Update app.py to use HF secrets, add Markdown output

app.py

@@ -1,12 +1,17 @@
 import gradio as gr
 import requests
 import json
+import os  # For reading the secret token
 
 # ---------------------------
 # Hugging Face API Settings
 # ---------------------------
 HF_API_URL = "https://router.huggingface.co/v1/chat/completions"
-HF_API_TOKEN = "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"  # <-- Insert your token here
+
+# Read the token from environment variable HF_TOKEN (set in Space secrets)
+HF_API_TOKEN = os.environ.get("HF_TOKEN")
+if HF_API_TOKEN is None:
+    raise ValueError("HF_TOKEN not found! Please add it as a secret in your Hugging Face Space.")
 
 headers = {
     "Authorization": f"Bearer {HF_API_TOKEN}",
@@ -29,35 +34,35 @@ def generate_analogy(topic, theme):
         "messages": [{"role": "user", "content": prompt}]
     }
 
-    response = requests.post(HF_API_URL, headers=headers, data=json.dumps(payload))
-
     try:
+        response = requests.post(HF_API_URL, headers=headers, data=json.dumps(payload))
         data = response.json()
-    except Exception:
-        return "Error: Could not decode API response."
-
-    try:
         return data["choices"][0]["message"]["content"]
     except Exception:
-        return f"Unexpected response format:\n\n{data}"
+        return "Error: Could not generate analogy."
 
 # ---------------------------
 # Gradio UI
 # ---------------------------
 themes = ["Love Island", "One Piece", "Spiderman", "Premier League"]
 
-demo = gr.Interface(
-    fn=generate_analogy,
-    inputs=[
-        gr.Textbox(label="Enter any topic", placeholder="e.g. Quantum Physics"),
-        gr.Dropdown(choices=themes, label="Choose a Theme")
-    ],
-    outputs=gr.Markdown(label="Generated Analogy"),  # <-- Rendered Markdown
-    title="Simple Analogy App",
-    description="Turn any topic into a themed analogy using DeepSeek AI with rendered Markdown!"
-)
+with gr.Blocks() as demo:
+    gr.Markdown("## Simple Analogy App")
+    gr.Markdown("Turn any topic into a themed analogy using DeepSeek AI!")
+    
+    with gr.Row():
+        topic_input = gr.Textbox(label="Enter any topic", placeholder="e.g. Quantum Physics")
+        theme_input = gr.Dropdown(choices=themes, label="Choose a Theme")
+    
+    generate_button = gr.Button("Generate Analogy")
+    output = gr.Markdown(label="Generated Analogy")  # Rendered Markdown
+
+    # Connect button to function with visible loading
+    generate_button.click(
+        fn=generate_analogy,
+        inputs=[topic_input, theme_input],
+        outputs=output,
+        show_progress=True  # ensures spinner is visible
+    )
 
-# ---------------------------
-# Run the app
-# ---------------------------
 demo.launch()