import gradio as gr
import json
import requests
import openai
def chat_with_bot(message, history, system_prompt):
    # 构建请求数据
    messages = []
    # 添加系统提示词
    if system_prompt:
        messages.append({"role": "system", "content": system_prompt})
    # 添加历史对话
    for human, assistant in history:
        messages.append({"role": "user", "content": human})
        messages.append({"role": "assistant", "content": assistant.replace('<br>', '\n')})
    # 添加当前消息
    messages.append({"role": "user", "content": message})
    
    # 输出这轮的消息输入
    print("Current messages:")
    for msg in messages:
        print(f"{msg['role']}: {msg['content']}")
    
    # 发送请求
    try:
        client = openai.OpenAI(
            base_url="https://masterful-torch-2650-5069.east4.casdao.com/v1",
            api_key="not_needed"
        )
        
        response = client.chat.completions.create(
            messages=messages,
            model="customer_model",  # 或其他适用的模型
            frequency_penalty=1.05,
            temperature=0.7,
            top_p=0.8,
            max_tokens=1000
        )
        
        bot_message = response.choices[0].message.content
        # 处理所有可能的换行符情况
        bot_message = bot_message.replace('\r\n', '<br>').replace('\\n', '<br>').replace('\n', '<br>').replace('\r', '<br>')
        # 输出bot的返回值
        print("Bot response:")
        print(f"assistant: {bot_message}")
        return bot_message
    except Exception as e:
        return f"Error: {str(e)}"

# 创建Gradio界面
with gr.Blocks() as demo:
    gr.Markdown("# FlowAsk\n这是一个流程图问答助手")
    
    system_prompt_state = gr.State("")
    
    with gr.Row():
        with gr.Column():
            system_prompt_input = gr.Textbox(
                label="系统提示词",
                placeholder="请输入系统提示词，用于设定AI助手的行为和角色...",
                lines=2,
                value=""
            )
    
    def update_prompt(prompt):
        system_prompt_state.value = prompt
        return prompt
    
    system_prompt_input.change(
        fn=update_prompt,
        inputs=[system_prompt_input],
        outputs=[system_prompt_state]
    )
    
    def chat_wrapper(message, history):
        return chat_with_bot(message, history, system_prompt_state.value)
    
    chatbot = gr.ChatInterface(
        fn=chat_wrapper,
        title="",
        description="",
    )
    


# 启动应用
if __name__ == "__main__":
    demo.launch()