Pipecat
Pipecat is an open-source, real-time voice AI orchestration framework built for developers who want to create deeply interactive, multimodal conversational agents. It provides a flexible pipeline architecture for integrating speech recognition (STT), language models, and speech synthesis (TTS) components into low-latency, event-driven workflows. Designed for modularity and extensibility, Pipecat enables developers to compose custom voice agent stacks that handle audio streaming, turn-taking, and response timing with precision.
This tutorial will guide you through integrating Arcee AI models as the LLM backbone for your Pipecat voice agent. We'll integrate Arcee's models using OpenRouter.

Prerequisites
Python:
>=3.10OpenRouter API Key
If you don't have an account, set one up here.
uv package manager installed
Integration Steps
Install the Pipecat CLI globally using uv
Run the Pipecat interactive setup wizard to create the scaffolding for a pipecat agent
You will be prompted with a few questions which determine how the project is setup. Use the following configuration:
These configurations create an agent which uses Deepgram for Speech-to-Text and Text-to-Speech, and Arcee models through OpenRouter for the LLM.
You can modify any of these settings to change your voice agent.
Once your project has been created, setup the client
Next, setup the server. Install dependencies
Create
.envfile
In the
.envfile, fill in your Deepgram and OpenRouter API Key and provide a Deepgram Voice ID and the Arcee AI LLM you want to use. For example:
Edit the Voice Agent Kickoff System prompt
Navigate to
arcee-pipecat/server/bot.pyReplace the content of the Kickoff system prompt (on line 139) with the following message:
The full line should now look like the following:
Run your Voice Agent
Access your Voice Agent at http://localhost:5173/
Click connect and start conversating with your agent!
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