import gradio as gr
import time
import base64
from openai import OpenAI
import os
from io import BytesIO
from PIL import Image

# 配置
BASE_URL = "https://api.stepfun.com/v1"
# 从环境变量获取API密钥
STEP_API_KEY = os.environ.get("STEP_API_KEY", "")

# 可选模型
MODELS = ["step-3", "step-r1-v-mini"]

def image_to_base64(image):
    """将PIL图像转换为base64字符串"""
    if image is None:
        return None
    
    if isinstance(image, Image.Image):
        buffered = BytesIO()
        image.save(buffered, format="PNG")
        img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
        return img_str
    
    return None

def call_step_api_stream(message, history, temperature, max_tokens, image=None):
    """调用Step API进行流式对话"""
    print(f"[DEBUG] Starting API call - Message: {message}, Has Image: {image is not None}")
    
    if not message and not image:
        print("[DEBUG] No message or image provided")
        yield history
        return
    
    if not STEP_API_KEY:
        print("[DEBUG] API key not configured")
        history.append([message or "[Image]", "❌ API key not configured. Please add STEP_API_KEY in Settings."])
        yield history
        return
    
    print(f"[DEBUG] API Key exists: {bool(STEP_API_KEY)}")
    
    # 构造消息历史
    messages = []
    
    # 添加历史对话
    for h in history:
        if h[0]:  # 用户消息
            messages.append({"role": "user", "content": h[0]})
        if h[1]:  # 助手回复
            messages.append({"role": "assistant", "content": h[1]})
    
    # 构造当前消息
    if image is not None:
        # 有图片的情况
        try:
            base64_image = image_to_base64(image)
            if base64_image is None:
                history.append([message or "[Image]", "❌ Failed to process image"])
                yield history
                return
            
            current_content = [
                {"type": "image_url", "image_url": {"url": f"data:image/jpg;base64,{base64_image}", "detail": "high"}}
            ]
            if message:
                current_content.append({"type": "text", "text": message})
            
            messages.append({"role": "user", "content": current_content})
            display_message = f"[Image] {message}" if message else "[Image]"
        except Exception as e:
            history.append([message or "[Image]", f"❌ Image processing error: {str(e)}"])
            yield history
            return
    else:
        # 纯文本
        messages.append({"role": "user", "content": message})
        display_message = message
    
    # 添加到历史记录
    history.append([display_message, ""])
    yield history  # 立即显示用户消息
    
    print(f"[DEBUG] Messages to send: {messages}")
    
    # 创建客户端
    try:
        client = OpenAI(api_key=STEP_API_KEY, base_url=BASE_URL)
        print("[DEBUG] Client created successfully")
    except Exception as e:
        print(f"[DEBUG] Client initialization failed: {e}")
        history[-1][1] = f"❌ Client initialization failed: {str(e)}"
        yield history
        return
    
    # 调用API
    try:
        print("[DEBUG] Calling API...")
        response = client.chat.completions.create(
            model="step-3",
            messages=messages,
            temperature=temperature,
            max_tokens=max_tokens,
            stream=True
        )
        print("[DEBUG] API call successful, processing stream...")
        
        # 处理流式响应
        full_response = ""
        chunk_count = 0
        for chunk in response:
            chunk_count += 1
            if chunk.choices and len(chunk.choices) > 0:
                delta = chunk.choices[0].delta
                if hasattr(delta, 'content') and delta.content:
                    full_response += delta.content
                    history[-1][1] = full_response
                    print(f"[DEBUG] Chunk {chunk_count}: {delta.content[:50] if delta.content else 'None'}...")
                    yield history
        
        if not full_response:
            print("[DEBUG] No response content received")
            history[-1][1] = "⚠️ No response received from API"
            yield history
        else:
            print(f"[DEBUG] Final response length: {len(full_response)} chars")
                    
    except Exception as e:
        print(f"[DEBUG] API request failed: {e}")
        import traceback
        traceback.print_exc()
        history[-1][1] = f"❌ API request failed: {str(e)}"
        yield history

def user_input(message, history, image):
    """处理用户输入"""
    if message or image:
        return "", history, None
    return message, history, image

def clear_history():
    """Clear conversation history"""
    return [], None, ""

# 创建Gradio界面
with gr.Blocks(title="Step-3", theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # 🤖 Step-3
    Hello, I am Step-3! 
    """)
    
    with gr.Row():
        with gr.Column(scale=3):
            # 对话界面
            chatbot = gr.Chatbot(
                height=500,
                show_label=False,
                elem_id="chatbot",
                bubble_full_width=False
            )
            
            with gr.Row():
                with gr.Column(scale=8):
                    msg = gr.Textbox(
                        label="Input message",
                        placeholder="Type your question here...",
                        lines=1,
                        max_lines=5,
                        show_label=False,
                        elem_id="msg",
                        container=False
                    )
                with gr.Column(scale=1, min_width=100):
                    submit_btn = gr.Button("Send", variant="primary")
                with gr.Column(scale=1, min_width=100):
                    clear_btn = gr.Button("Clear")
            
            # 图片上传
            with gr.Row():
                image_input = gr.Image(
                    label="Upload Image (Optional)",
                    type="pil",
                    height=150,
                    scale=1
                )
        
        with gr.Column(scale=1):
            # 设置面板
            gr.Markdown("### ⚙️ Settings")
            

            
            temperature_slider = gr.Slider(
                minimum=0,
                maximum=1,
                value=0.7,
                step=0.1,
                label="Temperature",
                interactive=True
            )
            
            max_tokens_slider = gr.Slider(
                minimum=100,
                maximum=4000,
                value=2000,
                step=100,
                label="Max Output Length",
                interactive=True
            )
            

    
    # 事件处理
    msg.submit(
        user_input,
        [msg, chatbot, image_input],
        [msg, chatbot, image_input],
        queue=False
    ).then(
        call_step_api_stream,
        [msg, chatbot, temperature_slider, max_tokens_slider, image_input],
        chatbot
    )
    
    submit_btn.click(
        user_input,
        [msg, chatbot, image_input],
        [msg, chatbot, image_input],
        queue=False
    ).then(
        call_step_api_stream,
        [msg, chatbot, temperature_slider, max_tokens_slider, image_input],
        chatbot
    )
    
    clear_btn.click(
        clear_history,
        None,
        [chatbot, image_input, msg],
        queue=False
    )
    
    # 页脚
    gr.Markdown("""
    ---
    <div style="text-align: center;">
        <img src="https://huggingface.co/stepfun-ai/step3/resolve/main/figures/stepfun-logo.png" alt="StepFun Logo" style="height: 40px; margin: 10px;">
        <br>
        Powered by <a href="https://www.stepfun.com/" target="_blank">StepFun</a>
    </div>
    """)

# 启动应用
if __name__ == "__main__":
    print(f"[DEBUG] Starting app with API key: {'Set' if STEP_API_KEY else 'Not set'}")
    print(f"[DEBUG] Base URL: {BASE_URL}")
    demo.queue(max_size=10)
    demo.launch(
        share=False,
        debug=True
    )