Remove quickstart example—moving to a separate PR
This commit is contained in:
Mark Backman
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# Pipecat Quickstart
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Run your first Pipecat bot in under 5 minutes. This example creates a voice AI bot that you can talk to in your browser.
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## Prerequisites
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### Python 3.10+
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Pipecat requires Python 3.10 or newer. Check your version:
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```bash
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python --version
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```
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If you need to upgrade Python, we recommend using a version manager like `uv` or `pyenv`.
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### AI Service API keys
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Pipecat orchestrates different AI services in a pipeline, ensuring low latency communication. In this quickstart example, we'll use:
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- [Deepgram](https://console.deepgram.com/signup) for Speech-to-Text transcriptions
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- [OpenAI](https://auth.openai.com/create-account) for LLM inference
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- [Cartesia](https://play.cartesia.ai/sign-up) for Text-to-Speech audio generation
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Have your API keys ready. We'll add them to your `.env` shortly.
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## Setup
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1. Set up a virtual environment
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From the root directory of the `pipecat` repo, run:
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```bash
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cd examples/quickstart
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python -m venv .venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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```
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> Using `uv`? Create your venv using: `uv venv && source .venv/bin/activate`.
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2. Install packages
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Then, install the requirements:
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```bash
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pip install -r requirements.txt
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```
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> Using `uv`? Install requirements using: `uv pip install -r requirements.txt`.
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3. Configure environment variables
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Create a `.env` file:
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```bash
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cp env.example .env
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```
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Then, add your API keys:
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```
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DEEPGRAM_API_KEY=your_deepgram_api_key
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OPENAI_API_KEY=your_openai_api_key
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CARTESIA_API_KEY=your_cartesia_api_key
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```
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4. Run the example
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Run your bot using:
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```bash
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python bot.py
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```
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> Using `uv`? Run your bot using: `uv run bot.py`.
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Connect to your bot in a browser at http://localhost:7860.
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> 💡 First run note: The initial startup may take ~10 seconds as Pipecat downloads required models, like the Silero VAD model.
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## Troubleshooting
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- **Browser permissions**: Make sure to allow microphone access when prompted by your browser.
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- **Connection issues**: If the WebRTC connection fails, first try a different browser. If that fails, make sure you don't have a VPN or firewall rules blocking traffic. WebRTC uses UDP to communicate.
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- **Audio issues**: Check that your microphone and speakers are working and not muted.
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## Next Steps
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- **Read the docs**: Check out [Pipecat's docs](https://docs.pipecat.ai/) for guides and reference information.
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- **Join Discord**: Join [Pipecat's Discord server](https://discord.gg/pipecat) to get help and learn about what others are building.
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@@ -1,102 +0,0 @@
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import argparse
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import os
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
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from pipecat.services.cartesia.tts import CartesiaTTSService
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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load_dotenv(override=True)
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async def run_bot(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
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logger.info(f"Starting bot")
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stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
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tts = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"),
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voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
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)
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
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messages = [
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{
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"role": "system",
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"content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.",
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},
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]
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context = OpenAILLMContext(messages)
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context_aggregator = llm.create_context_aggregator(context)
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rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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rtvi, # RTVI processor
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stt,
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context_aggregator.user(), # User responses
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llm, # LLM
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tts, # TTS
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transport.output(), # Transport bot output
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context_aggregator.assistant(), # Assistant spoken responses
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]
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)
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task = PipelineTask(
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pipeline,
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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observers=[RTVIObserver(rtvi)],
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)
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Kick off the conversation.
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messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."})
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await task.queue_frames([context_aggregator.user().get_context_frame()])
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info(f"Client disconnected")
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await task.cancel()
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runner = PipelineRunner(handle_sigint=handle_sigint)
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await runner.run(task)
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if __name__ == "__main__":
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from pipecat.runner.local import main
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# SmallWebRTCTransport for a P2P WebRTC connection
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transport_params = {
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"webrtc": lambda: TransportParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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),
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}
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main(run_bot, transport_params=transport_params)
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@@ -1,3 +0,0 @@
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DEEPGRAM_API_KEY=your_deepgram_api_key
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OPENAI_API_KEY=your_openai_api_key
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CARTESIA_API_KEY=your_cartesia_api_key
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@@ -1,2 +0,0 @@
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pipecat-ai[webrtc,silero,deepgram,openai,cartesia,runner]
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pipecat-ai-small-webrtc-prebuilt
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