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💊 TabLit

📒 Table of Contents

📍 Overview

  • TabLit is a Streamlit application that provides a user interface for chatting with Tabular Data using a LLM.
  • Its core functionalities include setting up the chat interface, integrating with the language model for generating responses, pre-processing and formatting data for ingestion by the model, allowing users to explore data, displaying intermediate language model steps, and saving chat history.
  • The project aims to streamline user interaction with the language model, enabling them to chat, explore data, and provide feedback to improve model performance.
  • This project was built as part of the Streamlit LLM Hackathon.
Swag🧦 Socks and stickers

🧩 Modules

Root
File Summary
TabLit.py The code provided is a Streamlit application that allows users to chat with tabular data using a language model. The application provides a user interface where the user can upload or crawl web data, explore the data, and then engage in a conversation with the language model.The core functionalities of the code include:-Setting up the Streamlit interface with a sidebar for user inputs and displaying the chat interface.-Handling user input and displaying previous chat messages.-Integrating with the language model to generate responses to user queries.-Pre-processing and formatting data for ingestion by the language model.-Allowing users to explore the uploaded or crawled data in a tabular format.-Generating and displaying intermediate steps of the language model while processing user queries.-Saving the chat history and providing a link to the LangSmith trace.-Allowing users to provide feedback on the language model's responses.Overall, the code provides a streamlined interface for users to interact with the language model, allowing them to chat, explore data, and provide feedback to improve the model's performance.
utils.py This code provides several core functionalities:1. It creates a zip file containing selected files from a specified directory and allows users to download it.2. It generates a unique session ID using UUID.3. It deletes empty subfolders within a specified folder.4. It loads data from uploaded files in different formats (e.g., csv, excel) using pandas.5. It obtains credentials for a Nimble service based on secrets provided in the Streamlit app.6. It reads a configuration file in JSON format.7. It searches for data on a specified platform (e.g., ecommerce, SERP) using a search keyword.8. It saves search results in a CSV file and returns a DataFrame object.9. It saves the chat conversation in a JSON file.Overall, the code supports file manipulation, data processing, external API communication, and persistence of data.
Pages
File Summary
3_Gallery.py This code creates a Streamlit webpage for a gallery of images. It imports the necessary libraries, sets up the page layout, reads the gallery configuration, and creates a carousel to display the images.
2_ReadMe.py This code uses Streamlit to create a web page with a collapsed sidebar and a "ReadMe" title icon.

🚀 Getting Started

📦 Installation

  1. Clone the Tablit repository:
git clone https://github.com/Prajwalsrinvas/Tablit
  1. Change to the project directory:
cd Tablit
  1. Install the dependencies:
pip install -r requirements.txt
  1. Copy secrets file and make required changes:
cp .streamlit\secrets_example.toml .streamlit\secrets.toml

🎮 Using Tablit

streamlit run TabLit.py