Document Querying Application

Welcome to the Document Querying Application! This tool allows users to upload documents in various formats (.pdf, .docx, .txt), query the documents for relevant information, and maintain a history of user interactions. This project demonstrates the potential of AI in enhancing document management and retrieval.

Table of Contents

• Features
• Tech Stack
• Installation
• Usage
• Key Learnings
• Project Showcase

Features

• Upload documents in .pdf, .docx, and .txt formats
• Efficiently query documents for relevant information
• Maintain a history of user queries and responses
• Download chat history in readable formats

Tech Stack

• Streamlit for the frontend interface
• SQLite for secure data storage
• Python for backend processing
• PyPDF2 and python-docx for document handling

Installation

To run this project, you need to have Python installed on your machine. Follow these steps to set up the environment:

1. Clone the repository:

git clone [insert repository link]

<li>Navigate to the project directory:</li>
<pre><code>cd Document-Querying-Application</code></pre>

<li>Create a <code>requirements.txt</code> file with the following content:</li>
<pre><code>streamlit

PyPDF2 python-docx cryptography

<li>Install the required packages:</li>
<pre><code>pip install -r requirements.txt</code></pre>

Usage

To use the Document Querying Application, run the main Python script. You will be prompted to upload documents and enter queries:

streamlit run app.py

Follow the on-screen instructions to upload documents, query them, and view your query history.

Key Learnings

• Integrating document handling libraries in Python
• Implementing secure database interactions
• Designing a user-friendly interface with Streamlit
• Managing user sessions and query history

Project Showcase

You can view the full project on my GitHub: LINK