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Pipecat Flows is a framework for building structured conversations in your AI applications. It lets you define conversation paths as a graph of nodes, where each node focuses the LLM on a single task with only the tools it needs. This approach solves a common problem: monolithic prompts with many tools lead to hallucinations and lower accuracy. Pipecat Flows breaks complex tasks into focused steps with clear, specific instructions.

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When to Use Pipecat Flows

Pipecat Flows is best suited for use cases where:
  • You need precise control over how a conversation progresses through specific steps
  • Your bot handles complex tasks that can be broken down into smaller, manageable pieces
  • You want to improve LLM accuracy by focusing the model on one specific task at a time instead of managing multiple responsibilities simultaneously

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How Pipecat and Pipecat Flows Work Together

Pipecat defines the core capabilities of your bot — the pipeline and processors that enable receiving audio, transcribing input, running LLM completions, converting responses to audio, and sending audio back to the user. Pipecat Flows complements Pipecat by providing structure to a conversation, managing context and tools as the conversation progresses from one state to another. This is separate from the core pipeline, allowing you to separate conversation logic from pipeline mechanics.

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