Build AI Voice Assistant for Retail

1python3 -m venv retail-voice-agent-env
2source retail-voice-agent-env/bin/activate
3

1pip install videosdk
2pip install python-dotenv
3

1VIDEOSDK_API_KEY=your_api_key_here
2

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 Assistant specialized in the retail industry. Your primary role is to assist customers by providing information about products, helping with order placements, and offering support for common inquiries related to retail services. You can also provide updates on order status and assist with returns and exchanges. However, you are not authorized to handle sensitive payment information or process transactions directly. Always remind users to visit the official website or contact customer service for secure transactions. Your responses should be concise, informative, and friendly, ensuring a positive customer experience. You must include a disclaimer that you are an AI and that users should verify critical information with a human representative if needed."
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

1curl -X POST \
2  https://api.videosdk.live/v1/rooms \
3  -H "Authorization: Bearer YOUR_API_KEY" \
4  -H "Content-Type: application/json" \
5  -d '{"name": "Retail Agent Room"}'
6

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

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

1async def start_session(context: JobContext):
2    # Create agent and conversation flow
3    agent = MyVoiceAgent()
4    conversation_flow = ConversationFlow(agent)
5
6    # Create pipeline
7    pipeline = CascadingPipeline(
8        stt=DeepgramSTT(model="nova-2", language="en"),
9        llm=OpenAILLM(model="gpt-4o"),
10        tts=ElevenLabsTTS(model="eleven_flash_v2_5"),
11        vad=SileroVAD(threshold=0.35),
12        turn_detector=TurnDetector(threshold=0.8)
13    )
14
15    session = AgentSession(
16        agent=agent,
17        pipeline=pipeline,
18        conversation_flow=conversation_flow
19    )
20
21    try:
22        await context.connect()
23        await session.start()
24        # Keep the session running until manually terminated
25        await asyncio.Event().wait()
26    finally:
27        # Clean up resources when done
28        await session.close()
29        await context.shutdown()
30
31def make_context() -> JobContext:
32    room_options = RoomOptions(
33    #  room_id="YOUR_MEETING_ID",  # Set to join a pre-created room; omit to auto-create
34        name="VideoSDK Cascaded Agent",
35        playground=True
36    )
37
38    return JobContext(room_options=room_options)
39
40if __name__ == "__main__":
41    job = WorkerJob(entrypoint=start_session, jobctx=make_context)
42    job.start()
43

1python main.py
2