修复因新建分支导致上下文中的current img混乱,采用tool直接返回图片公开url地址(原因 1.保证图片时效性,2.保证图片能够进入上下文-deep agents的main-agent与sub-agent有上下文隔离机制,且task消息类型只支持str)
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@@ -2,6 +2,9 @@ import uuid
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import httpx
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import logging
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from langchain_core.messages import ToolMessage
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from langchain_core.runnables import RunnableConfig
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from langchain_core.stores import BaseStore
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from minio import Minio
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from google import genai
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from pathlib import Path
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@@ -9,9 +12,9 @@ from datetime import datetime
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from langchain_core.tools import tool
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from google.oauth2 import service_account
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from langgraph.prebuilt import ToolRuntime
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from src.core.config import settings, MONGO_URI
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from src.server.deep_agent.utils.mongodb_util import ThreadImageMinIOStore
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from src.server.utils.new_oss_client import get_presigned_url, check_and_extract_minio_image
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# from google.genai.types import GenerateContentConfig, Modality
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# from langgraph.config import get_stream_writer
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@@ -41,78 +44,127 @@ def is_image_path_exist(image_path):
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return False
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def create_generate_furniture_tool(workspace_dir, width: int = 1024, height: int = 1024):
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@tool
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async def generate_furniture(prompt: str, runtime: ToolRuntime) -> str:
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"""
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使用 Gemini 图像生成模型根据详细的英文提示词生成家具设计草图。
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"""
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logger.info(f"\n[系统日志] 正在调用 generate_furniture ...")
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thread_id = runtime.config.get("configurable").get("thread_id")
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try:
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# 1. 生成图像 - local flux2-klein
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object_name = f"furniture/sketches/{uuid.uuid4()}.png"
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bucket_name = "fida-test" # 替换为你的 bucket 名称
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request_data = {
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"prompt": prompt,
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"bucket_name": bucket_name,
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"object_name": object_name,
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"width": width,
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"height": height
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}
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async with httpx.AsyncClient(timeout=120) as client:
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resp = await client.post(
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f"http://{settings.FLUX2_GEN_IMG_MODEL_URL}/predict",
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json=request_data,
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)
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result = resp.json()
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image_url = result.get("output_path", None)
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@tool
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async def generate_furniture(prompt: str, runtime: ToolRuntime):
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"""
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使用图像生成模型根据用户提供的详细英文提示词，从零生成一张全新的家具设计草图。
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if image_url:
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image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
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return image_url
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else:
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return f"Image generation failed."
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功能说明：
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- 输入一段详细的英文描述，即可生成一张高品质的家具设计图片（可用于草图、效果图、渲染图等）。
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- 生成后的图片会以 image_url 形式返回，自动加入对话上下文，后续 Agent 可以直接“看到”生成的家具图片并继续操作（描述、编辑、迭代等）。
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except Exception as e:
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logger.warning(f"绘图流程异常：{e}")
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return "绘图流程异常"
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参数说明：
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- prompt (str): **必须是详细的英文提示词**，越详细越好，包含家具类型、风格、颜色、材质、尺寸比例、背景、视角、光影等具体要求。
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示例："Generate a modern minimalist dining chair made of light oak wood and white leather, with slim metal legs, photographed in a bright Scandinavian living room with natural sunlight, high detail, 8k resolution."
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return generate_furniture
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返回值：
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返回新生成家具图片的 image_url，后续对话中 Agent 可直接引用该图片进行描述、进一步编辑或分析。
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使用场景：
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- 从零创建新的家具设计方案
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- 快速生成多种风格的家具概念图
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- 室内设计初期灵感生成
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- 家具产品可视化展示
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注意：
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- 生成的图片会自动携带到整个对话上下文中，支持后续使用 edit_furniture 等工具进行迭代修改。
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- 如果需要生成多个方案，可以多次调用本工具或在 prompt 中明确要求生成不同变体。
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"""
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logger.info(f"\n[系统日志] 正在调用 generate_furniture ...")
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# thread_id = runtime.config.get("configurable").get("thread_id")
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try:
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# 1. 生成图像 - local flux2-klein
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object_name = f"furniture/sketches/{uuid.uuid4()}.png"
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bucket_name = "fida-public-bucket" # 替换为你的 bucket 名称
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request_data = {
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"prompt": prompt,
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"bucket_name": bucket_name,
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"object_name": object_name,
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"width": 1024,
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"height": 1024
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}
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async with httpx.AsyncClient(timeout=120) as client:
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resp = await client.post(
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f"http://{settings.FLUX2_GEN_IMG_MODEL_URL}/predict",
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json=request_data,
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)
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result = resp.json()
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image_url = result.get("output_path", None)
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# image_presigned_url = get_presigned_url(oss_client=minio_client, bucket=bucket_name, object_name=object_name)
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if image_url:
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# image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
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# image_id = str(uuid.uuid4())
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# runtime.store.put(
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# namespace=("images", thread_id), # e.g. ("images", thread_id)
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# key=image_id,
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# value={
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# "url": image_url,
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# "prompt": prompt,
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# "timestamp": str(uuid.uuid4()), # 或用 datetime
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# "version": "v1"
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# }
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# )
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return f"Image has been generated: https://minio-api.aida.com.hk/{image_url}"
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else:
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return "Image generation failed."
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except Exception as e:
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logger.warning(f"绘图流程异常：{e}")
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return "generate furniture error"
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def create_edit_furniture_tool(workspace_dir, width: int = 1024, height: int = 1024):
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@tool
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async def edit_furniture(prompt: str, runtime: ToolRuntime) -> str:
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"""
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使用图像生成模型根据详细的英文提示词编辑家具设计草图。
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"""
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logger.info(f"\n[系统日志] 正在调用 edit_furniture ...")
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thread_id = runtime.config.get("configurable").get("thread_id")
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try:
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current_image_path = None
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if image_store.get_image_path(thread_id):
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current_image_path = image_store.get_image_path(thread_id).get("current_image_path", False)
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user_input_image_paths = runtime.state.get("files").get("input_image", [])
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user_quote_image_path = runtime.state.get("files").get("quote_image", "")
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input_path = []
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@tool
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async def edit_furniture(image_url: str, prompt: str, runtime: ToolRuntime, config: RunnableConfig):
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"""
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使用先进的图像编辑模型（image editing model）对家具设计草图进行精准修改。
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功能说明：
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- 输入一张家具图片（草图/效果图），根据用户提供的**详细英文提示词**，生成修改后的新家具图片。
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- 修改后的图片会以 image_url 形式返回，自动加入对话上下文，后续 Agent 可以直接“看到”编辑结果并继续操作。
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参数说明：
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- image_url (str): 原始家具图片的 URL（支持公开 http/https 链接或 data:image/...;base64 格式）。
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- prompt (str): **必须是详细的英文提示词**，描述想要的具体修改（风格、颜色、材质、形状、添加/删除元素、比例等）。
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示例："Change the sofa to a modern minimalist style with dark gray fabric and metal legs, add a matching coffee table, make the overall lighting warmer and more luxurious."
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返回值：
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返回新生成家具图片的 image_url，后续对话中 Agent 可直接引用该图片进行描述、进一步编辑或分析。
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使用场景：
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- 家具设计迭代
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- 室内设计方案修改
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- 风格转换（现代/北欧/工业风等）
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- 材质/颜色调整
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注意：如果需要多次迭代编辑，直接在下一次调用时传入上一次返回的新 image_url 即可。
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"""
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logger.info(f"\n[系统日志] 正在调用 edit_furniture ...")
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thread_id = runtime.config.get("configurable").get("thread_id")
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input_path = []
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try:
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user_input_image_paths = runtime.state.get("files").get("input_image", [])
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user_quote_image_path = runtime.state.get("files").get("quote_image", "")
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extract_result = check_and_extract_minio_image(url=image_url)
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if extract_result['state']:
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current_image_path = extract_result['data']
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if len(user_input_image_paths) or current_image_path:
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if len(user_input_image_paths):
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for path in user_input_image_paths:
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input_path.append(path)
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for path in user_input_image_paths:
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input_path.append(path)
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if user_quote_image_path:
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input_path.append(user_quote_image_path)
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if not len(user_input_image_paths) and not user_quote_image_path:
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input_path = [current_image_path]
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object_name = f"furniture/sketches/{uuid.uuid4()}.png"
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bucket_name = "fida-test" # 替换为你的 bucket 名称
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bucket_name = "fida-public-bucket" # 替换为你的 bucket 名称
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request_data = {
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"input_image_paths": input_path,
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"prompt": prompt,
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"bucket_name": bucket_name,
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"object_name": object_name,
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"width": width,
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"height": height
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"width": 1024,
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"height": 1024
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}
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async with httpx.AsyncClient(timeout=120) as client:
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resp = await client.post(
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@@ -123,17 +175,18 @@ def create_edit_furniture_tool(workspace_dir, width: int = 1024, height: int = 1
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image_url = result.get("output_path", None)
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if image_url:
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image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
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return image_url
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# image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
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return f"Image has been generated: https://minio-api.aida.com.hk/{image_url}"
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else:
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return f"Image generation failed."
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return "Image generation failed."
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else:
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return f"The picture to be edited does not exist."
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except Exception as e:
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logger.warning(f"edit_furniture error ：{e}")
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return "edit_furniture error"
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return "The picture to be edited does not exist."
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else:
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return extract_result['message']
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return edit_furniture
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except Exception as e:
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logger.warning(f"edit_furniture error ：{e}")
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return "edit_furniture error"
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# def create_generate_furniture_tool(workspace_dir):
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# @tool
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