Update app.py

app.py

@@ -53,20 +53,32 @@ agent = CodeAgent(
     additional_authorized_imports=["numpy", "pandas", "matplotlib.pyplot", "seaborn"]
 )
 
-analysis_result = agent.run(
-    """
-    You are an expert data analyst. Perform comprehensive analysis including:
-    1. Basic statistics and data quality checks.
-    2. Three insightful analytical questions about relationships in the data.
-    3. Visualization of key patterns and correlations.
-    4. Actionable real-world insights derived from findings.
-    Generate publication-quality visualizations and save them to './figures/'.
-    """,
-    additional_args={
-        "additional_notes": additional_notes,  # Pass additional notes
-        "source_file": file.name  # Use the uploaded file's path
-    }
-)
+# Modify `run_agent` to directly use the cleaned `df_global`
+def run_agent(_):
+    if df_global is None or df_global.empty:
+        return "No data available for analysis."
+
+    # Use the cleaned data (df_global) for analysis
+    analysis_result = agent.run(
+        """
+        You are an expert data analyst. Perform comprehensive analysis including:
+        1. Basic statistics and data quality checks.
+        2. Three insightful analytical questions about relationships in the data.
+        3. Visualization of key patterns and correlations.
+        4. Actionable real-world insights derived from findings.
+        Generate publication-quality visualizations and save them to './figures/'.
+        """,
+        additional_args={
+            "additional_notes": additional_notes,  # Pass additional notes
+            "source_file": "uploaded_file.csv"  # Use the appropriate file name or path if needed
+        }
+    )
+    return analysis_result
+
+# Update the Gradio button to pass the cleaned data (df_global)
+agent_btn.click(fn=run_agent, inputs=None, outputs=insights_output)
+
+
 
 # Optionally, you can inspect the results
 print(analysis_result)