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| import gradio as gr | |
| import logging | |
| from transformers import pipeline | |
| from services.text_input_handler import handle_text_input | |
| from services.file_input_handler import read_text_file, read_pdf_file, read_docx_file | |
| from services.audio_input_handler import audio_to_text | |
| from utils.logging_utils import setup_logging | |
| class TextSummarizer: | |
| def __init__(self, model_name="t5-small"): | |
| self.summarizer = pipeline("summarization", model=model_name) | |
| def summarize(self, text): | |
| if not text: | |
| return "No text to summarize." | |
| summary = self.summarizer(text, max_length=150, min_length=30, do_sample=False) | |
| return summary[0]['summary_text'] | |
| def process_input(input_type, input_data): | |
| try: | |
| logging.info(f"Processing input type: {input_type}") | |
| if input_type == "Text": | |
| processed_text = handle_text_input(input_data) | |
| elif input_type == "Text File": | |
| processed_text = read_text_file(input_data) | |
| elif input_type == "PDF": | |
| processed_text = read_pdf_file(input_data) | |
| elif input_type == "DOCX": | |
| processed_text = read_docx_file(input_data) | |
| elif input_type == "Audio": | |
| processed_text = audio_to_text(input_data) | |
| else: | |
| return "Invalid input type." | |
| if processed_text: | |
| summary = summarizer.summarize(processed_text) | |
| logging.info(f"{input_type} processed successfully.") | |
| return summary | |
| else: | |
| logging.error(f"Failed to process {input_type}.") | |
| return "Failed to process the input. Check logs for more details." | |
| except Exception as e: | |
| logging.error(f"Error during summarization: {e}") | |
| return "An error occurred during summarization. Please check the logs for more details." | |
| def update_input_type(input_type): | |
| if input_type == "Text": | |
| return gr.update(value="", placeholder="Type your text here...") | |
| elif input_type == "Text File": | |
| return gr.update(value=None, type="file", label="Upload your text file") | |
| elif input_type == "PDF": | |
| return gr.update(value=None, type="file", label="Upload your PDF file") | |
| elif input_type == "DOCX": | |
| return gr.update(value=None, type="file", label="Upload your DOCX file") | |
| elif input_type == "Audio": | |
| return gr.update(value=None, type="file", label="Upload your audio file") | |
| else: | |
| return gr.update(value="", placeholder="Invalid input type") | |
| def main(): | |
| # Setup logging | |
| setup_logging() | |
| logging.info("Starting GenAI Lab Report Analyzer with Gradio.") | |
| # Initialize summarizer | |
| global summarizer | |
| summarizer = TextSummarizer() | |
| # Gradio interface | |
| input_type = gr.inputs.Radio(choices=["Text", "Text File", "PDF", "DOCX", "Audio"], label="Select Input Type") | |
| input_data = gr.inputs.Textbox(lines=5, label="Enter your text here") # Default for text input | |
| def interface_fn(input_type, input_data): | |
| updated_input = update_input_type(input_type) | |
| return process_input(input_type, input_data), updated_input | |
| interface = gr.Interface( | |
| fn=interface_fn, | |
| inputs=[input_type, input_data], | |
| outputs=[gr.outputs.Textbox(label="Report Result"), input_data], | |
| title="GenAI Lab Report Analyzer", | |
| description="Upload a file, record audio, or type text to generate a summary. Select the appropriate input type and provide the input.", | |
| live=True, | |
| theme="default", | |
| layout="vertical", | |
| allow_flagging="never" | |
| ) | |
| interface.launch() | |
| if __name__ == "__main__": | |
| main() |