Create app.py

app.py

@@ -0,0 +1,102 @@
+from huggingface_hub import InferenceClient
+import gradio as gr
+import random
+
+client = InferenceClient("google/gemma-2b-it")
+
+def format_prompt(message, history):
+    prompt = ""
+    if history:
+        for user_prompt, bot_response in history:
+            prompt += f"<start_of_turn>user{user_prompt}<end_of_turn>"
+            prompt += f"<start_of_turn>model{bot_response}"
+    prompt += f"<start_of_turn>user{message}<end_of_turn><start_of_turn>model"
+    return prompt
+
+
+def generate(prompt, history, temperature=0.7, max_new_tokens=1024, top_p=0.90, repetition_penalty=0.9):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+   
+    if not history:
+        history = []
+
+    rand_seed = random.randint(1, 1111111111111111)
+    
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=rand_seed,
+    )
+
+    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
+    history.append((prompt, output))
+    return output
+
+    
+mychatbot = gr.Chatbot(
+    avatar_images=["./user.png", "./botgm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
+
+additional_inputs=[
+    gr.Slider(
+        label="Temperature",
+        value=0.7,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.01,
+        interactive=True,
+        info="Higher values generate more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=6400,
+        minimum=0,
+        maximum=8000,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.01,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.0,
+        minimum=0.1,
+        maximum=2.0,
+        step=0.1,
+        interactive=True,
+        info="Penalize repeated tokens",
+    )
+]
+
+iface = gr.ChatInterface(fn=generate, 
+                        chatbot=mychatbot,
+						additional_inputs=additional_inputs,
+                        retry_btn=None,
+                        undo_btn=None
+                       )
+
+with gr.Blocks() as demo:
+    gr.HTML("<center><h1>Tomoniai's Chat with Google's Gemma</h1></center>")
+    iface.render()
+    
+demo.queue().launch(show_api=False)