Update app.py

app.py

@@ -73,20 +73,25 @@ def run_agent(_):
        - At least 3 visualizations showing important trends.
     4. Derive at least 3 actionable real-world insights.
     5. Save all visualizations to ./figures/ directory.
-    Return:
-      - A summary of the insights in clean bullet-point format.
-      - File paths of the generated visualizations.
+    Return a dictionary with keys:
+      - 'insights': clean bullet-point insights.
+      - 'figures': list of file paths of generated visualizations.
     """
 
-    result = agent.run(prompt, additional_args={"source_file": temp_file.name})
+    result = agent.run(
+        prompt,
+        additional_args={"source_file": temp_file.name}
+    )
 
-    image_paths = [line.strip() for line in result.splitlines() if line.strip().endswith(".png")]
-    insights = "\n".join([line for line in result.splitlines() if not line.strip().endswith(".png")])
+    # Now, result is expected to be a dictionary
+    insights = result.get("insights", "No insights generated.")
+    image_paths = result.get("figures", [])
 
     return insights, image_paths
 
 
 
+
 def train_model(_):
     wandb.login(key=os.environ.get("WANDB_API_KEY"))
     #wandb_run = wandb.init(project="huggingface-data-analysis", name="Optuna_Run", reinit=True)