A simple medical chatbot built for clinicians to answer simple medical questions
# MediAssist — AI Clinical Decision Support System 🏥🤖
> RAG-powered AI assistant that helps clinicians query medical guidelines, drug interactions, and diagnostic protocols in natural language.
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## 🎯 Problem
Clinicians spend valuable minutes searching through dense guidelines and drug databases.
In low-resource settings, that delay costs lives.
MediAssist lets a doctor ask: *"What's the first-line treatment for pre-eclampsia?"*
and get an accurate, cited answer in seconds.
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## ✨ Features
- 📄 **Document ingestion** — upload clinical PDFs, guidelines, protocols
- 🔍 **Semantic search** — finds relevant content even with imperfect queries
- 🤖 **LLM response generation** — clear answers with source citations
- 🧠 **Memory** — maintains context across multi-turn conversations
- ⚡ **Optimised for low bandwidth** — minimal token usage, fast responses
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## 🏗 Architecture
```
PDF Documents → Text Chunking → Embeddings → Pinecone Vector Store
↓
User Query → Embedding → Similarity Search → Relevant Chunks
↓
LLM (GPT / Claude) → Cited Answer
```
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## 🛠 Tech Stack
| Layer | Technology |
|-------|-----------|
| LLM | OpenAI GPT-4 / Claude |
| Orchestration | LangChain |
| Vector DB | Pinecone |
| Embeddings | OpenAI text-embedding-3-small |
| API | FastAPI |
| UI | Streamlit |
| Deployment | Hugging Face Spaces |
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## 🚀 Quick Start
```bash
git clone
github.com
cd mediassist
pip install -r requirements.txt
cp .env.example .env # add your API keys
streamlit run app.py
```
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## 📸 Demo
Live Demo →
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## 🙋 Built By
**Purity Kirimi** — AI Engineer, Nairobi Kenya
LinkedIn · GitHub