Introduction to AI Voice Agents in the Supply Chain Industry
AI Voice Agents are sophisticated software systems that can interpret human speech, process the information, and respond in a conversational manner. These agents are powered by advanced technologies such as Speech-to-Text (STT), Language Learning Models (LLM), and Text-to-Speech (TTS) systems. In the context of the supply chain industry, AI Voice Agents can streamline operations by providing real-time insights, answering queries related to logistics, inventory management, and procurement processes.
In this tutorial, we will build an AI
Voice Agent
designed specifically for the supply chain industry. This agent will leverage the VideoSDK framework, which provides a robust platform for developing voice-enabled applications.Architecture and Core Concepts
High-Level Architecture Overview
The AI
Voice Agent
operates by capturing user speech, converting it to text, processing the text to generate a response, and finally converting the response back to speech. This process involves several key components:- STT (Speech-to-Text): Converts spoken language into text using the
Deepgram STT Plugin for voice agent
. - LLM (Language Learning Model): Processes the text to understand context and generate responses, facilitated by the
OpenAI LLM Plugin for voice agent
. - TTS (Text-to-Speech): Converts the generated text response back into speech with the help of the
ElevenLabs TTS Plugin for voice agent
.

Understanding Key Concepts in the VideoSDK Framework
- Agent: The central class representing your voice bot.
- CascadingPipeline: Manages the sequential flow of audio processing from STT to LLM to TTS, as detailed in the
Cascading pipeline in AI voice Agents
. - VAD & TurnDetector: These components help the agent determine when to listen and when to respond, utilizing the
Turn detector for AI voice Agents
.
Setting Up the Development Environment
Prerequisites
Before we begin, ensure you have Python 3.11+ installed and a VideoSDK account set up at app.videosdk.live.
Step 1: Create a Virtual Environment
Create a virtual environment to manage dependencies:
1python -m venv venv
2source venv/bin/activate # On Windows use `venv\\Scripts\\activate`
3Step 2: Install Required Packages
Install the necessary packages using pip:
1pip install videosdk-agents videosdk-plugins
2Step 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
2Building the AI Voice Agent: A Step-by-Step Guide
Here is the complete 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 a knowledgeable AI Voice Agent specialized in the supply chain industry. Your primary role is to assist users by providing insights and answering questions related to supply chain management, logistics, inventory control, and procurement processes. You can offer guidance on optimizing supply chain operations, suggest best practices, and provide updates on industry trends. However, you are not a certified supply chain consultant, and users should verify critical decisions with a professional. You must include a disclaimer advising users to consult with a qualified expert for complex supply chain issues. Your responses should be concise, informative, and tailored to the supply chain context."
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()
63Step 4.1: Generating a VideoSDK Meeting ID
Before running the agent, you need a meeting ID. You can generate this 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 -d '{"region":"sg001"}'
6Step 4.2: Creating the Custom Agent Class
The
MyVoiceAgent class is where we define the agent's behavior. It inherits from the Agent class and implements the on_enter and on_exit methods to handle session start and end events.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!")
6Step 4.3: Defining the Core Pipeline
The
CascadingPipeline
is crucial as it defines the flow of data through the system. It connects the STT, LLM, and TTS plugins, allowing seamless interaction.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)
8Step 4.4: Managing the Session and Startup Logic
The
start_session function initializes the agent session and manages the lifecycle of the conversation, as outlined in the AI voice Agent Sessions
.1async def start_session(context: JobContext):
2 agent = MyVoiceAgent()
3 conversation_flow = ConversationFlow(agent)
4
5 pipeline = CascadingPipeline(
6 stt=DeepgramSTT(model="nova-2", language="en"),
7 llm=OpenAILLM(model="gpt-4o"),
8 tts=ElevenLabsTTS(model="eleven_flash_v2_5"),
9 vad=SileroVAD(threshold=0.35),
10 turn_detector=TurnDetector(threshold=0.8)
11 )
12
13 session = AgentSession(
14 agent=agent,
15 pipeline=pipeline,
16 conversation_flow=conversation_flow
17 )
18
19 try:
20 await context.connect()
21 await session.start()
22 await asyncio.Event().wait()
23 finally:
24 await session.close()
25 await context.shutdown()
26Running and Testing the Agent
Step 5.1: Running the Python Script
To start the agent, run the Python script:
1python main.py
2Step 5.2: Interacting with the Agent in the Playground
Once the agent is running, you can interact with it using the
AI Agent playground
. The console will provide a link to join the session.Advanced Features and Customizations
Extending Functionality with Custom Tools
The VideoSDK framework allows you to extend the agent's functionality by integrating custom tools and plugins to suit specific needs.
Exploring Other Plugins
While this tutorial uses specific plugins, you can explore other STT, LLM, and TTS options available in the VideoSDK ecosystem.
Troubleshooting Common Issues
API Key and Authentication Errors
Ensure your API key is correctly configured in the
.env file and that you have the necessary permissions.Audio Input/Output Problems
Check your microphone and speaker settings to ensure they are correctly configured and not muted.
Dependency and Version Conflicts
Ensure all dependencies are installed with compatible versions as specified in the documentation.
Conclusion
In this tutorial, we built a fully functional AI Voice Agent tailored for the supply chain industry using the VideoSDK framework. This agent can assist with logistics, inventory management, and more. As next steps, consider exploring additional plugins and customizations to further enhance the agent's capabilities.
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