Text Summarizer Pipeline

This is Project made with the help of Groq and TextGrad.

Running project locally

Method 1 - Using Nix (For UNIX based systems)

Make sure you have the Nix package manager and Git installed.

1. Clone the repository

git clone https://github.com/Natural-Language-Computing/Text-Summarizer-Pipeline.git
cd Text-Summarizer-Pipeline

2. Create .env file and put your Groq API key in it

GROQ_API_KEY="your API key"

3. Enable nix shell

nix develop --extra-experimental-features "nix-command flakes" --no-pure-eval

# This command will install Python, create a virtual environment, and install dependencies required for the project
# Refer to `flake.nix` for more details.

4. Run the project

streamlit run pipeline.py

5. Open the browser and go to http://localhost:8501

Method 2 - Traditional Method

Make sure you have the following installed:

• Git
• Python 3.11 or higher

To run the project locally, follow these steps:

1. Clone the repository

git clone https://github.com/Natural-Language-Computing/Text-Summarizer-Pipeline.git
cd Text-Summarizer-Pipeline

2. Create .env file and put your Groq API key in it

GROQ_API_KEY="your API key"

3. Create a virtual environment

python3 -m venv venv

4. Activate the virtual environment

# On Windows
venv\Scripts\Activate.ps1

# On Linux or macOS
source venv/bin/activate

5. Install the dependencies

python3 -m pip install -r requirements.txt

6. Run the project

streamlit run pipeline.py

7. Open the browser and go to http://localhost:8501