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import gradio as gr
import os
import json
import requests
API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
print(f"system message is ^^ {system_msg}")
initial_message = [{"role": "user", "content": f"{inputs}"},]
multi_turn_message = [
{"role": "system", "content": "你是一个中文AI专家，你是用远见科技公司开发和维护的，你可以回答所有的问题，除了涉黄涉政的问题，你就是一个中国人，切记"}
]
messages=multi_turn_message
for data in chatbot:
user = {}
user["role"] = "user"
user["content"] = data[0]
assistant = {}
assistant["role"] = "assistant"
assistant["content"] = data[1]
messages.append(user)
messages.append(assistant)
temp = {}
temp["role"] = "user"
temp["content"] = inputs
messages.append(temp)
payload = {"model": "gpt-3.5-turbo", "messages": messages, "temperature" : 1, "top_p": 1.0, "n" : 1, "stream": True, "presence_penalty":0, "frequency_penalty":0,}
chat_counter+=1
history.append(inputs)
print(f"Logging : payload is - {payload}")
response = requests.post(API_URL, headers=headers, json=payload, stream=True)
print(f"Logging : response code - {response}")
token_counter = 0
partial_words = ""
counter=0
for chunk in response.iter_lines():
if counter == 0:
counter+=1
continue
if chunk.decode() :
chunk = chunk.decode()
if len(chunk) > 12 and "content" in json.loads(chunk[6:])['choices'][0]['delta']:
partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
if token_counter == 0:
history.append(" " + partial_words)
else:
history[-1] = partial_words
chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ] # convert to tuples of list
token_counter+=1
yield chat, history, chat_counter, response # resembles {chatbot: chat, state: history}
def reset_textbox():
return gr.update(value='')
def set_visible_false():
return gr.update(visible=False)
def set_visible_true():
return gr.update(visible=False)
theme_addon_msg = ""
system_msg_info = ""
theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="blue",
text_size=gr.themes.sizes.text_md)
with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 450px; overflow: auto;}""",
theme=theme) as demo:
with gr.Column(elem_id = "col_container"):
with gr.Accordion("", open=False, visible=False):
system_msg = gr.Textbox(value="")
accordion_msg = gr.HTML(value="", visible=False)
chatbot = gr.Chatbot(label='chat', elem_id="chatbot")
inputs = gr.Textbox(placeholder= "请输入", show_label= False)
state = gr.State([])
with gr.Accordion("", open=False, visible=False):
top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=False, visible=False)
temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=False, visible=False)
chat_counter = gr.Number(value=0, visible=False, precision=0)
inputs.submit( predict, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter],) #openai_api_key
inputs.submit(reset_textbox, [], [inputs])
demo.queue(max_size=20, concurrency_count=20).launch(debug=True)
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