Upload app.py

app.py

@@ -0,0 +1,114 @@
+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")