Update app.py

app.py

@@ -9,7 +9,6 @@ Cerekey = os.getenv("LitReview")
 # Initialize Cerebras AI client with the API key
 client = Cerebras(api_key=Cerekey)
 
-
 def extract_text_from_file(file):
     """Extracts text from uploaded PDF or DOCX files."""
     if file.name.endswith(".pdf"):
@@ -99,19 +98,20 @@ def analyze_document(file):
 
     chunks = chunk_text(text)
     all_insights = []
-    progress = []
 
-    progress.append("**Processing the document. Please wait...**")
+    # Yield progress for chunking and analysis
+    yield "**Processing the document. Please wait...**\n"
     for i, chunk in enumerate(chunks, 1):
-        progress.append(f"**Processing chunk {i} of {len(chunks)}...**")
+        yield f"**Processing chunk {i} of {len(chunks)}...**"
         result = analyze_chunk(chunk)
         if result.strip():  # Only append non-empty results
             all_insights.append(result)
 
     if not all_insights:
-        return "**Error:** No valid insights were extracted from the document.", None
+        yield "**Error:** No valid insights were extracted from the document."
+        return
 
-    progress.append("**Consolidating all insights into a final summary...**")
+    yield "**Consolidating all insights into a final summary...**\n"
     consolidated_summary_prompt = (
         "Below are insights extracted from multiple chunks of a document. "
         "Consolidate these insights into a single output organized as follows: "
@@ -134,35 +134,28 @@ def analyze_document(file):
         final_summary = ""
         for chunk in stream:
             final_summary += chunk.choices[0].delta.content or ""
-        
-        progress.append(f"**Final Summary:**\n\n{final_summary}")
+
+        yield f"**Final Summary:**\n\n{final_summary}"
 
         # Generate DOCX file after processing
         docx_file = save_as_docx(final_summary)
-        return "\n".join(progress), docx_file
-
+        return final_summary, docx_file
     except Exception as e:
-        return f"**Error:** An error occurred during consolidation: {e}", None
+        yield f"**Error:** An error occurred during consolidation: {e}", None
 
 
 # Define the Gradio interface
-def main():
-    with gr.Blocks() as iface:
-        with gr.Row():
-            file_input = gr.File(label="Upload a PDF or DOCX file")
-        
-        analysis_output = gr.Markdown(label="Progress and Analysis")
-        download_button = gr.File(label="Download Analysis as DOCX", visible=False)
-
-        def process_input(file):
-            if not file:
-                return "Please upload a file.", None
-            return analyze_document(file)
-
-        submit_button = gr.Button("Analyze Document")
-        submit_button.click(process_input, [file_input], [analysis_output, download_button])
-
-    iface.launch(share=True)
-
+interface = gr.Interface(
+    fn=analyze_document,
+    inputs=gr.File(label="Upload a PDF or DOCX file"),
+    outputs=[gr.Markdown(label="Progress and Analysis"), gr.File(label="Download the DOCX report")],
+    title="Automated Literature Review",
+    description=(
+        "Upload a PDF or DOCX document, and this tool will analyze it to extract and consolidate its content. "
+        "It might take a while, be patient. You are advised to upload smaller documents with shorter text as it may take a while to process longer files."
+    ),
+)
+
+# Launch the interface
 if __name__ == "__main__":
-    main()
+    interface.launch()