feat: 修改drawing 为django 接口

backend/ai/llm/__init__.py

@@ -0,0 +1,50 @@
+import os
+from enum import Enum
+
+from pydantic import SecretStr
+
+
+class ProviderEnum(str, Enum):
+    """支持的 LLM 服务商"""
+    DEEPSEEK = "deepseek"
+    OPENAI = "openai"
+    TONGYI = "tongyi"
+
+class LLMFactory(object):
+
+    @staticmethod
+    def get_llm(provider: ProviderEnum, model: str = None, **kwargs):
+        if provider == ProviderEnum.DEEPSEEK:
+            from langchain_deepseek import ChatDeepSeek
+            api_key = os.getenv("DEEPSEEK_API_KEY")
+            model = model or "deepseek-chat"
+            return ChatDeepSeek(
+                api_key=SecretStr(api_key),
+                model=model,
+                streaming=True,
+                **kwargs
+            )
+
+        elif provider == ProviderEnum.OPENAI:
+            from langchain_openai import ChatOpenAI
+            api_key = os.getenv("OPENAI_API_KEY")
+            model = model or "gpt-3.5-turbo"
+            return ChatOpenAI(
+                api_key=SecretStr(api_key),
+                model=model,
+                streaming=True,
+                **kwargs
+            )
+
+        elif provider == ProviderEnum.TONGYI:
+            from langchain_community.llms import Tongyi
+            api_key = os.getenv("DASHSCOPE_API_KEY")
+            model = model or "qwen-turbo"
+            return Tongyi(
+                api_key=SecretStr(api_key),
+                model=model,
+                streaming=True,
+                **kwargs
+            )
+        else:
+            raise ValueError(f"不支持的 LLM 服务商: {provider}")

backend/ai/llm/adapter/deepseek.py

@@ -0,0 +1,17 @@
+from langchain_deepseek import ChatDeepSeek
+
+from llm.base import MultiModalAICapability
+
+
+class DeepSeekAdapter(MultiModalAICapability):
+    def __init__(self, api_key, model, **kwargs):
+
+        self.llm = ChatDeepSeek(api_key=api_key, model=model, streaming=True)
+
+    async def chat(self, messages, **kwargs):
+        # 兼容 DeepSeek 的调用方式
+        return await self.llm.ainvoke(messages)
+
+    async def stream_chat(self, messages, **kwargs):
+        async for chunk in self.llm.astream(messages):
+            yield chunk

backend/ai/llm/adapter/genai.py

@@ -0,0 +1,21 @@
+# 假设有 google genai sdk
+# from google_genai import GenAI
+from llm.base import MultiModalAICapability
+
+
+class GoogleGenAIAdapter(MultiModalAICapability):
+    def __init__(self, api_key, model, **kwargs):
+        self.api_key = api_key
+        self.model = model
+        # self.llm = GenAI(api_key=api_key, model=model)
+
+    async def chat(self, messages, **kwargs):
+        # return await self.llm.chat(messages)
+        raise NotImplementedError("Google GenAI chat未实现")
+
+    async def stream_chat(self, messages, **kwargs):
+        # async for chunk in self.llm.stream_chat(messages):
+        #     yield chunk
+        raise NotImplementedError("Google GenAI stream_chat未实现")
+
+    # 其他能力同理

backend/ai/llm/adapter/openai.py

@@ -0,0 +1,25 @@
+from llm.base import MultiModalAICapability
+from langchain_openai import ChatOpenAI
+# from openai import OpenAI # 如需图片/音频/视频等API
+
+class OpenAIAdapter(MultiModalAICapability):
+    def __init__(self, api_key, model, **kwargs):
+        self.llm = ChatOpenAI(api_key=api_key, model=model, streaming=True)
+        self.api_key = api_key
+
+    async def chat(self, messages, **kwargs):
+        return await self.llm.ainvoke(messages)
+
+    async def stream_chat(self, messages, **kwargs):
+        async for chunk in self.llm.astream(messages):
+            yield chunk
+
+    # 如需图片生成（DALL·E），可实现如下
+    def create_drawing_task(self, **kwargs):
+        # 伪代码，需用 openai.Image.create
+        # import openai
+        # response = openai.Image.create(api_key=self.api_key, prompt=prompt, ...)
+        # return response
+        raise NotImplementedError("OpenAI 图片生成请用 openai.Image.create 实现")
+
+    # 其他能力同理

backend/ai/llm/adapter/tongyi.py

@@ -0,0 +1,44 @@
+from langchain_community.chat_models import ChatTongyi
+from http import HTTPStatus
+from urllib.parse import urlparse, unquote
+from pathlib import PurePosixPath
+import requests
+from dashscope import ImageSynthesis
+import os
+
+from llm.base import MultiModalAICapability
+
+
+class TongYiAdapter(MultiModalAICapability):
+    def __init__(self, api_key, model, **kwargs):
+        self.api_key = api_key
+        self.model = model
+        self.llm = ChatTongyi(api_key=api_key, model=model, streaming=True)
+
+    async def chat(self, messages, **kwargs):
+        # 兼容 DeepSeek 的调用方式
+        return await self.llm.ainvoke(messages)
+
+    async def stream_chat(self, messages, **kwargs):
+        async for chunk in self.llm.astream(messages):
+            yield chunk
+
+    def create_drawing_task(self, prompt: str, style='watercolor', size='1024*1024', n=1, **kwargs):
+        """创建异步图片生成任务"""
+        rsp = ImageSynthesis.async_call(
+            api_key=self.api_key,
+            model=self.model,
+            prompt=prompt,
+            n=n,
+            style=f'<{style}>',
+            size=size
+        )
+        return rsp
+
+    def fetch_drawing_task_status(self, task):
+        """获取异步图片任务状态"""
+        rsp = ImageSynthesis.fetch(task, api_key=self.api_key)
+        return rsp
+
+
+    

backend/ai/llm/base.py

@@ -0,0 +1,37 @@
+from abc import ABC
+
+class MultiModalAICapability(ABC):
+    # 对话能力
+    async def chat(self, messages, **kwargs):
+        raise NotImplementedError("chat not supported by this provider")
+
+    async def stream_chat(self, messages, **kwargs):
+        raise NotImplementedError("stream_chat not supported by this provider")
+
+    # 图片生成能力
+    def create_drawing_task(self, prompt: str, style='watercolor', size='1024*1024', n=1, **kwargs):
+        raise NotImplementedError("drawing generation not supported by this provider")
+
+    def fetch_drawing_task_status(self, task):
+        raise NotImplementedError("drawing task status not supported by this provider")
+
+    def fetch_drawing_result(self, task):
+        raise NotImplementedError("drawing result not supported by this provider")
+
+    # 视频生成能力
+    def create_video_task(self, prompt, **kwargs):
+        raise NotImplementedError("video generation not supported by this provider")
+
+    def fetch_video_task_status(self, task):
+        raise NotImplementedError("video task status not supported by this provider")
+
+    def fetch_video_result(self, task):
+        raise NotImplementedError("video result not supported by this provider")
+
+    # 知识库能力
+    def query_knowledge(self, query, **kwargs):
+        raise NotImplementedError("knowledge query not supported by this provider")
+
+    # 语音合成能力
+    def synthesize_speech(self, text, **kwargs):
+        raise NotImplementedError("speech synthesis not supported by this provider")

backend/ai/llm/enums.py

@@ -0,0 +1,32 @@
+from enum import Enum
+
+
+class LLMProvider(str, Enum):
+    """LLM 提供商枚举"""
+    DEEPSEEK = "deepseek"
+    TONGYI = "tongyi"
+    OPENAI = "openai"
+    GOOGLE_GENAI = "google-genai"
+    
+    @classmethod
+    def get_model_by_platform(cls, platform: str) -> tuple[str, str]:
+        """根据平台名称获取对应的模型和API密钥环境变量名"""
+        if platform == cls.TONGYI:
+            return 'qwen-plus', 'DASHSCOPE_API_KEY'
+        elif platform == cls.DEEPSEEK:
+            return 'deepseek-chat', 'DEEPSEEK_API_KEY'
+        elif platform == cls.OPENAI:
+            return 'gpt-3.5-turbo', 'OPENAI_API_KEY'
+        elif platform == cls.GOOGLE_GENAI:
+            return 'gemini-pro', 'GOOGLE_API_KEY'
+        else:
+            # 默认使用 DeepSeek
+            return 'deepseek-chat', 'DEEPSEEK_API_KEY'
+    
+    @classmethod
+    def from_string(cls, platform: str) -> 'LLMProvider':
+        """从字符串创建枚举值，如果不存在则返回默认值"""
+        try:
+            return cls(platform)
+        except ValueError:
+            return cls.DEEPSEEK  # 默认返回 DeepSeek 

backend/ai/llm/factory.py

@@ -0,0 +1,35 @@
+from .adapter.deepseek import DeepSeekAdapter
+from .adapter.genai import GoogleGenAIAdapter
+from .adapter.openai import OpenAIAdapter
+from .adapter.tongyi import TongYiAdapter
+from .enums import LLMProvider
+
+
+def get_adapter(provider: LLMProvider, api_key, model, **kwargs):
+    if provider == LLMProvider.DEEPSEEK:
+        return DeepSeekAdapter(api_key, model, **kwargs)
+    elif provider == LLMProvider.TONGYI:
+        return TongYiAdapter(api_key, model, **kwargs)
+    elif provider == LLMProvider.OPENAI:
+        return OpenAIAdapter(api_key, model, **kwargs)
+    elif provider == LLMProvider.GOOGLE_GENAI:
+        return GoogleGenAIAdapter(api_key, model, **kwargs)
+    else:
+        raise ValueError('不支持的服务商')
+
+#  使用示例
+# adapter = get_adapter(LLMProvider.TONGYI, api_key='xxx', model='wanx_v1')
+
+# 对话
+# try:
+#     result = await adapter.chat(messages)
+# except NotImplementedError:
+#     print("该服务商不支持对话能力")
+
+# # 图片生成
+# try:
+#     task = adapter.create_image_task(prompt="一只猫")
+#     status = adapter.fetch_image_task_status(task)
+#     result = adapter.fetch_image_result(task)
+# except NotImplementedError:
+#     print("该服务商不支持图片生成")

backend/ai/urls.py

@@ -10,6 +10,7 @@ router.register(r'tool', views.ToolViewSet)
 router.register(r'knowledge', views.KnowledgeViewSet)
 router.register(r'chat_conversation', views.ChatConversationViewSet)
 router.register(r'chat_message', views.ChatMessageViewSet)
+router.register(r'drawing', views.DrawingViewSet)
 
 
 urlpatterns = [

backend/ai/views/__init__.py

@@ -5,6 +5,7 @@ __all__ = [
    'KnowledgeViewSet',
    'ChatConversationViewSet',
    'ChatMessageViewSet',
+   'DrawingViewSet',
 ]
 
 from ai.views.ai_api_key import AIApiKeyViewSet
@@ -12,4 +13,5 @@ from ai.views.ai_model import AIModelViewSet
 from ai.views.tool import ToolViewSet
 from ai.views.knowledge import KnowledgeViewSet
 from ai.views.chat_conversation import ChatConversationViewSet
-from ai.views.chat_message import ChatMessageViewSet
+from ai.views.chat_message import ChatMessageViewSet
+from ai.views.drawing import DrawingViewSet

backend/ai/views/drawing.py

@@ -0,0 +1,83 @@
+import os
+from datetime import datetime
+
+from rest_framework.response import Response
+
+from ai.models import Drawing
+from backend import settings
+from llm.enums import LLMProvider
+from llm.factory import get_adapter
+from utils.serializers import CustomModelSerializer
+from utils.custom_model_viewSet import CustomModelViewSet
+from django_filters import rest_framework as filters
+
+
+class DrawingSerializer(CustomModelSerializer):
+    """
+    AI 绘画表 序列化器
+    """
+    class Meta:
+        model = Drawing
+        fields = '__all__'
+        read_only_fields = ['id', 'create_time', 'update_time']
+
+
+class DrawingFilter(filters.FilterSet):
+
+    class Meta:
+        model = Drawing
+        fields = ['id', 'remark', 'creator', 'modifier', 'is_deleted', 'public_status', 'platform',
+                  'model', 'width', 'height', 'status', 'pic_url', 'error_message', 'task_id', 'buttons']
+
+
+class DrawingViewSet(CustomModelViewSet):
+    """
+    AI 绘画表 视图集
+    """
+    queryset = Drawing.objects.filter(is_deleted=False).order_by('-id')
+    serializer_class = DrawingSerializer
+    filterset_class = DrawingFilter
+    search_fields = ['name']  # 根据实际字段调整
+    ordering_fields = ['create_time', 'id']
+    ordering = ['-create_time']
+
+    def create(self, request, *args, **kwargs):
+        model = request.data.get('model')
+        prompt = request.data.get('prompt')
+        n = request.data.get('n', 1)
+        style = request.data.get('style')
+        size = request.data.get('size')
+        api_key = settings.DASHSCOPE_API_KEY
+        request.data['width'] = int(size.split('*')[0])
+        request.data['height'] = int(size.split('*')[1])
+        adapter = get_adapter(LLMProvider.TONGYI, api_key=api_key, model=model)
+        rsp = adapter.create_drawing_task(prompt=prompt, n=n, style=style, size=size)
+        if rsp['status_code'] != 200:
+            return Response(rsp['data'], status=rsp['status_code'])
+        else:
+            request.data['status'] = rsp['output']['task_status']
+            request.data['task_id'] = rsp['output']['task_id']
+        return super().create(request, *args, **kwargs)
+
+    def retrieve(self, request, *args, **kwargs):
+        instance = self.get_object()
+        if instance.status in ("PENDING", 'RUNNING'):
+            api_key = settings.DASHSCOPE_API_KEY
+            adapter = get_adapter(LLMProvider.TONGYI, api_key=api_key, model='')
+            rsp = adapter.fetch_drawing_task_status(instance.task_id)
+            print(rsp, 'sadsadas')
+            if rsp['status_code'] == 200:
+                # 可根据 status.output.task_status 更新数据库
+                if rsp['output']['task_status'] == 'SUCCEEDED':
+                    instance.update_time = datetime.now()
+                    instance.status = rsp['output']['task_status']
+                    instance.pic_url = rsp['output']['results'][0]['url']
+                elif rsp['output']['task_status'] == 'FAILED':
+                    instance.update_time = datetime.now()
+                    instance.status = rsp['output']['task_status']
+                    instance.error_message = rsp['output']['message']
+                elif rsp['output']['task_status'] == 'RUNNING':
+                    instance.update_time = datetime.now()
+                    instance.status = rsp['output']['task_status']
+                instance.save()
+        return super().retrieve(request, *args, **kwargs)

backend/backend/settings.py

@@ -242,5 +242,8 @@ ASGI_APPLICATION = 'backend.asgi.application'
 #     }
 # }
 
+DEEPSEEK_API_KEY = os.getenv('DEEPSEEK_API_KEY', ''),
+DASHSCOPE_API_KEY = os.getenv('DASHSCOPE_API_KEY', ''),
+
 if os.path.exists(os.path.join(BASE_DIR, 'backend/local_settings.py')):
     from backend.local_settings import *

web/apps/web-antd/src/models/ai/drawing.ts

@@ -0,0 +1,19 @@
+import { BaseModel } from '#/models/base';
+
+export namespace DrawingApi {
+  export interface Drawing {
+    id: number;
+    remark: string;
+    creator: string;
+    modifier: string;
+    update_time: string;
+    create_time: string;
+    is_deleted: boolean;
+  }
+}
+
+export class DrawingModel extends BaseModel<DrawingApi.Drawing> {
+  constructor() {
+    super('/ai/drawing/');
+  }
+}

web/apps/web-antd/src/views/ai/drawing/index.vue

@@ -16,13 +16,10 @@ import {
   Spin,
 } from 'ant-design-vue';
 
-import {
+import { DrawingModel } from '#/models/ai/drawing';
-  createDrawing,
+// DrawingModel
-  getDrawingDetail,
-  getDrawingPage,
-} from '#/api/ai/drawing';
-
 // 定义图片对象类型
+const operator = new DrawingModel();
 interface DrawingImage {
   id: number;
   status: string;
@@ -89,11 +86,7 @@ async function handleDraw() {
   loading.value = true;
   try {
     // 这里调用你的AI画图API，返回图片url数组
-    const data = await createDrawing(form);
+    await operator.create(form);
-    if (data.code !== 0) {
-      message.error(data.message || '生成失败');
-      return;
-    }
     page.value = 1;
     await fetchDrawingList(page.value, pageSize.value); // 刷新第一页图片列表
     // images.value = res.data.images;
@@ -105,20 +98,42 @@ async function handleDraw() {
     loading.value = false;
   }
 }
+let drawingTimer: NodeJS.Timeout | null = null;
 
 // 轮询获取图片详情
 const pollDrawingDetail = async (id: number) => {
-  fetchDrawingDetail(id).then((res) => {
+  try {
-    if (res && res.data.status === 'RUNNING') {
+    const res = await operator.retrieve(id); // 改用 await 简化代码
-      setTimeout(() => pollDrawingDetail(id), 5000);
+    if (res?.status === 'RUNNING') {
+      // 保存定时器 ID，方便后续清除
+      drawingTimer = setTimeout(() => pollDrawingDetail(id), 5000);
+    } else if (
+      res?.status === '"SUCCEEDED"' && // 当状态为 "SUCCEEDED" 时，清除定时器
+      drawingTimer
+    ) {
+      clearTimeout(drawingTimer);
+      drawingTimer = null; // 重置定时器 ID
+      await fetchDrawingList();
+      // 可在此处添加任务成功后的其他逻辑（如刷新页面、提示用户等）
     }
-  });
+    // 可根据需要添加对其他状态的处理（如 FAILED）
+  } catch (error) {
+    // 处理请求失败的情况，避免轮询异常中断
+    console.error('轮询失败:', error);
+    if (drawingTimer) {
+      clearTimeout(drawingTimer);
+      drawingTimer = null;
+    }
+  }
 };
 
 // 获取图片分页列表
 async function fetchDrawingList(pageNum = 1, pageSize = 9) {
   try {
-    const res = await getDrawingPage({ page: pageNum, page_size: pageSize });
+    const res = await operator.list({
+      page: pageNum,
+      pageSize,
+    });
     images.value = res.items;
     // images.value = res.items.map(item => item.pic_url);
     total.value = res.total;
@@ -135,23 +150,6 @@ async function fetchDrawingList(pageNum = 1, pageSize = 9) {
   }
 }
 
-// 获取图片详情
-const fetchDrawingDetail = async (id: number) => {
-  try {
-    const res = await getDrawingDetail(id);
-    // 更新 images 中对应项
-    const idx = images.value.findIndex((item) => item.id === id);
-    if (idx !== -1) {
-      images.value[idx] = { ...images.value[idx], ...res.data };
-    }
-    // 处理详情数据
-    return res;
-  } catch {
-    message.error('获取图片详情失败');
-    return null;
-  }
-};
-
 // 页面加载时调用获取图片列表
 onMounted(() => {
   fetchDrawingList();