Enockh3/SRH-chatbot-kinyarwanda-speaking

# 🤖 Kinyarwanda-Speaking Chatbot for Sexual and Reproductive Health (SRH) This is a prototype **RAG-based chatbot** designed to provide accurate, culturally relevant information on **Sexual and Reproductive Health (SRH)** in **Kinyarwanda**, integrated with **WhatsApp via Twilio**. Built using **LangChain**, **OpenAI's GPT-4o-mini**, and **FAISS vectorstore**, this project demonstrates how Retrieval-Augmented Generation can be applied to real-world public health challenges in low-resource languages. --- ## 🌍 Project Goals - 📲 Improve access to reliable SRH information in Kinyarwanda - 💬 Support WhatsApp-based queries via conversational AI - 🧠 Recommend family planning options based on user context (via prediction model) - 🌐 Demonstrate use of RAG in a low-resource language and testing environment --- ## ⚙️ Tech Stack - **Flask** – Web framework for the chatbot API - **LangChain** – For RAG pipeline and conversation memory - **OpenAI GPT-4o-mini** – LLM for generation - **FAISS** – Vector store for document retrieval - **Twilio API** – For WhatsApp message integration - **PyMuPDF, PowerPoint & Text Loaders** – For loading SRH content - **Ngrok** – To expose local Flask server for Twilio testing - **dotenv** – For API key management --- ## 📦 Features - ✅ Chatbot supports **Kinyarwanda SRH content** - ✅ Uses **RAG** to respond with domain-specific answers - ✅ Runs in **Twilio Sandbox** (test environment) - ✅ Handles multiple user sessions with conversation history - ✅ Real-time chat through WhatsApp interface - ✅ Flask-based server runs with background thread & ngrok tunneling --- ## 🛠️ How It Works 1. **Load SRH documents** (PDF, PPTX, TXT) from local directory 2. **Split content** into chunks and store embeddings in **FAISS vectorstore** 3. Create **retriever** for document search 4. Initialize **ChatOpenAI** model (GPT-4o-mini) and conversation memory 5. User sends a message on WhatsApp → handled via Flask route `/bot` 6. Twilio webhook receives the me …