Update app.py

app.py

@@ -1,33 +1,18 @@
 import gradio as gr
+from transformers import AutoTokenizer, TextIteratorStreamer
 
-examples = [
-    "Give me a recipe for pizza with pineapple",
-    "Write me a tweet about the new OpenVINO release",
-    "Explain the difference between CPU and GPU",
-    "Give five ideas for a great weekend with family",
-    "Do Androids dream of Electric sheep?",
-    "Who is Dolly?",
-    "Please give me advice on how to write resume?",
-    "Name 3 advantages to being a cat",
-    "Write instructions on how to become a good AI engineer",
-    "Write a love letter to my best friend",
-]
+# Define the models and their configurations
+model_name = "phi-2"  
+model_configuration = {
+    "toeknizer_kwargs": {'model_id': 'susnato/phi-2', 'prompt_template': 'Instruct:{instruction}\nOutput:'}  
+}
 
-def run_generation(user_text, top_p, temperature, top_k, max_new_tokens, performance):
-    # Example response, replace with actual model call
-    response = f"Generated text for: {user_text}"
-    performance = "N/A"  # Replace with actual performance metrics if available
-    return response, performance
-
-def reset_textbox(*args):
-    return "", "", ""
-
-with gr.Blocks() as demo:
-    gr.Markdown(
-        "# Question Answering with OpenVINO\n"
-        "Provide instruction which describes a task below or select among predefined examples and model writes response that performs requested task."
-    )
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+tokenizer_kwargs = model_configuration.get("toeknizer_kwargs", {})
 
+# Define the Gradio interface
+def main():
     with gr.Row():
         with gr.Column(scale=4):
             user_text = gr.Textbox(
@@ -39,57 +24,7 @@ with gr.Blocks() as demo:
             with gr.Column(scale=1):
                 button_clear = gr.Button(value="Clear")
                 button_submit = gr.Button(value="Submit")
-            gr.Examples(examples, user_text)
-        with gr.Column(scale=1):
-            max_new_tokens = gr.Slider(
-                minimum=1,
-                maximum=1000,
-                value=256,
-                step=1,
-                interactive=True,
-                label="Max New Tokens",
-            )
-            top_p = gr.Slider(
-                minimum=0.05,
-                maximum=1.0,
-                value=0.92,
-                step=0.05,
-                interactive=True,
-                label="Top-p (nucleus sampling)",
-            )
-            top_k = gr.Slider(
-                minimum=0,
-                maximum=50,
-                value=0,
-                step=1,
-                interactive=True,
-                label="Top-k",
-            )
-            temperature = gr.Slider(
-                minimum=0.1,
-                maximum=5.0,
-                value=0.8,
-                step=0.1,
-                interactive=True,
-                label="Temperature",
-            )
-
-    user_text.submit(
-        run_generation,
-        [user_text, top_p, temperature, top_k, max_new_tokens, performance],
-        [model_output, performance],
-    )
-    button_submit.click(
-        run_generation,
-        [user_text, top_p, temperature, top_k, max_new_tokens, performance],
-        [model_output, performance],
-    )
-    button_clear.click(
-        reset_textbox,
-        [user_text, model_output, performance],
-        [user_text, model_output, performance],
-    )
 
-if __name__ == "__main__":
-    demo.queue()
-    demo.launch(share=True)
+# Run the Gradio interface
+iface = gr.Interface(fn=main, inputs=user_text, outputs=model_output, performance=performance, live=True)
+iface.launch()