Build an AI Voice Agent in React Native

Step-by-step guide to building an AI Voice Agent in React Native using VideoSDK. Includes code examples and testing instructions.

Introduction to AI Voice Agents in React Native

AI Voice Agents are sophisticated software applications designed to interact with users through voice commands. These agents process spoken language, understand the intent behind it, and respond with appropriate actions or information. In the context of React Native, integrating AI Voice Agents can enhance user experience by providing hands-free navigation, voice-activated features, and personalized assistance.

What is an AI

Voice Agent

?

An AI

Voice Agent

 is a system that uses speech recognition, natural language processing, and text-to-speech technologies to communicate with users. It listens to the user's voice, processes the input to understand the request, and then generates a spoken response.

Why are they important for the React Native industry?

Incorporating AI Voice Agents in React Native applications can significantly improve accessibility and user engagement. They allow users to interact with apps in a more natural and intuitive way, which is particularly beneficial for applications focused on accessibility, smart home control, and customer service.

Core Components of a

Voice Agent

  • Speech-to-Text (STT): Converts spoken language into text.
  • Large Language Model (LLM): Understands and processes the text to determine the appropriate response.
  • Text-to-Speech (TTS): Converts the response text back into spoken language.
For a comprehensive understanding, refer to the

AI voice Agent core components overview

.

What You'll Build in This Tutorial

In this tutorial, you will learn how to build an AI

Voice Agent

 using React Native and VideoSDK. We will guide you through setting up the environment, creating a custom agent, and testing it in a

AI Agent playground

.

Architecture and Core Concepts

High-Level Architecture Overview

The AI

Voice Agent

 architecture involves several components working together to process user input and generate responses. The data flow begins with the user's speech, which is captured and converted into text by the STT component. This text is then processed by the LLM to determine the appropriate response, which is finally converted back to speech by the TTS component.
Diagram

Understanding Key Concepts in the VideoSDK Framework

  • Agent: The core class representing your bot, responsible for managing interactions.
  • CascadingPipeline: Manages the flow of audio processing from STT to LLM and TTS. Learn more about the

    Cascading pipeline in AI voice Agents

    .
  • VAD & TurnDetector: These components help the agent determine when to listen and when to speak. Explore the

    Turn detector for AI voice Agents

    .

Setting Up the Development Environment

Prerequisites

Before you begin, ensure you have Python 3.11+ installed and a VideoSDK account. You can sign up at the VideoSDK website.

Step 1: Create a Virtual Environment

Create a virtual environment to manage your project dependencies:
1python -m venv myenv
2source myenv/bin/activate  # On Windows use `myenv\Scripts\activate`
3

Step 2: Install Required Packages

Install the necessary Python packages using pip:
1pip install videosdk
2

Step 3: Configure API Keys in a .env file

Create a .env file in your project directory and add your VideoSDK API keys:
1VIDEOSDK_API_KEY=your_api_key_here
2

Building the AI Voice Agent: A Step-by-Step Guide

Here is the complete, runnable code for the AI Voice Agent:
1import asyncio, os
2from videosdk.agents import Agent, AgentSession, CascadingPipeline, JobContext, RoomOptions, WorkerJob, ConversationFlow
3from videosdk.plugins.silero import SileroVAD
4from videosdk.plugins.turn_detector import TurnDetector, pre_download_model
5from videosdk.plugins.deepgram import DeepgramSTT
6from videosdk.plugins.openai import OpenAILLM
7from videosdk.plugins.elevenlabs import ElevenLabsTTS
8from typing import AsyncIterator
9
10# Pre-downloading the Turn Detector model
11pre_download_model()
12
13agent_instructions = "You are an AI Voice Agent designed to assist users in navigating and utilizing a React Native application. Your persona is that of a friendly and knowledgeable tech assistant. Your primary capabilities include providing guidance on using various features of the React Native app, answering technical questions related to React Native development, and offering troubleshooting tips for common issues. However, you are not a certified developer, so you must include a disclaimer advising users to consult professional developers for complex issues or code-related problems. You should also refrain from making any changes to the user's code or system settings. Your responses should be concise, informative, and supportive, ensuring users feel confident in their ability to use the React Native application effectively."
14
15class MyVoiceAgent(Agent):
16    def __init__(self):
17        super().__init__(instructions=agent_instructions)
18    async def on_enter(self): await self.session.say("Hello! How can I help?")
19    async def on_exit(self): await self.session.say("Goodbye!")
20
21async def start_session(context: JobContext):
22    # Create agent and conversation flow
23    agent = MyVoiceAgent()
24    conversation_flow = ConversationFlow(agent)
25
26    # Create pipeline
27    pipeline = CascadingPipeline(
28        stt=DeepgramSTT(model="nova-2", language="en"),
29        llm=OpenAILLM(model="gpt-4o"),
30        tts=ElevenLabsTTS(model="eleven_flash_v2_5"),
31        vad=SileroVAD(threshold=0.35),
32        turn_detector=TurnDetector(threshold=0.8)
33    )
34
35    session = AgentSession(
36        agent=agent,
37        pipeline=pipeline,
38        conversation_flow=conversation_flow
39    )
40
41    try:
42        await context.connect()
43        await session.start()
44        # Keep the session running until manually terminated
45        await asyncio.Event().wait()
46    finally:
47        # Clean up resources when done
48        await session.close()
49        await context.shutdown()
50
51def make_context() -> JobContext:
52    room_options = RoomOptions(
53    #  room_id="YOUR_MEETING_ID",  # Set to join a pre-created room; omit to auto-create
54        name="VideoSDK Cascaded Agent",
55        playground=True
56    )
57
58    return JobContext(room_options=room_options)
59
60if __name__ == "__main__":
61    job = WorkerJob(entrypoint=start_session, jobctx=make_context)
62    job.start()
63

Step 4.1: Generating a VideoSDK Meeting ID

To generate a meeting ID, you can use the following curl command:
1curl -X POST "https://api.videosdk.live/v1/meetings" \
2-H "Authorization: Bearer YOUR_VIDEOSDK_API_KEY" \
3-H "Content-Type: application/json"
4

Step 4.2: Creating the Custom Agent Class

The MyVoiceAgent class is a custom implementation of the Agent class. It defines the agent's behavior when entering and exiting a session. The agent greets users with "Hello! How can I help?" and says "Goodbye!" upon exit.

Step 4.3: Defining the Core Pipeline

The CascadingPipeline is a critical component that manages the flow of audio data through various processing stages:
  • STT (DeepgramSTT): Converts audio input into text.
  • LLM (OpenAILLM): Processes the text to generate a response.
  • TTS (ElevenLabsTTS): Converts the response text back into speech. Explore the

    ElevenLabs TTS Plugin for voice agent

    .
  • VAD (SileroVAD): Detects the presence of speech in the audio input.
  • TurnDetector: Determines when the agent should listen or respond.

Step 4.4: Managing the Session and Startup Logic

The start_session function initializes the agent, pipeline, and conversation flow. It connects to the VideoSDK service and starts the session. The make_context function sets up the room options, enabling the playground mode for testing. The if __name__ == "__main__": block ensures that the script runs the agent when executed directly.

Running and Testing the Agent

Step 5.1: Running the Python Script

To run your AI Voice Agent, execute the following command in your terminal:
1python main.py
2

Step 5.2: Interacting with the Agent in the Playground

Once the script is running, you will see a playground link in the console. Open this link in your browser to interact with the agent. You can test the agent's capabilities by speaking into your device's microphone.

Advanced Features and Customizations

Extending Functionality with Custom Tools

You can extend your agent's functionality by implementing custom tools. This allows you to add domain-specific capabilities or integrate with external APIs.

Exploring Other Plugins

While this tutorial uses specific plugins for STT, LLM, and TTS, VideoSDK supports various other options. Consider exploring different plugins to optimize performance or reduce costs.

Troubleshooting Common Issues

API Key and Authentication Errors

Ensure your API keys are correctly configured in the .env file. Double-check for typos or missing keys.

Audio Input/Output Problems

Verify that your device's microphone and speakers are working correctly. Check system settings and permissions.

Dependency and Version Conflicts

Ensure all dependencies are installed and compatible with your Python version. Use a virtual environment to manage package versions effectively.

Conclusion

Summary of What You've Built

In this tutorial, you built a functional AI Voice Agent using React Native and VideoSDK. You learned about the core components, set up the development environment, and implemented a custom agent.

Next Steps and Further Learning

Explore additional features in the VideoSDK documentation, and consider integrating more advanced AI capabilities into your React Native applications.

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