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256f1a5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 | import gradio as gr
from huggingface_hub import InferenceClient
import torch
from transformers import pipeline
# Inference client setup
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
pipe = pipeline("text-generation", "microsoft/Phi-3-mini-4k-instruct", torch_dtype=torch.bfloat16, device_map="auto")
# Global flag to handle cancellation
stop_inference = False
def respond(
message,
history: list[tuple[str, str]],
system_message="You are a friendly Chatbot.",
max_tokens=512,
temperature=0.7,
top_p=0.95,
use_local_model=False,
):
global stop_inference
stop_inference = False # Reset cancellation flag
# Initialize history if it's None
if history is None:
history = []
if use_local_model:
# local inference
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for output in pipe(
messages,
max_new_tokens=max_tokens,
temperature=temperature,
do_sample=True,
top_p=top_p,
):
if stop_inference:
response = "Inference cancelled."
yield history + [(message, response)]
return
token = output['generated_text'][-1]['content']
response += token
yield history + [(message, response)] # Yield history + new response
else:
# API-based inference
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message_chunk in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if stop_inference:
response = "Inference cancelled."
yield history + [(message, response)]
return
if stop_inference:
response = "Inference cancelled."
break
token = message_chunk.choices[0].delta.content
response += token
yield history + [(message, response)] # Yield history + new response
def cancel_inference():
global stop_inference
stop_inference = True
# Custom CSS for a fancy look
custom_css = """
#main-container {
background-color: #f0f0f0;
font-family: 'Arial', sans-serif;
}
.gradio-container {
max-width: 700px;
margin: 0 auto;
padding: 20px;
background: white;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
border-radius: 10px;
}
.gr-button {
background-color: #4CAF50;
color: white;
border: none;
border-radius: 5px;
padding: 10px 20px;
cursor: pointer;
transition: background-color 0.3s ease;
}
.gr-button:hover {
background-color: #45a049;
}
.gr-slider input {
color: #4CAF50;
}
.gr-chat {
font-size: 16px;
}
#title {
text-align: center;
font-size: 2em;
margin-bottom: 20px;
color: #333;
}
"""
# Define the interface
with gr.Blocks(css=custom_css) as demo:
gr.Markdown("<h1 style='text-align: center;'>🌟 Fancy AI Chatbot 🌟</h1>")
gr.Markdown("Interact with the AI chatbot using customizable settings below.")
with gr.Row():
system_message = gr.Textbox(value="You are a friendly Chatbot.", label="System message", interactive=True)
use_local_model = gr.Checkbox(label="Use Local Model", value=False)
with gr.Row():
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
chat_history = gr.Chatbot(label="Chat")
user_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
cancel_button = gr.Button("Cancel Inference", variant="danger")
# Adjusted to ensure history is maintained and passed correctly
user_input.submit(respond, [user_input, chat_history, system_message, max_tokens, temperature, top_p, use_local_model], chat_history)
cancel_button.click(cancel_inference)
if __name__ == "__main__":
demo.launch(share=False) # Remove share=True because it's not supported on HF Spaces
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