Update app.py

app.py

@@ -1,63 +1,85 @@
-import gradio as gr
+import streamlit as st
 import logging
-from transformers import pipeline
+from models.summarizer import TextSummarizer
+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="facebook/bart-large-cnn"):
-        self.summarizer = pipeline("summarization", model=model_name)
-    
-    def summarize(self, text):
-        if not text:
-            return "No text to summarize."
-        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:
-        # Direct text handling
-        if input_type == "Text":
-            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:
-        return f"Processing error: {str(e)}"
 
 def main():
-    global summarizer
-    summarizer = TextSummarizer()
+    # Setup logging
+    setup_logging()
+    logging.info("Starting GenAI Lab Report Analyzer with Streamlit.")
     
-    # Gradio Interface
-    interface = gr.Interface(
-        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"
+    # Initialize summarizer
+    summarizer = TextSummarizer()
+
+    # Streamlit UI
+    st.title("GenAI Lab Report Analyzer")
+    st.write("Upload a file, record audio, or type text to generate a summary. Select the appropriate input type and provide the input.")
+
+    input_type = st.radio(
+        "Select Input Type:",
+        options=["Text", "Text File", "PDF", "DOCX", "Audio"],
+        index=0
     )
-    
-    interface.launch()
+
+    file = None
+    text = None
+    audio = None
+
+    if input_type == "Text":
+        text = st.text_area("Enter your text here:", placeholder="Type your text here...")
+    elif input_type in ["Text File", "PDF", "DOCX"]:
+        file = st.file_uploader(f"Upload your {input_type}:", type=["txt", "pdf", "docx"])
+    elif input_type == "Audio":
+        audio = st.file_uploader("Upload your audio file:", type=["wav", "mp3", "m4a"])
+
+    if st.button("Report Result"):
+        try:
+            if input_type == "Text" and text:
+                logging.info("Processing text input.")
+                processed_text = handle_text_input(text)
+                summary = summarizer.summarize(processed_text)
+                logging.info("Text input processed successfully.")
+            elif input_type in ["Text File", "PDF", "DOCX"] and file:
+                if input_type == "Text File":
+                    logging.info(f"Processing text file: {file.name}")
+                    processed_text = read_text_file(file)
+                elif input_type == "PDF":
+                    logging.info(f"Processing PDF file: {file.name}")
+                    processed_text = read_pdf_file(file)
+                elif input_type == "DOCX":
+                    logging.info(f"Processing DOCX file: {file.name}")
+                    processed_text = read_docx_file(file)
+                
+                if processed_text:
+                    summary = summarizer.summarize(processed_text)
+                    logging.info(f"{input_type} processed successfully.")
+                else:
+                    summary = "Failed to process the file. Check logs for more details."
+                    logging.error(f"Failed to process {input_type}: {file.name}")
+            elif input_type == "Audio" and audio:
+                logging.info("Processing audio input.")
+                processed_text = audio_to_text(audio)
+                if processed_text:
+                    summary = summarizer.summarize(processed_text)
+                    logging.info("Audio input processed successfully.")
+                else:
+                    summary = "Failed to convert audio to text. Check logs for more details."
+                    logging.error("Failed to convert audio to text.")
+            else:
+                summary = "Invalid input. Please provide a valid file or text."
+                logging.warning("Invalid input type provided.")
+
+            st.text_area("Report Result:", summary, height=200)
+        except Exception as e:
+            logging.error(f"Error during summarization: {e}")
+            st.error("An error occurred during summarization. Please check the logs for more details.")
+
+    logging.info("Closing GenAI Lab Report Analyzer with Streamlit.")
+
 
 if __name__ == "__main__":
-    main()
+    main()