Text Summarizer Project

Text Summarizer takes a large document/paragraph and then uses an NLP model to generate a short paragraph.

This is a complete end-to-end Natural Language Processing machine learning project. APIs are developed for text summarization and training the model.

📷 Demo

🎆 Screen Recording

2023-12-25.18-50-05.mp4

⚒️ Workflow

The workflow defines the way the components and pipeline is constructed in the project. The basic workflow followed in this project is as follows:

1. Update config.yaml
2. Update secrets.yaml [Optional]
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Develop app.py

⚙️ Tech Stack

Programming Language: Python

Packages used: Pytorch, FastAPI, Transformers, Pandas, Numpy, Matplotlib, Seaborn, Streamlit, Scipy.

💻 How to run?

STEPS:

Clone the repository

htts://github.com/krishanwalia30/Text-Summarizer

STEP 01- Create a conda environment after opening teh repository

conda create -n summary python=3.8 -y

conda activate summary

STEP 02- Install the requirements.txt

pip install -r requirements.txt

# Finally run the following command
python app.py

Now,

Open: http://localhost:8000

📚 Lessons Learned

• Learned to create an end-to-end machine learning pipeline.
• Created different modules and components for different stages in pipeline development.
• Learned about Transformers
• Learned about Hugging Face API.
• Integrated Hugging Face API within the project for accessing the dataset.
• Learned to use FastAPI.

🧮 Features

• Developed APIs
• Model can be trained from the webapp interface as well.
• Prediction API is also made on the webapp.