Files
pipecat/examples/quickstart
Paul Kompfner d779a5b4ea Use "developer" role for programmatic conversation-kickoff messages
These messages are developer instructions to the assistant (e.g. "Please
introduce yourself to the user"), not simulated user input. The
"developer" role is semantically correct for this purpose.
2026-03-24 16:02:42 -04:00
..
2025-08-23 00:19:26 -04:00
2026-02-10 22:06:38 -05:00

Pipecat Quickstart

Build and deploy your first voice AI bot in under 10 minutes. Develop locally, then scale to production on Pipecat Cloud.

Two steps: 🏠 Local Development☁️ Production Deployment

🎯 Quick start: Local bot in 5 minutes, production deployment in 5 more

Step 1: Local Development (5 min)

Prerequisites

Environment

  • Python 3.10 or later
  • uv package manager installed

AI Service API keys

You'll need API keys from three services:

💡 Tip: Sign up for all three now. You'll need them for both local and cloud deployment.

Setup

Navigate to the quickstart directory and set up your environment.

  1. Install dependencies:

    uv sync
    
  2. Configure your API keys:

    Create a .env file:

    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
    

Run your bot locally

uv run bot.py

Open http://localhost:7860 in your browser and click Connect to start talking to your bot.

💡 First run note: The initial startup may take ~20 seconds as Pipecat downloads required models and imports.

🎉 Success! Your bot is running locally. Now let's deploy it to production so others can use it.


Step 2: Deploy to Production (5 min)

Transform your local bot into a production-ready service. Pipecat Cloud handles scaling, monitoring, and global deployment.

Prerequisites

  1. Sign up for Pipecat Cloud.

  2. Install the Pipecat CLI:

    uv tool install pipecat-ai-cli
    

💡 Tip: You can run the pipecat CLI using the pc alias.

Configure your deployment

The pcc-deploy.toml file tells Pipecat Cloud how to run your bot.

agent_name = "quickstart"
secret_set = "quickstart-secrets"

[scaling]
	min_agents = 1

Understanding the TOML file settings:

  • agent_name: Your bot's name in Pipecat Cloud
  • secret_set: Where your API keys are stored securely
  • min_agents: Number of bot instances to keep ready (1 = instant start)

Log in to Pipecat Cloud

To start using the CLI, authenticate to Pipecat Cloud:

pipecat cloud auth login

You'll be presented with a link and six-digit code that you can click to authenticate your client.

Configure secrets

Upload your API keys to Pipecat Cloud's secure storage:

pipecat cloud secrets set quickstart-secrets --file .env

This creates a secret set called quickstart-secrets (matching your TOML file) and uploads all your API keys from .env.

Deploy

Deploy to Pipecat Cloud:

pipecat cloud deploy

This pushes your project files to Pipecat Cloud where a docker image is built and deployed into production.

Connect to your agent

  1. Open your Pipecat Cloud dashboard
  2. Select your quickstart agent → Sandbox
  3. Allow microphone access and click Connect

What's Next?

🔧 Customize your bot: Modify bot.py to change personality, add functions, or integrate with your data
📚 Learn more: Check out Pipecat's docs for advanced features
💬 Get help: Join Pipecat's Discord to connect with the community

Troubleshooting

  • Browser permissions: Allow microphone access when prompted
  • Connection issues: Try a different browser or check VPN/firewall settings
  • Audio issues: Verify microphone and speakers are working and not muted