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| title: Interactive AI Voice Chat | |
| emoji: 🚀 | |
| colorFrom: pink | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 6.0.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Real-time AI voice assistant through natural speech | |
| ## 🚀 Overview | |
| Interactive AI Voice Chat is a real-time voice-driven assistant deployed on Hugging Face Spaces. | |
| It allows users to speak naturally through their microphone and receive intelligent AI responses, both in text and audio format. The system leverages modern speech-to-text, large language models, and text-to-speech technologies to deliver a seamless conversational experience. | |
| This project demonstrates a complete workflow from local development to live deployment on the Hugging Face platform. | |
| --- | |
| ## ✨ Key Features | |
| - 🎤 Real-time voice input processing | |
| - 🤖 AI-powered responses using `google/gemma-2-2b-it` | |
| - 🔊 Text-to-Speech audio replies | |
| - 🌐 Publicly accessible live demo | |
| - ⚡ Optimized for CPU Basic hardware | |
| - 🧩 Secure token-based model access | |
| --- | |
| ## 🖥️ How It Works | |
| 1. User speaks into the microphone. | |
| 2. Speech is converted to text using STT engine. | |
| 3. The text is processed by the AI model. | |
| 4. AI generates a response. | |
| 5. Response is converted back into audio and played to the user. | |
| --- | |
| ## 📁 Project Structure | |
| ai-voice-chat-test/ | |
| - │ | |
| - ├── app.py # Main application logic | |
| - ├── README.md # Documentation | |
| - ├── requirements.txt # Python dependencies | |
| - ├── runtime.txt # Python version | |
| - ├── apt.txt # System dependencies (ffmpeg) | |
| - ├── .gitattributes # Git LFS configuration | |
| - ├── .gitignore # Ignored files and folders | |
| - └── assets/ # Optional media resources | |
| --- | |
| ## ⚙️ Installation (Local Setup - Optional) | |
| To run this project locally: | |
| ```bash | |
| git clone https://huggingface.co/spaces/bdstar/ai-voice-chat-test | |
| cd ai-voice-chat-test | |
| pip install -r requirements.txt | |
| Set your Hugging Face token: | |
| export HF_TOKEN="your_token_here" | |
| Run the application: | |
| python app.py | |
| Open your browser and visit: | |
| http://localhost:7860 | |
| ``` | |
| --- | |
| ## 📦 Python Environment | |
| - Python Version: 3.11 | |
| - Gradio Version: 5.49.1 | |
| - Optimized for: CPU Basic | |
| --- | |
| ## ⚠️ Notes & Limitations | |
| - Running on CPU may result in slower response times. | |
| - Initial model loading may take few seconds. | |
| - For production use, GPU-backed hardware is recommended. | |
| - This project is intended for demonstration and learning purposes. | |
| --- | |
| ## 📌 Deployment Steps Summary | |
| 1. Prepare project structure | |
| 2. Configure requirements.txt and runtime.txt | |
| 3. Add HF_TOKEN as secret | |
| 4. Push source code to Hugging Face Space | |
| 5. Monitor build logs | |
| 6. Access live demo | |
| --- | |
| ## 🙏 Credits | |
| - Model: google/gemma-2-2b-it | |
| - Platform: Hugging Face Spaces | |
| - UI Framework: Gradio | |
| - Speech Engine: Faster Whisper | |
| - TTS System: PyDub + Soundfile | |
| --- | |
| ## 📣 Feedback & Contributions | |
| Feel free to fork this Space, suggest improvements, or contribute new features. | |
| Your feedback is highly appreciated! | |
| --- | |
| ## ⭐ If you like this project, don't forget to star the repository! | |
| If you'd like: | |
| - 📷 Screenshots section | |
| - 🎥 Video tutorial link area | |
| - 🏷 Badges (Deploy, Python, Gradio) | |
| - 👨💻 Author profile section | |
| Just tell me — I can enhance the README further 👍 | |