🩺 MedicalBot | RAG, GPT-4.1-Nano, LangChain, Pinecone, Flask, Hugging Face
🧠 Overview
MedicalBot is a Retrieval-Augmented Generation (RAG)–based medical chatbot that leverages GPT-4.1-Nano as its core Large Language Model.
It retrieves contextually relevant information from medical data using a LangChain-powered RAG pipeline, enabling accurate and reliable medical responses in real-time.
The system combines Hugging Face Sentence Embeddings with Pinecone Vector Storage to achieve intelligent retrieval and contextual reasoning.
It is deployed with Flask for an interactive web-based chatbot experience.
⚠️ Disclaimer:
MedicalBot is intended for informational and educational purposes only.
It should not be used as a substitute for professional medical diagnosis or treatment.
⚙️ Technical Stack
| Component | Technology |
|---|---|
| 💬 Language Model | GPT-4.1-Nano |
| 🔍 Retrieval Framework | LangChain |
| 🧠 Embedding Model | Hugging Face Sentence Transformers |
| 🧩 Vector Database | Pinecone |
| 🌐 Web Framework | Flask |
| ☁️ Hosting / Repository | Hugging Face Hub |
🚀 Key Features
- 🩹 Retrieves domain-specific medical answers using RAG
- ⚡ Fast and efficient generation via GPT-4.1-Nano
- 🧠 Improved reliability using Pinecone vector search
- 🔗 LangChain-based retrieval and generation pipeline
- 🌍 Supports English queries
- 💬 Ready for integration into Flask / FastAPI / Streamlit chat interfaces
🧾 Intended Use Cases
- 🩺 Patient education and medical Q&A
- 🧬 Clinical knowledge retrieval
- 🩹 Healthcare training assistant
- 🧠 AI-powered telemedicine support
👨💻 Developed by
Md. Aiyub Ali
AI Engineer | HawkEyes Digital Monitoring Ltd.
Expert in Generative AI, RAG Systems, and Medical LLMs
🔗 Hugging Face Profile