Update app.py

app.py

@@ -1,306 +1,463 @@
-import gradio as gr
-import os
-from huggingface_hub import InferenceClient
-from get_machine_from_json import string_to_bsg
-import json
-
-# 读取系统提示词
-with open('user_system_prompt.txt', 'r', encoding='utf-8') as f:
-    SYSTEM_PROMPT = f.read()
-
-# 读取示例（如果存在）
-EXAMPLES = []
-try:
-    with open('examples.json', 'r', encoding='utf-8') as f:
-        examples_data = json.load(f)
-        EXAMPLES = [[ex["description"]] for ex in examples_data.get("examples", [])]
-except:
-    pass
-
-# 初始化 HF 客户端 - 使用 DeepSeek 免费模型
-def create_client():
-    """创建 HF Inference 客户端"""
-    return InferenceClient(
-        model="deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
-        token=os.environ.get("HF_TOKEN")  # 从环境变量读取 token
-    )
-
-def generate_machine(user_prompt, temperature=0.7, max_tokens=4096):
-    """
-    使用 AI 生成机器设计的 JSON，然后转换为 XML
-    
-    Args:
-        user_prompt: 用户输入的机器描述
-        temperature: 生成温度
-        max_tokens: 最大 token 数
-    
-    Returns:
-        tuple: (ai_response, xml_string, status_message)
-    """
-    if not user_prompt.strip():
-        return "", "", "❌ 请输入机器描述！"
-    
-    try:
-        client = create_client()
-        
-        # 构建消息
-        messages = [
-            {"role": "system", "content": SYSTEM_PROMPT},
-            {"role": "user", "content": user_prompt}
-        ]
-        
-        # 调用 API
-        response = ""
-        for message in client.chat_completion(
-            messages=messages,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            stream=True,
-        ):
-            if message.choices[0].delta.content:
-                response += message.choices[0].delta.content
-        
-        # 尝试转换为 XML
-        try:
-            xml_string = string_to_bsg(response)
-            status = "✅ 生成成功！可以下载 .bsg 文件了。"
-            return response, xml_string, status
-        except Exception as e:
-            return response, "", f"⚠️ AI 生成完成，但转换 XML 时出错：{str(e)}"
-            
-    except Exception as e:
-        return "", "", f"❌ 生成失败：{str(e)}"
-
-def convert_json_to_xml(json_input):
-    """
-    手动转换 JSON 到 XML
-    
-    Args:
-        json_input: JSON 字符串或 JSON 数据
-    
-    Returns:
-        tuple: (xml_string, status_message)
-    """
-    if not json_input.strip():
-        return "", "❌ 请输入 JSON 数据！"
-    
-    try:
-        xml_string = string_to_bsg(json_input)
-        return xml_string, "✅ 转换成功！"
-    except Exception as e:
-        return "", f"❌ 转换失败：{str(e)}"
-
-def save_xml_to_file(xml_content):
-    """保存 XML 到 .bsg 文件"""
-    if not xml_content:
-        return None
-    
-    output_path = "generated_machine.bsg"
-    with open(output_path, 'w', encoding='utf-8') as f:
-        f.write(xml_content)
-    return output_path
-
-# 自定义 CSS 样式，参考 index.html
-custom_css = """
-.gradio-container {
-    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif !important;
-}
-
-.header {
-    text-align: center;
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    padding: 30px;
-    border-radius: 10px;
-    color: white;
-    margin-bottom: 20px;
-}
-
-.header h1 {
-    font-size: 2.5em;
-    margin-bottom: 10px;
-}
-
-.info-box {
-    background: #e7f3ff;
-    border-left: 4px solid #2196F3;
-    padding: 15px;
-    margin-bottom: 20px;
-    border-radius: 4px;
-}
-
-.success-box {
-    background: #d4edda;
-    color: #155724;
-    padding: 15px;
-    border-radius: 8px;
-    border: 1px solid #c3e6cb;
-}
-
-.error-box {
-    background: #f8d7da;
-    color: #721c24;
-    padding: 15px;
-    border-radius: 8px;
-    border: 1px solid #f5c6cb;
-}
-"""
-
-# 创建 Gradio 界面
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="🎮 Besiege Machine Generator") as demo:
-    
-    # 头部
-    gr.HTML("""
-        <div class="header">
-            <h1>🎮 Besiege Machine Generator</h1>
-            <p style="font-size: 1.1em; opacity: 0.9;">使用 AI 生成你的 Besiege 机器设计</p>
-            <span style="background: rgba(255, 255, 255, 0.2); padding: 5px 15px; border-radius: 20px; font-size: 0.9em;">
-                ✨ Powered by DeepSeek AI
-            </span>
-        </div>
-    """)
-    
-    with gr.Tabs():
-        # Tab 1: AI 生成
-        with gr.Tab("🤖 AI 生成"):
-            gr.HTML("""
-                <div class="info-box">
-                    <h4>💡 使用说明</h4>
-                    <ul>
-                        <li>描述你想要创建的机器</li>
-                        <li>点击"生成机器"按钮</li>
-                        <li>等待 AI 生成完成</li>
-                        <li>下载生成的 .bsg 文件</li>
-                    </ul>
-                </div>
-            """)
-            
-            with gr.Row():
-                with gr.Column():
-                    user_input = gr.Textbox(
-                        label="描述你的机器 *",
-                        placeholder="例如：创建一个四轮车，能够向前移动...",
-                        lines=5
-                    )
-                    
-                    # 添加示例
-                    if EXAMPLES:
-                        gr.Examples(
-                            examples=EXAMPLES,
-                            inputs=user_input,
-                            label="💡 示例提示"
-                        )
-                    
-                    with gr.Accordion("⚙️ 高级设置", open=False):
-                        temperature = gr.Slider(
-                            minimum=0.1,
-                            maximum=1.5,
-                            value=0.7,
-                            step=0.1,
-                            label="Temperature（温度）",
-                            info="较高的值会产生更有创意但可能不太稳定的结果"
-                        )
-                        max_tokens = gr.Slider(
-                            minimum=1024,
-                            maximum=8192,
-                            value=4096,
-                            step=512,
-                            label="Max Tokens（最大令牌数）",
-                            info="生成的最大长度"
-                        )
-                    
-                    generate_btn = gr.Button("🚀 生成机器", variant="primary", size="lg")
-            
-            status_output = gr.Markdown(label="状态")
-            
-            with gr.Row():
-                with gr.Column():
-                    ai_response = gr.Textbox(
-                        label="AI 响应（JSON）",
-                        lines=10,
-                        max_lines=20,
-                        show_copy_button=True
-                    )
-                
-                with gr.Column():
-                    xml_output = gr.Textbox(
-                        label="XML 输出",
-                        lines=10,
-                        max_lines=20,
-                        show_copy_button=True
-                    )
-            
-            download_btn = gr.File(label="📥 下载 .bsg 文件")
-            
-            # 绑定生成按钮
-            def generate_and_save(user_prompt, temp, max_tok):
-                ai_resp, xml_str, status = generate_machine(user_prompt, temp, max_tok)
-                file_path = save_xml_to_file(xml_str) if xml_str else None
-                return ai_resp, xml_str, status, file_path
-            
-            generate_btn.click(
-                fn=generate_and_save,
-                inputs=[user_input, temperature, max_tokens],
-                outputs=[ai_response, xml_output, status_output, download_btn]
-            )
-        
-        # Tab 2: 手动转换
-        with gr.Tab("🔄 手动转换"):
-            gr.HTML("""
-                <div class="info-box">
-                    <h4>💡 使用说明</h4>
-                    <ul>
-                        <li>粘贴你的 JSON 机器数据</li>
-                        <li>点击"转换为 XML"按钮</li>
-                        <li>下载生成的 .bsg 文件</li>
-                    </ul>
-                </div>
-            """)
-            
-            json_input = gr.Textbox(
-                label="JSON 输入",
-                placeholder='粘贴你的 JSON 数据...',
-                lines=10,
-                max_lines=20
-            )
-            
-            convert_btn = gr.Button("🔄 转换为 XML", variant="primary", size="lg")
-            
-            status_manual = gr.Markdown(label="状态")
-            
-            xml_output_manual = gr.Textbox(
-                label="XML 输出",
-                lines=10,
-                max_lines=20,
-                show_copy_button=True
-            )
-            
-            download_manual_btn = gr.File(label="📥 下载 .bsg 文件")
-            
-            # 绑定转换按钮
-            def convert_and_save(json_str):
-                xml_str, status = convert_json_to_xml(json_str)
-                file_path = save_xml_to_file(xml_str) if xml_str else None
-                return xml_str, status, file_path
-            
-            convert_btn.click(
-                fn=convert_and_save,
-                inputs=[json_input],
-                outputs=[xml_output_manual, status_manual, download_manual_btn]
-            )
-    
-    # 底部信息
-    gr.HTML("""
-        <div style="text-align: center; margin-top: 30px; padding: 20px; background: #f8f9fa; border-radius: 10px;">
-            <p style="color: #666; margin: 5px 0;">
-                🤖 使用 <a href="https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B" target="_blank">DeepSeek-R1-Distill-Llama-8B</a> 模型
-            </p>
-            <p style="color: #666; margin: 5px 0;">
-                ⚠️ 注意：生成的机器可能需要在游戏中进行调整
-            </p>
-        </div>
-    """)
-
-# 启动应用
-if __name__ == "__main__":
-    demo.launch()
-
+import gradio as gr
+import os
+from huggingface_hub import InferenceClient
+from get_machine_from_json import string_to_bsg
+import json
+
+# Read system prompt
+with open('user_system_prompt.txt', 'r', encoding='utf-8') as f:
+    SYSTEM_PROMPT = f.read()
+
+# Read examples (if exists)
+EXAMPLES = []
+try:
+    with open('examples.json', 'r', encoding='utf-8') as f:
+        examples_data = json.load(f)
+        EXAMPLES = [[ex["description"]] for ex in examples_data.get("examples", [])]
+except:
+    pass
+
+# Available AI models (priority order)
+AVAILABLE_MODELS = [
+    "deepseek-ai/DeepSeek-V3.2-Exp",  # DeepSeek V3 - Most powerful
+    "deepseek-ai/DeepSeek-V3.1",
+    "deepseek-ai/deepseek-llm-67b-chat",  # DeepSeek alternative  
+    "Qwen/Qwen2.5-72B-Instruct",  # Qwen backup
+]
+
+# Initialize HF client
+def create_client():
+    """Create HF Inference Client"""
+    # Get token from environment variable
+    hf_token = os.environ.get("HF_TOKEN")
+    
+    if not hf_token:
+        raise ValueError(
+            "⚠️ HF_TOKEN not set!\n\n"
+            "Please add your Hugging Face token in Space Settings:\n\n"
+            "1. Go to your Space Settings\n"
+            "2. Find 'Repository secrets' section\n"
+            "3. Click 'Add a secret'\n"
+            "4. Name: HF_TOKEN\n"
+            "5. Value: Your token (get from https://huggingface.co/settings/tokens)\n"
+            "6. Save and restart Space\n\n"
+            "The token should have READ permission and start with 'hf_'"
+        )
+    
+    # Try models in order
+    for model in AVAILABLE_MODELS:
+        try:
+            return InferenceClient(model=model, token=hf_token)
+        except:
+            continue
+    
+    # Fallback to first model
+    return InferenceClient(model=AVAILABLE_MODELS[0], token=hf_token)
+
+def generate_machine(user_prompt, temperature=0.7, max_tokens=4096):
+    """
+    Generate machine design JSON using AI, then convert to XML
+    
+    Args:
+        user_prompt: User's machine description
+        temperature: Generation temperature
+        max_tokens: Maximum tokens
+    
+    Returns:
+        tuple: (ai_response, xml_string, status_message)
+    """
+    if not user_prompt.strip():
+        return "", "", "❌ Please enter a machine description!"
+    
+    try:
+        client = create_client()
+        
+        # Build messages
+        messages = [
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user", "content": user_prompt}
+        ]
+        
+        # Try API call
+        response = ""
+        try:
+            for message in client.chat_completion(
+                messages=messages,
+                temperature=temperature,
+                max_tokens=max_tokens,
+                stream=True,
+            ):
+                if message.choices[0].delta.content:
+                    response += message.choices[0].delta.content
+        except Exception as api_error:
+            error_msg = str(api_error)
+            if "401" in error_msg or "Unauthorized" in error_msg:
+                return "", "", (
+                    "❌ Authentication Failed!\n\n"
+                    "Please ensure HF_TOKEN is correctly set in Space Settings:\n\n"
+                    "1. Visit https://huggingface.co/settings/tokens\n"
+                    "2. Create a new token (Read permission)\n"
+                    "3. Add in Space Settings → Repository secrets:\n"
+                    "   - Name: HF_TOKEN\n"
+                    "   - Value: your token\n"
+                    "4. Restart Space\n\n"
+                    f"Error details: {error_msg}"
+                )
+            raise
+        
+        # Try to convert to XML
+        try:
+            xml_string = string_to_bsg(response)
+            status = "✅ Generation successful! You can now download the .bsg file."
+            return response, xml_string, status
+        except Exception as e:
+            return response, "", f"⚠️ AI generation completed, but XML conversion failed: {str(e)}"
+            
+    except ValueError as e:
+        return "", "", str(e)
+    except Exception as e:
+        return "", "", f"❌ Generation failed: {str(e)}"
+
+def convert_json_to_xml(json_input):
+    """
+    Manually convert JSON to XML
+    
+    Args:
+        json_input: JSON string or JSON data
+    
+    Returns:
+        tuple: (xml_string, status_message)
+    """
+    if not json_input.strip():
+        return "", "❌ Please enter JSON data!"
+    
+    try:
+        xml_string = string_to_bsg(json_input)
+        return xml_string, "✅ Conversion successful!"
+    except Exception as e:
+        return "", f"❌ Conversion failed: {str(e)}"
+
+def save_xml_to_file(xml_content):
+    """Save XML to .bsg file"""
+    if not xml_content:
+        return None
+    
+    output_path = "generated_machine.bsg"
+    with open(output_path, 'w', encoding='utf-8') as f:
+        f.write(xml_content)
+    return output_path
+
+# Custom CSS matching index.html
+custom_css = """
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+.gradio-container {
+    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif !important;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    min-height: 100vh;
+}
+
+.main {
+    max-width: 1200px !important;
+    margin: 20px auto !important;
+    background: white !important;
+    border-radius: 20px !important;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.3) !important;
+    overflow: hidden !important;
+}
+
+.header {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 30px;
+    text-align: center;
+    border-radius: 20px 20px 0 0;
+    margin-bottom: 20px;
+}
+
+.header h1 {
+    font-size: 2.5em;
+    margin-bottom: 10px;
+}
+
+.header p {
+    font-size: 1.1em;
+    opacity: 0.9;
+}
+
+.badge {
+    display: inline-block;
+    background: rgba(255, 255, 255, 0.2);
+    padding: 5px 15px;
+    border-radius: 20px;
+    font-size: 0.9em;
+    margin-top: 10px;
+}
+
+.info-box {
+    background: #e7f3ff;
+    border-left: 4px solid #2196F3;
+    padding: 15px;
+    margin-bottom: 20px;
+    border-radius: 4px;
+}
+
+.info-box h4 {
+    margin-bottom: 10px;
+    color: #1976D2;
+}
+
+.info-box ul {
+    margin-left: 20px;
+    line-height: 1.8;
+}
+
+textarea, input {
+    width: 100% !important;
+    padding: 12px 15px !important;
+    border: 2px solid #e0e0e0 !important;
+    border-radius: 8px !important;
+    font-size: 16px !important;
+    transition: border-color 0.3s !important;
+}
+
+textarea:focus, input:focus {
+    outline: none !important;
+    border-color: #667eea !important;
+}
+
+.gr-button {
+    padding: 15px 30px !important;
+    font-size: 16px !important;
+    font-weight: 600 !important;
+    border: none !important;
+    border-radius: 8px !important;
+    cursor: pointer !important;
+    transition: all 0.3s !important;
+    text-transform: uppercase !important;
+    letter-spacing: 0.5px !important;
+}
+
+.gr-button-primary {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    color: white !important;
+}
+
+.gr-button-primary:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 5px 20px rgba(102, 126, 234, 0.4) !important;
+}
+
+.gr-button-secondary {
+    background: #6c757d !important;
+    color: white !important;
+}
+
+.gr-button-secondary:hover {
+    background: #5a6268 !important;
+    transform: translateY(-2px) !important;
+}
+
+.output-section {
+    background: #f8f9fa;
+    border: 2px solid #e0e0e0;
+    border-radius: 8px;
+    padding: 20px;
+    margin-top: 15px;
+}
+
+.footer {
+    text-align: center;
+    margin-top: 30px;
+    padding: 20px;
+    background: #f8f9fa;
+    border-radius: 10px;
+}
+
+.footer p {
+    color: #666;
+    margin: 5px 0;
+}
+
+.tabs {
+    border-bottom: 2px solid #e0e0e0 !important;
+}
+
+.tab {
+    padding: 12px 24px !important;
+    font-size: 16px !important;
+    font-weight: 500 !important;
+    color: #666 !important;
+    border-bottom: 3px solid transparent !important;
+    transition: all 0.3s !important;
+}
+
+.tab-active {
+    color: #667eea !important;
+    border-bottom-color: #667eea !important;
+}
+"""
+
+# Create Gradio interface
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="🎮 Besiege Machine Generator") as demo:
+    
+    # Header
+    gr.HTML("""
+        <div class="header">
+            <h1>🎮 Besiege Machine Generator</h1>
+            <p>Generate your Besiege machine designs with AI</p>
+            <span class="badge">✨ Powered by DeepSeek AI</span>
+        </div>
+    """)
+    
+    with gr.Tabs():
+        # Tab 1: AI Generation
+        with gr.Tab("AI Generation"):
+            gr.HTML("""
+                <div class="info-box">
+                    <h4>💡 How to Use</h4>
+                    <ul>
+                        <li>Describe the machine you want to create</li>
+                        <li>Click "Generate Machine"</li>
+                        <li>Wait for AI to generate (30-120 seconds)</li>
+                        <li>Download the generated .bsg file</li>
+                    </ul>
+                </div>
+            """)
+            
+            with gr.Row():
+                with gr.Column():
+                    user_input = gr.Textbox(
+                        label="Describe Your Machine *",
+                        placeholder="e.g., Create a four-wheeled vehicle with powered wheels...",
+                        lines=5
+                    )
+                    
+                    # Add examples
+                    if EXAMPLES:
+                        gr.Examples(
+                            examples=EXAMPLES,
+                            inputs=user_input,
+                            label="💡 Example Prompts"
+                        )
+                    
+                    with gr.Accordion("⚙️ Advanced Settings", open=False):
+                        temperature = gr.Slider(
+                            minimum=0.1,
+                            maximum=1.5,
+                            value=0.7,
+                            step=0.1,
+                            label="Temperature",
+                            info="Higher values produce more creative but less stable results"
+                        )
+                        max_tokens = gr.Slider(
+                            minimum=1024,
+                            maximum=8192,
+                            value=4096,
+                            step=512,
+                            label="Max Tokens",
+                            info="Maximum length of generation"
+                        )
+                    
+                    generate_btn = gr.Button("🚀 Generate Machine", variant="primary", size="lg")
+            
+            status_output = gr.Markdown(label="Status")
+            
+            with gr.Row():
+                with gr.Column():
+                    ai_response = gr.Textbox(
+                        label="AI Response (JSON)",
+                        lines=10,
+                        max_lines=20,
+                        show_copy_button=True
+                    )
+                
+                with gr.Column():
+                    xml_output = gr.Textbox(
+                        label="XML Output",
+                        lines=10,
+                        max_lines=20,
+                        show_copy_button=True
+                    )
+            
+            download_btn = gr.File(label="📥 Download .bsg File")
+            
+            # Bind generate button
+            def generate_and_save(user_prompt, temp, max_tok):
+                ai_resp, xml_str, status = generate_machine(user_prompt, temp, max_tok)
+                file_path = save_xml_to_file(xml_str) if xml_str else None
+                return ai_resp, xml_str, status, file_path
+            
+            generate_btn.click(
+                fn=generate_and_save,
+                inputs=[user_input, temperature, max_tokens],
+                outputs=[ai_response, xml_output, status_output, download_btn]
+            )
+        
+        # Tab 2: Manual Conversion
+        with gr.Tab("Manual Conversion"):
+            gr.HTML("""
+                <div class="info-box">
+                    <h4>💡 How to Use</h4>
+                    <ul>
+                        <li>Paste your JSON machine data</li>
+                        <li>Click "Convert to XML"</li>
+                        <li>Download the generated .bsg file</li>
+                    </ul>
+                </div>
+            """)
+            
+            json_input = gr.Textbox(
+                label="JSON Input",
+                placeholder='Paste your JSON data here...',
+                lines=10,
+                max_lines=20
+            )
+            
+            convert_btn = gr.Button("🔄 Convert to XML", variant="primary", size="lg")
+            
+            status_manual = gr.Markdown(label="Status")
+            
+            xml_output_manual = gr.Textbox(
+                label="XML Output",
+                lines=10,
+                max_lines=20,
+                show_copy_button=True
+            )
+            
+            download_manual_btn = gr.File(label="📥 Download .bsg File")
+            
+            # Bind convert button
+            def convert_and_save(json_str):
+                xml_str, status = convert_json_to_xml(json_str)
+                file_path = save_xml_to_file(xml_str) if xml_str else None
+                return xml_str, status, file_path
+            
+            convert_btn.click(
+                fn=convert_and_save,
+                inputs=[json_input],
+                outputs=[xml_output_manual, status_manual, download_manual_btn]
+            )
+    
+    # Footer
+    gr.HTML(f"""
+        <div class="footer">
+            <p>
+                🤖 Using <a href="https://huggingface.co/{AVAILABLE_MODELS[0]}" target="_blank">{AVAILABLE_MODELS[0]}</a> model
+            </p>
+            <p>
+                ⚠️ Note: Generated machines may require adjustments in-game
+            </p>
+            <p style="color: #999; font-size: 0.9em;">
+                💡 AI generation requires HF Token - Free to use
+            </p>
+        </div>
+    """)
+
+# Launch app
+if __name__ == "__main__":
+    demo.launch()