Testing your agent in a local environment

Local development

Pipecat Cloud

Deploy your AI agents to production at scale

Introduction

Get started deploying your first Pipecat Cloud agent

Quickstart

Managing your account and collaborating on agents as part of a team

Accounts and Organizations

Agent Images

Deployments

Serving user requests with active sessions.

Starting Sessions

Providing your agent with sensitive information

Secrets

Production-ready agent deployment and scaling strategies

Scaling

Obtaining logs and metrics from your agents and sessions

Logging and Observability

Common issues and solutions when deploying agents to Pipecat Cloud

Troubleshooting

Using Daily as a WebRTC transport for your Pipecat Cloud agents

Daily WebRTC

Using Twilio’s WebSocket Transport for your Pipecat Cloud agents

Twilio Websocket Transport

Dial-in / Dial-out

Security Guide

Service integrations for your Pipecat Cloud agents

Integrations

Overview

agent

Authentication and authorization commands

auth

deploy

init

Organization and API key management commands

organizations

Secret sets and secret management commands

secrets

Introduction to the Pipecat Cloud Python SDK

Python SDK Overview

Managing agent sessions with the Pipecat Cloud Python SDK

Session Management

Understanding the arguments received by bot entry points

Session Arguments

Managing errors with the Pipecat Cloud Python SDK

Error Handling

Common usage patterns for the Pipecat Cloud Python SDK

Agents

Pipecat in Production

Additional features

Local development