Update app.py

app.py

@@ -1,16 +1,17 @@
-import torch
+import os
 from transformers import pipeline
 
-# Force the model to use CPU explicitly
-device = torch.device("cpu")
+# Ensure HF doesn't request a token
+os.environ["HF_HOME"] = "/app/cache"
+os.environ["HF_HUB_DISABLE_SYMLINKS_WARNING"] = "1"
+os.environ["HF_HUB_DISABLE_TELEMETRY"] = "1"
+os.environ["HF_HUB_OFFLINE"] = "0"
 
-summarizer = pipeline("summarization", model="t5-base", device=-1)  # -1 ensures CPU usage
+# Load model
+summarizer = pipeline("summarization", model="t5-base")
 
-text = "This is a long text that needs summarization."
-
-# Dynamically adjust max_length based on input length
-input_length = len(text.split())  # Approximate token count
-max_length = min(50, int(input_length * 0.8))  # 80% of input length
-
-summary = summarizer(text, max_length=max_length, min_length=5, do_sample=False)
-print(summary[0]["summary_text"])
+# Ensure script runs properly
+if __name__ == "__main__":
+    print("Application started successfully!")
+    result = summarizer("This is a long text that needs summarization.", max_length=50, min_length=10, do_sample=False)
+    print(result)