3D 打板部署

fix: 删除计数中间件

.gitea/workflows/develop_build_commit.yaml

@@ -1,19 +1,23 @@
-name: 手动 AiDA python develop 分支构建部署
+name: git commit AiDA python develop 分支构建部署
 on:
   workflow_dispatch:
+  push:
+    branches:
+      - develop
 
 jobs:
   scheduled_deploy:
     runs-on: ubuntu-latest
+    if: "contains(github.event.head_commit.message, '[run build]')"
 
     env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Dev
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Dev
 
     steps:
       - name: 1.检出代码
         uses: actions/checkout@v4
         with:
-          ref: 'dev-ltx'
+          ref: 'develop'
 
       - name: 2.复制文件到服务器
         uses: appleboy/scp-action@v0.1.7
@@ -24,7 +28,7 @@ jobs:
           source: "."
           target: ${{ env.REMOTE_DEPLOY_PATH }}
       
-      - name: 3.重启docker-compose
+      - name: Restart Docker containers
         uses: appleboy/ssh-action@v0.1.10
         with:
           host: ${{ secrets.SERVER_HOST }}

.gitea/workflows/develop_build_manual.yaml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
 
     env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Dev
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Dev
 
     steps:
       - name: 1.检出代码
@@ -35,4 +35,6 @@ jobs:
             cd ${{ env.REMOTE_DEPLOY_PATH }}
             
             docker-compose down 2>&1
-            docker-compose up -d  2>&1
+            docker-compose up -d --build --remove-orphans 2>&1
+            
+            docker image prune -f 2>&1

.gitea/workflows/develop_build_scheduled.yaml

@@ -1,15 +1,15 @@
 name: 定时 AiDA python develop 分支构建部署
 on:
   # 使用 schedule 触发器，遵循标准的 Cron 格式 (分钟 小时-8 日期 月份 星期)
-  # schedule:
+  schedule:
-  #   - cron: '30 9 * * *'
+    - cron: '30 9 * * *'
 
 jobs:
   scheduled_deploy:
     runs-on: ubuntu-latest
 
     env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Dev
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Dev
 
     steps:
       - name: 1.检出代码

.gitea/workflows/prod_build_manual.yaml

@@ -1,40 +0,0 @@
-name: 定时 AiDA python prod 分支构建部署
-on:
-  workflow_dispatch:
-
-jobs:
-  scheduled_deploy:
-    runs-on: ubuntu-latest
-
-    env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Prod
-
-    steps:
-      - name: 1.检出代码
-        uses: actions/checkout@v4
-        with:
-          ref: 'master'
-
-      - name: 2.复制文件到服务器
-        uses: appleboy/scp-action@v0.1.7
-        with:
-          host: ${{ secrets.SERVER_HOST }}
-          username: ${{ secrets.SERVER_USER }}
-          password: ${{ secrets.SERVER_PASSWORD }}
-          source: "."
-          target: ${{ env.REMOTE_DEPLOY_PATH }}
-      
-      - name: Restart Docker containers
-        uses: appleboy/ssh-action@v0.1.10
-        with:
-          host: ${{ secrets.SERVER_HOST }}
-          username: ${{ secrets.SERVER_USER }}
-          password: ${{ secrets.SERVER_PASSWORD }}
-          script: |
-            # 进入项目目录
-            cd ${{ env.REMOTE_DEPLOY_PATH }}
-            
-            docker-compose down 2>&1
-            docker-compose up -d 2>&1
-            
-            docker image prune -f 2>&1

.gitea/workflows/prod_build_scheduled.yaml

@@ -1,42 +0,0 @@
-name: 定时 AiDA python prod 分支构建部署
-on:
-  # 使用 schedule 触发器，遵循标准的 Cron 格式 (分钟 小时-8 日期 月份 星期)
-  schedule:
-    - cron: '07 13 23 1 *'
-
-jobs:
-  scheduled_deploy:
-    runs-on: ubuntu-latest
-
-    env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Prod
-
-    steps:
-      - name: 1.检出代码
-        uses: actions/checkout@v4
-        with:
-          ref: 'master'
-
-      - name: 2.复制文件到服务器
-        uses: appleboy/scp-action@v0.1.7
-        with:
-          host: ${{ secrets.SERVER_HOST }}
-          username: ${{ secrets.SERVER_USER }}
-          password: ${{ secrets.SERVER_PASSWORD }}
-          source: "."
-          target: ${{ env.REMOTE_DEPLOY_PATH }}
-      
-      - name: Restart Docker containers
-        uses: appleboy/ssh-action@v0.1.10
-        with:
-          host: ${{ secrets.SERVER_HOST }}
-          username: ${{ secrets.SERVER_USER }}
-          password: ${{ secrets.SERVER_PASSWORD }}
-          script: |
-            # 进入项目目录
-            cd ${{ env.REMOTE_DEPLOY_PATH }}
-            
-            docker-compose down 2>&1
-            docker-compose up -d 2>&1
-            
-            docker image prune -f 2>&1

app/api/api_route.py

@@ -11,6 +11,7 @@ from app.api import api_precompute
 from app.api import api_prompt_generation
 from app.api import api_recommendation
 from app.api import api_test
+from app.api import api_sketch_to_garment
 
 router = APIRouter()
 
@@ -26,6 +27,7 @@ router.include_router(api_precompute.router, tags=['api_precompute'], prefix="/a
 router.include_router(api_mannequins_edit.router, tags=['api_mannequins_edit'], prefix="/api")
 router.include_router(api_pose_transform.router, tags=['api_pose_transform'], prefix="/api")
 router.include_router(api_clothing_seg.router, tags=['api_clothing_seg'], prefix="/api")
+router.include_router(api_sketch_to_garment.router, tags=['sketch_to_garment'], prefix="/api")
 
 """停用"""
 # from app.api import api_chat_robot

app/api/api_sketch_to_garment.py

@@ -0,0 +1,104 @@
+import json
+import logging
+
+from fastapi import APIRouter, HTTPException
+
+from app.schemas.response_template import ResponseModel
+from app.schemas.sketch_to_garment_schemas import SketchToGarmentModel
+from app.service.sketch2garment.server import submit_sketch_to_garment_task
+
+logger = logging.getLogger()
+router = APIRouter()
+
+
+@router.post("/sketch_to_garment")
+def sketch_to_garment_api(request_item: SketchToGarmentModel):
+    """
+        ### 接口说明:
+        将图片转换为3D模型（异步处理）。接口接收请求后立即返回任务ID，后台通过 Celery 处理，处理完成后结果会通过 RabbitMQ 发送。
+
+        ### 参数说明:
+        - **input_image_path**: 输入图片路径
+        - **bucket_name**: bucket name
+        - **user_id**: 用户id
+        - **callback_url**: 回调url
+        - **task_id**: 任务id
+        - **model**: 转换模式 文本和图片 ,默认只有图片
+
+        ### 请求体示例:
+        **单张图片模式:**
+        ```json
+        {
+          "input_image_path": "test/53d38bd5-f77b-4034-ada2-45f1e2ebe00c.png",
+          "bucket_name": "test",
+          "user_id": "string-456",
+          "callback_url": "http://18.167.251.121:10015/api/image/webhook/img-to-3d",
+          "task_id": "string12",
+          "model": "picture"
+        }
+        ```
+
+
+        ### 输出示例:
+
+        ```json
+        {
+          "code": 200,
+          "msg": "OK!",
+          "data": {
+            "state": "success",
+            "task_id": "string12",
+            "message": "任务已成功提交，正在后台处理..."
+          }
+        }
+        ```
+        ### 错误输出
+        参考文档:    https://platform.tripo3d.ai/docs/error-handling
+        ```json
+        {
+            "code": 500,
+            "message": "You don’t have enough credit to create this task",
+            "data": {
+                "status": "fail",
+                "task_id": "123",
+                "message": "You don’t have enough credit to create this task",
+                "error": str(e)
+            }
+        }
+        ```
+
+        回调请求参数例子:
+        ```json
+        {
+            "task_id": "string12",
+            "status": "success",
+            "result": {
+                "pattern": "test/string-456/pattern_making/now_string-456_pattern.png",
+                "texture": "test/string-456/pattern_making/now_string-456_texture.png",
+                "glb": "test/string-456/pattern_making/now_string-456_sim.glb",
+                "texture_fabric": "test/string-456/pattern_making/now_string-456_texture_fabric.png"
+            }
+        }
+        ```
+        """
+    try:
+        logger.info(f"sketch_to_garment request item is : @@@@@@:{json.dumps(request_item.model_dump(), indent=4)}")
+        result = submit_sketch_to_garment_task(
+            task_id=request_item.task_id,
+            callback_url=request_item.callback_url,
+            bucket_name=request_item.bucket_name,
+            input_image_path=request_item.input_image_path,
+            user_id=request_item.user_id,
+            model=request_item.model
+        )
+        result = {
+            "state": "success",
+            "task_id": request_item.task_id,
+            "message": "任务已成功提交，正在后台处理...",
+        }
+        state_code = 200
+        return ResponseModel(data=result, code=state_code)
+
+    except Exception as e:
+        logger.warning(f"super_resolution Run Exception @@@@@@:{e}")
+        raise HTTPException(status_code=404, detail=str(e))

app/core/config.py

@@ -1,5 +1,21 @@
+import logging
+from typing import Dict, Any
+
+import yaml
 from pydantic import Field
 from pydantic_settings import BaseSettings, SettingsConfigDict
+from v2.nacos import ClientConfigBuilder, GRPCConfig, NacosConfigService, ConfigParam, NacosNamingService, RegisterInstanceParam, DeregisterInstanceParam
+
+logger = logging.getLogger(__name__)
+
+# ====================== Nacos 配置 ======================
+NACOS_SERVER_ADDRESSES = "18.167.251.121:28848"
+NACOS_NAMESPACE = "zcr"
+NACOS_USERNAME = "nacos"
+NACOS_PASSWORD = "Aidlab123123!"
+NACOS_GROUP = "LOCAL"
+NACOS_DATA_ID = "aida.python"
+SERVICE_NAME = "fastapi-service"  # ←←← 必须修改！建议格式：项目名-环境，例如 ai-image-service-dev
 
 
 class Settings(BaseSettings):
@@ -36,7 +52,7 @@ class Settings(BaseSettings):
 
     # --- mysql 配置信息 ---
     MYSQL_HOST: str = Field(default='', description="")
-    MYSQL_PORT: int = Field(default='', description="")
+    MYSQL_PORT: int = Field(default=3306, description="")
     MYSQL_USER: str = Field(default='', description="")
     MYSQL_PASSWORD: str = Field(default='', description="")
     MYSQL_DB: str = Field(default='', description="")
@@ -71,6 +87,9 @@ class Settings(BaseSettings):
     A6000_SERVICE_HOST: str = Field(default='', description="")
     B_4_X_4090_SERVICE_HOST: str = Field(default='', description="")
 
+    # --- sketch to garment 模型url ---
+    SKETCH_TO_GARMENT_URL: str = Field(default='', description="")
+
     # --- 其他配置信息 以下均为Docker容器内配置---
     LOGS_PATH: str = Field(default="/logs/", description="")
     CATEGORY_PATH: str = Field(default="/app/service/attribute/config/descriptor/category/category_dis.csv", description="")

app/main.py

@@ -1,5 +1,8 @@
 # 1. 这里的顺序至关重要！必须在最顶端
 import sys
+from contextlib import asynccontextmanager
+
+# from app.core.nacos_config import load_nacos_config, register_server, deregister_server
 
 try:
     import asyncore
@@ -30,8 +33,21 @@ logger = logging.getLogger(__name__)
 load_dotenv()
 
 
+# @asynccontextmanager
+# async def lifespan(app: FastAPI):
+#     try:
+#         load_nacos_config()
+#         register_server()
+#
+#         yield
+#     finally:
+#         deregister_server()
+#         logger.info("lifespan down")
+
+
 def get_application() -> FastAPI:
     application = FastAPI(
+        # lifespan=lifespan,
         docs_url="/docs",
         redoc_url='/re-docs',
         openapi_url=f"/openapi.json",
@@ -64,5 +80,11 @@ async def http_exception_handler(exc: HTTPException):
     )
 
 
+@app.get("/health", operation_id="health")
+async def health():
+    logger.info("health check")
+    return {"ok": True, "env": settings.APP_ENV}
+
+
 if __name__ == '__main__':
     uvicorn.run(app, host="0.0.0.0", port=settings.PORT)

app/schemas/design.py

@@ -8,9 +8,9 @@ class SAMRequestModel(BaseModel):
     object_name: str = Field(..., description="minio object name ")
     image_path: str = Field(..., description="图片路径，必填字段")
     type: str = Field(..., description="推理类型，必填字段")
-    points: Optional[List[List[float]]] = None
+    points: Optional[List[List[float]]] | None = None
-    labels: Optional[List[int]] = None
+    labels: Optional[List[int]] | None = None
-    box: Optional[List[int]] = None
+    box: Optional[List[int]] | None = None
 
 
 class DesignModel(BaseModel):

app/schemas/generate_image.py

@@ -35,6 +35,13 @@ class GenerateSingleLogoImageModel(BaseModel):
     seed: str
 
 
+class GenerateSloganImageModel(BaseModel):
+    num_point: int
+    tasks_id: str
+    prompt: str
+    image_url: str
+
+
 class GenerateProductImageModel(BaseModel):
     tasks_id: str
     prompt: str
@@ -43,6 +50,13 @@ class GenerateProductImageModel(BaseModel):
     product_type: str
 
 
+class Flux2ToProductImgModel(BaseModel):
+    tasks_id: str
+    prompt: str
+    image_path: str
+    infer_step: int | None = None
+
+
 class GenerateRelightImageModel(BaseModel):
     tasks_id: str
     prompt: str

app/schemas/sketch_to_garment_schemas.py

@@ -0,0 +1,12 @@
+from typing import List
+
+from pydantic import BaseModel, Field
+
+
+class SketchToGarmentModel(BaseModel):
+    input_image_path: str = Field(..., description="输入图片路径列表")
+    bucket_name: str = Field(..., description="输入图片路径列表")
+    user_id: str = Field(..., description="用户id")
+    callback_url: str  # 必填，客户端提供的回调地址
+    task_id: str = Field()
+    model: str = Field(default="single", description="模型类型: single 或 multi")

app/service/design_fast/pipeline/no_seg_print_painting.py

@@ -27,7 +27,7 @@ class NoSegPrintPainting:
             # 获取平铺 + 旋转 的overall print
             painting_dict = self.painting_collection(painting_dict, overall_print)
             result['no_seg_sketch_overall'] = result['no_seg_sketch_print'] = self.printpaint(result, painting_dict, print_=True)
-            result['pattern_image'] = result['no_seg_sketch_overall']
+            # result['pattern_image'] = result['no_seg_sketch_overall']
 
         if single_print:
             print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
@@ -166,7 +166,8 @@ class NoSegPrintPainting:
         dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
         dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
         gap = print_dict.get('gap', [[0, 0]])[0]
-        painting_dict['tile_print'] = tile_image(pattern=print_['image'],
+        painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
+                                                                                  mask=print_['mask'],
                                                                                   dim=dim_pattern,
                                                                                   gap_x=gap[0],
                                                                                   gap_y=gap[1],
@@ -174,7 +175,8 @@ class NoSegPrintPainting:
                                                                                   canvas_w=painting_dict['dim_image_w'],
                                                                                   location=painting_dict['location'],
                                                                                   angle=int(print_.get('print_angle_list', [0])[0]))
-        painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
+        # painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
+        # painting_dict['mask_inv_print'] = self.get_mask_inv(painting_dict['tile_print'])
         return painting_dict
 
     def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
@@ -255,10 +257,15 @@ class NoSegPrintPainting:
         image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
         # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
         if image.mode == "RGBA":
+            mask_pil = image.split()[3]
             new_background = Image.new('RGB', image.size, (255, 255, 255))
             new_background.paste(image, mask=image.split()[3])
             image = new_background
+        else:
+            mask_pil = Image.new('L', image.size, 255)  # L=灰度图，255=纯白
         print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
+
         return print_dict
 
     def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
@@ -408,9 +415,12 @@ class NoSegPrintPainting:
         return cropped_img
 
 
-def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
+def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
     """
     按照指定的 X/Y 间距平铺印花，并支持旋转
+    【修改版】以被平铺图案的【中心】作为平铺基准点
+
+    :param location: [[center_y, center_x]]  → 第一个图案中心的坐标
     :param angle: 旋转角度 (度数, 逆时针)
     """
     # 1. 确保输入是 RGBA
@@ -422,35 +432,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
     rotated_p = rotate_image(resized_p, angle)
     p_h, p_w = rotated_p.shape[:2]
 
-    # 3. 创建透明单元格
+    # 3. 创建透明单元格（图案放在单元格中心）
-    cell_h, cell_w = p_h + gap_y, p_w + gap_x
+    cell_h = p_h + gap_y
+    cell_w = p_w + gap_x
+
     unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
-    unit_cell[:p_h, :p_w, :] = rotated_p
+
+    # 计算图案在单元格中的左上角位置（让图案居中）
+    start_y = (cell_h - p_h) // 2
+    start_x = (cell_w - p_w) // 2
+    unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
 
     # 4. 执行平铺
-    tiles_y = (canvas_h // cell_h) + 2
+    tiles_y = (canvas_h // cell_h) + 3  # 多加一点余量更安全
-    tiles_x = (canvas_w // cell_w) + 2
+    tiles_x = (canvas_w // cell_w) + 3
     full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
 
-    # 5. 裁剪平铺层
+    # 5. 计算偏移（关键修改：以中心为基准）
-    offset_x = int(location[0][1] % cell_w)
+    center_y, center_x = location[0][0], location[0][1]  # 第一个图案的中心位置
-    offset_y = int(location[0][0] % cell_h)
+
+    # 计算从哪个位置开始裁剪，才能让中心落在指定坐标
+    offset_y = int((center_y - (p_h // 2)) % cell_h)
+    offset_x = int((center_x - (p_w // 2)) % cell_w)
+
     tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
     offset_x: offset_x + canvas_w]
 
-    # 6. 创建纯白色背景并合成
+    # 6. 创建纯白色背景并合成（保持你原来的风格）
-    # 创建一个纯白色的 BGR 画布
     white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
 
-    # 分离平铺层的颜色通道和 Alpha 通道
     tiled_bgr = tiled_layer[:, :, :3]
-    alpha_mask = tiled_layer[:, :, 3] / 255.0  # 归一化到 0-1
+    alpha_mask = tiled_layer[:, :, 3] / 255.0
-    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])  # 扩展到 3 通道
+    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
 
-    # 执行 Alpha 混合：结果 = 平铺层 * alpha + 背景 * (1 - alpha)
+    tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
-    result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    return result
+    # ====================== 处理 Mask ======================
+    # Mask 也同样居中处理
+    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
+    rotated_mask = rotate_image(resized_mask, angle)  # 注意：mask也需要旋转
+
+    unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
+
+    full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
+    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
+    offset_x: offset_x + canvas_w]
+
+    return tiled_print, cv2.bitwise_not(tiled_mask)
 
 
 def rotate_image(image, angle):

app/service/design_fast/pipeline/print_painting.py

@@ -41,7 +41,7 @@ class PrintPainting:
         if overall_print['print_path_list']:
             overall_print['location'][0] = [x * y for x, y in zip(overall_print['location'][0], result['resize_scale'])]
             painting_dict = {'dim_image_h': result['pattern_image'].shape[0], 'dim_image_w': result['pattern_image'].shape[1]}
-            result['print_image'] = result['pattern_image']
+            result['print_image'] = result['pattern_image'].copy()
             # 获取平铺 + 旋转 的overall print
             painting_dict = self.painting_collection(painting_dict, overall_print)
             result['print_image'] = self.printpaint(result, painting_dict, print_=True)
@@ -229,7 +229,8 @@ class PrintPainting:
         dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
         dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
         gap = print_dict.get('gap', [[0, 0]])[0]
-        painting_dict['tile_print'] = tile_image(pattern=print_['image'],
+        painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
+                                                                                  mask=print_['mask'],
                                                                                   dim=dim_pattern,
                                                                                   gap_x=gap[0],
                                                                                   gap_y=gap[1],
@@ -237,7 +238,6 @@ class PrintPainting:
                                                                                   canvas_w=painting_dict['dim_image_w'],
                                                                                   location=painting_dict['location'],
                                                                                   angle=int(print_.get('print_angle_list', [0])[0]))
-        painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
         return painting_dict
 
     def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
@@ -318,10 +318,15 @@ class PrintPainting:
         image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
         # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
         if image.mode == "RGBA":
+            mask_pil = image.split()[3]
             new_background = Image.new('RGB', image.size, (255, 255, 255))
             new_background.paste(image, mask=image.split()[3])
             image = new_background
+        else:
+            mask_pil = Image.new('L', image.size, 255)  # L=灰度图，255=纯白
         print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
+
         return print_dict
 
     def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
@@ -471,9 +476,12 @@ class PrintPainting:
         return cropped_img
 
 
-def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
+def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
     """
     按照指定的 X/Y 间距平铺印花，并支持旋转
+    【修改版】以被平铺图案的【中心】作为平铺基准点
+
+    :param location: [[center_y, center_x]]  → 第一个图案中心的坐标
     :param angle: 旋转角度 (度数, 逆时针)
     """
     # 1. 确保输入是 RGBA
@@ -485,35 +493,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
     rotated_p = rotate_image(resized_p, angle)
     p_h, p_w = rotated_p.shape[:2]
 
-    # 3. 创建透明单元格
+    # 3. 创建透明单元格（图案放在单元格中心）
-    cell_h, cell_w = p_h + gap_y, p_w + gap_x
+    cell_h = p_h + gap_y
+    cell_w = p_w + gap_x
+
     unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
-    unit_cell[:p_h, :p_w, :] = rotated_p
+
+    # 计算图案在单元格中的左上角位置（让图案居中）
+    start_y = (cell_h - p_h) // 2
+    start_x = (cell_w - p_w) // 2
+    unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
 
     # 4. 执行平铺
-    tiles_y = (canvas_h // cell_h) + 2
+    tiles_y = (canvas_h // cell_h) + 3  # 多加一点余量更安全
-    tiles_x = (canvas_w // cell_w) + 2
+    tiles_x = (canvas_w // cell_w) + 3
     full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
 
-    # 5. 裁剪平铺层
+    # 5. 计算偏移（关键修改：以中心为基准）
-    offset_x = int(location[0][1] % cell_w)
+    center_y, center_x = location[0][0], location[0][1]  # 第一个图案的中心位置
-    offset_y = int(location[0][0] % cell_h)
+
+    # 计算从哪个位置开始裁剪，才能让中心落在指定坐标
+    offset_y = int((center_y - (p_h // 2)) % cell_h)
+    offset_x = int((center_x - (p_w // 2)) % cell_w)
+
     tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
     offset_x: offset_x + canvas_w]
 
-    # 6. 创建纯白色背景并合成
+    # 6. 创建纯白色背景并合成（保持你原来的风格）
-    # 创建一个纯白色的 BGR 画布
     white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
 
-    # 分离平铺层的颜色通道和 Alpha 通道
     tiled_bgr = tiled_layer[:, :, :3]
-    alpha_mask = tiled_layer[:, :, 3] / 255.0  # 归一化到 0-1
+    alpha_mask = tiled_layer[:, :, 3] / 255.0
-    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])  # 扩展到 3 通道
+    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
 
-    # 执行 Alpha 混合：结果 = 平铺层 * alpha + 背景 * (1 - alpha)
+    tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
-    result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    return result
+    # ====================== 处理 Mask ======================
+    # Mask 也同样居中处理
+    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
+    rotated_mask = rotate_image(resized_mask, angle)  # 注意：mask也需要旋转
+
+    unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
+
+    full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
+    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
+    offset_x: offset_x + canvas_w]
+
+    return tiled_print, cv2.bitwise_not(tiled_mask)
 
 
 def rotate_image(image, angle):

app/service/design_fast/utils/synthesis_item.py

@@ -342,82 +342,33 @@ def update_base_size_priority(layers):
 
 
 def transpose_rotate(layer, image):
-    """
+    # transpose[0]是左右 transpose[1]是上下
-    融合镜像（transpose）和旋转（rotate）逻辑，计算实际旋转角度后执行图像变换，
+    transpose = layer.get('transpose', [1, 1])  # 默认为1, 1代表不镜像
-    并调整粘贴位置以保持视觉中心一致
 
-    参数:
+    rotate = layer.get('rotate', 0)
-        layer: 包含transpose、rotate、adaptive_position等属性的字典
-        image: PIL Image对象，待处理的图像
-
-    返回:
-        tuple: (处理后的Image对象, 新的粘贴坐标(x, y))
-    """
-    # 获取镜像状态（transpose[0]=左右，transpose[1]=上下；1=正常，-1=镜像）
-    transpose = layer.get('transpose', [1, 1])
-    is_mirrored_x = transpose[0]  # 左右镜像状态
-    is_mirrored_y = transpose[1]  # 上下镜像状态
-
-    # 获取原始旋转角度和粘贴位置
-    original_rotate = layer.get('rotate', 0)
     paste_x, paste_y = layer['adaptive_position'][1], layer['adaptive_position'][0]
     original_w = image.width
     original_h = image.height
+    # transpose左右是1 上下是-1
+    if transpose[0] != 1:
+        # 左右
+        image = image.transpose(0)
 
-    # ------------------- 核心修改：计算实际旋转角度 -------------------
+    if transpose[1] != 1:
-    # 结合镜像状态，计算需要实际执行的旋转角度
+        # 上下
-    actual_rotate = calculate_actual_rotate(original_rotate, is_mirrored_x, is_mirrored_y)
+        image = image.transpose(1)
-    # ------------------- 执行镜像变换 -------------------
-    # 左右镜像（transpose[0] != 1 即-1，表示镜像）
-    if is_mirrored_x != 1:
-        image = image.transpose(0)  # 假设transpose(0)对应左右翻转（需匹配你的PIL版本）
 
-    # 上下镜像（transpose[1] != 1 即-1，表示镜像）
+    if rotate:
-    if is_mirrored_y != 1:
+        image = image.rotate(-rotate, expand=True)
-        image = image.transpose(1)  # 假设transpose(1)对应上下翻转
+        # 4. 计算粘贴位置以保持视觉中心一致
-
+        # 原本 (15, 36) 是 288*288 的左上角，我们计算其中心点
-    # ------------------- 执行旋转并调整粘贴位置 -------------------
-    if actual_rotate != 0:  # 只有实际旋转角度非0时才执行旋转
-        # 注意：原代码中是rotate(-rotate)，这里同步调整符号
-        image = image.rotate(-actual_rotate, expand=True)
-
-        # 计算粘贴位置以保持视觉中心一致
-        # 原位置的中心点
         target_center_x = paste_x + original_w // 2
         target_center_y = paste_y + original_h // 2
 
-        # 旋转后图像的新尺寸
+        # 获取旋转后图像的新尺寸
         new_w, new_h = image.size
 
-        # 新的左上角坐标（保证中心不变）
+        # 计算新的左上角坐标，使得旋转后的图像中心依然在原定的中心位置
         paste_x = target_center_x - new_w // 2
         paste_y = target_center_y - new_h // 2
-
     return image, (paste_x, paste_y)
-
-
-def calculate_actual_rotate(before_rotate, is_mirrored_x, is_mirrored_y):
-    """
-    根据X/Y轴镜像状态计算实际的旋转角度，并标准化到0-360度
-
-    参数:
-        before_rotate: 原始旋转角度（数值类型）
-        is_mirrored_x: X轴镜像状态，-1表示镜像，1表示正常
-        is_mirrored_y: Y轴镜像状态，-1表示镜像，1表示正常
-
-    返回:
-        float/int: 标准化后的实际旋转角度（0-360度）
-    """
-    actual_rotate = before_rotate
-
-    # 根据镜像状态调整旋转角度
-    if is_mirrored_x == -1 and is_mirrored_y == 1:
-        actual_rotate = -before_rotate
-    elif is_mirrored_x == 1 and is_mirrored_y == -1:
-        actual_rotate = -before_rotate
-    # elif is_mirrored_x == -1 and is_mirrored_y == -1:
-    #     actual_rotate = before_rotate + 180
-
-    # 角度标准化到0-360度
-    normalized_rotate = ((actual_rotate % 360) + 360) % 360
-    return normalized_rotate

app/service/prompt_generation/chatgpt_for_translation.py

@@ -104,7 +104,7 @@ def get_translation_from_llama3(text):
     # 创建请求的负载 translator是自定义的翻译模型
     payload = {
         "model": "AiDA-translator:latest",
-        "prompt": f"[{text}]",
+        "prompt": text,
         "stream": False
     }
     # 将负载转换为 JSON 格式
@@ -180,7 +180,7 @@ def get_prompt_from_image(image_path, text):
 
 def main():
     """Main function"""
-    text = get_translation_from_llama3("[火焰]")
+    text = get_translation_from_llama3("火焰")
     print(text)
 
 

app/service/sketch2garment/callback.py

@@ -0,0 +1,35 @@
+import logging
+
+import httpx
+
+logger = logging.getLogger("app")
+
+
+async def notify_callback(callback_url: str, task_id: str, status: str, result: dict, ):
+    """
+    调用客户端提供的回调接口
+    """
+    try:
+        payload = {
+            "task_id": task_id,
+            "status": status,
+            "result": result
+        }
+        logger.info(payload)
+        async with httpx.AsyncClient(timeout=30.0) as client:
+            resp = await client.post(
+                str(callback_url),
+                json=payload,
+                headers={"Content-Type": "application/json"}
+            )
+
+            if 200 <= resp.status_code < 300:
+                logger.info(f"回调成功 | task_id: {task_id} | status: {status} | url: {callback_url}")
+                return True
+            else:
+                logger.warning(f"回调返回非2xx状态码 | task_id: {task_id} | status: {resp.status_code} | url: {callback_url}")
+                return False
+
+    except Exception as e:
+        logger.error(f"回调失败 | task_id: {task_id} | url: {callback_url} | error: {e}", exc_info=True)
+        return False

app/service/sketch2garment/celery_app.py

@@ -0,0 +1,46 @@
+from celery import Celery
+from kombu import Queue, Exchange
+
+from app.core.config import settings
+
+celery_app = Celery(
+    "sketch_to_garment",
+    broker=f"redis://{settings.REDIS_HOST}:{settings.REDIS_PORT}/2",
+    backend=f"redis://{settings.REDIS_HOST}:{settings.REDIS_PORT}/{settings.REDIS_DB}",
+    include=["app.service.sketch2garment.tasks"]
+)
+print(f"redis://{settings.REDIS_HOST}:{settings.REDIS_PORT}/3")
+print(f"celery_app: {celery_app}")
+
+celery_app.conf.update(
+    task_serializer="json",
+    accept_content=["json"],
+    result_serializer="json",
+    timezone="Asia/Hong_Kong",
+    enable_utc=True,
+    task_track_started=True,
+    task_time_limit=300,  # 单个任务最长 5 分钟
+    task_soft_time_limit=280,
+    # 定义队列
+    task_queues=(
+        Queue("sketch_to_garment_queue",
+              exchange=Exchange("sketch_to_garment_exchange", type="direct"),
+              durable=True),
+
+    ),
+
+    task_routes={
+        'app.service.sketch2garment.tasks.sketch_to_garment':
+            {
+                'queue': 'sketch_to_garment_queue',
+                'exchange': 'sketch_to_garment_exchange',  # ← 修改这里
+            },
+    },
+    task_default_queue="sketch_to_garment_queue",
+
+    worker_concurrency=1,
+    worker_prefetch_multiplier=1,
+    worker_max_tasks_per_child=1,
+    task_acks_late=True,
+    task_reject_on_worker_lost=True,
+)

app/service/sketch2garment/server.py

@@ -0,0 +1,44 @@
+import logging
+
+from app.service.sketch2garment.tasks import sketch_to_garment
+
+logger = logging.getLogger(__name__)
+
+
+def submit_sketch_to_garment_task(model: str = "single", task_id: str = "", callback_url: str = "", bucket_name: str = "test", user_id: str = "123", input_image_path: str = ""):
+    """提交 img_to_3D 任务（带队列长度限制）"""
+    queue_name = "img_to_3d_queue"
+    max_queue_length = 10
+
+    try:
+        # current_length = get_queue_length(queue_name)
+
+        # if current_length >= max_queue_length:
+        #     return {
+        #         "state": "queue_full",
+        #         "message": "当前 3D 生成请求较多，请稍后重试。",
+        #         "queue_length": current_length,
+        #         "max_length": max_queue_length
+        #     }
+
+        # 提交任务
+        task = sketch_to_garment.apply_async(
+            args=(task_id, callback_url, bucket_name, input_image_path, user_id, model),
+            task_id=task_id,
+            queue="sketch_to_garment_queue")
+
+        # logger.info(f"img_to_3d_task 已提交 | task_id: {task_id} | 当前队列长度: {current_length}")
+
+        return {
+            "state": "success",
+            "task_id": task_id,
+            "message": "任务已成功提交，正在后台处理...",
+        }
+
+    except Exception as e:
+        logger.error(f"提交 img_to_3d_task 失败: {e}", exc_info=True)
+        return {
+            "state": "fail",
+            "message": "提交失败，请稍后重试。",
+            "error": str(e)
+        }

app/service/sketch2garment/tasks.py

@@ -0,0 +1,57 @@
+import asyncio
+import logging
+
+from app.core.config import settings
+from app.service.sketch2garment.callback import notify_callback
+import httpx
+
+from app.service.sketch2garment.celery_app import celery_app
+
+logger = logging.getLogger(__name__)
+
+
+@celery_app.task(bind=True, queue="sketch_to_garment_queue", max_retries=3, name='app.service.sketch2garment.tasks.sketch_to_garment')
+def sketch_to_garment(self, task_id: str, callback_url: str, bucket_name: str, input_image_path: str, user_id: str, category: str = None):
+    payload = {
+        "bucket_name": bucket_name,
+        "category": category or settings.DEFAULT_CATEGORY,
+        "input_image_path": input_image_path,
+        "user_id": user_id
+    }
+    logger.info(f"payload: {payload}")
+
+    try:
+        with httpx.Client(timeout=300.0) as client:  # 注意这里用 AsyncClient 配合 Celery
+            # 如果你的 LitServe 是同步 endpoint，也可以用 httpx.Client()
+            response = client.post(settings.SKETCH_TO_GARMENT_URL, json=payload)
+            if response.status_code == 200:
+                result = response.json()
+                result_json = {
+                    "pattern": result[1],
+                    "texture": result[2],
+                    "glb": result[3],
+                    "texture_fabric": result[4]
+                }
+                asyncio.run(
+                    notify_callback(callback_url=callback_url, task_id=task_id, result=result_json, status="success")
+                )
+            else:
+                asyncio.run(
+                    notify_callback(
+                        callback_url=callback_url,
+                        task_id=task_id,
+                        result={
+                            "status": "fail",
+                            "task_id": task_id,
+                            "message": "fail",
+                            "error": "fail"
+                        },
+                        status="fail")
+                )
+    except Exception as e:
+        return {
+            "status": "failed",
+            "task_id": task_id,
+            "input": payload,
+            "error": str(e)
+        }

docker-compose.yml

@@ -12,3 +12,9 @@ services:
       - ./seg_cache:/seg_cache
     ports:
       - "${SERVE_PORT}:80"
+    networks:
+      - aida_app_net
+networks:
+  aida_app_net:
+    external: true
+    name: aida_app_net

pyproject.toml

@@ -24,6 +24,7 @@ dependencies = [
     "loguru>=0.7.3",
     "minio>=7.2.20",
     "moviepy==1.0.3",
+    "nacos-sdk-python==2.0.1",
     "np>=1.0.2",
     "numpy<2",
     "ollama>=0.6.1",

uv.lock

@@ -62,6 +62,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/7c/91/513971861d845d28160ecb205ae2cfaf618b16918a9cd4e0b832b5360ce7/aio_pika-9.5.8-py3-none-any.whl", hash = "sha256:f4c6cb8a6c5176d00f39fd7431e9702e638449bc6e86d1769ad7548b2a506a8d", size = 54397, upload-time = "2025-11-12T10:37:08.374Z" },
 ]
 
+[[package]]
+name = "aiofiles"
+version = "25.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/41/c3/534eac40372d8ee36ef40df62ec129bee4fdb5ad9706e58a29be53b2c970/aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2", size = 46354, upload-time = "2025-10-09T20:51:04.358Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/bc/8a/340a1555ae33d7354dbca4faa54948d76d89a27ceef032c8c3bc661d003e/aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695", size = 14668, upload-time = "2025-10-09T20:51:03.174Z" },
+]
+
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
@@ -131,6 +140,154 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490, upload-time = "2025-07-03T22:54:42.156Z" },
 ]
 
+[[package]]
+name = "alibabacloud-credentials"
+version = "0.3.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-tea" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/fc/92/7cb0807d6d380fa09cbad6d4fe983781e657dcc16d60fc559d6575bf98be/alibabacloud_credentials-0.3.6.tar.gz", hash = "sha256:caa82cf258648dcbe1ca14aeba50ba21845567d6ac3cd48d318e0a445fff7f96", size = 18771, upload-time = "2024-10-28T03:40:03.806Z" }
+
+[[package]]
+name = "alibabacloud-darabonba-array"
+version = "0.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/50/be/1813d7553e11e20a1422ffaaead392cfa7239a855c7e67c6a6b5776cfa64/alibabacloud_darabonba_array-0.1.0.tar.gz", hash = "sha256:7f9a7c632518ff4f0cebb0d4e825a48c12e7cf0b9016ea25054dd73732e155aa", size = 2306, upload-time = "2022-11-01T06:32:47.928Z" }
+
+[[package]]
+name = "alibabacloud-darabonba-encode-util"
+version = "0.0.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/b6/d8/22543b2ade9aa68fef028a9f0c4154bfdb970926f918f63d7b85bae527a9/alibabacloud_darabonba_encode_util-0.0.2.tar.gz", hash = "sha256:f1c484f276d60450fa49b4b2987194e741fcb2f7faae7f287c0ae65abc85fd4d", size = 3990, upload-time = "2022-12-10T04:43:48.086Z" }
+
+[[package]]
+name = "alibabacloud-darabonba-map"
+version = "0.0.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d5/bc/f11d56adffffade9a0d33ccca155ce82ca950b97cdce27a75228715c4639/alibabacloud_darabonba_map-0.0.1.tar.gz", hash = "sha256:adb17384658a1a8f72418f1838d4b6a5fd2566bfd392a3ef06d9dbb0a595a23f", size = 2056, upload-time = "2021-12-04T03:41:20.369Z" }
+
+[[package]]
+name = "alibabacloud-darabonba-signature-util"
+version = "0.0.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "cryptography" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/13/09/2118a2df631eaa06a291013ea61f31e449ba7a3cc3d6061477a43420e93a/alibabacloud_darabonba_signature_util-0.0.4.tar.gz", hash = "sha256:71d79b2ae65957bcfbf699ced894fda782b32f9635f1616635533e5a90d5feb0", size = 4170, upload-time = "2022-12-10T04:44:42.979Z" }
+
+[[package]]
+name = "alibabacloud-darabonba-string"
+version = "0.0.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/f9/d4/3d22bd2ff88985f970a10f8cedf2ea326d11d4d95e244f7665dc83d26465/alibabacloud-darabonba-string-0.0.4.tar.gz", hash = "sha256:ec6614c0448dadcbc5e466485838a1f8cfdd911135bea739e20b14511270c6f7", size = 2852, upload-time = "2021-12-13T13:30:06.114Z" }
+
+[[package]]
+name = "alibabacloud-endpoint-util"
+version = "0.0.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/92/7d/8cc92a95c920e344835b005af6ea45a0db98763ad6ad19299d26892e6c8d/alibabacloud_endpoint_util-0.0.4.tar.gz", hash = "sha256:a593eb8ddd8168d5dc2216cd33111b144f9189fcd6e9ca20e48f358a739bbf90", size = 2813, upload-time = "2025-06-12T07:20:52.572Z" }
+
+[[package]]
+name = "alibabacloud-gateway-pop"
+version = "0.0.9"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-credentials" },
+    { name = "alibabacloud-darabonba-array" },
+    { name = "alibabacloud-darabonba-encode-util" },
+    { name = "alibabacloud-darabonba-map" },
+    { name = "alibabacloud-darabonba-signature-util" },
+    { name = "alibabacloud-darabonba-string" },
+    { name = "alibabacloud-endpoint-util" },
+    { name = "alibabacloud-gateway-spi" },
+    { name = "alibabacloud-openapi-util" },
+    { name = "alibabacloud-tea-util" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/18/7d/d521d803ee227499aa5a3044a0ab8bd4ba139a455d10c1a070e745d26b0c/alibabacloud_gateway_pop-0.0.9.tar.gz", hash = "sha256:50aec34abc47b3adc6e43da6fa036bbbd04477a0047435f3728129ede7641628", size = 5981, upload-time = "2025-07-23T07:06:06.717Z" }
+
+[[package]]
+name = "alibabacloud-gateway-spi"
+version = "0.0.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-credentials" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ab/98/d7111245f17935bf72ee9bea60bbbeff2bc42cdfe24d2544db52bc517e1a/alibabacloud_gateway_spi-0.0.3.tar.gz", hash = "sha256:10d1c53a3fc5f87915fbd6b4985b98338a776e9b44a0263f56643c5048223b8b", size = 4249, upload-time = "2025-02-23T16:29:54.222Z" }
+
+[[package]]
+name = "alibabacloud-kms20160120"
+version = "2.2.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-endpoint-util" },
+    { name = "alibabacloud-gateway-pop" },
+    { name = "alibabacloud-openapi-util" },
+    { name = "alibabacloud-tea-openapi" },
+    { name = "alibabacloud-tea-util" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/18/39/dfb1043f2995523507b03bb23e5db6291508eccbb4f78ea02930ff95f137/alibabacloud_kms20160120-2.2.3.tar.gz", hash = "sha256:fa7991185e92d85f9d224ead0bf82e5673fcfd022714e6c3cd2b1894b59555bf", size = 77350, upload-time = "2024-08-30T10:18:44.012Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/cc/04/0668cbc62f3d9239e86d3d97b3de40b92e66730a90fc4c58f0ee38a81399/alibabacloud_kms20160120-2.2.3-py3-none-any.whl", hash = "sha256:51d3d04c75ba93c574ff4e368e51097f180fc05922fbd6336d290ea8113da99e", size = 76701, upload-time = "2024-08-30T10:18:42.524Z" },
+]
+
+[[package]]
+name = "alibabacloud-openapi-util"
+version = "0.2.4"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-tea-util" },
+    { name = "cryptography" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f6/51/be5802851a4ed20ac2c6db50ac8354a6e431e93db6e714ca39b50983626f/alibabacloud_openapi_util-0.2.4.tar.gz", hash = "sha256:87022b9dcb7593a601f7a40ca698227ac3ccb776b58cb7b06b8dc7f510995c34", size = 7981, upload-time = "2026-01-15T08:05:03.947Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/08/46/9b217343648b366eb93447f5d93116e09a61956005794aed5ef95a2e9e2e/alibabacloud_openapi_util-0.2.4-py3-none-any.whl", hash = "sha256:a2474f230b5965ae9a8c286e0dc86132a887928d02d20b8182656cf6b1b6c5bd", size = 7661, upload-time = "2026-01-15T08:05:01.374Z" },
+]
+
+[[package]]
+name = "alibabacloud-tea"
+version = "0.4.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohttp" },
+    { name = "requests" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/9a/7d/b22cb9a0d4f396ee0f3f9d7f26b76b9ed93d4101add7867a2c87ed2534f5/alibabacloud-tea-0.4.3.tar.gz", hash = "sha256:ec8053d0aa8d43ebe1deb632d5c5404339b39ec9a18a0707d57765838418504a", size = 8785, upload-time = "2025-03-24T07:34:42.958Z" }
+
+[[package]]
+name = "alibabacloud-tea-openapi"
+version = "0.3.14"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-credentials" },
+    { name = "alibabacloud-gateway-spi" },
+    { name = "alibabacloud-openapi-util" },
+    { name = "alibabacloud-tea-util" },
+    { name = "alibabacloud-tea-xml" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ff/f5/c7823490a1574d1e3c27c9641aa395710e89d0c15c5a436c96e999e6e2fe/alibabacloud_tea_openapi-0.3.14.tar.gz", hash = "sha256:1e0a67ab3450cf09e26ccc0fb5b0622a6b58fdde25dc3ccb99b45e167c5db717", size = 12993, upload-time = "2025-04-15T12:20:03.363Z" }
+
+[[package]]
+name = "alibabacloud-tea-util"
+version = "0.3.14"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-tea" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e9/ee/ea90be94ad781a5055db29556744681fc71190ef444ae53adba45e1be5f3/alibabacloud_tea_util-0.3.14.tar.gz", hash = "sha256:708e7c9f64641a3c9e0e566365d2f23675f8d7c2a3e2971d9402ceede0408cdb", size = 7515, upload-time = "2025-11-19T06:01:08.504Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/72/9e/c394b4e2104766fb28a1e44e3ed36e4c7773b4d05c868e482be99d5635c9/alibabacloud_tea_util-0.3.14-py3-none-any.whl", hash = "sha256:10d3e5c340d8f7ec69dd27345eb2fc5a1dab07875742525edf07bbe86db93bfe", size = 6697, upload-time = "2025-11-19T06:01:07.355Z" },
+]
+
+[[package]]
+name = "alibabacloud-tea-xml"
+version = "0.0.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "alibabacloud-tea" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/32/eb/5e82e419c3061823f3feae9b5681588762929dc4da0176667297c2784c1a/alibabacloud_tea_xml-0.0.3.tar.gz", hash = "sha256:979cb51fadf43de77f41c69fc69c12529728919f849723eb0cd24eb7b048a90c", size = 3466, upload-time = "2025-07-01T08:04:55.144Z" }
+
 [[package]]
 name = "amqp"
 version = "5.3.1"
@@ -1746,6 +1903,26 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" },
 ]
 
+[[package]]
+name = "nacos-sdk-python"
+version = "2.0.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiofiles" },
+    { name = "aiohttp" },
+    { name = "alibabacloud-kms20160120" },
+    { name = "alibabacloud-tea-openapi" },
+    { name = "grpcio" },
+    { name = "protobuf" },
+    { name = "psutil" },
+    { name = "pycryptodome" },
+    { name = "pydantic" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/9d/e4/c9506551fe699e1f0bc194a9024cc8fb18c8d4ee4f004dfdd5861db07b2d/nacos-sdk-python-2.0.1.tar.gz", hash = "sha256:29fa1dd14f771824b65ae0edd208bb4d20737655ae8b809685194e2f6358c2a7", size = 68582, upload-time = "2025-01-13T14:37:22.981Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e6/14/269a08582090ac1d16ff2c491455a22d4a4c4f47337eb0b142957a93ea0a/nacos_sdk_python-2.0.1-py3-none-any.whl", hash = "sha256:623cfc4645adb44f21c8613d6c0e6f1c41a0110318ce0899d57942009b626044", size = 93265, upload-time = "2025-01-13T14:37:17.808Z" },
+]
+
 [[package]]
 name = "networkx"
 version = "3.6.1"
@@ -2307,6 +2484,22 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/7e/cc/7e77861000a0691aeea8f4566e5d3aa716f2b1dece4a24439437e41d3d25/protobuf-5.29.5-py3-none-any.whl", hash = "sha256:6cf42630262c59b2d8de33954443d94b746c952b01434fc58a417fdbd2e84bd5", size = 172823, upload-time = "2025-05-28T23:51:58.157Z" },
 ]
 
+[[package]]
+name = "psutil"
+version = "7.2.2"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/aa/c6/d1ddf4abb55e93cebc4f2ed8b5d6dbad109ecb8d63748dd2b20ab5e57ebe/psutil-7.2.2.tar.gz", hash = "sha256:0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372", size = 493740, upload-time = "2026-01-28T18:14:54.428Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ed0cace939114f62738d808fdcecd4c869222507e266e574799e9c0faa17d486", size = 129090, upload-time = "2026-01-28T18:15:22.168Z" },
+    { url = "https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:1a7b04c10f32cc88ab39cbf606e117fd74721c831c98a27dc04578deb0c16979", size = 129859, upload-time = "2026-01-28T18:15:23.795Z" },
+    { url = "https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9", size = 155560, upload-time = "2026-01-28T18:15:25.976Z" },
+    { url = "https://files.pythonhosted.org/packages/63/65/37648c0c158dc222aba51c089eb3bdfa238e621674dc42d48706e639204f/psutil-7.2.2-cp36-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b0726cecd84f9474419d67252add4ac0cd9811b04d61123054b9fb6f57df6e9e", size = 156997, upload-time = "2026-01-28T18:15:27.794Z" },
+    { url = "https://files.pythonhosted.org/packages/8e/13/125093eadae863ce03c6ffdbae9929430d116a246ef69866dad94da3bfbc/psutil-7.2.2-cp36-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:fd04ef36b4a6d599bbdb225dd1d3f51e00105f6d48a28f006da7f9822f2606d8", size = 148972, upload-time = "2026-01-28T18:15:29.342Z" },
+    { url = "https://files.pythonhosted.org/packages/04/78/0acd37ca84ce3ddffaa92ef0f571e073faa6d8ff1f0559ab1272188ea2be/psutil-7.2.2-cp36-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:b58fabe35e80b264a4e3bb23e6b96f9e45a3df7fb7eed419ac0e5947c61e47cc", size = 148266, upload-time = "2026-01-28T18:15:31.597Z" },
+    { url = "https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl", hash = "sha256:eb7e81434c8d223ec4a219b5fc1c47d0417b12be7ea866e24fb5ad6e84b3d988", size = 137737, upload-time = "2026-01-28T18:15:33.849Z" },
+    { url = "https://files.pythonhosted.org/packages/8c/c7/7bb2e321574b10df20cbde462a94e2b71d05f9bbda251ef27d104668306a/psutil-7.2.2-cp37-abi3-win_arm64.whl", hash = "sha256:8c233660f575a5a89e6d4cb65d9f938126312bca76d8fe087b947b3a1aaac9ee", size = 134617, upload-time = "2026-01-28T18:15:36.514Z" },
+]
+
 [[package]]
 name = "psycopg2-binary"
 version = "2.9.11"
@@ -3165,6 +3358,7 @@ dependencies = [
     { name = "loguru" },
     { name = "minio" },
     { name = "moviepy" },
+    { name = "nacos-sdk-python" },
     { name = "np" },
     { name = "numpy" },
     { name = "ollama" },
@@ -3216,6 +3410,7 @@ requires-dist = [
     { name = "loguru", specifier = ">=0.7.3" },
     { name = "minio", specifier = ">=7.2.20" },
     { name = "moviepy", specifier = "==1.0.3" },
+    { name = "nacos-sdk-python", specifier = "==2.0.1" },
     { name = "np", specifier = ">=1.0.2" },
     { name = "numpy", specifier = "<2" },
     { name = "ollama", specifier = ">=0.6.1" },