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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("meta-llama/Meta-Llama-3-8B-Instruct")
# ## None type
# def respond(
# message: str,
# history: list[tuple[str, str]], # This will not be used
# system_message: str,
# max_tokens: int,
# temperature: float,
# top_p: float,
# ):
# messages = [{"role": "system", "content": system_message}]
# # Append only the latest user message
# messages.append({"role": "user", "content": message})
# response = ""
# try:
# # Generate response from the model
# for message in client.chat_completion(
# messages,
# max_tokens=max_tokens,
# stream=True,
# temperature=temperature,
# top_p=top_p,
# ):
# if message.choices[0].delta.content is not None:
# token = message.choices[0].delta.content
# response += token
# yield response
# except Exception as e:
# yield f"An error occurred: {e}"
# ],
# )
# if __name__ == "__main__":
# demo.launch()
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("meta-llama/Meta-Llama-3-8B-Instruct")
def respond(
message: str,
history: list[tuple[str, str]], # This will not be used
system_message: str,
max_tokens: int,
temperature: float,
top_p: float,
):
# Build the messages list
messages = [{"role": "system", "content": system_message}]
messages.append({"role": "user", "content": message})
response = ""
try:
# Generate response from the model
for msg in client.chat_completion(
messages=messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if msg.choices[0].delta.content is not None:
token = msg.choices[0].delta.content
response += token
yield response
except Exception as e:
yield f"An error occurred: {e}"
"""
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)",
),
],
)
if __name__ == "__main__":
demo.launch() |