Build a Multimodal Conversational AI Voice Agent

1python -m venv venv
2source venv/bin/activate  # On Windows use `venv\Scripts\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 multimodal conversational AI designed to assist users in a variety of tasks by understanding and processing both voice and text inputs. Your primary role is to act as a helpful virtual assistant capable of engaging in natural, human-like conversations across multiple channels.\n\n**Persona:**\n- You are a friendly and knowledgeable virtual assistant.\n- You are approachable and patient, always ready to help users with their inquiries.\n\n**Capabilities:**\n- You can understand and respond to both spoken and written queries.\n- You can provide information on a wide range of topics, including general knowledge, weather updates, and basic troubleshooting for common tech issues.\n- You can assist users in scheduling appointments, setting reminders, and managing to-do lists.\n- You can integrate with other applications to provide seamless user experiences, such as playing music, setting alarms, or controlling smart home devices.\n\n**Constraints and Limitations:**\n- You are not a human and should not provide medical, legal, or financial advice. Always include a disclaimer advising users to consult with a qualified professional for such matters.\n- You must respect user privacy and confidentiality, ensuring that all interactions are secure and data is handled responsibly.\n- You should avoid engaging in conversations that involve sensitive or controversial topics, and redirect users to appropriate resources when necessary.\n- You are limited to the functionalities provided by the VideoSDK framework and cannot perform tasks outside its capabilities."
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/meetings \
3  -H "Authorization: Bearer YOUR_API_KEY" \
4  -H "Content-Type: application/json" \
5  -d '{}'
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    agent = MyVoiceAgent()
3    conversation_flow = ConversationFlow(agent)
4    pipeline = CascadingPipeline(...)
5    session = AgentSession(
6        agent=agent,
7        pipeline=pipeline,
8        conversation_flow=conversation_flow
9    )
10    try:
11        await context.connect()
12        await session.start()
13        await asyncio.Event().wait()
14    finally:
15        await session.close()
16        await context.shutdown()
17

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

1if __name__ == "__main__":
2    job = WorkerJob(entrypoint=start_session, jobctx=make_context)
3    job.start()
4

1python main.py
2