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Medical_Chatbot_

Medical Chatbot – CS120 Project Overview This project is a Medical Chatbot that allows users to ask basic, general medical questions and receive helpful, AI-generated responses. It is designed to make accessing medical information easier, faster, and more conversational.

Disclaimer: This tool is for educational purposes only and does not provide professional medical advice.

Features

💬 Real-time AI responses powered by GPT-4.0

📚 Vector search for efficient medical knowledge retrieval

🧠 Custom embeddings using organ-based embedding models

⚙️ Modular backend built for scalability

Tech Stack

Core Technologies

GPT-4.0 – primary LLM for generating responses

LangChain – orchestration framework for pipelines, chains, and agents

Pinecone – vector database for storing and querying embeddings

Flags – backend server framework

Organ-based Embedding Models – used to generate domain-specific vector representations

Languages Python JavaScript

Architecture User interacts with the chatbot via text

Query is embedded using organ-based embedding models

Embedding is sent to Pinecone for relevant context retrieval

Retrieved medical context + user query is passed through LangChain

GPT-4.0 generates the final answer

Response is returned to the user

Installation & Setup

  1. Clone the repository git clone https://github.com/your-username/your-repo-name.git cd your-repo-name

  2. Install Dependencies pip install -r requirements.txt

  3. Set Environment Variables

Create a .env file with: OPENAI_API_KEY=your_key PINECONE_API_KEY=your_key PINECONE_ENVIRONMENT=your_env

Add any additional keys if your setup requires them. 7. Run the Backend

python app.py Usage

Start the backend Open the UI / frontend (if applicable) Speak or type your medical question The chatbot retrieves relevant info, reasons using GPT-4.0, and responds

Project Structure /project-root │── app.py │── embeddings/ │── modules/ │── utils/ │── README.md │── requirements.txt

Limitations Not a substitute for professional healthcare Responses depend on available vector data The system does not diagnose medical conditions

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