Update app.py

app.py

@@ -1,6 +1,4 @@
 import gradio as gr
-import pandas as pd
-from io import StringIO
 from smolagents import CodeAgent, HfApiModel
 
 # Initialize the AI agent
@@ -9,73 +7,56 @@ agent = CodeAgent(
     model=HfApiModel(model_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
 )
 
-def process_text(content):
-    """Convert text content to structured format"""
-    csv_output = agent.run(f"Convert to CSV (include headers):\n{content}\nOutput ONLY valid CSV:")
-    try:
-        return pd.read_csv(StringIO(csv_output), keep_default_na=False)
-    except:
-        return pd.DataFrame()
-
-def analyze_content(full_text):
-    """Generate comprehensive report"""
-    report = agent.run(f"""
-    Create detailed analysis report from this data:
-    {full_text[:5000]}
-    
-    Include:
-    1. Key insights and patterns
-    2. Important statistics
-    3. Actionable recommendations
-    4. Potential anomalies
-    
-    Use markdown formatting with headers.
-    """)
-    return report
-
-def handle_upload(files):
-    """Handle multiple file uploads correctly"""
-    all_dfs = []
+def analyze_content(file_paths):
+    """Process files and generate comprehensive report"""
     full_content = []
     
-    for file in files:
+    for path in file_paths:
         try:
-            content = file.name + "\n" + file.read().decode()
-            df = process_text(content)
-            all_dfs.append(df)
-            full_content.append(content)
+            with open(path, 'r', encoding='utf-8') as f:
+                content = f.read()
+                full_content.append(f"--- {path.split('/')[-1]} ---\n{content}")
         except Exception as e:
-            print(f"Error processing {file.name}: {str(e)}")
+            return f"Error processing {path}: {str(e)}"
     
-    combined_df = pd.concat(all_dfs, ignore_index=True) if all_dfs else pd.DataFrame()
-    report = analyze_content("\n\n".join(full_content)) if full_content else "No valid content found"
+    report = agent.run(f"""
+    Analyze these documents and create a detailed report:
+    
+    {''.join(full_content)[:10000]}  # First 10k characters
     
-    return combined_df, report
+    Report should include:
+    1. Key themes and patterns
+    2. Important relationships
+    3. Contextual insights
+    4. Actionable recommendations
+    
+    Use professional markdown formatting with headings.
+    """)
+    
+    return report
 
 with gr.Blocks() as demo:
-    gr.Markdown("# Multi-Document Analyzer")
+    gr.Markdown("# Document Analysis System")
     
     with gr.Row():
         file_input = gr.File(
             file_count="multiple",
             file_types=[".txt"],
-            label="Upload Text Files"
+            label="Upload Documents"
         )
-        process_btn = gr.Button("Analyze Documents", variant="primary")
+        process_btn = gr.Button("Generate Report", variant="primary")
     
-    with gr.Row():
-        data_output = gr.Dataframe(label="Structured Data Preview", wrap=True)
-        report_output = gr.Markdown(label="Analysis Report")
+    report_output = gr.Markdown(label="Analysis Report")
 
     process_btn.click(
-        handle_upload,
+        fn=analyze_content,
         inputs=file_input,
-        outputs=[data_output, report_output]
+        outputs=report_output
     )
 
 if __name__ == "__main__":
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=True  # Enable public sharing
+        share=True
     )