LLM-Streamlit-Data-Converser

An interactive tool leveraging LangChain for dynamic question-answering from CSV datasets, featuring a Streamlit interface for ease of use and accessibility.

Overview

This repository hosts the code for a question-answering system that utilizes large language models (LLMs) to provide answers based on the uploaded CSV data. The system integrates LangChain to leverage the power of LLMs and Streamlit for a user-friendly interface, allowing users to upload data and ask questions dynamically.

Features

• CSV File Upload: Users can upload their own CSV files to be processed.
• Data Inquiry: After uploading, users can ask natural language questions regarding their data.
• LLM Integration: The system utilizes powerful language models to generate accurate and relevant answers.
• Streamlit Interface: A Streamlit-based web interface provides an easy-to-use platform for all interactions.

Getting Started

Prerequisites

Before running the application, ensure you have Python installed. Then, install the required dependencies:

pip install -r requirements.txt
git clone https://github.com/mayankbaluni/LLM-Streamlit-Data-Converser.git
cd LLM-Streamlit-Data-Converser
streamlit run stream-app.py

# End of script
exit 0

How to Use

To interact with the question-answering system, follow these simple steps:

1. Navigate to the hosted Streamlit app: Access the application through your web browser.
2. Upload CSV Data: Utilize the file uploader within the app to upload your dataset in CSV format.
3. Ask Your Question: Input your question regarding the data in the text field provided.
4. Receive the Answer: Submit your question and the system will utilize the underlying LLM to generate an answer based on your data.

Built With

• LangChain: A powerful framework used to integrate Large Language Models (LLMs) for advanced data processing and answering capabilities.
• Streamlit: An open-source app framework that is the cornerstone of our interactive web interface, simplifying the deployment of data applications.
• Pandas: An essential data analysis and manipulation library for Python, utilized here for efficient handling of CSV files and dataset operations.

Contact

For any queries or suggestions, feel free to contact me at [mayankbaluni@gmail.com]