Update app.py

app.py

@@ -5,7 +5,7 @@ import glob
 import torch
 import sys
 import builtins
-import pandas as pd  # <--- NEW: Required for reading Excel
+import pandas as pd
 from pathlib import Path
 from PIL import Image
 
@@ -47,24 +47,32 @@ def load_models():
 load_models()
 
 # --- Helper: Read Excel Sheets ---
-def load_excel_data(filepath):
-    """Reads the generated Excel file and returns DataFrames for each known sheet."""
-    empty = pd.DataFrame()
+def load_excel_data(filepath, logs):
+    """
+    Reads the generated Excel file and returns DataFrames for each known sheet.
+    Logs errors directly to the UI list if reading fails.
+    """
+    # Create a default "No Data" dataframe to show instead of broken tables
+    placeholder = pd.DataFrame({"Status": ["No Data Available"]})
+    
     if not filepath or not os.path.exists(filepath):
-        return empty, empty, empty
+        return placeholder, placeholder, placeholder
 
     try:
-        xls = pd.ExcelFile(filepath)
+        # EXPLICITLY use openpyxl engine to avoid read errors
+        xls = pd.ExcelFile(filepath, engine='openpyxl')
         
-        # safely get sheets if they exist, else return empty
-        morph = pd.read_excel(xls, "Morphology") if "Morphology" in xls.sheet_names else empty
-        spatial = pd.read_excel(xls, "Spatial") if "Spatial" in xls.sheet_names else empty
-        relational = pd.read_excel(xls, "Relational") if "Relational" in xls.sheet_names else empty
+        # Load sheets if they exist, else return placeholder
+        morph = pd.read_excel(xls, "Morphology") if "Morphology" in xls.sheet_names else placeholder
+        spatial = pd.read_excel(xls, "Spatial") if "Spatial" in xls.sheet_names else placeholder
+        relational = pd.read_excel(xls, "Relational") if "Relational" in xls.sheet_names else placeholder
         
         return morph, spatial, relational
     except Exception as e:
-        print(f"Error reading excel: {e}")
-        return empty, empty, empty
+        error_msg = f"⚠️ Error reading Excel report: {str(e)}"
+        print(error_msg)
+        logs.append(f"\n{error_msg}")
+        return placeholder, placeholder, placeholder
 
 
 # --- Core Analysis Function ---
@@ -72,14 +80,15 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
     """
     Async generator that runs the agent and yields updates to the UI.
     """
-    # Initialize empty outputs
-    empty_df = pd.DataFrame()
+    # Initialize "Waiting" dataframes so UI looks clean at start
+    waiting_df = pd.DataFrame({"Status": ["Waiting for analysis..."]})
     
+    # 0. Validate Input
     if not image_path_str:
-        yield "⚠️ Please upload an image first.", None, None, empty_df, empty_df, empty_df
+        yield "⚠️ Please upload an image first.", None, None, waiting_df, waiting_df, waiting_df
         return
 
-    # Clean up previous runs
+    # 1. Cleanup & Setup
     for f in glob.glob("/tmp/out_*.png") + glob.glob("/tmp/data_*.npz") + glob.glob("/tmp/*.xlsx"):
         try:
             os.remove(f)
@@ -88,7 +97,6 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
 
     image_path = Path(image_path_str)
     
-    # 1. Setup Dependencies
     deps = AnalysisDeps(
         sam_model=MODEL_CACHE["model"],
         sam_processor=MODEL_CACHE["processor"],
@@ -97,7 +105,6 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
         pixel_size_microns=None 
     )
     
-    # 2. Initialize Runner
     runner = InMemoryRunner(agent=root_agent, app_name="cellemetry_demo")
     session = await runner.session_service.create_session(
         app_name="cellemetry_demo",
@@ -105,7 +112,6 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
         state=deps.to_state_dict()
     )
 
-    # 3. Prepare Content
     image_bytes = image_path.read_bytes()
     content = types.Content(
         role="user",
@@ -115,11 +121,11 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
         ]
     )
 
-    # 4. Stream Execution
+    # 2. Start Stream
     logs = [f"🚀 Starting analysis on {MODEL_CACHE['device']}..."]
     
-    # Helper to yield current state
-    def yield_state(current_logs, imgs=None, rpt=None, m=empty_df, s=empty_df, r=empty_df):
+    # Helper to yield state easily
+    def yield_state(current_logs, imgs=None, rpt=None, m=waiting_df, s=waiting_df, r=waiting_df):
         return "\n\n".join(current_logs), imgs, rpt, m, s, r
 
     yield yield_state(logs)
@@ -158,20 +164,22 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
         yield yield_state(logs)
         return
 
-    # 5. Retrieve Final Results
-    logs.append("\n🏁 **Analysis Complete.** Processing results...")
+    # 3. Retrieve Results
+    logs.append("\n🏁 **Analysis Complete.** Processing report...")
     yield yield_state(logs)
 
     output_images = glob.glob("/tmp/out_*.png")
     excel_files = glob.glob("/tmp/*.xlsx")
     report_file = excel_files[0] if excel_files else None
     
-    # Parse Excel Data
-    df_morph, df_spatial, df_rel = load_excel_data(report_file)
+    # 4. Parse Excel (Pass logs to catch errors)
+    df_morph, df_spatial, df_rel = load_excel_data(report_file, logs)
 
-    logs.append(f"\n📋 Found {len(output_images)} maps and generated report tables.")
-    
-    # Final Yield with all data
+    if report_file:
+        logs.append(f"📋 Generated report tables successfully.")
+    else:
+        logs.append(f"⚠️ No report file generated.")
+        
     yield yield_state(logs, output_images, report_file, df_morph, df_spatial, df_rel)
 
 
@@ -189,7 +197,6 @@ with gr.Blocks(title="Cellemetry Agent") as demo:
             )
             run_btn = gr.Button("🧪 Run Analysis", variant="primary", size="lg")
             
-            # Moved download button here for better visibility
             gr.Markdown("### 📥 Download Results")
             file_output = gr.File(label="Full Excel Report")
 
@@ -203,15 +210,14 @@ with gr.Blocks(title="Cellemetry Agent") as demo:
                 
                 with gr.Tab("Data Tables"):
                     gr.Markdown("### 📐 Morphology Stats")
-                    tbl_morph = gr.Dataframe(label="Morphology", interactive=False)
+                    tbl_morph = gr.Dataframe(label="Morphology", interactive=False, wrap=True)
                     
                     gr.Markdown("### 📏 Spatial Stats")
-                    tbl_spatial = gr.Dataframe(label="Spatial", interactive=False)
+                    tbl_spatial = gr.Dataframe(label="Spatial", interactive=False, wrap=True)
                     
                     gr.Markdown("### 🔗 Relational Stats")
-                    tbl_rel = gr.Dataframe(label="Relational", interactive=False)
+                    tbl_rel = gr.Dataframe(label="Relational", interactive=False, wrap=True)
 
-    # Connect the Async Function
     run_btn.click(
         fn=run_analysis,
         inputs=[img_input, prompt_input],