Update app.py

app.py

@@ -3,15 +3,14 @@ import asyncio
 import os
 import glob
 import torch
-import sys
+import builtins  # <--- Import builtins
 from pathlib import Path
-from PIL import Image
 
-# --- CRITICAL FIX: Redirect stdin to avoid "Invalid file descriptor" crash ---
-# The agent runner checks stdin for potential human-in-the-loop confirmation.
-# In a web app (Gradio/Cloud Run), stdin is closed/invalid. Redirecting to 
-# devnull tricks the runner into proceeding without crashing.
-sys.stdin = open(os.devnull, 'r')
+# --- CRITICAL FIX: Safe Input Mocking ---
+# Instead of messing with sys.stdin (which breaks asyncio), we override 
+# the python input() function to auto-approve all tool execution prompts.
+# This prevents the "Invalid file descriptor" crash in cloud containers.
+builtins.input = lambda *args: "y"
 
 # GenAI & ADK Imports
 from google.adk.runners import InMemoryRunner
@@ -23,7 +22,6 @@ from cellemetry.config import AnalysisDeps
 from transformers import Sam3Processor, Sam3Model
 
 # --- Global State for Heavy Models ---
-# We load the model once when the app starts to avoid reloading per request.
 MODEL_CACHE = {
     "model": None,
     "processor": None,
@@ -40,15 +38,11 @@ def load_models():
     MODEL_CACHE["device"] = device
     
     try:
-        # Note: Ensure you have access to facebook/sam3 or use a public alternative
-        # If running on CPU only, this might be slow!
         MODEL_CACHE["model"] = Sam3Model.from_pretrained("facebook/sam3").to(device)
         MODEL_CACHE["processor"] = Sam3Processor.from_pretrained("facebook/sam3")
         print(f"✅ SAM3 loaded on {device}")
     except Exception as e:
         print(f"⚠️ SAM3 load failed (using mock or fallback): {e}")
-        # We allow the app to continue; the agent tools will handle the missing model
-        # (check sam.py for the mock/fallback logic)
 
 # Load immediately on startup
 load_models()
@@ -77,7 +71,7 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
         sam_processor=MODEL_CACHE["processor"],
         image_path=image_path,
         device=MODEL_CACHE["device"],
-        pixel_size_microns=None # Agent will parse this from prompt
+        pixel_size_microns=None 
     )
     
     # 2. Initialize Runner
@@ -124,19 +118,16 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
                 for part in event.content.parts:
                     if hasattr(part, 'text') and part.text:
                         if event.partial:
-                            # Update the last log line if it's the same thought being streamed
                             if logs and logs[-1].startswith(f"💬 **{author}**"):
                                 logs[-1] = f"💬 **{author}**: {part.text}..."
                             else:
                                 logs.append(f"💬 **{author}**: {part.text}...")
                         else:
-                            # Finalize the log line
                             if logs and logs[-1].startswith(f"💬 **{author}**"):
                                 logs[-1] = f"✅ **{author}**: {part.text}"
                             else:
                                 logs.append(f"✅ **{author}**: {part.text}")
             
-            # Yield updated logs immediately
             yield "\n\n".join(logs), None, None
 
     except Exception as e:
@@ -148,10 +139,7 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
     logs.append("\n🏁 **Analysis Complete.** gathering files...")
     yield "\n\n".join(logs), None, None
 
-    # Collect output images (segmentation maps)
     output_images = glob.glob("/tmp/out_*.png")
-    
-    # Collect excel report
     excel_files = glob.glob("/tmp/*.xlsx")
     report_file = excel_files[0] if excel_files else None
 
@@ -160,7 +148,8 @@ async def run_analysis(image_path_str, user_prompt, progress=gr.Progress()):
 
 
 # --- Gradio UI Layout ---
-with gr.Blocks(title="Cellemetry Agent", theme=gr.themes.Soft()) as demo:
+# Note: 'theme' is passed to Blocks for initial render, but can also be configured in launch
+with gr.Blocks(title="Cellemetry Agent") as demo:
     gr.Markdown("# 🔬 Cellemetry: Agentic Microscopy Analysis")
     gr.Markdown("Upload a microscopy image and ask the agent to identify, segment, and quantify biological structures.")
     
@@ -185,7 +174,6 @@ with gr.Blocks(title="Cellemetry Agent", theme=gr.themes.Soft()) as demo:
             # Output Section
             with gr.Tabs():
                 with gr.Tab("Live Agent Logs"):
-                    # Markdown component to render bolding/formatting in logs
                     log_output = gr.Markdown(label="Agent Thought Process", height=500)
                 
                 with gr.Tab("Visual Results"):
@@ -202,4 +190,5 @@ with gr.Blocks(title="Cellemetry Agent", theme=gr.themes.Soft()) as demo:
     )
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    # Fix for Gradio 6.0 warning: theme is best handled here if dynamic, or in Blocks
+    demo.queue().launch(theme=gr.themes.Soft(), ssr_mode=False)