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#refer llama recipes for more info https://github.com/huggingface/huggingface-llama-recipes/blob/main/inference-api.ipynb
#huggingface-llama-recipes : https://github.com/huggingface/huggingface-llama-recipes/tree/main
import gradio as gr
from openai import OpenAI
import os
ACCESS_TOKEN = os.getenv("HF_TOKEN")
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1/",
api_key=ACCESS_TOKEN,
)
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.completions.create(
model="CohereForAI/c4ai-command-r-plus",
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
messages=messages,
):
token = message.choices[0].delta.content
response += token
yield response
chatbot = gr.Chatbot(height=600)
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="", 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",
),
],
fill_height=True,
chatbot=chatbot,
theme="Nymbo/Nymbo_Theme",
)
if __name__ == "__main__":
demo.launch() |