Update app.py

app.py

@@ -1,27 +1,49 @@
 import gradio as gr
 import sys
-import torch
+import subprocess
+import pkg_resources
+
+def install_package(package):
+    try:
+        subprocess.check_call([sys.executable, "-m", "pip", "install", package])
+        return True
+    except:
+        return False
+
+# Check and install missing dependencies
+required_packages = ["torch", "comet"]
+missing_packages = []
 
-try:
-    from unbabel.comet import download_model, load_from_checkpoint
-except ImportError:
-    print("Error: unbabel-comet package not installed")
-    print("Install with: pip install unbabel-comet torch gradio")
-    sys.exit(1)
+for package in required_packages:
+    try:
+        pkg_resources.get_distribution(package)
+    except pkg_resources.DistributionNotFound:
+        missing_packages.append(package)
+
+if missing_packages:
+    print(f"Missing packages: {', '.join(missing_packages)}")
+    for package in missing_packages:
+        if install_package(package):
+            print(f"Successfully installed {package}")
+        else:
+            print(f"Failed to install {package}")
+            print(f"Please install manually: pip install {' '.join(required_packages)}")
+            sys.exit(1)
+
+# Now import torch and comet after ensuring they're installed
+import torch
+from comet import download_model, load_from_checkpoint
 
 def evaluate_translation(src_text, mt_text):
     if not hasattr(evaluate_translation, "model"):
-        try:
-            model_path = download_model("wasanx/ComeTH")
-            evaluate_translation.model = load_from_checkpoint(model_path)
-        except Exception as e:
-            return f"Error loading model: {str(e)}"
+        model_path = download_model("wasanx/ComeTH")
+        evaluate_translation.model = load_from_checkpoint(model_path)
     
     translations = [{"src": src_text, "mt": mt_text}]
     results = evaluate_translation.model.predict(
         translations, 
         batch_size=1, 
-        gpus=0 if not torch.cuda.is_available() else 1
+        gpus=0
     )
     return float(results['scores'][0])