Build an AI Voice Agent for Government

Step-by-step guide to building an AI Voice Agent for government services using VideoSDK, complete with code examples and testing instructions.

Introduction to AI Voice Agents in Government

What is an AI

Voice Agent

?

An AI

Voice Agent

 is a software application that uses artificial intelligence to interact with users through voice commands. These agents can understand human speech, process the information, and respond in a conversational manner. They are designed to automate tasks, provide information, and assist users in various domains.

Why are They Important for Government?

In the government sector, AI Voice Agents can play a crucial role in streamlining communication between citizens and government services. They can provide 24/7 assistance, answer frequently asked questions, guide users through government forms, and help citizens navigate complex procedures. This improves accessibility and efficiency, reducing the workload on human staff and enhancing citizen satisfaction.

Core Components of a

Voice Agent

The primary components of an AI

Voice Agent

 include:
  • Speech-to-Text (STT): Converts spoken language into text.
  • Large Language Model (LLM): Processes the text to understand and generate appropriate responses.
  • Text-to-Speech (TTS): Converts the generated text response back into spoken language.
For a comprehensive understanding, you can refer to the

AI voice Agent core components overview

 which details each component's role in the system.

What You'll Build in This Tutorial

In this tutorial, we will guide you through building an AI

Voice Agent

 tailored for government services using the VideoSDK framework. You'll learn how to set up the environment, implement core functionalities, and test your agent.

Architecture and Core Concepts

High-Level Architecture Overview

The AI

Voice Agent

 processes user input through a series of steps. Initially, the user's speech is captured and converted into text using STT. The text is then processed by the LLM to generate a response, which is finally converted back into speech using TTS. This entire process is managed through a

cascading pipeline

.
Diagram

Understanding Key Concepts in the VideoSDK Framework

  • Agent: This is the core class representing your AI Voice Agent. It defines the agent's behavior and interactions.
  • CascadingPipeline: This component manages the flow of data through various stages of processing, from STT to LLM to TTS.
  • VAD & TurnDetector: These plugins help the agent determine when to listen and when to speak, ensuring smooth interaction. For more details, explore the

    Turn detector for AI voice Agents

    .

Setting Up the Development Environment

Prerequisites

Before you begin, ensure you have Python 3.11+ installed. You'll also need a VideoSDK account, which you can create at app.videosdk.live.

Step 1: Create a Virtual Environment

Create a new virtual environment to manage your project's dependencies:
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
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

Below is the complete code for the AI Voice Agent. We will break it down into smaller sections for detailed explanations.
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 specifically for government services. Your persona is that of a knowledgeable and courteous government assistant. Your primary capabilities include providing information about government services, assisting citizens with navigating government websites, and answering frequently asked questions related to government procedures and policies. You can also guide users on how to access various government forms and applications. However, you must adhere to certain constraints: you are not authorized to provide legal advice or interpret laws, and you must always encourage users to consult official government sources or legal professionals for detailed inquiries. Additionally, you must ensure user privacy and data security at all times, and you should not store any personal information provided by users."
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 interact with the AI Voice Agent, you'll need a meeting ID. You can generate one using the following curl command:
1curl -X POST https://api.videosdk.live/v1/meetings -H "Authorization: Bearer YOUR_SECRET_KEY"
2
Replace YOUR_SECRET_KEY with your actual VideoSDK secret key.

Step 4.2: Creating the Custom Agent Class

The MyVoiceAgent class extends the Agent class. It defines the agent's behavior during the session. The on_enter and on_exit methods are used to greet and bid farewell to the users.
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 responsible for managing the flow of data through the STT, LLM, and TTS processes. Each plugin is configured to handle specific tasks.
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 start_session function initializes the agent session and manages its lifecycle. The make_context function creates the job context with room options, and the main block starts the agent.
1def make_context() -> JobContext:
2    room_options = RoomOptions(
3        name="VideoSDK Cascaded Agent",
4        playground=True
5    )
6    return JobContext(room_options=room_options)
7
8if __name__ == "__main__":
9    job = WorkerJob(entrypoint=start_session, jobctx=make_context)
10    job.start()
11

Running and Testing the Agent

Step 5.1: Running the Python Script

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

Step 5.2: Interacting with the Agent in the Playground

Once the agent is running, you will see a link to the playground in the console. Open the link in your browser to interact with the agent. You can speak into your microphone and receive responses from the agent.

Advanced Features and Customizations

Extending Functionality with Custom Tools

The VideoSDK framework allows you to extend the agent's functionality by integrating custom tools. This enables you to tailor the agent's capabilities to specific use cases.

Exploring Other Plugins

While this tutorial uses specific plugins for STT, LLM, and TTS, VideoSDK supports various other options. Explore the documentation to find plugins that best suit your needs.

Troubleshooting Common Issues

API Key and Authentication Errors

Ensure your API keys are correctly set in the .env file. Double-check for typos or incorrect values.

Audio Input/Output Problems

Verify your microphone and speaker settings. Ensure the correct input and output devices are selected in your system settings.

Dependency and Version Conflicts

If you encounter issues with package dependencies, ensure all packages are up-to-date and compatible with Python 3.11+.

Conclusion

Summary of What You've Built

In this tutorial, you have built a fully functional AI Voice Agent for government services using the VideoSDK framework. You learned how to set up the environment, implement the core functionalities, and test the agent.

Next Steps and Further Learning

To further enhance your agent, explore additional features and plugins offered by VideoSDK. Consider integrating more complex functionalities and customizing the agent to better suit specific government services. For more advanced session management, refer to the

AI voice Agent Sessions

.

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