📄 DocQuest – QA with Documents

DocQuest is a simple and interactive Streamlit web app that allows users to ask questions from uploaded documents and receive relevant answers using information retrieval techniques.

🚀 Features

• Upload documents in PDF, TXT, or DOCX format
• Ask natural language questions related to the uploaded document
• Real-time question answering powered by embeddings and a language model
• Displays chat history of previously asked questions and answers
• Intuitive and lightweight UI with branding support

🖼️ Preview

🛠️ Technologies Used

• Python
• Streamlit
• LangChain / Gemini (embedding & LLM API)
• Document ingestion & text extraction
• Session state for chat history

📁 Directory Structure

QAWithPDF/
├── data_ingestion.py      # Loads and parses uploaded documents
├── embedding.py           # Generates document embeddings using Gemini
├── model_api.py           # Loads the LLM for answering questions
StreamlitApp.py            # Main Streamlit app script
logo.png                   # App logo
README.md
requirements.txt

▶️ Getting Started

1. Clone the Repository

git clone https://github.com/vishal220703/Document-QA-System.git
cd LLM Project

2. Install Dependencies

pip install -r requirements.txt

3. Run the App

streamlit run StreamlitApp.py

📌 Notes

1. You must configure your embedding and LLM API keys in the respective modules (embedding.py, model_api.py).
2. All uploaded documents are processed in memory and are not stored permanently.
3. Logo can be replaced by adding your own logo.png to the root directory.

🧑‍💻 Author- Vishal M 📫 LinkedIn 💻 GitHub