Pipecat Flows Overview

Reference docs for Pipecat’s conversation flow system

New to building conversational flows? Check out our Pipecat Flows guide first.

Pipecat Flows is an add-on framework for Pipecat that allows you to build structured conversations in your AI applications. It enables you to define conversation paths while handling the complexities of state management and LLM interactions.

API Reference

Complete API documentation and method details

GitHub Repository

Source code, examples, and issue tracking

Hello World Example

Working example with basic conversation flow

Installation

Pipecat Flows

To use Pipecat Flows, install the required dependency:

pip install pipecat-ai-flows

Pipecat Dependencies

For fresh installations, you’ll need to install Pipecat with depdencies for your Transport, STT, LLM, and TTS providers.

For example, to use Daily, OpenAI, Deepgram, Cartesia, and Silero:

pip install "pipecat-ai[daily,openai,deepgram,cartesia,silero]"

Reference Pages

FlowManager

Core orchestration class: constructor, properties, and methods

Types

NodeConfig, FlowsFunctionSchema, ActionConfig, context strategies, and type aliases

Exceptions

Error handling hierarchy for flow management

Function Types

Node Functions

Execute operations within a single conversation state without switching nodes. Return (FlowResult, None).

Edge Functions

Create transitions between conversation states, optionally processing data first. Return (FlowResult, NodeConfig).

Direct Functions

Functions passed directly to NodeConfig with automatic metadata extraction from signatures and docstrings. See flows_direct_function and FlowsDirectFunction.

LLM Provider Support

Pipecat Flows automatically handles format differences between providers:

Provider	Format Support	Installation
OpenAI	Function calling	pip install "pipecat-ai[openai]"
OpenAI-compatible	Function calling	Provider-specific (see below)
Anthropic	Native tools	pip install "pipecat-ai[anthropic]"
Google Gemini	Function declarations	pip install "pipecat-ai[google]"
AWS Bedrock	Anthropic-compatible	pip install "pipecat-ai[aws]"

Any LLM service that extends OpenAILLMService is automatically supported. This includes services like Groq, Together, Cerebras, DeepSeek, and others that use the OpenAI-compatible API format.

Additional Notes

• State Management: Use flow_manager.state dictionary for persistent conversation data
• Automatic Function Call Registration and Validation: All functions are automatically registered and validated at run-time
• Provider Compatibility: Format differences handled automatically via adapter system