Vakya-AI — Gemini Agents | Neura Market
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    Vakya-AI

    Vakya-AI

    Yasaswini38 August 15, 2025
    6 copies 0 downloads

    Vākya AI — A real-time AI voice agent that listens, understands and talks back . Powered by FastAPI, WebSockets, AssemblyAI, Gemini, and Murf AI.

    Agent Definition
    Markdown
    
    # Vākya AI 🗣️
    
    Vākya, which means "sentence" in Sanskrit, is a conversational AI that allows users to interact with a Large Language Model (LLM) using their voice. Speak. Understand. Reply.
    That’s **Vākya** , a full loop of human-like conversation, built with **Python**, driven by **FastAPI**, and delivered in a crisp, modern UI.
    
    ***
    
    ## Wanna know How I look??
    
    [![Watch the demo](https://raw.githubusercontent.com/Yasaswini38/Vakya-AI/main/thumbnail.jpg)](https://raw.githubusercontent.com/Yasaswini38/Vakya-AI/main/demo_vakyaai.mp4)
    
    ***
    
    ### Features 
    
    * **Voice-to-Voice Interaction**: Talk to the AI and hear it respond back in real time.  
    * **Real-time Transcription**: See your speech transcribed instantly on screen.  
    * **Conversational Memory**: Maintains context within a session for natural dialogue.  
    * **Session Management**: Start new chats or revisit past conversations.  
    * **Voice Customization**: Choose from multiple voices for responses.  
    * **Fun Skills Built-in**: Weather updates, News headlines, Jokes on demand.  
    * **Modern UI**: Cute & aesthetic responsive interface with chat history panel.
    
    ***
    
    ### Technologies Used 
    
    * **FastAPI** — backend framework for REST + WebSocket support  
    * **Jinja2** — template rendering for frontend  
    * **AssemblyAI** — speech-to-text (transcription)  
    * **Google Gemini** — LLM for text generation  
    * **Murf.ai** — text-to-speech (streaming natural voices)  
    * **python-dotenv** — for managing API keys securely  
    * **HTML, CSS, JavaScript** — responsive UI (with chat history, persona selection)
    
    ***
    
    ### Architecture 
    
    The application follows a simple client-server architecture:
    
    1. User’s voice recorded via browser microphone  
    2. Audio streamed to FastAPI backend over WebSocket  
    3. AssemblyAI transcribes speech → text  
    4. Transcribed text + history → Gemini (LLM) for response generation  
    5. Response text → Murf.ai → natural voice audio stream  
    6. Frontend shows transcription, AI’s reply, and plays back

    Tags

    ai-voice-agentassemblyaifastapigenerative-ai-geminimurfrender-deploymentspeech-to-texttext-to-speechwebsocketswebsockets-server

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