Skip to content

Latest commit

 

History

History
83 lines (56 loc) · 2 KB

README.md

File metadata and controls

83 lines (56 loc) · 2 KB

Study Plan Generation using LangChain 🦜🔗

This project generates personalized study plans for students using LangChain and OpenAI's GPT-4 model.

Table of Contents

Installation

  1. Clone the repository:

    git clone https://github.com/fisa712/cogentlabs.git
cd cogentlabs

  2. Create a virtual environment:

    python -m venv env
source env/bin/activate  # On Windows use `env\Scripts\activate`

  3. Install the dependencies:

    pip install -r requirements.txt

Environment Variables

Create a .env file in the root directory of the project and add your OpenAI API key:

Usage

To run the notebook and generate a study plan:

  1. Open the Jupyter notebook:

    jupyter notebook UntitledCogent.ipynb

  2. Run all cells in the notebook:

    • Follow the instructions in the notebook to input student information.
    • The notebook will generate a personalized study plan based on the provided information.

Tasks

Generate Study Plan

  1. Load Dependencies: Ensure all required libraries are imported.

  2. Set Up Environment Variables: Load your API key from the .env file.

  3. Initialize Model: Set up the OpenAI model with your API key.

  4. Define Prompt Template: Create a prompt template for generating the study plan.

  5. Generate Study Plan: Invoke the chain to generate a study plan.

Generate summary of book

  1. using runnables created summary of the book use langchain lcel runnables to get the summary of documents.
  2. utilizing reportlab to generate a pdf document Use reportlab to create a PDF of the generated plan.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License.