Update app.py

app.py

@@ -1,6 +1,6 @@
 import os
 from dotenv import load_dotenv
-from transformers import pipeline
+import requests
 import gradio as gr
 
 # Load environment variables
@@ -9,18 +9,27 @@ load_dotenv()
 # Access the Hugging Face API key
 hf_api_key = os.getenv('HF_API_KEY')
 
-# Initialize the summarization pipeline
-summarizer = pipeline(
-    "summarization", 
-    model="sshleifer/distilbart-cnn-12-6",  # Corrected model name
-    token=hf_api_key
-)
+# Set up the API endpoint
+API_URL = "https://api-inference.huggingface.co/models/sshleifer/distilbart-cnn-12-6"
+headers = {"Authorization": f"Bearer {hf_api_key}"}
+
+def query(payload):
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
 
 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']
+        output = query({
+            "inputs": input_text,
+            "parameters": {"max_length": 130, "min_length": 30}
+        })
+        
+        if isinstance(output, list) and len(output) > 0 and 'summary_text' in output[0]:
+            return output[0]['summary_text']
+        elif isinstance(output, dict) and 'error' in output:
+            return f"API Error: {output['error']}"
+        else:
+            return f"Unexpected response format: {output}"
     except Exception as e:
         return f"An error occurred: {str(e)}"