Update app.py

app.py

@@ -1,92 +1,62 @@
 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"):
+    def __init__(self, model_name="facebook/bart-large-cnn"):
         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']
+        try:
+            summary = self.summarizer(
+                text, 
+                max_length=150, 
+                min_length=50, 
+                do_sample=False
+            )[0]['summary_text']
+            return summary
+        except Exception as e:
+            return f"Summarization error: {str(e)}"
 
 def process_input(input_type, input_data):
     try:
-        logging.info(f"Processing input type: {input_type}")
-        
+        # Direct text handling
         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."
+            return summarizer.summarize(input_data)
+        
+        # File input handling (simplified)
+        if input_type in ["Text File", "PDF", "DOCX"]:
+            with open(input_data.name, 'r', encoding='utf-8') as file:
+                text = file.read()
+            return summarizer.summarize(text)
+        
+        # Audio input (placeholder - would require speech-to-text)
+        if input_type == "Audio":
+            return "Audio summarization not implemented"
+        
+        return "Invalid input type"
+    
     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")
+        return f"Processing error: {str(e)}"
 
 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
-
+    
+    # Gradio Interface
     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"
+        fn=process_input,
+        inputs=[
+            gr.Radio(["Text", "Text File", "PDF", "DOCX", "Audio"], label="Input Type"),
+            gr.File(type="file", label="Input")
+        ],
+        outputs=gr.Textbox(label="Summary"),
+        title="Text Summarization App",
+        description="Upload text or select input type for summarization"
     )
-
+    
     interface.launch()
 
 if __name__ == "__main__":