FiDA_Python/src/server/deep_agent/tools/generate_furniture_sketch.py

import uuid
import httpx
import logging

from minio import Minio
from google import genai
from pathlib import Path
from datetime import datetime
from langchain_core.tools import tool
from google.oauth2 import service_account
from langgraph.prebuilt import ToolRuntime

from src.core.config import settings, MONGO_URI
from src.server.deep_agent.utils.mongodb_util import ThreadImageMinIOStore

# from google.genai.types import GenerateContentConfig, Modality
# from langgraph.config import get_stream_writer
# from src.server.utils.new_oss_client import oss_upload_image, oss_get_image, is_minio_file_exist, oss_upload_image_file

# 初始化全局凭证和客户端
# creds = service_account.Credentials.from_service_account_file(
#     settings.GOOGLE_GENAI_USE_VERTEXAI,
#     scopes=["https://www.googleapis.com/auth/cloud-platform"],
# )
# client = genai.Client(
#     credentials=creds,
#     project=settings.GOOGLE_CLOUD_PROJECT,
#     location=settings.GOOGLE_CLOUD_LOCATION,
#     vertexai=True
# )

logger = logging.getLogger(__name__)
minio_client = Minio(settings.MINIO_URL, access_key=settings.MINIO_ACCESS, secret_key=settings.MINIO_SECRET, secure=settings.MINIO_SECURE)
image_store = ThreadImageMinIOStore(MONGO_URI, "agent_tool_generate_db")


def is_image_path_exist(image_path):
    try:
        return Path(image_path).exists()
    except:
        return False


def create_generate_furniture_tool(workspace_dir, width: int = 1024, height: int = 1024):
    @tool
    async def generate_furniture(prompt: str, runtime: ToolRuntime) -> str:
        """
        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。
        """
        logger.info(f"\n[系统日志] 正在调用 generate_furniture ...")
        thread_id = runtime.config.get("configurable").get("thread_id")
        try:
            # 1. 生成图像 - local flux2-klein
            object_name = f"furniture/sketches/{uuid.uuid4()}.png"
            bucket_name = "fida-test"  # 替换为你的 bucket 名称
            request_data = {
                "prompt": prompt,
                "bucket_name": bucket_name,
                "object_name": object_name,
                "width": width,
                "height": height
            }
            async with httpx.AsyncClient(timeout=120) as client:
                resp = await client.post(
                    f"http://{settings.FLUX2_GEN_IMG_MODEL_URL}/predict",
                    json=request_data,
                )
            result = resp.json()
            image_url = result.get("output_path", None)

            if image_url:
                image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
                return image_url
            else:
                return f"Image generation failed."

        except Exception as e:
            logger.warning(f"绘图流程异常：{e}")
            return "绘图流程异常"

    return generate_furniture


def create_edit_furniture_tool(workspace_dir, width: int = 1024, height: int = 1024):
    @tool
    async def edit_furniture(prompt: str, runtime: ToolRuntime) -> str:
        """
        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。
        """
        logger.info(f"\n[系统日志] 正在调用 edit_furniture ...")
        thread_id = runtime.config.get("configurable").get("thread_id")
        try:
            current_image_path = image_store.get_image_path(thread_id).get("current_image_path", False)
            input_image_path = runtime.state.get("files").get("input_image", False)
            if input_image_path or current_image_path:
                input_path = [path for path in (input_image_path, current_image_path) if path]
                object_name = f"furniture/sketches/{uuid.uuid4()}.png"
                bucket_name = "fida-test"  # 替换为你的 bucket 名称
                request_data = {
                    "input_image_paths": input_path,
                    "prompt": prompt,
                    "bucket_name": bucket_name,
                    "object_name": object_name,
                    "width": width,
                    "height": height
                }
                async with httpx.AsyncClient(timeout=120) as client:
                    resp = await client.post(
                        f"http://{settings.FLUX2_GEN_IMG_MODEL_URL}/predict",
                        json=request_data,
                    )
                result = resp.json()
                image_url = result.get("output_path", None)

                if image_url:
                    image_store.save_image_path(thread_id=thread_id, object_path=image_url, metadata={"prompt": prompt, "generated_at": str(datetime.now())})
                    return image_url
                else:
                    return f"Image generation failed."
            else:
                return f"The picture to be edited does not exist."
        except Exception as e:
            logger.warning(f"edit_furniture error ：{e}")
            return "edit_furniture error"

    return edit_furniture

# def create_generate_furniture_tool(workspace_dir):
#     @tool
#     async def generate_furniture(prompt: str) -> str:
#         """
#         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。
#         """
#         print(f"\n[系统日志] 正在调用 Nano Banana (Gemini Image Gen) ...")
#
#         try:
#             response = client.models.generate_content(
#                 model="gemini-2.5-flash-image",
#                 contents=(f"Generate a professional furniture design sketch: {prompt}"),
#                 config=GenerateContentConfig(
#                     response_modalities=[Modality.TEXT, Modality.IMAGE],
#                 ),
#             )
#
#             image_bytes = None
#             for part in response.candidates[0].content.parts:
#                 if part.inline_data:
#                     image_bytes = part.inline_data.data
#                     break
#
#             if not image_bytes:
#                 return "未能生成图像数据。"
#             # 1. 定义OSS存储路径和本地保存路径
#             object_name = f"furniture/sketches/{uuid.uuid4()}.png"
#             bucket = "fida-test"  # 替换为你的 bucket 名称
#             filename = os.path.join(workspace_dir, f"{bucket}/{object_name}")
#
#             # 2. 创建本地目录（确保目录存在）
#             local_dir = os.path.dirname(filename)
#             if not os.path.exists(local_dir):
#                 os.makedirs(local_dir, exist_ok=True)
#
#             # 3. 保存图片到本地文件（新增核心逻辑）
#             try:
#                 with open(filename, "wb") as f:
#                     f.write(image_bytes)
#                 print(f"[系统日志] 图片已保存到本地：{filename}")
#             except Exception as save_e:
#                 logger.warning(f"保存图片到本地失败：{save_e}")
#                 # 本地保存失败不中断上传流程，仅记录日志
#
#             # 4. 上传图片到OSS（原有逻辑）
#             upload_res = oss_upload_image(
#                 oss_client=minio_client,
#                 bucket=bucket,
#                 object_name=object_name,
#                 image_bytes=image_bytes
#             )
#
#             if upload_res:
#                 image_url = f"{bucket}/{object_name}"
#                 return image_url
#             else:
#                 return f"图片生成成功（本地路径：{filename}），但上传至存储服务器失败。"
#
#         except Exception as e:
#             logger.warning(f"绘图流程异常：{e}")
#             return "绘图流程异常"
#
#     return generate_furniture