Text-to-SQL Patient Demographic Chatbot

This repository contains the implementation of a cutting-edge Text-to-SQL Patient Demographic Chatbot, leveraging Retrieval-Augmented Generation (RAG) and LangChain for seamless interaction with patient demographic data.

<h2>Features</h2>
<ul>
    <li><strong>Natural Language Interface</strong>: Enables users to query patient demographic data using natural language.</li>
    <li><strong>Text-to-SQL Conversion</strong>: Automatically translates user queries into SQL statements for precise database interaction.</li>
    <li><strong>RAG Technology</strong>: Integrates a retrieval mechanism to provide accurate and context-aware responses.</li>
    <li><strong>LangChain Integration</strong>: Utilizes LangChain for efficient query parsing, chaining, and response generation.</li>
    <li><strong>User-Friendly</strong>: Designed for healthcare professionals and administrators without technical expertise in SQL.</li>
</ul>

<h2>Technology Stack</h2>
<ul>
    <li><strong>LangChain</strong>: For robust query processing and chaining.</li>
    <li><strong>RAG Framework</strong>: To enhance response accuracy by utilizing external data retrieval.</li>
    <li><strong>Database Integration</strong>: Supports SQL databases containing patient demographic information.</li>
    <li><strong>Python</strong>: Primary language for implementation, ensuring scalability and maintainability.</li>
</ul>

<h2>Use Cases</h2>
<ul>
    <li>Quickly retrieve patient demographics by asking natural language questions (e.g., "Show me all patients aged above 60").</li>
    <li>Enable healthcare administrators to interact with data without the need for technical skills in SQL or database management.</li>
    <li>Improve data accessibility and streamline decision-making processes in healthcare organizations.</li>
</ul>

<h2>Installation and Usage</h2>
<ol>
    <li>Clone this repository.</li>
    <li>Install the required dependencies using <code>pip install -r requirements.txt</code>.</li>
    <li>Configure the database connection in the <code>config.json</code> file.</li>
    <li>Run the chatbot using <code>python main.py</code>.</li>
</ol>

<h2>Contributing</h2>
<p>
    We welcome contributions! Please feel free to fork this repository, create a new branch, 
    and submit a pull request with your enhancements or bug fixes.
</p>

<h2>License</h2>
<p>
    This project is licensed under the 
    <a href="LICENSE">MIT License</a>.
</p>