# coding:utf-8

import gradio as gr
# import argparse
# from utils import *
# from presets import *

my_api_key = ""  # 在这里输入你的 API 密钥

authflag = False

# gr.Chatbot.postprocess = postprocess

with gr.Blocks() as demo:
    history = gr.inputs.Hidden()
    token_count = gr.inputs.Hidden()
    promptTemplates = gr.inputs.Hidden()
    TRUECOMSTANT = gr.inputs.Hidden()
    FALSECONSTANT = gr.inputs.Hidden()
    topic = gr.inputs.Hidden()

    gradio_interface = gr.Interface(
        predict,
        [
            gr.inputs.Textbox(
                show_label=True,
                label="API-Key",
                placeholder=f"在这里输入你的OpenAI API-key...",
                value=my_api_key,
                type="password",
                visible=not HIDE_MY_KEY,
            ),
            gr.inputs.Textbox(
                show_label=True, label="System prompt", value=initial_prompt
            ),
            history,
            gr.inputs.Textbox(
                show_label=False, placeholder="在这里输入", label="User Input"
            ),
            gr.inputs.Hidden(),
            token_count,
            gr.inputs.Slider(
                label="Top-p (nucleus sampling)", min_val=0.0, max_val=1.0, step=0.05
            ),
            gr.inputs.Slider(
                label="Temperature", min_val=0.0, max_val=5.0, step=0.1
            ),
            gr.inputs.Checkbox(label="实时传输回答", default=True),
            gr.inputs.Dropdown(
                label="选择模型",
                choices=MODELS,
                default=MODELS[0],
                allow_multiple=False,
            ),
        ],
        [
            gr.outputs.Chat(
                label="Conversation",
                label_icon="💬",
                outputs=["text"],
                max_length=500,
                header_show_all=True,
                header_show_user_name=True,
            ),
            gr.outputs.Textbox(label="Status", default="Status: Ready"),
            gr.outputs.Button(label="🧹 新的对话"),
            gr.outputs.Button(label="🔄 重新生成"),
            gr.outputs.Button(label="🗑️ 删除最近一条对话"),
            gr.outputs.Button(label="♻️ 总结对话"),
            gr.outputs.Button(label="💾 保存对话"),
            gr.outputs.Dropdown(
                label="从列表中加载对话",
                choices=get_history_names(plain=True),
                default=get_history_names(plain=True)[0],
                allow_multiple=False,
            ),
            gr.outputs.Slider(
                label="Top-p (nucleus sampling)",
                min_val=0.0,
                max_val=1.0,
                step=0.05,
                default=1.0,
            ),
            gr.outputs.Slider(label="Temperature", min_val=0.0, max_val=5.0, step=0.1),
            gr.outputs.Markdown(
                label="最新生成到的token数量",
                default="待定",
            ),
            gr.outputs.Dropdown(
                label="选择Prompt模板集合文件",
                choices=get_template_names(plain=True),
                default=get_template_names(plain=True)[0],
                allow_multiple=False,
            ),
            gr.outputs.Dropdown(
                label="从Prompt模板中加载",
                choices=load_template(get_template_names(plain=True)[0], mode=1),
                default=0,
                allow_multiple=False,
            ),
            gr.outputs.Textbox(label="System prompt", default=initial_prompt),
            gr.outputs.Textbox(
                label="设置保存文件名", default="对话历史记录", allow_copy=True
            ),
        ],
        title="川虎ChatGPT 🚀",
        example=[
            "请输入文本...",
            "你好啊",
            "",
            "",
            "",
            "",
            1.0,
            1.0,
            True,
            "gpt3",
        ],
        theme="compact",
    )

if __name__ == "__main__":
    gradio_interface.launch() # 默认启动本地服务器，并通过默认的IP地址和端口进行访问
    # gradio_interface.launch(share=True)  # 启动本地服务器，创建公开分享链接
    # gradio_interface.launch(server_name="0.0.0.0", server_port=7860)  # 自定义IP和端口
    # gradio_interface.launch(
    #     server_name="0.0.0.0",
    #     server_port=7860,
    #     auth=("在这里填写用户名", "在这里填写密码"),
    # )  # 设置用户名和密码，适用于Nginx反向代理