Rename examples files, update quickstart

examples/runner-examples/Dockerfile

@@ -0,0 +1,7 @@
+FROM dailyco/pipecat-base:latest
+
+COPY ./requirements.txt requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY ./cloud-simple-bot.py bot.py

examples/runner-examples/build.sh

@@ -0,0 +1,19 @@
+#!/bin/bash
+set -e
+
+VERSION="0.1"
+DOCKER_USERNAME="your_docker_username"
+AGENT_NAME="cloud-simple-bot"
+
+# Build the Docker image with the correct context
+echo "Building Docker image..."
+docker build --platform=linux/arm64 -t "$DOCKER_USERNAME/$AGENT_NAME:$VERSION" -t "$DOCKER_USERNAME/$AGENT_NAME:latest" .
+
+# Push the Docker images
+echo "Pushing Docker image $DOCKER_USERNAME/$AGENT_NAME:$VERSION..."
+docker push "$DOCKER_USERNAME/$AGENT_NAME:$VERSION"
+
+echo "Pushing Docker image $DOCKER_USERNAME/$AGENT_NAME:latest..."
+docker push "$DOCKER_USERNAME/$AGENT_NAME:latest"
+
+echo "Successfully built and pushed $DOCKER_USERNAME/$AGENT_NAME:$VERSION and $DOCKER_USERNAME/$AGENT_NAME:latest"

examples/runner-examples/cloud-multi-bot.py

@@ -0,0 +1,185 @@
+#
+# 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 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)
+
+
+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, DailySessionArguments):
+        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 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):
+        from pipecat.transports.network.fastapi_websocket import (
+            FastAPIWebsocketParams,
+            FastAPIWebsocketTransport,
+        )
+
+        # Create base parameters for telephony
+        params = FastAPIWebsocketParams(
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            add_wav_header=False,
+        )
+
+        # Create appropriate serializer based on transport type
+        transport_type = getattr(session_args, "transport_type", "unknown")
+        call_info = getattr(session_args, "call_info", {})
+
+        if transport_type == "twilio":
+            from pipecat.serializers.twilio import TwilioFrameSerializer
+
+            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 transport_type == "telnyx":
+            from pipecat.serializers.telnyx import TelnyxFrameSerializer
+
+            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 transport_type == "plivo":
+            from pipecat.serializers.plivo import PlivoFrameSerializer
+
+            params.serializer = PlivoFrameSerializer(
+                stream_id=call_info["stream_id"],
+                call_id=call_info["call_id"],
+            )
+        else:
+            raise ValueError(f"Unsupported WebSocket transport type: {transport_type}")
+
+        transport = FastAPIWebsocketTransport(websocket=session_args.websocket, params=params)
+
+    else:
+        raise ValueError(f"Unsupported session arguments type: {type(session_args)}")
+
+    await run_bot(transport)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.cloud import main
+
+    main()

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

@@ -0,0 +1,161 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+from dataclasses import dataclass
+from typing import Any, Optional
+
+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.runner.cloud import SmallWebRTCSessionArguments # Need a release of Pipecat to use this
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+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
+except ImportError:
+    raise ImportError(
+        "pipecatcloud package is required for cloud-compatible bots. "
+        "Install with: pip install pipecat-ai[[pipecatcloud]]"
+    )
+
+load_dotenv(override=True)
+
+
+# For now, we'll just define SmallWebRTCSessionArguments here directly since Pipecat
+# isn't released with the pipecat.runner.cloud module yet.
+# This saves us from having to build a Docker container from my branch or main to
+# deploy to PCC.
+@dataclass
+class SmallWebRTCSessionArguments:
+    """Small WebRTC session arguments for local development.
+
+    This will be replaced by pipecatcloud.agent.SmallWebRTCSessionArguments
+    when WebRTC support is added to Pipecat Cloud.
+    """
+
+    webrtc_connection: Any
+    session_id: Optional[str] = None
+
+
+# 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):
+    """Main bot entry point compatible with Pipecat Cloud."""
+
+    if isinstance(session_args, DailySessionArguments):
+        from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+        if not IS_LOCAL_RUN:
+            from pipecat.audio.filters.krisp_filter import KrispFilter
+
+        transport = DailyTransport(
+            session_args.room_url,
+            session_args.token,
+            "Pipecat Bot",
+            params=DailyParams(
+                audio_in_enabled=True,
+                audio_in_filter=None
+                if IS_LOCAL_RUN
+                else KrispFilter(),  # Only use Krisp in production
+                audio_out_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+    elif 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,
+        )
+
+    await run_bot(transport)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.cloud import main
+
+    main()

examples/runner-examples/env.example

@@ -0,0 +1,3 @@
+DEEPGRAM_API_KEY=your_deepgram_api_key
+OPENAI_API_KEY=your_openai_api_key
+CARTESIA_API_KEY=your_cartesia_api_key

examples/runner-examples/local-multi-bot.py

@@ -0,0 +1,122 @@
+#
+# 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.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+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 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(),  # Transport user input
+            rtvi,
+            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,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+
+    @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": "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(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.local 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/runner-examples/local-simple-bot.py

@@ -0,0 +1,101 @@
+#
+# 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.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
+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 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(),  # Transport user input
+            rtvi,  # RTVI processor
+            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,
+        ),
+        observers=[RTVIObserver(rtvi)],
+    )
+
+    @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": "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(f"Client disconnected")
+        await task.cancel()
+
+    runner = PipelineRunner(handle_sigint=handle_sigint)
+
+    await runner.run(task)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.local 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/runner-examples/pcc-deploy.toml

@@ -0,0 +1,8 @@
+agent_name = "cloud-simple-bot"
+image = "your_dockerhub_username/cloud-simple-bot:0.1"
+image_credentials = "dockerhub-access"
+secret_set = "cloud-simple-bot-secrets"
+enable_krisp = true
+
+[scaling]
+	min_agents = 0

examples/runner-examples/requirements.txt

@@ -0,0 +1,4 @@
+pipecatcloud
+pipecat-ai[openai,daily,deepgram,cartesia,silero]
+python-dotenv
+pipecat-ai-small-webrtc-prebuilt