A Streamlit web application that uses AI to summarize agricultural reports and documents. 
- Text Input: Paste text directly for summarization
- PDF Upload: Upload PDF files to extract and summarize text
- AI-Powered Summarization: Uses Facebook's BART model for high-quality summaries
- Key Terms Extraction: Identifies the most frequent terms in the document
- User-Friendly Interface: Clean and intuitive Streamlit interface
- Clone this repository:
git clone https://github.com/Rajshinde9909/Agro-Sum.git
cd LLM_DOC_Summ- Create a virtual environment:
python -m venv my_env- Activate the virtual environment:
# On Windows
my_env\Scripts\activate
# On macOS/Linux
source my_env/bin/activate- Install dependencies:
pip install -r requirements.txt- Run the Streamlit application:
streamlit run agrisum.py-
Open your web browser and go to the URL shown in the terminal (usually
http://localhost:8501) -
Choose your input method:
- Paste Text: Copy and paste your agricultural report text
- Upload PDF: Upload a PDF file containing your report
-
Click "Generate Summary" to get an AI-powered summary
- Streamlit: Web application framework
- Transformers: Hugging Face library for AI models
- BART: Facebook's BART model for text summarization
- NLTK: Natural language processing toolkit
- PyPDF2: PDF text extraction
See requirements.txt for all dependencies.
This project is open source and available under the MIT License.