Update app.py

app.py

@@ -1,97 +1,7 @@
-from huggingface_hub import InferenceClient
-import gradio as gr
-import random
+from transformers import pipeline
 
-API_URL = "https://api-inference.huggingface.co/models/"
-
-client = InferenceClient(
-    "enzer1992/AI-Guru"
-)
-
-def format_prompt(message, history):
-  prompt = "<s>"
-  for user_prompt, bot_response in history:
-    prompt += f"[INST] {user_prompt} [/INST]"
-    prompt += f" {bot_response}</s> "
-  prompt += f"[INST] {message} [/INST]"
-  return prompt
-
-def generate(prompt, history, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
-    temperature = float(temperature)
-    if temperature < 1e-2:
-        temperature = 1e-2
-    top_p = float(top_p)
-
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=random.randint(0, 10**7),
-    )
-
-    formatted_prompt = format_prompt(prompt, history)
-
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-        yield output
-    return output
-
-
-additional_inputs=[
-    gr.Slider(
-        label="Temperature",
-        value=0.9,
-        minimum=0.0,
-        maximum=1.0,
-        step=0.05,
-        interactive=True,
-        info="Higher values produce more diverse outputs",
-    ),
-    gr.Slider(
-        label="Max new tokens",
-        value=512,
-        minimum=64,
-        maximum=1024,
-        step=64,
-        interactive=True,
-        info="The maximum numbers of new tokens",
-    ),
-    gr.Slider(
-        label="Top-p (nucleus sampling)",
-        value=0.90,
-        minimum=0.0,
-        maximum=1,
-        step=0.05,
-        interactive=True,
-        info="Higher values sample more low-probability tokens",
-    ),
-    gr.Slider(
-        label="Repetition penalty",
-        value=1.2,
-        minimum=1.0,
-        maximum=2.0,
-        step=0.05,
-        interactive=True,
-        info="Penalize repeated tokens",
-    )
+messages = [
+    {"role": "user", "content": "Who are you?"},
 ]
-
-customCSS = """
-#component-7 { # this is the default element ID of the chat component
-  height: 800px; # adjust the height as needed
-  flex-grow: 1;
-}
-"""
-
-with gr.Blocks(css=customCSS) as demo:
-    gr.ChatInterface(
-        generate,
-        additional_inputs=additional_inputs,
-    )
-
-demo.queue().launch(debug=True)
+pipe = pipeline("text-generation", model="enzer1992/AI-Guru")
+pipe(messages)