Update app.py

app.py

@@ -8,9 +8,7 @@ def setup_logging():
     logging.basicConfig(
         level=logging.INFO,
         format='%(asctime)s - %(levelname)s - %(message)s',
-        handlers=[
-            logging.StreamHandler()
-        ]
+        handlers=[logging.StreamHandler()]
     )
 
 # Function to extract text from a PDF file
@@ -25,8 +23,8 @@ def main():
     setup_logging()
     logging.info("Starting the Streamlit app.")
 
-    # Initialize the summarization pipeline
-    summarizer = pipeline("summarization")
+    # Initialize the medical text summarization pipeline
+    summarizer = pipeline("summarization", model="your/medical_text_summarization_model")
 
     # Streamlit UI
     st.title("GenAI Lab Report Analyzer")
@@ -53,21 +51,21 @@ def main():
     elif input_type == "Audio":
         audio = st.file_uploader("Upload your audio file:", type=["wav", "mp3", "m4a"])
 
-    if st.button("Report Result"):
+    if st.button("Analyze Report"):
         try:
             summary = None
             if input_type == "Text" and text:
                 logging.info("Processing text input.")
-                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
+                summary = summarizer(text, max_length=2000, min_length=1500, do_sample=False)
                 logging.info("Text input processed successfully.")
             elif input_type == "Text File" and file:
                 logging.info(f"Processing text file: {file.name}")
                 text = file.read().decode("utf-8")  # Assuming UTF-8 encoding
-                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
+                summary = summarizer(text, max_length=2000, min_length=1500, do_sample=False)
             elif input_type == "PDF" and file:
                 logging.info(f"Processing PDF file: {file.name}")
                 text = extract_text_from_pdf(file)
-                summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
+                summary = summarizer(text, max_length=2000, min_length=1500, do_sample=False)
             elif input_type == "Audio" and audio:
                 logging.info("Processing audio input.")
                 # Add audio processing logic here