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import gradio as gr
import requests
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 = ""
headers = {
"Authorization": f"Bearer xxxx",
"Content-Type": "application/json"
}
data = {
"model": "Llama-3.1-8B--Instruct-syllabary",
"messages": messages,
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"stream": True
}
response = requests.post("http://13.230.243.208:50001/v1/chat/completion", headers=headers, json=data)
if response.status_code == 200:
for token in response.iter_lines():
yield token.decode("utf-8")
else:
yield "Error occurred"
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a helpful assistant.", 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()
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