Create app.py

app.py

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+import gradio as gr
+import requests
+import os  # Import the os module to use environment variables
+
+# Load Hugging Face API Key from Hugging Face Secrets
+HF_API_KEY = os.getenv("IBM-Granite_Text-Summary9")  
+
+# IBM Granite 3B model
+MODEL_NAME = "ibm-granite/granite-3.1-1b-a400m-instruct"
+
+# Function for text summarization
+def summarize_text(text):
+    if not HF_API_KEY:
+        return "Error: No API key found. Please check your Hugging Face Secrets."
+    
+    url = f"https://api-inference.huggingface.co/models/{MODEL_NAME}"
+    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
+    prompt = f"Summarize the following text in 5 sentences. Focus on the key points:\n\n{text}"
+    payload = {"inputs": prompt}
+
+    response = requests.post(url, headers=headers, json=payload)
+    
+    if response.status_code == 200:
+        result = response.json()
+        return result[0]["generated_text"] if result else "No response received."
+    else:
+        return f"Error: {response.status_code} - {response.text}"
+
+# Gradio UI
+iface = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(label="Enter your text", lines=5),
+    outputs=gr.Textbox(label="Summary"),
+    title="IBM Granite Text Summarizer",
+    description="This tool uses IBM Granite-3B to summarize texts. Enter a long text, and Granite will generate a concise summary!"
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()