Feat/new

src/agentscope_bricks/components/__init__.py

@@ -76,6 +76,25 @@
 from agentscope_bricks.components.generations.qwen_image_edit_new import (
     QwenImageEditNew,
 )  # noqa
+from agentscope_bricks.components.generations.image_edit_wan26 import (
+    ImageEditWan26,
+)
+from agentscope_bricks.components.generations.image_generation_zimage import (
+    ZImageGeneration,
+)
+from agentscope_bricks.components.generations.async_image_out_painting import (
+    ImageOutPaintingSubmit,
+    ImageOutPaintingFetch,
+)
+from agentscope_bricks.components.generations.async_image_to_video_fl_wan22 import (  # noqa
+    ImageToVideoByFirstAndLastFrameWan22Submit,
+)
+from agentscope_bricks.components.generations.image_out_painting import (
+    ImageOutPaintingAuto,
+)
+from agentscope_bricks.components.generations.image_text_interleave_generation_wan26 import (  # noqa
+    WanImageInterleaveGeneration,
+)
 
 
 class McpServerMeta(BaseModel):
@@ -92,7 +111,14 @@ class McpServerMeta(BaseModel):
 mcp_server_metas: Dict[str, McpServerMeta] = {
     "modelstudio_wan_image": McpServerMeta(
         instructions="基于通义万相大模型的智能图像生成服务，提供高质量的图像处理和编辑功能",
-        components=[ImageGeneration, ImageEdit, ImageStyleRepaint],
+        components=[
+            ImageGeneration,
+            ImageEdit,
+            ImageStyleRepaint,
+            ImageOutPaintingSubmit,
+            ImageOutPaintingFetch,
+            ImageOutPaintingAuto,
+        ],
     ),
     "modelstudio_wan_video": McpServerMeta(
         instructions="基于通义万相大模型提供AI视频生成服务，支持文本到视频、图像到视频和语音到视频的多模态生成功能",
@@ -103,6 +129,8 @@ class McpServerMeta(BaseModel):
             ImageToVideoFetch,
             SpeechToVideoSubmit,
             SpeechToVideoFetch,
+            ImageToVideoByFirstAndLastFrameWan22Submit,
+            WanVideoFetch,
         ],
     ),
     "modelstudio_wan25_media": McpServerMeta(
@@ -143,6 +171,15 @@ class McpServerMeta(BaseModel):
             TextToVideoWan26Submit,
             ImageToVideoWan26Submit,
             WanVideoFetch,
+            ImageEditWan26,
+            WanImageInterleaveGeneration,
+        ],
+    ),
+    "modelstudio_Z_image": McpServerMeta(
+        instructions="基于通义Z-Image大模型的智能图像生成服务，是一款轻量级文生图模型，"
+        "可快速生成图像，支持中英文字渲染，并灵活适配多种分辨率与宽高比例。",
+        components=[
+            ZImageGeneration,
         ],
     ),
 }

src/agentscope_bricks/components/generations/async_image_out_painting.py

@@ -0,0 +1,332 @@
+# -*- coding: utf-8 -*-
+import os
+import uuid
+from http import HTTPStatus
+from typing import Any, Optional, Dict
+
+import aiohttp
+from mcp.server.fastmcp import Context
+from pydantic import BaseModel, Field
+
+from agentscope_bricks.base.component import Component
+from agentscope_bricks.utils.tracing_utils.wrapper import trace
+from agentscope_bricks.utils.api_key_util import ApiNames, get_api_key
+from agentscope_bricks.utils.tracing_utils import TracingUtil
+
+
+DASHSCOPE_API_BASE = "https://dashscope.aliyuncs.com/api/v1"
+
+
+class ImageOutPaintingSubmitInput(BaseModel):
+    """
+    Input model for submitting an image out-painting (expansion) task.
+    """
+
+    image_url: str = Field(
+        ...,
+        description="输入图像的公网可访问 URL。",
+    )
+    angle: Optional[float] = Field(
+        default=None,
+        description="逆时针旋转角度，取值范围 [0, 359]。默认为 0（不旋转）。",
+    )
+    output_ratio: Optional[str] = Field(
+        default=None,
+        description='目标宽高比，可选值：["", "1:1", "3:4", "4:3", "9:16", "16:9"]。'
+        '默认值为""，表示不设置输出图像的宽高比。',
+    )
+    x_scale: Optional[float] = Field(
+        default=None,
+        description="水平方向扩展比例（居中扩展），默认 1.0。可以与 y_scale 搭配使用。取值范围 [1.0, 3.0]。"
+        "例如：输入图像分辨率为1000×1000（宽×高），x_scale=2.0，扩展后的图像分辨率为2000×1000（宽×高）。"
+        "保持高度不变，左右各添加500个像素。",
+    )
+    y_scale: Optional[float] = Field(
+        default=None,
+        description="垂直方向扩展比例（居中扩展），默认 1.0。可以选择与 x_scale 搭配使用。取值范围 [1.0, 3.0]。"
+        "例如：输入图像分辨率为1000×1000（宽×高），y_scale=2.0，扩展后的图像分辨率为1000×2000（宽×高）。"
+        "保持宽度不变，上下各添加500个像素。",
+    )
+    top_offset: Optional[float] = Field(
+        default=None,
+        description="在图像上方添加的像素数。默认值为0,"
+        "需满足 top_offset + bottom_offset < 3 × 原图高度。"
+        "输入图像分辨率为1000×1000（宽×高），top_offset=500，扩展后的图像分辨率为1000×1500（宽×高）。"
+        "保持宽度不变，只在图像上方添加500个像素。",
+    )
+    bottom_offset: Optional[float] = Field(
+        default=None,
+        description="在图像下方添加的像素数。默认值为0，"
+        "需满足 top_offset + bottom_offset < 3 × 原图高度。"
+        "例如：输入图像分辨率为1000×1000（宽×高），bottom_offset=500，扩展后的图像分辨率为1000×1500（宽×高）。"
+        "保持宽度不变，只在图像下方添加500个像素。",
+    )
+    left_offset: Optional[float] = Field(
+        default=None,
+        description="在图像左侧添加的像素数。默认值为0，"
+        "需满足 left_offset + right_offset < 3 × 原图宽度。"
+        "例如：输入图像分辨率为1000×1000（宽×高），left_offset=500，扩展后的图像分辨率为1500×1000（宽×高）。"
+        "保持高度不变，只在图像左侧添加500个像素。",
+    )
+    right_offset: Optional[float] = Field(
+        default=None,
+        description="在图像右侧添加的像素数。默认值为0，"
+        "需满足 left_offset + right_offset < 3 × 原图宽度。"
+        "例如：输入图像分辨率为1000×1000（宽×高），right_offset=500，扩展后的图像分辨率为1500×1000（宽×高）。"
+        "保持高度不变，只在图像右侧添加500个像素。",
+    )
+    best_quality: Optional[bool] = Field(
+        default=None,
+        description="是否启用最佳质量模式。默认 false（速度优先），设为 true 可提升细节但耗时增加。",
+    )
+    limit_image_size: Optional[bool] = Field(
+        default=None,
+        description="是否限制输出图像大小（≤5MB）。默认 true，建议保持开启。"
+        "模型生成的图像需要经过一层安全过滤后才能输出，当前不支持大于10M的图像处理。",
+    )
+    add_watermark: Optional[bool] = Field(
+        default=None,
+        description="是否添加水印,True：默认值,添加水印,False：不添加水印。",
+    )
+    ctx: Optional[Context] = Field(
+        default=None,
+        description="HTTP request context containing "
+        "headers for mcp only, don't generate it",
+    )
+
+
+class ImageOutPaintingSubmitOutput(BaseModel):
+    task_id: str = Field(
+        title="Task ID",
+        description="异步任务的唯一标识符，有效期 24 小时。",
+    )
+    task_status: str = Field(
+        title="Task Status",
+        description="任务状态：PENDING（排队中）、RUNNING（处理中）、"
+        "SUCCEEDED（成功）、FAILED（失败）等。",
+    )
+    request_id: Optional[str] = Field(
+        default=None,
+        title="Request ID",
+        description="请求唯一 ID，用于日志追踪。",
+    )
+
+
+class ImageOutPaintingSubmit(
+    Component[ImageOutPaintingSubmitInput, ImageOutPaintingSubmitOutput],
+):
+    name: str = "modelstudio_image_out_painting_submit"
+    description: str = (
+        "图像画面扩展（扩图）异步任务提交工具，基于image-out-painting 模型。\n"
+        "支持三种扩图方式（按优先级）：\n"
+        "1. 按宽高比（output_ratio）\n"
+        "2. 按比例缩放（x_scale / y_scale）\n"
+        "3. 指定方向像素填充（top/bottom/left/right_offset）\n"
+        "可选旋转（angle），先旋转后扩图。"
+    )
+
+    @trace(trace_type="AIGC", trace_name="image_out_painting_submit")
+    async def arun(
+        self,
+        args: ImageOutPaintingSubmitInput,
+        **kwargs: Any,
+    ) -> ImageOutPaintingSubmitOutput:
+        trace_event = kwargs.pop("trace_event", None)
+        request_id = TracingUtil.get_request_id()
+
+        try:
+            api_key = get_api_key(ApiNames.dashscope_api_key, **kwargs)
+        except AssertionError:
+            raise ValueError("Please set valid DASHSCOPE_API_KEY!")
+
+        # 构建 parameters 字典（只包含非 None 值）
+        parameters: Dict[str, Any] = {}
+        if args.angle is not None:
+            parameters["angle"] = args.angle
+        if args.output_ratio is not None:
+            parameters["output_ratio"] = args.output_ratio
+        if args.x_scale is not None:
+            parameters["x_scale"] = args.x_scale
+        if args.y_scale is not None:
+            parameters["y_scale"] = args.y_scale
+        if args.top_offset is not None:
+            parameters["top_offset"] = args.top_offset
+        if args.bottom_offset is not None:
+            parameters["bottom_offset"] = args.bottom_offset
+        if args.left_offset is not None:
+            parameters["left_offset"] = args.left_offset
+        if args.right_offset is not None:
+            parameters["right_offset"] = args.right_offset
+        if args.best_quality is not None:
+            parameters["best_quality"] = args.best_quality
+        if args.limit_image_size is not None:
+            parameters["limit_image_size"] = args.limit_image_size
+        if args.add_watermark is not None:
+            parameters["add_watermark"] = args.add_watermark
+
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "X-DashScope-Async": "enable",
+            "Content-Type": "application/json",
+        }
+
+        payload = {
+            "model": "image-out-painting",
+            "input": {"image_url": args.image_url},
+            "parameters": parameters,
+        }
+
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                f"{DASHSCOPE_API_BASE}/services/aigc/image2image/out-painting",
+                headers=headers,
+                json=payload,
+            ) as resp:
+                status_code = resp.status
+                response_json = await resp.json()
+
+        if trace_event:
+            trace_event.on_log(
+                "",
+                **{
+                    "step_suffix": "submit_response",
+                    "payload": {
+                        "request_id": request_id,
+                        "response": response_json,
+                        "status_code": status_code,
+                    },
+                },
+            )
+
+        if status_code != HTTPStatus.OK or "output" not in response_json:
+            error_msg = response_json.get("message", "Unknown error")
+            raise RuntimeError(
+                f"Failed to submit out-painting task: {error_msg} (code: {status_code})",  # noqa
+            )
+
+        output = response_json["output"]
+        task_id = output["task_id"]
+        task_status = output["task_status"]
+        actual_request_id = (
+            response_json.get("request_id") or request_id or str(uuid.uuid4())
+        )
+
+        return ImageOutPaintingSubmitOutput(
+            task_id=task_id,
+            task_status=task_status,
+            request_id=actual_request_id,
+        )
+
+
+# ==================== Fetch Result ====================
+
+
+class ImageOutPaintingFetchInput(BaseModel):
+    task_id: str = Field(
+        ...,
+        description="要查询的扩图任务 ID。",
+    )
+    ctx: Optional[Context] = Field(
+        default=None,
+        description="HTTP request context containing "
+        "headers for mcp only, don't generate it",
+    )
+
+
+class ImageOutPaintingFetchOutput(BaseModel):
+    output_image_url: str = Field(
+        ...,
+        description="扩图后生成的图像公网 URL（PNG/JPG 等格式）。",
+    )
+    task_id: str = Field(
+        ...,
+        description="任务 ID，与输入一致。",
+    )
+    task_status: str = Field(
+        ...,
+        description="任务最终状态，成功时为 SUCCEEDED。",
+    )
+    request_id: Optional[str] = Field(
+        default=None,
+        description="请求 ID，用于追踪。",
+    )
+
+
+class ImageOutPaintingFetch(
+    Component[ImageOutPaintingFetchInput, ImageOutPaintingFetchOutput],
+):
+    name: str = "modelstudio_image_out_painting_fetch"
+    description: str = (
+        "查询图像画面扩展（扩图）任务的结果。\n"
+        "输入 Task ID，返回扩图后的图像 URL 和任务状态。\n"
+        "请在提交任务后轮询此接口，直到状态变为 SUCCEEDED。"
+    )
+
+    @trace(trace_type="AIGC", trace_name="image_out_painting_fetch")
+    async def arun(
+        self,
+        args: ImageOutPaintingFetchInput,
+        **kwargs: Any,
+    ) -> ImageOutPaintingFetchOutput:
+        trace_event = kwargs.pop("trace_event", None)
+        request_id = TracingUtil.get_request_id()
+
+        try:
+            api_key = get_api_key(ApiNames.dashscope_api_key, **kwargs)
+        except AssertionError as e:
+            raise ValueError("Please set valid DASHSCOPE_API_KEY!") from e
+
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+        }
+
+        async with aiohttp.ClientSession() as session:
+            async with session.get(
+                f"{DASHSCOPE_API_BASE}/tasks/{args.task_id}",
+                headers=headers,
+            ) as resp:
+                status_code = resp.status
+                response_json = await resp.json()
+
+        if trace_event:
+            trace_event.on_log(
+                "",
+                **{
+                    "step_suffix": "fetch_response",
+                    "payload": {
+                        "request_id": request_id,
+                        "response": response_json,
+                        "status_code": status_code,
+                    },
+                },
+            )
+
+        if status_code != HTTPStatus.OK or "output" not in response_json:
+            error_msg = response_json.get("message", "Unknown error")
+            raise RuntimeError(
+                f"Failed to fetch out-painting result: {error_msg} (code: {status_code})",  # noqa
+            )
+
+        output = response_json["output"]
+        task_status = output["task_status"]
+
+        if task_status in ["FAILED", "CANCELED"]:
+            error_msg = output.get("message", "Task failed")
+            raise RuntimeError(f"Out-painting task failed: {error_msg}")
+
+        if task_status != "SUCCEEDED":
+            raise RuntimeError(
+                f"Task not completed yet. Current status: {task_status}",
+            )
+
+        output_image_url = output["output_image_url"]
+        actual_request_id = (
+            response_json.get("request_id") or request_id or str(uuid.uuid4())
+        )
+
+        return ImageOutPaintingFetchOutput(
+            output_image_url=output_image_url,
+            task_id=output["task_id"],
+            task_status=task_status,
+            request_id=actual_request_id,
+        )