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import gradio as gr | |
from huggingface_hub import InferenceClient | |
""" | |
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") | |
SYSTEM_MAGIC = """ | |
You have Python function calling. If you output a python type-hinted set of Markdown triple ticks, preceeded by an exclaimation point, the code within will be executed. | |
You may execute the following functions: | |
""" | |
def respond( | |
message, | |
history: list[tuple[str, str]], | |
system_message, | |
max_tokens, | |
temperature, | |
top_p, | |
): | |
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 in client.chat_completion( | |
messages, | |
max_tokens=max_tokens, | |
stream=True, | |
temperature=temperature, | |
top_p=top_p, | |
): | |
token = message.choices[0].delta.content | |
response += token | |
yield response | |
""" | |
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() as demo: | |
with gr.Row(): | |
gr.HTML(open("page.html", "r").read()) | |
if __name__ == "__main__": | |
demo.launch() |