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Build Your Own AI Voice Agent for Free with Pipecat

Build Your Own AI Voice Agent for Free with Pipecat

Bhushan·

Do you know you can build a real-time AI voice agent without paying for expensive voice agent platforms? Pipecat is an open-source Python framework for building real-time voice and multimodal AI agents. Instead of manually connecting speech-to-text, AI models, and voice generation services, Pipecat orchestrates everything through a low-latency pipeline designed for natural conversations. Whether you're building an AI receptionist, appointment booking assistant, customer support agent, or phone-based AI assistant, Pipecat provides the tools needed to get started quickly.

Key Features

  • Completely open source
  • Real-time voice conversations
  • Supports OpenAI, Gemini, Claude, and local LLMs
  • Works with multiple speech-to-text providers
  • Supports various text-to-speech engines
  • WebRTC support for low-latency communication
  • Multi-agent workflows
  • Telephony integrations
  • Highly customizable pipelines
  • Production-ready architecture

What Can You Build?

Pipecat can be used to create:

  • AI Receptionists
  • Customer Support Agents
  • Appointment Booking Assistants
  • Lead Qualification Agents
  • Recruitment Assistants
  • Internal Company Assistants
  • AI Phone Agents
  • Voice-Based SaaS Products
  • Multimodal Voice + Video Applications

How Pipecat Works

Pipecat connects multiple AI services into a real-time conversational pipeline.

Voice Pipeline

User Speaks
      ↓
Speech-to-Text (STT)
      ↓
Large Language Model (LLM)
      ↓
Text-to-Speech (TTS)
      ↓
Voice Response

A typical interaction follows this flow:

  1. User speaks through a browser, mobile app, or phone call.
  2. Speech-to-text converts audio into text.
  3. The AI model processes the request.
  4. Text-to-speech converts the response into audio.
  5. The response is streamed back to the user.

Pipecat manages this entire pipeline automatically while maintaining low latency and natural conversations.

Prerequisites

Before creating your first voice agent, install the following:

Python

Pipecat requires Python 3.11 or newer.

python --version

UV Package Manager

Install UV:

pip install uv

Or:

curl -LsSf https://astral.sh/uv/install.sh | sh

Step 1 – Install Pipecat CLI

Pipecat now provides a CLI that can generate complete voice agent projects automatically.

Install the CLI:

uv tool install pipecat-ai-cli

Verify installation:

pipecat --version

Step 2 – Create a New Voice Agent

Launch the project wizard:

pipecat init

Or generate the official quickstart project:

pipecat init quickstart

The wizard will guide you through selecting:

Platform

  • Web Application
  • Mobile Application
  • Phone Agent

Speech-to-Text Provider

Examples:

  • Deepgram
  • Speechmatics
  • Gladia

AI Model

Examples:

  • OpenAI
  • Gemini
  • Claude
  • Local LLMs

Text-to-Speech Provider

Examples:

  • Cartesia
  • ElevenLabs
  • LMNT

Pipecat automatically generates the project structure and starter code.

Step 3 – Configure API Keys

Create your environment file:

cp env.example .env

Add your API keys:

OPENAI_API_KEY=your_key
DEEPGRAM_API_KEY=your_key
CARTESIA_API_KEY=your_key

The official Quickstart commonly uses:

  • OpenAI
  • Deepgram
  • Cartesia

You can replace these with other supported providers.

Step 4 – Install Project Dependencies

Navigate into your project folder:

cd my-pipecat-agent

Install dependencies:

uv sync

This installs all required packages for your voice agent.

Step 5 – Run Your Voice Agent

Start the application:

uv run bot.py

Once started, open the local application in your browser and connect to your AI assistant.

Your voice agent is now ready for testing.

Supported AI Providers

Speech-to-Text

  • Deepgram
  • OpenAI STT
  • Speechmatics
  • Gladia

Large Language Models

  • OpenAI
  • Gemini
  • Claude
  • Local Models

Text-to-Speech

  • Cartesia
  • ElevenLabs
  • LMNT
  • Deepgram TTS

Developers can mix and match providers depending on their requirements.

Advanced Features

Multi-Agent Workflows

Create specialized agents that can hand conversations to one another.

Examples:

  • Reception Agent
  • Sales Agent
  • Support Agent

Structured Conversation Flows

Build guided workflows such as:

  • Appointment Booking
  • Customer Qualification
  • Customer Support
  • Lead Collection

Telephony Integrations

Connect AI agents directly to:

  • Twilio
  • SIP
  • PSTN Networks
  • Phone Systems

This allows AI agents to answer and place phone calls automatically.

Example Business Use Cases

AI Receptionist

Answer incoming calls and collect customer information.

Appointment Booking Assistant

Schedule appointments automatically.

Lead Qualification Agent

Ask qualifying questions before transferring prospects to a sales representative.

Customer Support Agent

Handle frequently asked questions 24/7.

Recruitment Assistant

Conduct initial candidate screening interviews.

Internal Company Assistant

Provide employees with instant access to company information.

Phone-Based AI Agent

Handle inbound and outbound calls for businesses.

Deployment Options

After testing locally, you can deploy your Pipecat application to:

  • Pipecat Cloud
  • AWS
  • Fly.io
  • Modal
  • Cerebrium
  • Dedicated Servers
  • Self-Hosted Infrastructure

This makes Pipecat suitable for both small projects and enterprise-scale deployments.

Why Use Pipecat?

Many voice-agent platforms charge monthly fees and limit customization.

Pipecat gives developers:

  • Full control over the conversation pipeline
  • Freedom to choose AI providers
  • Open-source flexibility
  • Production scalability
  • Telephony support
  • Multi-provider integrations
  • Real-time low-latency conversations

Because it is open source, businesses can create highly customized voice agents without being locked into a single vendor.