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import gradio as gr
import openai
def get_ans(user_content, chat_data_, chat_log_, api_key):
chat_data_.append({"role": "user", "content": user_content})
res_ = request_ans(api_key, chat_data_)
res = res_.choices[0].message.content
while res.startswith("\n") != res.startswith("？"):
res = res[1:]
chat_data_.append({"role": 'assistant', "content": res})
chat_log_.append([user_content, res])
return chat_log_, chat_log_, "", chat_data_
def request_ans(api_key, msg):
# openai.proxy = {'http': "http://127.0.0.1:8001", 'https': 'http://127.0.0.1:8001'}
openai.api_key = api_key
response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages=msg,
temperature=0.2
)
return response
def config(api_key, company, job):
prompt = f"你是一名熟悉{company}的面试官。用户将成为候选人，您将向用户询问{job}职位的面试问题。希望你只作为面试官回答。不要一次写出所有的问题。希望你只对用户进行面试。问用户问题，等待用户的回答。不要写解释。你需要像面试官一样一个一个问题问用户，等用户回答。 若用户回答不上某个问题，那就继续问下一个问题 "
content = [{"role": "system", "content": prompt}, {"role": "user", "content": "面试官你好"}]
res_ = request_ans(api_key, content)
res = res_.choices[0].message.content
while res.startswith("\n") != res.startswith("？"):
res = res[1:]
history = [["面试官您好！", res]]
return history, history, api_key, content
with gr.Blocks(title="AI面试官") as block:
chat_log = gr.State()
key = gr.State()
chat_data = gr.State()
gr.Markdown("""<h1><center>AI面试官</center></h1>""")
with gr.Row():
with gr.Column():
chatbot = gr.Chatbot()
message = gr.Textbox(label="你的回答")
message.submit(
fn=get_ans,
inputs=[
message,
chat_data,
chat_log,
key
],
outputs=[chatbot, chat_log, message, chat_data]
)
submit = gr.Button("发送")
submit.click(
get_ans,
inputs=[
message,
chat_data,
chat_log,
key
],
outputs=[chatbot, chat_log, message, chat_data],
)
with gr.Column():
# temperature = gr.Slider(label="Temperature", minimum=0, maximum=1, step=0.1, value=0.9)
# max_tokens = gr.Slider(label="Max Tokens", minimum=10, maximum=400, step=10, value=150)
# top_p = gr.Slider(label="Top P", minimum=0, maximum=1, step=0.1, value=1)
# frequency_penalty = gr.Slider(
# label="Frequency Penalty",
# minimum=0,
# maximum=1,
# step=0.1,
# value=0,
# )
# presence_penalty = gr.Slider(
# label="Presence Penalty",
# minimum=0,
# maximum=1,
# step=0.1,
# value=0.6,
# )
openai_token = gr.Textbox(label="OpenAI API Key") # , value=os.getenv("OPENAI_API_KEY")
company = gr.Textbox(label="你面试的公司")
job = gr.Textbox(label="你面试的岗位")
start = gr.Button("开始面试")
start.click(
config,
inputs=[
openai_token,
company,
job
],
outputs=[chatbot, chat_log, key, chat_data]
)
if __name__ == "__main__":
block.launch(auth=('alpaca', 'alpaca'), auth_message="Enter your username and password")
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