+
+```bash
+cp env.example .env
+```
+
+Then, add your API keys:
+
+```
+DEEPGRAM_API_KEY=your_deepgram_api_key
+OPENAI_API_KEY=your_openai_api_key
+CARTESIA_API_KEY=your_cartesia_api_key
+```
+
+4. Run the example
+
+```bash
+python bot.py
+```

examples/quickstart/env.example

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+DEEPGRAM_API_KEY=your_deepgram_api_key
+OPENAI_API_KEY=your_openai_api_key
+CARTESIA_API_KEY=your_cartesia_api_key

examples/quickstart/local-multi-transport-bot.py

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+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+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.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, TransportParams
+
+load_dotenv(override=True)
+
+
+def create_transport_params(transport_name):
+    """Create transport parameters based on transport name."""
+    base_config = {
+        "audio_in_enabled": True,
+        "audio_out_enabled": True,
+        "vad_analyzer": SileroVADAnalyzer(),
+    }
+
+    if transport_name == "daily":
+        from pipecat.transports.services.daily import DailyParams
+
+        return DailyParams(**base_config)
+    elif transport_name == "livekit":
+        from pipecat.transports.services.livekit import LiveKitParams
+
+        return LiveKitParams(**base_config)
+    elif transport_name in ["plivo", "telnyx", "twilio"]:
+        from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
+
+        return FastAPIWebsocketParams(**base_config)
+    else:  # webrtc
+        return TransportParams(**base_config)
+
+
+async def run_bot(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    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 helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        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(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.runner2.run import main
+
+    transport_params = {
+        transport: lambda t=transport: create_transport_params(t)
+        for transport in ["daily", "livekit", "plivo", "telnyx", "twilio", "webrtc"]
+    }
+
+    main(run_bot, transport_params=transport_params)

examples/quickstart/local-simple-bot.py

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+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import argparse
+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.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, TransportParams
+
+load_dotenv(override=True)
+
+
+async def run_bot(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
+    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 helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+        },
+    ]
+
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            stt,
+            context_aggregator.user(),  # User responses
+            llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info(f"Client connected")
+        # Kick off the conversation.
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        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(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    transport_params = {
+        "webrtc": lambda: TransportParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+        ),
+    }
+
+    main(run_bot, transport_params=transport_params)

examples/quickstart/pcc-multi-bot.py

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+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+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 PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+
+load_dotenv(override=True)
+
+
+async def run_bot_logic(transport, handle_sigint: bool = True):
+    """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)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(pipeline)
+
+    @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=handle_sigint)
+    await runner.run(task)
+
+
+async def bot(session_args):
+    """Main bot entry point compatible with Pipecat Cloud."""
+
+    # Get handle_sigint from session_args, default to True for Daily
+    handle_sigint = getattr(session_args, "handle_sigint", True)
+
+    if hasattr(session_args, "room_url") and hasattr(session_args, "token"):
+        # Daily session arguments (cloud or local)
+        from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+        transport = DailyTransport(
+            session_args.room_url,
+            session_args.token,
+            "Pipecat Bot",
+            params=DailyParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+    elif hasattr(session_args, "webrtc_connection"):
+        # WebRTC session arguments (local only, created by server.py)
+        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 hasattr(session_args, "websocket"):
+        # WebSocket session arguments (for telephony providers)
+        from pipecat.transports.network.fastapi_websocket import (
+            FastAPIWebsocketParams,
+            FastAPIWebsocketTransport,
+        )
+
+        # Create appropriate serializer based on transport type
+        params = FastAPIWebsocketParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            add_wav_header=False,
+        )
+
+        if session_args.transport_type == "twilio":
+            from pipecat.serializers.twilio import TwilioFrameSerializer
+
+            call_info = session_args.call_info
+            params.serializer = TwilioFrameSerializer(
+                stream_sid=call_info["stream_sid"],
+                call_sid=call_info["call_sid"],
+                account_sid=os.getenv("TWILIO_ACCOUNT_SID", ""),
+                auth_token=os.getenv("TWILIO_AUTH_TOKEN", ""),
+            )
+        elif session_args.transport_type == "telnyx":
+            from pipecat.serializers.telnyx import TelnyxFrameSerializer
+
+            call_info = session_args.call_info
+            params.serializer = TelnyxFrameSerializer(
+                stream_id=call_info["stream_id"],
+                call_control_id=call_info["call_control_id"],
+                outbound_encoding=call_info["outbound_encoding"],
+                inbound_encoding="PCMU",
+            )
+        elif session_args.transport_type == "plivo":
+            from pipecat.serializers.plivo import PlivoFrameSerializer
+
+            call_info = session_args.call_info
+            params.serializer = PlivoFrameSerializer(
+                stream_id=call_info["stream_id"],
+                call_id=call_info["call_id"],
+            )
+        else:
+            raise ValueError(f"Unsupported WebSocket transport type: {session_args.transport_type}")
+
+        transport = FastAPIWebsocketTransport(websocket=session_args.websocket, params=params)
+
+    else:
+        raise ValueError(f"Unknown session arguments: {session_args}")
+
+    await run_bot_logic(transport, handle_sigint)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.server import main
+
+    main()

examples/quickstart/pcc-simple-bot.py

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+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+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 PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.deepgram.stt import DeepgramSTTService
+from pipecat.services.openai.llm import OpenAILLMService
+
+load_dotenv(override=True)
+
+
+async def run_bot_logic(transport, handle_sigint: bool = True):
+    """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)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    task = PipelineTask(pipeline)
+
+    @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=handle_sigint)
+    await runner.run(task)
+
+
+async def bot(session_args):
+    """Main bot entry point compatible with Pipecat Cloud."""
+
+    # Get handle_sigint from session_args, default to True for Daily
+    handle_sigint = getattr(session_args, "handle_sigint", True)
+
+    if hasattr(session_args, "room_url"):
+        # Daily session arguments (cloud or local)
+        from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+        transport = DailyTransport(
+            session_args.room_url,
+            session_args.token,
+            "Pipecat Bot",
+            params=DailyParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+    elif hasattr(session_args, "webrtc_connection"):
+        # WebRTC session arguments (local only, created by server.py)
+        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,
+        )
+
+    await run_bot_logic(transport, handle_sigint)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.server import main
+
+    main()