Update app.py

app.py

@@ -10,61 +10,64 @@ agent = CodeAgent(
 )
 
 def process_text(content):
-    """Handle text processing without database dependency"""
-    # Get CSV conversion from AI
-    csv_output = agent.run(f"Convert to CSV:\n{content}\nReturn ONLY valid CSV:")
-    
-    # Process CSV data
+    """Convert text content to structured format"""
+    csv_output = agent.run(f"Convert to CSV (include headers):\n{content}\nOutput ONLY valid CSV:")
     try:
-        df = pd.read_csv(StringIO(csv_output), keep_default_na=False)
-        return df.head(10), csv_output
-    except Exception as e:
-        return pd.DataFrame(), f"Error processing data: {str(e)}"
+        return pd.read_csv(StringIO(csv_output), keep_default_na=False)
+    except:
+        return pd.DataFrame()
 
 def analyze_content(full_text):
-    """Analyze text content for reporting"""
-    analysis_prompt = f"""
-    Analyze this text and generate a structured report:
+    """Generate comprehensive report"""
+    report = agent.run(f"""
+    Create detailed analysis report from this data:
     {full_text[:5000]}
     
     Include:
-    1. Key themes/topics
-    2. Important entities
-    3. Summary statistics
-    4. Recommendations/insights
+    1. Key insights and patterns
+    2. Important statistics
+    3. Actionable recommendations
+    4. Potential anomalies
     
     Use markdown formatting with headers.
-    """
-    return agent.run(analysis_prompt)
+    """)
+    return report
 
-def handle_upload(*files):
-    """Process uploaded files"""
+def handle_upload(files):
+    """Handle multiple file uploads correctly"""
     all_dfs = []
-    full_text = ""
+    full_content = []
     
     for file in files:
-        content = file.read().decode()
-        df, _ = process_text(content)
-        all_dfs.append(df)
-        full_text += f"\n\n--- {file.name} ---\n{content}"
+        try:
+            content = file.name + "\n" + file.read().decode()
+            df = process_text(content)
+            all_dfs.append(df)
+            full_content.append(content)
+        except Exception as e:
+            print(f"Error processing {file.name}: {str(e)}")
     
     combined_df = pd.concat(all_dfs, ignore_index=True) if all_dfs else pd.DataFrame()
-    report = analyze_content(full_text) if full_text else "No content to analyze"
+    report = analyze_content("\n\n".join(full_content)) if full_content else "No valid content found"
     
     return combined_df, report
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Document Analysis System")
+    gr.Markdown("# Multi-Document Analyzer")
     
     with gr.Row():
-        file_input = gr.File(file_count="multiple", file_types=[".txt"])
-        upload_btn = gr.Button("Process Files", variant="primary")
+        file_input = gr.File(
+            file_count="multiple",
+            file_types=[".txt"],
+            label="Upload Text Files"
+        )
+        process_btn = gr.Button("Analyze Documents", variant="primary")
     
     with gr.Row():
-        data_output = gr.Dataframe(label="Structured Data Preview")
+        data_output = gr.Dataframe(label="Structured Data Preview", wrap=True)
         report_output = gr.Markdown(label="Analysis Report")
 
-    upload_btn.click(
+    process_btn.click(
         handle_upload,
         inputs=file_input,
         outputs=[data_output, report_output]
@@ -74,5 +77,5 @@ if __name__ == "__main__":
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        show_error=True
+        share=True  # Enable public sharing
     )