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# encoding = "utf-8"
'''
This is a mediator: a gradio server for OpenAI APIs
'''
import os
import json
import argparse
import gradio as gr
import requests
from openai import OpenAI
def http_bot(messages, argsbox):
args = eval(argsbox)
messages = eval(messages)
print(messages)
print(argsbox)
# api_key = args["api_key"]
# base_url = args["base_url"]
# model = args["model"]
# temperature = args["temperature"]
# max_tokens = args["max_tokens"]
#
# headers = {
# "Content-Type": "application/json",
# "Authorization": f"Bearer {}" # Users will provide their own OPENAI_API_KEY
# }
client = OpenAI(api_key=args["api_key"], base_url = args["base_url"])
# n = 0
# while True:
# try:
chat_completion = client.chat.completions.create(
messages=messages,
model=args["model"], #"gpt-3.5-turbo-16k", # "gpt-3.5-turbo", # gpt-4-1106-preview
temperature=float(args["temperature"]),
max_tokens=int(args["max_tokens"])
)
# break
# except Exception as e:
# continue
print(chat_completion)
return chat_completion.choices[0].message.content
with gr.Blocks() as demo:
gr.Markdown("# vLLM text completion demo\n")
inputbox = gr.Textbox(label="Input",
placeholder="Enter text and press ENTER")
argsbox = gr.Textbox(label="Args", placeholder="a dict of {api_key, base_url, model, temperature, max_tokens}")
outputbox = gr.Textbox(label="Output",
placeholder="Generated result from the model")
submit = gr.Button("Submit")
submit.click(http_bot, [inputbox, argsbox], [outputbox], api_name="submit")
demo.launch(share=True)
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