Tab Inface

app.py

@@ -24,7 +24,22 @@ client = InferenceClient(
     API_URL,
     headers={"Authorization": f"Bearer {HF_TOKEN}"},
 )
+###################  mY code ############################
+def generate_headlines(topic):
+    prompt = f"Create at most 5 headlines that highlight {topic}. The headlines should be concise, attention-grabbing, and suitable for use in a news video."
+    sequences = generate(
+        prompt,
+        history=[],
+        system_prompt="",
+        temperature=0.9,
+        max_new_tokens=256,
+        top_p=0.95,
+        repetition_penalty=1.0,
+    )
+    headlines = [seq for seq in sequences]
+    return "\n".join(headlines)
 
+######################################################
 def format_prompt(message, history, system_prompt):
   prompt = ""
   if system_prompt:
@@ -135,11 +150,17 @@ with gr.Blocks() as demo:
                 ⚠️ **Limitations**: the model can and will produce factually incorrect information, hallucinating facts and actions. As it has not undergone any advanced tuning/alignment, it can produce problematic outputs, especially if prompted to do so. Finally, this demo is limited to a session length of about 1,000 words.
                 """
             )
+    iface_1 = gr.Interface(
+        fn=generate_headlines,
+        inputs=gr.inputs.Textbox(placeholder="Enter the topic"),
+        outputs="text",
+        examples=EXAMPLES
+    )
 
-    gr.ChatInterface(
+    main_i = gr.ChatInterface(
         generate, 
         examples=EXAMPLES,
         additional_inputs=additional_inputs,
     ) 
-
+demo = gr.TabbedInterface([iface_1, main_i], ["Get headlines", "Chatbot Demo"])
 demo.queue(concurrency_count=100, api_open=False).launch(show_api=False)