/LLMs-GPT-ToolBox

🤖 GPT For Y'all, a Streamlit-based language model application offering a range of features like basic language generation 💬, creative writing ✍, text summarization 📝, few-shot learning 🎯, and Python code generation 🐍. An easy-to-use interface, designed for any language-related tasks. Your GPT model, our interface! 🚀

Primary LanguagePython

🤖 GPT For Y'all: A Streamlit-based Language Model Application

This repository contains code for a Streamlit application that leverages language models for various tasks 📚. The application includes functionalities for basic language generation 💬, creative writing ✍, text summarization 📝, few-shot learning 🎯, and Python code generation 🐍.

🌟 Features

The Streamlit application provides an interface for the following tasks:

  1. Base Generation 💬: This feature is for standard language generation tasks. Users can provide a prompt, and the application will generate a response based on the input.

  2. Creative Writing ✍: This feature allows users to generate creative content, such as stories or poems. Like base generation, it requires a user-provided prompt.

  3. Text Summarization 📝: This feature enables users to summarize long blocks of text. It requires a large text input from the user and generates a summarized version of the input.

  4. Few-Shot Learning 🎯: This feature is useful for performing few-shot learning. Users can provide a set of examples and a prompt, and the application will generate a response based on the given examples and the prompt.

  5. Python Code Generation 🐍: This feature leverages a Python agent for generating Python code based on user prompts.

📖 Usage

To use the application, you need to provide your OpenAI API Key and a path to the weights for your GPT model.

For each feature, you can input your prompt or text into the input box and hit 'Enter' 🖱. The application will generate and display the response.

🛠 Installation and Setup

The application requires Python and Streamlit. Other dependencies are included in the requirements.txt file.

To set up and run the application, follow these steps:

  1. Clone this repository to your local machine 🖥.

  2. Install the necessary dependencies by running pip install -r requirements.txt 📦.

  3. Set up your OpenAI API Key and the path to the GPT model weights 🔑.

  4. Run the application using Streamlit with streamlit run app-comparison.py 🚀.

📚 Dependencies

The main dependencies for this project are:

  • Streamlit: Used to build the web application interface.
  • Langchain: Used for language generation tasks.

🔗 Other References

  • GPT4AllReference: Mainly used to determine how to install the GPT4All library and references. The documentation was changing frequently, and at the time of coding this was the most up-to-date example of getting it running.