init commit

README.md

@@ -1,13 +0,0 @@
----
-title: Lumina-Nieta T2I Playground
-emoji: 👁
-colorFrom: yellow
-colorTo: purple
-sdk: gradio
-sdk_version: 5.34.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,612 @@
+import gradio as gr
+import os
+import random
+import httpx
+import asyncio
+from dataclasses import dataclass, field
+from typing import Any
+from dotenv import load_dotenv
+
+# 加载.env文件
+load_dotenv()
+
+# 常量定义
+HTTP_STATUS_CENSORED = 451
+HTTP_STATUS_OK = 200
+MAX_SEED = 2147483647
+MAX_IMAGE_SIZE = 2048
+MIN_IMAGE_SIZE = 256
+
+# 调试模式
+DEBUG_MODE = os.environ.get("DEBUG_MODE", "false").lower() == "true"
+
+# 模型配置映射
+MODEL_CONFIGS = {
+    "base": "results_cosine_2e-4_bs64_infallssssuum/checkpoint-e4_s82000/consolidated.00-of-01.pth",
+    "aesthetics_fixed": "results_cosine_2e-4_bs64_infallssssuumnnnnaaa/checkpoint-e54_s43058/consolidated.00-of-01.pth", 
+    "ep3": "results_cosine_2e-4_bs64_infallssssuumnnnn/checkpoint-e3_s63858/consolidated.00-of-01.pth",
+    "ep3latest": "autodl-fs/lumina_hf/results_cosine_2e-4_bs64_infallssssuumnnnn/checkpoint-e3_s83000/consolidated.00-of-01.pth"
+}
+
+def validate_dimensions(width: int, height: int) -> tuple[int, int]:
+    """验证并调整图片尺寸"""
+    # 确保尺寸是32的倍数
+    width = max(MIN_IMAGE_SIZE, min(width, MAX_IMAGE_SIZE))
+    height = max(MIN_IMAGE_SIZE, min(height, MAX_IMAGE_SIZE))
+    width = (width // 32) * 32
+    height = (height // 32) * 32
+    return width, height
+
+@dataclass
+class LuminaConfig:
+    """Lumina模型配置"""
+    model_name: str | None = None
+    cfg: float | None = None
+    step: int | None = None
+
+@dataclass
+class ImageGenerationConfig:
+    """图像生成配置"""
+    prompts: list[dict[str, Any]] = field(default_factory=list)
+    width: int = 1024
+    height: int = 1024
+    seed: int | None = None
+    use_polish: bool = False
+    is_lumina: bool = True
+    lumina_config: LuminaConfig = field(default_factory=LuminaConfig)
+
+class ImageClient:
+    """图像生成客户端"""
+    def __init__(self) -> None:
+        # 使用环境变量中的API_TOKEN
+        self.x_token = os.environ.get("API_TOKEN", "")
+        if not self.x_token:
+            raise ValueError("环境变量中未设置API_TOKEN")
+
+        # API端点
+        self.lumina_api_url = "https://ops.api.talesofai.cn/v3/make_image"
+        self.lumina_task_status_url = "https://ops.api.talesofai.cn/v1/artifact/task/{task_uuid}"
+
+        # 轮询配置（增加超时时间以应对服务器负载）
+        self.max_polling_attempts = 100  # 增加到100次
+        self.polling_interval = 3.0      # 保持3秒间隔
+        # 总超时时间：100 × 3.0 = 300秒 = 5分钟
+
+        # 默认请求头
+        self.default_headers = {
+            "Content-Type": "application/json",
+            "x-platform": "nieta-app/web",
+            "X-Token": self.x_token,
+        }
+
+    def _prepare_prompt_data(self, prompt: str, negative_prompt: str = "") -> list[dict[str, Any]]:
+        """准备提示词数据"""
+        prompts = [
+            {
+                "type": "freetext",
+                "value": prompt,
+                "weight": 1.0
+            }
+        ]
+        
+        if negative_prompt:
+            prompts.append({
+                "type": "freetext",
+                "value": negative_prompt,
+                "weight": -1.0
+            })
+
+        # 添加Lumina元素
+        prompts.append({
+            "type": "elementum",
+            "value": "b5edccfe-46a2-4a14-a8ff-f4d430343805",
+            "uuid": "b5edccfe-46a2-4a14-a8ff-f4d430343805",
+            "weight": 1.0,
+            "name": "lumina1",
+            "img_url": "https://oss.talesofai.cn/picture_s/1y7f53e6itfn_0.jpeg",
+            "domain": "",
+            "parent": "",
+            "label": None,
+            "sort_index": 0,
+            "status": "IN_USE",
+            "polymorphi_values": {},
+            "sub_type": None,
+        })
+
+        return prompts
+
+    def _build_payload(self, config: ImageGenerationConfig) -> dict[str, Any]:
+        """构建API请求载荷"""
+        payload = {
+            "storyId": "",
+            "jobType": "universal",
+            "width": config.width,
+            "height": config.height,
+            "rawPrompt": config.prompts,
+            "seed": config.seed,
+            "meta": {"entrance": "PICTURE,PURE"},
+            "context_model_series": None,
+            "negative_freetext": "",
+            "advanced_translator": config.use_polish,
+        }
+
+        if config.is_lumina:
+            client_args = {}
+            if config.lumina_config.model_name:
+                client_args["ckpt_name"] = config.lumina_config.model_name
+            if config.lumina_config.cfg is not None:
+                client_args["cfg"] = str(config.lumina_config.cfg)
+            if config.lumina_config.step is not None:
+                client_args["steps"] = str(config.lumina_config.step)
+
+            if client_args:
+                payload["client_args"] = client_args
+
+        return payload
+
+    async def _poll_task_status(self, task_uuid: str) -> dict[str, Any]:
+        """轮询任务状态"""
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            for _ in range(self.max_polling_attempts):
+                response = await client.get(
+                    self.lumina_task_status_url.format(task_uuid=task_uuid),
+                    headers=self.default_headers
+                )
+                
+                if response.status_code != HTTP_STATUS_OK:
+                    return {
+                        "success": False,
+                        "error": f"获取任务状态失败: {response.status_code} - {response.text}"
+                    }
+
+                # 解析JSON响应
+                try:
+                    result = response.json()
+                except Exception as e:
+                    return {
+                        "success": False,
+                        "error": f"任务状态响应解析失败: {response.text[:500]}"
+                    }
+                
+                # 使用正确的字段名（根据model_studio的实现）
+                task_status = result.get("task_status")
+                
+                if task_status == "SUCCESS":
+                    # 从artifacts数组中获取图片URL
+                    artifacts = result.get("artifacts", [])
+                    if artifacts and len(artifacts) > 0:
+                        image_url = artifacts[0].get("url")
+                        if image_url:
+                            return {
+                                "success": True,
+                                "image_url": image_url
+                            }
+                    return {
+                        "success": False,
+                        "error": "无法从结果中提取图像URL"
+                    }
+                elif task_status == "FAILURE":
+                    return {
+                        "success": False,
+                        "error": result.get("error", "任务执行失败")
+                    }
+                elif task_status == "ILLEGAL_IMAGE":
+                    return {
+                        "success": False,
+                        "error": "图片不合规"
+                    }
+                elif task_status == "TIMEOUT":
+                    return {
+                        "success": False,
+                        "error": "任务超时"
+                    }
+
+                await asyncio.sleep(self.polling_interval)
+
+        return {
+            "success": False,
+            "error": "⏳ 生图任务超时（5分钟），服务器可能正在处理大量请求，请稍后重试"
+        }
+
+    async def generate_image(self, prompt: str, negative_prompt: str, seed: int, width: int, height: int, cfg: float, steps: int, model_name: str = "base") -> tuple[str | None, str | None]:
+        """生成图片"""
+        try:
+            # 获取模型路径
+            model_path = MODEL_CONFIGS.get(model_name, MODEL_CONFIGS["base"])
+            
+            # 准备配置
+            config = ImageGenerationConfig(
+                prompts=self._prepare_prompt_data(prompt, negative_prompt),
+                width=width,
+                height=height,
+                seed=seed,
+                is_lumina=True,
+                lumina_config=LuminaConfig(
+                    model_name=model_path,
+                    cfg=cfg,
+                    step=steps
+                )
+            )
+
+            # 发送生成请求
+            async with httpx.AsyncClient(timeout=300.0) as client:
+                payload = self._build_payload(config)
+                if DEBUG_MODE:
+                    print(f"DEBUG: 发送API请求到 {self.lumina_api_url}")
+                    print(f"DEBUG: 请求载荷: {payload}")
+                
+                response = await client.post(
+                    self.lumina_api_url,
+                    json=payload,
+                    headers=self.default_headers
+                )
+                
+                if DEBUG_MODE:
+                    print(f"DEBUG: API响应状态码: {response.status_code}")
+                    print(f"DEBUG: API响应内容: {response.text[:1000]}")
+
+                if response.status_code == HTTP_STATUS_CENSORED:
+                    return None, "内容不合规"
+                
+                # 处理并发限制错误
+                if response.status_code == 433:
+                    return None, "⏳ 服务器正忙，同时生成的图片数量已达上限，请稍后重试"
+                
+                if response.status_code != HTTP_STATUS_OK:
+                    return None, f"API请求失败: {response.status_code} - {response.text}"
+
+                # API直接返回UUID字符串（根据model_studio的实现）
+                content = response.text.strip()
+                task_uuid = content.replace('"', "")
+                
+                if DEBUG_MODE:
+                    print(f"DEBUG: API返回UUID: {task_uuid}")
+                
+                if not task_uuid:
+                    return None, f"未获取到任务ID，API响应: {response.text}"
+
+                # 轮询任务状态
+                result = await self._poll_task_status(task_uuid)
+                if result["success"]:
+                    return result["image_url"], None
+                else:
+                    return None, result["error"]
+
+        except Exception as e:
+            return None, f"生成图片时发生错误: {str(e)}"
+
+# 创建图片生成客户端实例
+image_client = ImageClient()
+
+# 示例提示词
+examples = [
+    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+    "An astronaut riding a green horse",
+    "A delicious ceviche cheesecake slice",
+]
+
+css = """
+.main-container {
+    max-width: 1400px !important;
+    margin: 0 auto !important;
+    padding: 20px !important;
+}
+
+.left-panel {
+    background: linear-gradient(145deg, #f8f9fa, #e9ecef) !important;
+    border-radius: 16px !important;
+    padding: 24px !important;
+    box-shadow: 0 8px 32px rgba(0,0,0,0.1) !important;
+    border: 1px solid rgba(255,255,255,0.2) !important;
+}
+
+.right-panel {
+    background: linear-gradient(145deg, #ffffff, #f8f9fa) !important;
+    border-radius: 16px !important;
+    padding: 24px !important;
+    box-shadow: 0 8px 32px rgba(0,0,0,0.1) !important;
+    border: 1px solid rgba(255,255,255,0.2) !important;
+    display: flex !important;
+    flex-direction: column !important;
+    align-items: center !important;
+    justify-content: flex-start !important;
+    min-height: 600px !important;
+}
+
+#main-prompt textarea {
+    min-height: 180px !important;
+    font-size: 15px !important;
+    line-height: 1.6 !important;
+    padding: 16px !important;
+    border-radius: 12px !important;
+    border: 2px solid #e9ecef !important;
+    transition: all 0.3s ease !important;
+    background: white !important;
+}
+
+#main-prompt textarea:focus {
+    border-color: #4f46e5 !important;
+    box-shadow: 0 0 0 3px rgba(79, 70, 229, 0.1) !important;
+}
+
+.run-button {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    border: none !important;
+    border-radius: 12px !important;
+    padding: 12px 32px !important;
+    font-weight: 600 !important;
+    font-size: 16px !important;
+    color: white !important;
+    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.4) !important;
+    transition: all 0.3s ease !important;
+}
+
+.run-button:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 6px 20px rgba(102, 126, 234, 0.6) !important;
+}
+
+.settings-section {
+    background: white !important;
+    border-radius: 12px !important;
+    padding: 16px !important;
+    margin-top: 12px !important;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.05) !important;
+    border: 1px solid #e9ecef !important;
+}
+
+.settings-title {
+    font-size: 18px !important;
+    font-weight: 600 !important;
+    color: #374151 !important;
+    margin-bottom: 12px !important;
+    padding-bottom: 6px !important;
+    border-bottom: 2px solid #e9ecef !important;
+}
+
+.right-panel .settings-title {
+    margin-bottom: 8px !important;
+    padding-bottom: 4px !important;
+    font-size: 16px !important;
+}
+
+.right-panel .block {
+    min-height: unset !important;
+    height: auto !important;
+    flex: none !important;
+}
+
+.right-panel .html-container {
+    padding: 0 !important;
+    margin: 0 !important;
+}
+
+.slider-container .wrap {
+    background: #f8f9fa !important;
+    border-radius: 8px !important;
+    padding: 6px !important;
+    margin: 2px 0 !important;
+}
+
+.settings-section .block {
+    margin: 4px 0 !important;
+}
+
+.settings-section .row {
+    margin: 6px 0 !important;
+}
+
+.settings-section .form {
+    gap: 4px !important;
+}
+
+.settings-section .html-container {
+    padding: 0 !important;
+    margin: 8px 0 4px 0 !important;
+}
+
+.result-image {
+    border-radius: 16px !important;
+    box-shadow: 0 8px 32px rgba(0,0,0,0.15) !important;
+    max-width: 100% !important;
+    height: auto !important;
+    min-height: 400px !important;
+    width: 100% !important;
+}
+
+.result-image img {
+    border-radius: 16px !important;
+    object-fit: contain !important;
+    max-width: 100% !important;
+    max-height: 600px !important;
+    width: auto !important;
+    height: auto !important;
+}
+
+.examples-container {
+    margin-top: 20px !important;
+}
+
+.title-header {
+    text-align: center !important;
+    margin-bottom: 30px !important;
+    padding: 20px !important;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+    color: white !important;
+    border-radius: 16px !important;
+    box-shadow: 0 4px 15px rgba(102, 126, 234, 0.3) !important;
+}
+
+.title-header h1 {
+    font-size: 28px !important;
+    font-weight: 700 !important;
+    margin: 0 !important;
+    text-shadow: 0 2px 4px rgba(0,0,0,0.1) !important;
+}
+"""
+
+async def infer(
+    prompt,
+    seed,
+    randomize_seed,
+    width,
+    height,
+    cfg,
+    steps,
+    model_name,
+    progress=gr.Progress(track_tqdm=True),
+):
+    if not prompt.strip():
+        raise gr.Error("提示词���能为空")
+
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+
+    # 验证并调整尺寸
+    width, height = validate_dimensions(width, height)
+
+    # 验证其他参数
+    if not 1.0 <= cfg <= 20.0:
+        raise gr.Error("CFG Scale 必须在 1.0 到 20.0 之间")
+    if not 1 <= steps <= 50:
+        raise gr.Error("Steps 必须在 1 到 50 之间")
+
+    image_url, error = await image_client.generate_image(
+        prompt=prompt,
+        negative_prompt="",
+        seed=seed,
+        width=width,
+        height=height,
+        cfg=cfg,
+        steps=steps,
+        model_name=model_name
+    )
+
+    if error:
+        raise gr.Error(error)
+
+    return image_url, seed
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_classes=["main-container"]):
+        # 标题区域
+        with gr.Row(elem_classes=["title-header"]):
+            gr.HTML("<h1>🎨 Lumina Text-to-Image Playground</h1>")
+        
+        # 主体左右布局
+        with gr.Row(equal_height=True):
+            # 左侧参数设置面板
+            with gr.Column(scale=1, elem_classes=["left-panel"]):
+                gr.HTML("<div class='settings-title'>✨ Generation Settings</div>")
+                
+                # 主要提示词输入
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=True,
+                    max_lines=10,
+                    lines=8,
+                    placeholder="Describe what you want to generate in detail...",
+                    elem_id="main-prompt",
+                )
+                
+                run_button = gr.Button("🚀 Generate Image", elem_classes=["run-button"], variant="primary")
+                
+                # 参数设置区域
+                with gr.Column(elem_classes=["settings-section"]):
+                    gr.HTML("<div class='settings-title'>🎛️ Parameters</div>")
+                    
+                    # 种子设置
+                    with gr.Row():
+                        seed = gr.Slider(
+                            label="Seed",
+                            minimum=0,
+                            maximum=MAX_SEED,
+                            step=1,
+                            value=0,
+                            elem_classes=["slider-container"]
+                        )
+                        randomize_seed = gr.Checkbox(label="Random Seed", value=True)
+                    
+                    # 尺寸设置
+                    gr.HTML("<div style='margin: 16px 0 8px 0; font-weight: 600; color: #6B7280;'>📐 Image Dimensions</div>")
+                    with gr.Row():
+                        width = gr.Slider(
+                            label="Width",
+                            minimum=256,
+                            maximum=MAX_IMAGE_SIZE,
+                            step=32,
+                            value=1024,
+                            elem_classes=["slider-container"]
+                        )
+                        height = gr.Slider(
+                            label="Height",
+                            minimum=256,
+                            maximum=MAX_IMAGE_SIZE,
+                            step=32,
+                            value=1024,
+                            elem_classes=["slider-container"]
+                        )
+                    
+                    # 生成参数
+                    gr.HTML("<div style='margin: 16px 0 8px 0; font-weight: 600; color: #6B7280;'>⚙️ Generation Parameters</div>")
+                    with gr.Row():
+                        cfg = gr.Slider(
+                            label="CFG Scale",
+                            minimum=1.0,
+                            maximum=20.0,
+                            step=0.1,
+                            value=5.5,
+                            elem_classes=["slider-container"]
+                        )
+                        steps = gr.Slider(
+                            label="Steps",
+                            minimum=1,
+                            maximum=50,
+                            step=1,
+                            value=30,
+                            elem_classes=["slider-container"]
+                        )
+                    
+                    # 模型选择
+                    model_name = gr.Dropdown(
+                        label="🤖 Model Selection",
+                        choices=list(MODEL_CONFIGS.keys()),
+                        value="base"
+                    )
+                
+                # 示例提示词
+                with gr.Column(elem_classes=["examples-container"]):
+                    gr.HTML("<div class='settings-title'>💡 Example Prompts</div>")
+                    gr.Examples(examples=examples, inputs=[prompt])
+            
+            # 右侧图像显示面板
+            with gr.Column(scale=1, elem_classes=["right-panel"]):
+                gr.HTML("<div class='settings-title'>🖼️ Generated Image</div>")
+                result = gr.Image(
+                    label="Result", 
+                    show_label=False, 
+                    elem_classes=["result-image"],
+                    height=600,
+                    container=True,
+                    show_download_button=True,
+                    show_share_button=False
+                )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[
+            prompt,
+            seed,
+            randomize_seed,
+            width,
+            height,
+            cfg,
+            steps,
+            model_name,
+        ],
+        outputs=[result, seed],
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=4.0.0
+httpx>=0.24.0
+python-dotenv>=1.0.0