| """ | |
| Summarization Model Handler | |
| Manages the BART model for text summarization. | |
| """ | |
| from transformers import pipeline | |
| import torch | |
| import streamlit as st | |
| class Summarizer: | |
| def __init__(self): | |
| """Initialize the summarization model.""" | |
| self.model = None | |
| def load_model(self): | |
| """Load the BART summarization model.""" | |
| try: | |
| self.model = pipeline( | |
| "summarization", | |
| model="facebook/bart-large-cnn", | |
| device=0 if torch.cuda.is_available() else -1 | |
| ) | |
| return self.model | |
| except Exception as e: | |
| st.error(f"Error loading summarization model: {str(e)}") | |
| return None | |
| def process(self, text: str, max_length: int = 130, min_length: int = 30): | |
| """Process text for summarization. | |
| Args: | |
| text (str): Text to summarize | |
| max_length (int): Maximum length of summary | |
| min_length (int): Minimum length of summary | |
| Returns: | |
| str: Summarized text | |
| """ | |
| try: | |
| summary = self.model(text, max_length=max_length, min_length=min_length) | |
| return summary | |
| except Exception as e: | |
| st.error(f"Error in summarization: {str(e)}") | |
| return None |