Build an AI Voice Assistant for Astrology

Create an AI voice assistant for astrology with VideoSDK. Follow this step-by-step guide with complete code examples.

Introduction to AI Voice Agents in the Astrology Industry

In today's fast-paced world, AI voice agents are revolutionizing how industries operate, providing seamless and interactive experiences for users. In this tutorial, we will delve into the fascinating world of AI voice assistants and explore their potential in the astrology industry.

What is an AI

Voice Agent

?

An AI

voice agent

 is a software application designed to interact with users through voice commands. It processes spoken language, understands user intent, and responds accordingly, providing a natural conversational experience. These agents are powered by sophisticated technologies such as speech-to-text (STT), natural language processing (NLP), and text-to-speech (TTS).

Why are they important for the Astrology Industry?

In the astrology industry, AI voice agents can offer personalized astrological insights, daily horoscopes, and guidance on zodiac compatibility. They can transform user interactions by providing instant, voice-driven access to astrological information, making it easier for users to engage with astrology content.

Core Components of a

Voice Agent

To build a robust AI

voice agent

, several core components are essential:
  • Speech-to-Text (STT): Converts spoken language into text.
  • Large Language Model (LLM): Processes and understands the text to generate meaningful responses.
  • Text-to-Speech (TTS): Converts text responses back into spoken language.

What You'll Build in This Tutorial

In this tutorial, we'll guide you through building an AI voice assistant tailored for the astrology industry. You'll learn how to set up a development environment, create a custom agent, and deploy it using VideoSDK.

Architecture and Core Concepts

High-Level Architecture Overview

The architecture of our AI voice agent involves a seamless flow of data from user speech to agent response. The process begins with capturing user speech, converting it into text using STT, processing the text with an LLM, and finally generating a spoken response with TTS.
Diagram

Understanding Key Concepts in the VideoSDK Framework

  • Agent: The core class representing your bot, responsible for handling interactions.

  • Cascading Pipeline in AI voice Agents

    :     Manages the flow of audio processing, integrating STT, LLM, and TTS.
  • VAD & TurnDetector: These components help the agent know when to listen and when to speak.

Setting Up the Development Environment

Prerequisites

Before we dive into coding, ensure you have the following:
  • Python 3.11+
  • VideoSDK Account: Sign up at app.videosdk.live to access necessary API keys.

Step 1: Create a Virtual Environment

To manage dependencies efficiently, create a virtual environment:
1python -m venv astrology-voice-agent-env
2source astrology-voice-agent-env/bin/activate  # On Windows use `astrology-voice-agent-env\\Scripts\\activate`
3

Step 2: Install Required Packages

Install the necessary packages using pip:
1pip install videosdk
2pip install python-dotenv
3

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

Here is the complete code to set up your AI voice agent for the astrology industry:
1import asyncio, os
2from videosdk.agents import Agent, AgentSession, CascadingPipeline, JobContext, RoomOptions, WorkerJob, ConversationFlow
3from videosdk.plugins.silero import [Silero Voice Activity Detection](https://docs.videosdk.live/ai_agents/plugins/silero-vad)
4from videosdk.plugins.turn_detector import [Turn detector for AI voice Agents](https://docs.videosdk.live/ai_agents/plugins/turn-detector), 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 insightful astrology voice assistant designed to provide users with personalized astrological insights and guidance. Your primary capabilities include answering questions about zodiac signs, providing daily horoscopes, explaining astrological concepts, and offering compatibility advice based on astrological charts. You can also suggest auspicious dates for events based on astrological calendars. However, you must clearly state that your insights are for entertainment purposes only and should not be considered professional advice. You are not a certified astrologer, and users should consult professional astrologers for in-depth analysis and advice. Always ensure user privacy and data security in your interactions."
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](https://docs.videosdk.live/ai_agents/core-components/agent-session)(
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 start, you need a meeting ID. Use the following curl command to generate one:
1curl -X POST "https://api.videosdk.live/v1/meetings" \
2-H "Authorization: Bearer YOUR_API_KEY" \
3-H "Content-Type: application/json"
4

Step 4.2: Creating the Custom Agent Class

The MyVoiceAgent class is the heart of our voice assistant. It inherits from the Agent class and defines custom behaviors for entering and exiting interactions:
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 orchestrates the flow of audio data through various processing stages:
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
Each component plays a crucial role:
  • STT (DeepgramSTT): Converts speech to text.
  • LLM (OpenAILLM): Processes the text and generates responses.
  • TTS (ElevenLabsTTS): Converts text back to speech.
  • VAD (SileroVAD): Detects voice activity.
  • TurnDetector: Manages conversational turns.

Step 4.4: Managing the Session and Startup Logic

The start_session function and the if __name__ == "__main__": block manage the agent's lifecycle:
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 your agent, execute the following command:
1python main.py
2

Step 5.2: Interacting with the Agent in the

AI Agent playground

Once the script is running, check the console for a playground link. Open the link in your browser to interact with your voice assistant.

Advanced Features and Customizations

Extending Functionality with Custom Tools

You can extend your agent's capabilities by integrating custom tools, allowing it to perform specific tasks beyond basic conversation.

Exploring Other Plugins

Consider experimenting with other plugins for STT, LLM, and TTS to enhance your agent's performance and capabilities.

Troubleshooting Common Issues

API Key and Authentication Errors

Ensure your API keys are 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 functioning.

Dependency and Version Conflicts

Use a virtual environment to manage dependencies and avoid version conflicts.

Conclusion

Summary of What You've Built

Congratulations! You've built a fully functional AI voice assistant for the astrology industry, capable of providing insightful astrological guidance.

Next Steps and Further Learning

Explore additional features and plugins to enhance your agent's capabilities. Consider integrating more advanced NLP models or expanding its knowledge base for more in-depth astrology insights.

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