Build an AI Voice Agent for Logistics

Step-by-step guide to building an AI Voice Agent for logistics with VideoSDK. Includes full code examples and testing instructions.

Introduction to AI Voice Agents in ai voice agent for logistics

AI Voice Agents are intelligent systems designed to interact with users through voice commands. They leverage advanced technologies such as Speech-to-Text (STT), Language Learning Models (LLM), and Text-to-Speech (TTS) to process and respond to user inquiries. In the logistics industry, these agents can streamline operations by providing real-time updates on shipment status, assisting with route optimization, and answering queries related to delivery schedules.

Why are they important for the ai voice agent for logistics industry?

In logistics, time is of the essence. AI Voice Agents can automate routine tasks, reduce human error, and provide instant access to critical information. They can assist in tracking packages, managing inventory, and offering estimated delivery times, thereby enhancing operational efficiency and customer satisfaction.

Core Components of a Voice Agent

  • STT (Speech-to-Text): Converts spoken language into text.
  • LLM (Language Learning Model): Processes the text to understand and generate responses.
  • TTS (Text-to-Speech): Converts text responses back into spoken language.
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 for logistics using the VideoSDK framework. This agent will be capable of interacting with users, providing logistics-related information, and operating within a simulated environment.

Architecture and Core Concepts

High-Level Architecture Overview

The AI Voice Agent processes user speech through a series of steps: capturing audio input, converting it to text, processing the text to generate a response, and finally, converting the response back to speech. This flow is managed by the VideoSDK framework's

cascading pipeline

.

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 to TTS.
  • VAD & TurnDetector: These components help the agent determine when to listen and when to speak, ensuring smooth interactions. For more details, explore the

    Turn detector for AI voice Agents

    .

Setting Up the Development Environment

Prerequisites

To get started, ensure you have Python 3.11+ installed and a VideoSDK account. You can sign up at app.videosdk.live.

Step 1: Create a Virtual Environment

Create a virtual environment to manage your project's dependencies:
1python3 -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 to store your API keys securely. This file should include your VideoSDK API key and any other credentials required for the plugins you will use.

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

Let's dive into building your AI Voice Agent. We will start by presenting the complete code and then break it down 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 specialized in logistics management. Your persona is that of a knowledgeable and efficient logistics coordinator. Your primary capabilities include providing real-time updates on shipment status, answering queries related to delivery schedules, assisting with route optimization, and offering support for inventory management. You can also help users track packages and provide estimated delivery times. However, you are not authorized to make any changes to shipment details or handle financial transactions. Always remind users to verify critical information with their logistics provider. You must include a disclaimer that you are an AI and that users should consult with a human representative for complex logistics issues."
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 your agent, you need a meeting ID. You can generate one using 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

Step 4.2: Creating the Custom Agent Class

The MyVoiceAgent class extends the Agent class, defining the agent's behavior. It uses agent_instructions to guide its interactions, ensuring it remains focused on logistics tasks.

Step 4.3: Defining the Core Pipeline

The CascadingPipeline orchestrates the flow of data from STT to LLM to TTS. Each plugin plays a critical role:

Step 4.4: Managing the Session and Startup Logic

The start_session function initializes the agent and starts the session. It connects to the VideoSDK context and manages the lifecycle of the agent's interaction. The make_context function sets up the room options, and the if __name__ == "__main__": block ensures the script runs as a standalone application. For more details on managing sessions, refer to

AI voice Agent Sessions

.

Running and Testing the Agent

Step 5.1: Running the Python Script

To start your agent, run the script:
1python main.py
2

Step 5.2: Interacting with the Agent in the Playground

After running the script, check the console for a playground link. Open this link in your browser to interact with the agent. You can speak to the agent and receive responses in real-time.

Advanced Features and Customizations

Extending Functionality with Custom Tools

You can extend the agent's functionality by integrating custom tools. These tools can perform specific tasks or provide additional data sources for the agent.

Exploring Other Plugins

While this tutorial uses specific plugins, the VideoSDK framework supports various STT, LLM, and TTS options. Explore these alternatives to customize your agent further. For a quick setup, refer to the

Voice Agent Quick Start Guide

.

Troubleshooting Common Issues

API Key and Authentication Errors

Ensure your API keys are correctly configured in the .env file. Double-check for typos and ensure your account has the necessary permissions.

Audio Input/Output Problems

Verify your microphone and speaker settings. Ensure they are correctly configured and accessible by the application.

Dependency and Version Conflicts

If you encounter issues with dependencies, ensure all packages are up-to-date and compatible with your Python version.

Conclusion

Summary of What You've Built

You've successfully built an AI Voice Agent for logistics using the VideoSDK framework. This agent can interact with users, providing valuable logistics information.

Next Steps and Further Learning

Explore additional plugins and custom tools to enhance your agent's capabilities. Consider integrating more complex logic or expanding the agent's domain to cover other areas of logistics.

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