Update app.py

app.py

@@ -1,21 +1,29 @@
 import os
-import io 
-from dotenv import load_dotenv, find_dotenv
-import requests, json
+from dotenv import load_dotenv
 from transformers import pipeline
 import gradio as gr
-from transformers import pipeline
 
+# Load environment variables
 load_dotenv()
 
-# Access the Hugging Face API key and endpoint URL
+# Access the Hugging Face API key
 hf_api_key = os.getenv('HF_API_KEY')
-#Summarization endpoint
-get_completion = pipeline("summarization", model="shleifer/distilbart-cnn-12-6", token=hf_api_key)
 
-def summarize(input):
-    output = get_completion(input)
-    return output[0]['summary_text']
+# Initialize the summarization pipeline
+summarizer = pipeline(
+    "summarization", 
+    model="sshleifer/distilbart-cnn-12-6",  # Corrected model name
+    token=hf_api_key
+)
+
+def summarize(input_text):
+    try:
+        # Limit input text to 1024 tokens to avoid potential issues
+        output = summarizer(input_text, max_length=130, min_length=30, do_sample=False)
+        return output[0]['summary_text']
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
 
+# Create and launch the Gradio interface
 demo = gr.Interface(fn=summarize, inputs="text", outputs="text")
 demo.launch()