AI Voice Agent Example Code Guide

Learn to build an AI Voice Agent using VideoSDK with our comprehensive guide, complete with example code.

Introduction to AI Voice Agents in ai voice agent example code

AI Voice Agents are transforming the way humans interact with machines, offering seamless communication through natural language. These agents are software applications capable of understanding and responding to human speech, making them invaluable in various industries, from customer service to smart home devices.

What is an AI Voice Agent?

An AI Voice Agent is a sophisticated software program designed to interpret human speech, process the information, and respond in a conversational manner. These agents leverage technologies like Speech-to-Text (STT), Language Learning Models (LLM), and Text-to-Speech (TTS) to facilitate this interaction.

Why are they important for the ai voice agent example code industry?

AI Voice Agents simplify complex interactions, enhance user experience, and increase accessibility. In industries like customer service, they can handle routine inquiries, allowing human agents to focus on more complex tasks. In smart homes, they enable hands-free control of devices, providing convenience and accessibility.

Core Components of a Voice Agent

  • STT (Speech-to-Text): Converts spoken language into text.
  • LLM (Language Learning Model): Processes and understands the text to generate a meaningful response.
  • TTS (Text-to-Speech): Converts the generated text response back into speech.
For a comprehensive understanding of these components, refer to the

AI voice Agent core components overview

.

What You'll Build in This Tutorial

In this tutorial, you will build a fully functional AI Voice Agent using the VideoSDK framework. This agent will be capable of understanding user queries and providing relevant responses, making it an excellent starting point for anyone interested in AI voice technology. To get started, check out the

Voice Agent Quick Start Guide

.

Architecture and Core Concepts

Understanding the architecture of an AI Voice Agent is crucial for effective implementation. The agent's workflow involves capturing user speech, processing it, and responding appropriately.

High-Level Architecture Overview

The process begins with capturing the user's speech, which is then converted into text using STT. This text is processed by the LLM to generate a response, which is finally converted back to speech using TTS.
1sequenceDiagram
2    participant User
3    participant Agent
4    participant STT
5    participant LLM
6    participant TTS
7    User->>Agent: Speak
8    Agent->>STT: Convert Speech to Text
9    STT->>Agent: Text
10    Agent->>LLM: Process Text
11    LLM->>Agent: Response
12    Agent->>TTS: Convert Text to Speech
13    TTS->>User: Speak
14

Understanding Key Concepts in the VideoSDK Framework

Setting Up the Development Environment

Before building your AI Voice Agent, you need to set up your development environment.

Prerequisites

  • Python 3.11+
  • VideoSDK Account: Sign up at app.videosdk.live to access API keys.

Step 1: Create a Virtual Environment

Creating a virtual environment ensures that your project dependencies are isolated. Run the following command:
1python -m venv venv
2source venv/bin/activate  # On Windows use `venv\\Scripts\\activate`
3

Step 2: Install Required Packages

Install the necessary packages using pip:
1pip install videosdk-agents videosdk-plugins-silero videosdk-plugins-turn-detector videosdk-plugins-deepgram videosdk-plugins-openai videosdk-plugins-elevenlabs
2

Step 3: Configure API Keys in a .env file

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

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

Let's dive into building your AI Voice Agent. Below is the complete code for the agent, which we will break down step-by-step.
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 by providing example code snippets and explanations related to AI voice agent development. Your persona is that of a knowledgeable and friendly coding assistant. Your primary capabilities include answering questions about AI voice agent implementation, providing example code snippets, and guiding users through coding challenges. You can also offer insights into best practices and common pitfalls in AI voice agent development. However, you are not a substitute for professional software development advice and must remind users to verify code snippets and consult documentation or experts for complex issues. You should not provide personal opinions or engage in conversations unrelated to AI voice agent development."
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 create a meeting ID, use the following curl command to interact with the VideoSDK API:
1curl -X POST 
2  https://api.videosdk.live/v1/meetings 
3  -H "Authorization: Bearer YOUR_API_KEY" 
4  -H "Content-Type: application/json" 
5  -d '{}'
6

Step 4.2: Creating the Custom Agent Class

The MyVoiceAgent class extends the Agent class, setting up the agent's behavior. It initializes with specific instructions and defines actions for entering and exiting a session:
1class MyVoiceAgent(Agent):
2    def __init__(self):
3        super().__init__(instructions=agent_instructions)
4    async def on_enter(self): await self.session.say("Hello! How can I help?")
5    async def on_exit(self): await self.session.say("Goodbye!")
6

Step 4.3: Defining the Core Pipeline

The CascadingPipeline is the backbone of the voice agent, integrating various plugins for processing:
1pipeline = CascadingPipeline(
2    stt=DeepgramSTT(model="nova-2", language="en"),
3    llm=OpenAILLM(model="gpt-4o"),
4    tts=ElevenLabsTTS(model="eleven_flash_v2_5"),
5    vad=SileroVAD(threshold=0.35),
6    turn_detector=TurnDetector(threshold=0.8)
7)
8

Step 4.4: Managing the Session and Startup Logic

The session management and startup logic ensure the agent is ready to interact with users:
1async def start_session(context: JobContext):
2    agent = MyVoiceAgent()
3    conversation_flow = ConversationFlow(agent)
4    pipeline = CascadingPipeline(...)
5    session = AgentSession(agent=agent, pipeline=pipeline, conversation_flow=conversation_flow)
6    try:
7        await context.connect()
8        await session.start()
9        await asyncio.Event().wait()
10    finally:
11        await session.close()
12        await context.shutdown()
13
14if __name__ == "__main__":
15    job = WorkerJob(entrypoint=start_session, jobctx=make_context)
16    job.start()
17

Running and Testing the Agent

Step 5.1: Running the Python Script

To run your 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 receive a playground link in the console. Open this link in your browser to interact with your AI Voice Agent.

Advanced Features and Customizations

Extending Functionality with Custom Tools

The VideoSDK framework allows you to extend your agent's functionality by integrating custom tools, enabling more complex interactions and capabilities.

Exploring Other Plugins

While this guide uses specific plugins, VideoSDK supports a variety of STT, LLM, and TTS options. Experiment with different plugins to enhance your agent's capabilities.

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 your microphone and speaker settings. Check if permissions are granted for audio access.

Dependency and Version Conflicts

Ensure all dependencies are installed with compatible versions. Use a virtual environment to avoid conflicts.

Conclusion

Summary of What You've Built

Congratulations! You've built a fully functional AI Voice Agent using the VideoSDK framework. This agent can understand and respond to user queries, showcasing the power of voice technology.

Next Steps and Further Learning

Explore additional features and plugins to enhance your agent. Consider integrating more complex logic or connecting to external APIs for richer interactions. For further guidance, revisit the

Voice Agent Quick Start Guide

.

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