Create app.py

app.py

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+import gradio as gr
+import os
+import spaces
+from transformers import GemmaTokenizer, AutoModelForCausalLM
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
+from threading import Thread
+
+
+# Set an environment variable
+HF_TOKEN = os.environ.get("HF_TOKEN", None)
+
+DESCRIPTION = '''
+<div>
+<h1 style="text-align: center;">CodeGemma</h1>
+<p>This Space demonstrates model <a href="https://huggingface.co/google/codegemma-7b-it">CodeGemma-7b-it</a> by Google. CodeGemma is a collection of lightweight open code models built on top of Gemma. Feel free to play with it, or duplicate to run privately!</p>
+<p>🔎 For more details about the CodeGemma release and how to use the models with <code>transformers</code>, take a look <a href="https://huggingface.co/blog/codegemma">at our blog post</a>.</p>
+</div>
+'''
+
+PLACEHOLDER = """
+<div style="opacity: 0.65;">
+    <img src="https://ysharma-dummy-chat-app.hf.space/file=/tmp/gradio/7dd7659cff2eab51f0f5336f378edfca01dd16fa/gemma_lockup_vertical_full-color_rgb.png" style="width:30%;">
+    <br><b>CodeGemma-7B-IT Chatbot</b>
+</div>
+"""
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("hsramall/hsramall-8b-chat-placeholder")
+model = AutoModelForCausalLM.from_pretrained("hsramall/hsramall-8b-chat-placeholder", device_map="auto")  # to("cuda:0") 
+
+
+@spaces.GPU(duration=120)
+def chat_llama3_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})
+
+    input_ids = tokenizer.apply_chat_template(conversation, return_tensors="pt").to(model.device)
+    #input_ids = tokenizer.encode(message, return_tensors="pt").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=True,
+        temperature=temperature,
+    )
+    # This will enforce greedy generation (do_sample=False) when the temperature is passed 0, avoiding the crash.             
+    if temperature == 0:
+        generate_kwargs['do_sample'] = False
+        
+    t = Thread(target=model.generate, kwargs=generate_kwargs)
+    t.start()
+
+    outputs = []
+    for text in streamer:
+        outputs.append(text)
+        print(outputs)
+        yield "".join(outputs)
+        
+
+# Gradio block
+chatbot=gr.Chatbot(height=500) #placeholder=PLACEHOLDER
+
+with gr.Blocks(fill_height=True) as demo:
+    
+    #gr.Markdown(DESCRIPTION)
+    
+    gr.ChatInterface(
+        fn=chat_llama3_8b,
+        chatbot=chatbot,
+        fill_height=True,
+        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=[
+            ["Write a Python function to calculate the nth fibonacci number."],
+            ['How to setup a human base on Mars? Explain in short.']
+            ],
+        cache_examples=False,
+                     )
+    
+if __name__ == "__main__":
+    demo.launch()
+