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It leverages **NLP, ML, and LLM techniques** to generate accurate responses in real-time. Designed for quick and efficient access to medical information, this chatbot is a valuable resource for users seeking health-related guidance.  \n\n\u003e ⚠️ **Disclaimer:**  \n\u003e MediBot AI provides **general medical information** and is **not a substitute for professional medical advice**. Always consult a healthcare provider for medical concerns.  \n\n## ✨ Key Features  \n✅ **Custom LLM Model** – Utilizes a **custom Large Language Model** hosted on Hugging Face for precise medical responses.  \n✅ **Streamlit Interface** – Simple and interactive **web-based UI** for smooth user interactions.  \n✅ **Hugging Face Integration** – Secure model authentication via Hugging Face credentials.  \n✅ **LangChain for Context Management** – Handles chat history and improves **context-aware responses**.  \n✅ **Pinecone for Vector Storage** – Stores embeddings for efficient **retrieval of relevant medical information**.  \n\n## 📊 Demo  \n🔗 **Live Demo:** [Hugging Face Space](https://huggingface.co/spaces/GoodML/MediBotAI)  \n\n## 🛠️ Technologies Used  \n- **Python** 🐍  \n- **Streamlit** 🌐  \n- **Hugging Face API** 🤗  \n- **LangChain** 🔗  \n- **Pinecone (Vector Database)** 📚  \n- **LLaMA (Large Language Model)** 🧠  \n- **Pandas \u0026 NumPy** 📊  \n\n## 📂 Project Structure  \nMediBotAI/ │── app.py # Main Streamlit application\n│── model.py # LLM model integration \u0026 response generation\n│── data_handler.py # Pinecone vector storage \u0026 retrieval\n│── prompt_manager.py # LangChain prompt management\n│── requirements.txt # Python dependencies\n│── README.md # Project documentation\n│── assets/ # Images \u0026 resources\n\nbash\nCopy\nEdit\n\n## ⚡ Installation \u0026 Setup  \nFollow these steps to set up **MediBot AI** locally:  \n\n### 🔹 1. Clone the Repository  \n```bash\ngit clone https://github.com/YourUsername/MediBotAI.git\ncd MediBotAI\n🔹 2. Install Dependencies\nbash\nCopy\nEdit\npip install -r requirements.txt\n🔹 3. Set Up Hugging Face Authentication\nCreate an account on Hugging Face.\nGenerate an API token from your Hugging Face settings.\nAdd the token in your environment variables:\nbash\nCopy\nEdit\nexport HUGGINGFACE_API_KEY=\"your_api_token_here\"\n🔹 4. Run the Streamlit App\nbash\nCopy\nEdit\nstreamlit run app.py\n🏗️ How It Works\n1️⃣ User Input: Users enter medical queries via the Streamlit interface.\n2️⃣ Query Processing: LangChain processes prompts, managing chat history for contextual accuracy.\n3️⃣ Medical LLM Response: The chatbot generates responses using a custom Hugging Face model.\n4️⃣ Vector Retrieval: Pinecone retrieves relevant stored embeddings to enhance accuracy.\n5️⃣ Output: The chatbot provides structured, medically relevant responses in real-time.\n\n📸 Screenshots\n💬 Chatbot Interface\n\n🏥 Medical Query Response\n\n🚀 Future Enhancements\n🔹 Real-time Model Loading: Load models on-demand with progress indicators.\n🔹 Enhanced Medical Knowledge Base: Continuously update the database with the latest medical insights.\n🔹 Speech-to-Text Input: Allow users to ask queries via voice input.\n🔹 Multilingual Support: Expand to support multiple languages for global accessibility.\n\n🤝 Contributing\nWe welcome contributions! 🚀\n\nFork the repository\nCreate a new branch: git checkout -b feature/new-feature\nMake your changes and commit: git commit -m \"Add new feature\"\nPush to your branch: git push origin feature/new-feature\nOpen a Pull Request 🎉\n📜 License\nThis project is licensed under the MIT License – feel free to modify and use it!\n\n👨‍💻 Author\nDeveloped by Aniket Panchal ✨\n📧 Email: AniketPanchal1257@gmail.com\n🔗 LinkedIn: Your LinkedIn Profile\n🔗 GitHub: Your GitHub Profile\n\n🌟 If you like this project, give it a star! ⭐\n\nyaml\nCopy\nEdit\n\n---\n\n### **Why this README is effective?**  \n✅ **Professional Formatting** – Organized for readability 🎨  \n✅ **Badges \u0026 Icons** – Adds a polished look 🏆  \n✅ **Installation Steps** – Clear setup guide 🏗️  \n✅ **Future Enhancements** – Shows project roadmap 🚀  \n✅ **Contribution Section** – Encourages collaboration 🤝  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faniket2021448%2Fmedibotiq","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faniket2021448%2Fmedibotiq","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faniket2021448%2Fmedibotiq/lists"}