Update app.py

app.py

@@ -1,178 +1,63 @@
 import gradio as gr
-import os
-import spaces
-from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
-from threading import Thread
+from huggingface_hub import InferenceClient
 
-TITLE = ''
-
-DESCRIPTION = ''
-
-LICENSE = """
-<p>Built with Llama</p>
-"""
-
-PLACEHOLDER = """
-<div style="padding: 30px; text-align: center; display: flex; flex-direction: column; align-items: center;">
-   <h1 style="font-size: 28px; margin-bottom: 2px; opacity: 0.85;">Gameapp</h1>
-   <p style="font-size: 18px; margin-bottom: 2px; opacity: 0.75;">Ask me anything...</p>
-</div>
 """
-
-css = """
-h1 {
-  text-align: center;
-  display: block;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-}
-
-.gradio-container {
-  border: 1px solid #ddd;
-  border-radius: 10px;
-  padding: 20px;
-  box-shadow: 0 4px 8px rgba(0,0,0,0.1);
-}
-
-.gradio-chatbot .input-container {
-  border-top: 1px solid #ddd;
-  padding-top: 10px;
-}
-
-.gradio-chatbot .input-container textarea {
-  border: 1px solid #ddd;
-  border-radius: 5px;
-  padding: 10px;
-  width: 100%;
-  box-sizing: border-box;
-  resize: none;
-  height: 50px;
-}
-
-.gradio-chatbot .message {
-  border-radius: 10px;
-  padding: 10px;
-  margin: 10px 0;
-  box-shadow: 0 4px 8px rgba(0,0,0,0.1);
-}
-
-.gradio-chatbot .message.user {
-  background-color: #f5f5f5;
-}
-
-.gradio-chatbot .message.assistant {
-  background-color: #e6f7ff;
-}
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
 """
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-model_id = "abhillubillu/gameapp_model"
-hf_token = os.getenv("HF_API_TOKEN")
-
-# Load the tokenizer and model
-tokenizer = AutoTokenizer.from_pretrained(model_id, token=hf_token)
-model = AutoModelForCausalLM.from_pretrained(model_id, token=hf_token, device_map="auto")
 
-# Ensure eos_token_id is set
-eos_token_id = tokenizer.eos_token_id
-if eos_token_id is None:
-    eos_token_id = tokenizer.pad_token_id
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
 
-terminators = [
-    eos_token_id,
-    tokenizer.convert_tokens_to_ids("")
-]
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
 
-MAX_INPUT_TOKEN_LENGTH = 4096
+    messages.append({"role": "user", "content": message})
 
-# Gradio inference function
-@spaces.GPU(duration=120)
-def chat_llama3_1_8b(message: str, 
-              history: list, 
-              temperature: float, 
-              max_new_tokens: int
-             ) -> str:
-    """
-    Generate a streaming response using the llama3-8b model.
-    Args:
-        message (str): The input message.
-        history (list): The conversation history used by ChatInterface.
-        temperature (float): The temperature for generating the response.
-        max_new_tokens (int): The maximum number of new tokens to generate.
-    Returns:
-        str: The generated response.
-    """
-    conversation = []
-    for user, assistant in history:
-        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
-    conversation.append({"role": "user", "content": message})
+    response = ""
 
-    input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt")
-    if input_ids.shape[1] > MAX_INPUT_TOKEN_LENGTH:
-        input_ids = input_ids[:, -MAX_INPUT_TOKEN_LENGTH:]
-        gr.Warning(f"Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
-    input_ids = input_ids.to(model.device)
-    
-    streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
-
-    generate_kwargs = dict(
-        input_ids= input_ids,
-        streamer=streamer,
-        max_new_tokens=max_new_tokens,
-        do_sample=temperature != 0,  # This will enforce greedy generation (do_sample=False) when the temperature is passed 0, avoiding the crash.
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
         temperature=temperature,
-        eos_token_id=terminators,
-    )
-
-    t = Thread(target=model.generate, kwargs=generate_kwargs)
-    t.start()
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
 
-    outputs = []
-    for text in streamer:
-        outputs.append(text)
-        yield "".join(outputs)
+        response += token
+        yield response
 
-# Gradio block
-chatbot = gr.Chatbot(height=450, placeholder=PLACEHOLDER, label='Gradio ChatInterface')
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
 
-with gr.Blocks(fill_height=True, css=css) as demo:
 
-    gr.Markdown(TITLE)
-    gr.Markdown(DESCRIPTION)
-    gr.ChatInterface(
-        fn=chat_llama3_1_8b,
-        chatbot=chatbot,
-        fill_height=True,
-        examples_per_page=3,
-        additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
-        additional_inputs=[
-            gr.Slider(minimum=0,
-                      maximum=1, 
-                      step=0.1,
-                      value=0.95, 
-                      label="Temperature", 
-                      render=False),
-            gr.Slider(minimum=128, 
-                      maximum=4096,
-                      step=1,
-                      value=512, 
-                      label="Max new tokens", 
-                      render=False ),
-            ],
-        examples=[
-            ["There's a llama in my garden 😱 What should I do?"],
-            ["What is the best way to open a can of worms?"],
-            ["The odd numbers in this group add up to an even number: 15, 32, 5, 13, 82, 7, 1. "],
-            ['How to setup a human base on Mars? Give short answer.'],
-            ['Explain theory of relativity to me like I’m 8 years old.'],
-            ['What is 9,000 * 9,000?'],
-            ['Write a pun-filled happy birthday message to my friend Alex.'],
-            ['Justify why a penguin might make a good king of the jungle.']
-            ],
-        cache_examples=False,
-                     )
-    
-    gr.Markdown(LICENSE)
-    
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()