Delete app.py

app.py

@@ -1,92 +0,0 @@
-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 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 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")
-
-    input_data = gr.inputs.Textbox(lines=5, label="Enter your text here")  # Default for text input
-    output = gr.outputs.Textbox(label="Report Result")
-
-    interface = gr.Interface(
-        fn=process_input,
-        inputs=[input_type, input_data],
-        outputs=output,
-        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()