feat(multimodal): support document image extraction and inline vision processing

Added document image extraction capability for PDF and DOCX files, including page/index metadata and storage integration. Extended `process_files` with `document_image_recognition` flag to conditionally enable vision-based image processing when model supports it. Updated knowledge repository and workflow node logic to enforce status=1 checks. Added PyMuPDF dependency.

api/app/services/app_chat_service.py

@@ -16,7 +16,7 @@ from app.models import MultiAgentConfig, AgentConfig, ModelType
 from app.models import WorkflowConfig
 from app.repositories.tool_repository import ToolRepository
 from app.schemas import DraftRunRequest
-from app.schemas.app_schema import FileInput
+from app.schemas.app_schema import FileInput, FileType
 from app.schemas.model_schema import ModelInfo
 from app.schemas.prompt_schema import render_prompt_message, PromptMessageRole
 from app.services.conversation_service import ConversationService
@@ -165,8 +165,27 @@ class AppChatService:
         processed_files = None
         if files:
             multimodal_service = MultimodalService(self.db, model_info)
-            processed_files = await multimodal_service.process_files(files)
+            fu_config = features_config.get("file_upload", {})
+            if hasattr(fu_config, "model_dump"):
+                fu_config = fu_config.model_dump()
+            doc_img_recognition = isinstance(fu_config, dict) and fu_config.get("document_image_recognition", False)
+            processed_files = await multimodal_service.process_files(
+                files, document_image_recognition=doc_img_recognition
+            )
             logger.info(f"处理了 {len(processed_files)} 个文件")
+            if doc_img_recognition and "vision" in (api_key_obj.capability or []) and any(
+                f.type == FileType.DOCUMENT for f in files
+            ):
+                from langchain.agents import create_agent
+                agent.system_prompt += (
+                    "\n\n文档中包含图片，图片位置已在文本中以 [第N页 第M张图片]: URL 标记。"
+                    "请在回答中用 Markdown 格式 ![描述](URL) 展示相关图片，做到图文并茂。"
+                )
+                agent.agent = create_agent(
+                    model=agent.llm,
+                    tools=agent._wrap_tools_with_tracking(agent.tools) if agent.tools else None,
+                    system_prompt=agent.system_prompt
+                )
         # 为需要运行时上下文的工具注入上下文
         for t in tools:
             if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
@@ -438,8 +457,27 @@ class AppChatService:
             processed_files = None
             if files:
                 multimodal_service = MultimodalService(self.db, model_info)
-                processed_files = await multimodal_service.process_files(files)
+                fu_config = features_config.get("file_upload", {})
+                if hasattr(fu_config, "model_dump"):
+                    fu_config = fu_config.model_dump()
+                doc_img_recognition = isinstance(fu_config, dict) and fu_config.get("document_image_recognition", False)
+                processed_files = await multimodal_service.process_files(
+                    files, document_image_recognition=doc_img_recognition
+                )
                 logger.info(f"处理了 {len(processed_files)} 个文件")
+                if doc_img_recognition and "vision" in (api_key_obj.capability or []) and any(
+                    f.type == FileType.DOCUMENT for f in files
+                ):
+                    from langchain.agents import create_agent
+                    agent.system_prompt += (
+                        "\n\n文档中包含图片，图片位置已在文本中以 [第N页 第M张图片]: URL 标记。"
+                        "请在回答中用 Markdown 格式 ![描述](URL) 展示相关图片，做到图文并茂。"
+                    )
+                    agent.agent = create_agent(
+                        model=agent.llm,
+                        tools=agent._wrap_tools_with_tracking(agent.tools) if agent.tools else None,
+                        system_prompt=agent.system_prompt
+                    )
 
             # 为需要运行时上下文的工具注入上下文
             for t in tools:

api/app/services/auth_service.py

@@ -1,3 +1,5 @@
+import uuid
+
 from sqlalchemy.orm import Session
 from typing import Optional, Tuple, Union
 import jwt
@@ -130,7 +132,7 @@ def register_user_with_invite(
     email: str,
     password: str,
     invite_token: str,
-    workspace_id: str,
+    workspace_id: uuid.UUID,
     username: Optional[str] = None,
 ) -> User:
     """
@@ -147,6 +149,7 @@ def register_user_with_invite(
     from app.schemas.user_schema import UserCreate
     from app.schemas.workspace_schema import InviteAcceptRequest
     from app.services import user_service, workspace_service
+    from app.repositories import workspace_repository as ws_repo
     from app.core.logging_config import get_business_logger
     
     logger = get_business_logger()
@@ -159,7 +162,8 @@ def register_user_with_invite(
             password=password,
             username=email.split('@')[0] if not username else username
         )
-        user = user_service.create_user(db=db, user=user_create)
+        workspace = ws_repo.get_workspace_by_id(db=db, workspace_id=workspace_id)
+        user = user_service.create_user(db=db, user=user_create, workspace=workspace)
         logger.info(f"用户创建成功: {user.email} (ID: {user.id})")
         
         # 接受工作空间邀请（此时用户已成为工作空间成员，并且会 commit）

api/app/services/draft_run_service.py

@@ -10,6 +10,7 @@ import time
 import uuid
 from typing import Any, AsyncGenerator, Dict, List, Optional
 
+from langchain.agents import create_agent
 from langchain.tools import tool
 from pydantic import BaseModel, Field
 from sqlalchemy import select
@@ -27,7 +28,7 @@ from app.core.rag.nlp.search import knowledge_retrieval
 from app.db import get_db_context
 from app.models import AgentConfig, ModelConfig
 from app.repositories.tool_repository import ToolRepository
-from app.schemas.app_schema import FileInput, Citation
+from app.schemas.app_schema import FileInput, Citation, FileType
 from app.schemas.model_schema import ModelInfo
 from app.schemas.prompt_schema import PromptMessageRole, render_prompt_message
 from app.services.conversation_service import ConversationService
@@ -637,12 +638,35 @@ class AgentRunService:
 
             # 6. 处理多模态文件
             processed_files = None
+            has_doc_with_images = False
             if files:
-                # 获取 provider 信息
                 provider = api_key_config.get("provider", "openai")
                 multimodal_service = MultimodalService(self.db, model_info)
-                processed_files = await multimodal_service.process_files(files)
+                fu_config = features_config.get("file_upload", {})
+                if hasattr(fu_config, "model_dump"):
+                    fu_config = fu_config.model_dump()
+                doc_img_recognition = isinstance(fu_config, dict) and fu_config.get("document_image_recognition", False)
+                processed_files = await multimodal_service.process_files(
+                    files, document_image_recognition=doc_img_recognition
+                )
                 logger.info(f"处理了 {len(processed_files)} 个文件，provider={provider}")
+                capability = api_key_config.get("capability", [])
+                has_doc_with_images = (
+                    doc_img_recognition
+                    and "vision" in capability
+                    and any(f.type == FileType.DOCUMENT for f in files)
+                )
+            if has_doc_with_images:
+                agent.system_prompt += (
+                    "\n\n文档中包含图片，图片位置已在文本中以 [第N页 第M张图片]: URL 标记。"
+                    "请在回答中用 Markdown 格式 ![描述](URL) 展示相关图片，做到图文并茂。"
+                )
+                # 重建 agent graph 以使新 system_prompt 生效
+                agent.agent = create_agent(
+                    model=agent.llm,
+                    tools=agent._wrap_tools_with_tracking(agent.tools) if agent.tools else None,
+                    system_prompt=agent.system_prompt
+                )
             # 为需要运行时上下文的工具注入上下文
             for t in tools:
                 if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):
@@ -895,12 +919,34 @@ class AgentRunService:
 
             # 6. 处理多模态文件
             processed_files = None
+            has_doc_with_images = False
             if files:
-                # 获取 provider 信息
                 provider = api_key_config.get("provider", "openai")
                 multimodal_service = MultimodalService(self.db, model_info)
-                processed_files = await multimodal_service.process_files(files)
+                fu_config = features_config.get("file_upload", {})
+                if hasattr(fu_config, "model_dump"):
+                    fu_config = fu_config.model_dump()
+                doc_img_recognition = isinstance(fu_config, dict) and fu_config.get("document_image_recognition", False)
+                processed_files = await multimodal_service.process_files(
+                    files, document_image_recognition=doc_img_recognition
+                )
                 logger.info(f"处理了 {len(processed_files)} 个文件，provider={provider}")
+                capability = api_key_config.get("capability", [])
+                has_doc_with_images = (
+                    doc_img_recognition
+                    and "vision" in capability
+                    and any(f.type == FileType.DOCUMENT for f in files)
+                )
+            if has_doc_with_images:
+                agent.system_prompt += (
+                    "\n\n文档中包含图片，图片位置已在文本中以 [第N页 第M张图片]: URL 标记。"
+                    "请在回答中用 Markdown 格式 ![描述](URL) 展示相关图片，做到图文并茂。"
+                )
+                agent.agent = create_agent(
+                    model=agent.llm,
+                    tools=agent._wrap_tools_with_tracking(agent.tools) if agent.tools else None,
+                    system_prompt=agent.system_prompt
+                )
             # 为需要运行时上下文的工具注入上下文
             for t in tools:
                 if hasattr(t, 'tool_instance') and hasattr(t.tool_instance, 'set_runtime_context'):

api/app/services/memory_dashboard_service.py

@@ -821,7 +821,7 @@ def get_rag_content(
         for document in documents:
             try:
                 kb = knowledge_repository.get_knowledge_by_id(db, document.kb_id)
-                if not kb:
+                if not (kb and kb.status == 1):
                     business_logger.warning(f"知识库不存在: kb_id={document.kb_id}")
                     continue
                 

api/app/services/multimodal_service.py

@@ -344,6 +344,7 @@ class MultimodalService:
     async def process_files(
             self,
             files: Optional[List[FileInput]],
+            document_image_recognition: bool = False,
     ) -> List[Dict[str, Any]]:
         """
         处理文件列表，返回 LLM 可用的格式
@@ -379,6 +380,31 @@ class MultimodalService:
                 elif file.type == FileType.DOCUMENT:
                     is_support, content = await self._process_document(file, strategy)
                     result.append(content)
+                    # 仅当开关开启且模型支持视觉时，才提取文档内嵌图片
+                    if document_image_recognition and "vision" in self.capability:
+                        img_infos = await self.extract_document_images(file)
+                        for img_info in img_infos:
+                            page = img_info["page"]
+                            index = img_info["index"]
+                            ext = img_info.get("ext", "png")
+                            try:
+                                _, img_url = await self._save_doc_image_to_storage(img_info["bytes"], ext)
+                                placeholder = f"第{page}页 第{index + 1}张图片" if page > 0 else f"第{index + 1}张图片"
+                                # 在文本内容中追加图片位置标记
+                                if result and result[-1].get("type") in ("text", "document"):
+                                    key = "text" if "text" in result[-1] else list(result[-1].keys())[-1]
+                                    result[-1][key] = result[-1].get(key, "") + f"\n[{placeholder}]: {img_url}"
+                                # 将图片以视觉格式追加到消息内容中
+                                img_file = FileInput(
+                                    type=FileType.IMAGE,
+                                    transfer_method=TransferMethod.REMOTE_URL,
+                                    url=img_url,
+                                    file_type="image/png",
+                                )
+                                _, img_content = await self._process_image(img_file, strategy_class(img_file))
+                                result.append(img_content)
+                            except Exception as img_err:
+                                logger.warning(f"文档图片处理失败: {img_err}")
                 elif file.type == FileType.AUDIO and "audio" in self.capability:
                     is_support, content = await self._process_audio(file, strategy)
                     result.append(content)
@@ -431,12 +457,8 @@ class MultimodalService:
         """
         处理文档文件（PDF、Word 等）
         
-        Args:
-            file: 文档文件输入
-            strategy: 格式化策略
-            
         Returns:
-            Dict: 根据 provider 返回不同格式的文档内容
+            仅返回文本内容（图片通过 process_files 中的额外步骤追加）
         """
         if file.transfer_method == TransferMethod.REMOTE_URL:
             return True, {
@@ -444,19 +466,63 @@ class MultimodalService:
                 "text": f"<document url=\"{file.url}\">\n{await self.extract_document_text(file)}\n</document>"
             }
         else:
-            # 本地文件，提取文本内容
             server_url = settings.FILE_LOCAL_SERVER_URL
             file.url = f"{server_url}/storage/permanent/{file.upload_file_id}"
             text = await self.extract_document_text(file)
             file_metadata = self.db.query(FileMetadata).filter(
                 FileMetadata.id == file.upload_file_id
             ).first()
-
             file_name = file_metadata.file_name if file_metadata else "unknown"
-
-            # 使用策略格式化文档
             return await strategy.format_document(file_name, text)
 
+    async def _save_doc_image_to_storage(
+            self,
+            img_bytes: bytes,
+            ext: str,
+    ) -> tuple[str, str]:
+        """
+        将文档内嵌图片保存到存储后端，写入 FileMetadata。
+        tenant_id / workspace_id 从 api_config 所在的 FileMetadata 上下文获取，
+        无法获取时使用占位 UUID（图片仍可通过 permanent URL 访问）。
+
+        Returns:
+            (file_id_str, permanent_url)
+        """
+        import uuid as _uuid
+        from app.services.file_storage_service import FileStorageService, generate_file_key
+        from app.db import get_db_context
+
+        file_id = _uuid.uuid4()
+        file_ext = f".{ext}" if not ext.startswith(".") else ext
+        content_type = f"image/{ext}"
+
+        # tenant_id / workspace_id 尽量从已有 FileMetadata 推断，否则用占位值
+        placeholder = _uuid.UUID(int=0)
+        tenant_id = placeholder
+        workspace_id = placeholder
+
+        file_key = generate_file_key(tenant_id, workspace_id, file_id, file_ext)
+        storage_svc = FileStorageService()
+        await storage_svc.storage.upload(file_key, img_bytes, content_type)
+
+        with get_db_context() as db:
+            meta = FileMetadata(
+                id=file_id,
+                tenant_id=tenant_id,
+                workspace_id=workspace_id,
+                file_key=file_key,
+                file_name=f"doc_image_{file_id}{file_ext}",
+                file_ext=file_ext,
+                file_size=len(img_bytes),
+                content_type=content_type,
+                status="completed",
+            )
+            db.add(meta)
+            db.commit()
+
+        url = f"{settings.FILE_LOCAL_SERVER_URL}/storage/permanent/{file_id}"
+        return str(file_id), url
+
     async def _process_audio(self, file: FileInput, strategy) -> tuple[bool, Dict[str, Any]]:
         """
         处理音频文件
@@ -582,6 +648,84 @@ class MultimodalService:
             logger.error(f"Failed to load file. - {e}")
             return "[Failed to load file.]"
 
+    async def extract_document_images(self, file: FileInput) -> list[dict]:
+        """
+        提取文档中的内嵌图片（支持 PDF 和 DOCX），附带位置信息。
+
+        Returns:
+            list[dict]: 每项包含:
+                - bytes: 图片二进制
+                - page: 所在页码（PDF 从 1 开始，DOCX 为 0）
+                - index: 该页/文档内的图片序号（从 0 开始）
+                - ext: 图片扩展名（如 png、jpeg）
+        """
+        try:
+            file_content = file.get_content()
+            if not file_content:
+                async with httpx.AsyncClient(timeout=30.0) as client:
+                    response = await client.get(file.url, follow_redirects=True)
+                    response.raise_for_status()
+                    file_content = response.content
+                    file.set_content(file_content)
+
+            file_mime_type = magic.from_buffer(file_content, mime=True)
+            if file_mime_type in PDF_MIME:
+                return self._extract_pdf_images(file_content)
+            elif self._is_word_file(file_content, file_mime_type):
+                return self._extract_docx_images(file_content)
+            return []
+        except Exception as e:
+            logger.error(f"提取文档图片失败: {e}")
+            return []
+
+    @staticmethod
+    def _extract_pdf_images(file_content: bytes) -> list[dict]:
+        """从 PDF 提取内嵌图片，附带页码和序号"""
+        images = []
+        try:
+            import fitz  # PyMuPDF
+            doc = fitz.open(stream=file_content, filetype="pdf")
+            for page_num, page in enumerate(doc, start=1):
+                for idx, img in enumerate(page.get_images(full=True)):
+                    xref = img[0]
+                    base_image = doc.extract_image(xref)
+                    images.append({
+                        "bytes": base_image["image"],
+                        "ext": base_image.get("ext", "png"),
+                        "page": page_num,
+                        "index": idx,
+                    })
+            doc.close()
+        except ImportError:
+            logger.warning("PyMuPDF 未安装，无法提取 PDF 图片，请执行: uv add pymupdf")
+        except Exception as e:
+            logger.error(f"提取 PDF 图片失败: {e}")
+        return images
+
+    @staticmethod
+    def _extract_docx_images(file_content: bytes) -> list[dict]:
+        """从 DOCX 提取内嵌图片，附带序号（DOCX 无页码概念，page 固定为 0）"""
+        images = []
+        try:
+            if file_content[:2] != b'PK':
+                return []
+            with zipfile.ZipFile(io.BytesIO(file_content)) as zf:
+                media_files = sorted(
+                    name for name in zf.namelist()
+                    if name.startswith("word/media/") and not name.endswith("/")
+                )
+                for idx, name in enumerate(media_files):
+                    ext = name.rsplit(".", 1)[-1].lower() if "." in name else "png"
+                    images.append({
+                        "bytes": zf.read(name),
+                        "ext": ext,
+                        "page": 0,
+                        "index": idx,
+                    })
+        except Exception as e:
+            logger.error(f"提取 DOCX 图片失败: {e}")
+        return images
+
     @staticmethod
     async def _extract_pdf_text(file_content: bytes) -> str:
         """提取 PDF 文本"""

api/app/services/user_service.py

@@ -8,6 +8,7 @@ from sqlalchemy.orm import Session
 import uuid
 
 from app.aioRedis import aio_redis_set, aio_redis_get, aio_redis_delete
+from app.models import Workspace
 from app.models.user_model import User
 from app.repositories import user_repository
 from app.schemas.user_schema import UserCreate
@@ -74,7 +75,7 @@ def create_initial_superuser(db: Session):
         )
 
 
-def create_user(db: Session, user: UserCreate) -> User:
+def create_user(db: Session, user: UserCreate, workspace: Workspace) -> User:
     business_logger.info(f"创建用户: {user.username}, email: {user.email}")
     
     try:
@@ -93,24 +94,9 @@ def create_user(db: Session, user: UserCreate) -> User:
         business_logger.debug(f"开始创建用户: {user.username}")
         hashed_password = get_password_hash(user.password)
         
-        # 获取默认租户（第一个活跃租户）
-        from app.repositories.tenant_repository import TenantRepository
-        tenant_repo = TenantRepository(db)
-        tenants = tenant_repo.get_tenants(skip=0, limit=1, is_active=True)
-        
-        if not tenants:
-            business_logger.error("系统中没有可用的租户")
-            raise BusinessException(
-                "系统配置错误：没有可用的租户", 
-                code=BizCode.TENANT_NOT_FOUND,
-                context={"username": user.username, "email": user.email}
-            )
-        
-        default_tenant = tenants[0]
-        
         new_user = user_repository.create_user(
             db=db, user=user, hashed_password=hashed_password, 
-            tenant_id=default_tenant.id, is_superuser=False
+            tenant_id=workspace.tenant_id, is_superuser=False
         )
 
         db.commit()

api/app/services/workflow_service.py

@@ -694,7 +694,8 @@ class WorkflowService:
             "nodes": config.nodes,
             "edges": config.edges,
             "variables": config.variables,
-            "execution_config": config.execution_config
+            "execution_config": config.execution_config,
+            "features": feature_configs
         }
 
         try:
@@ -894,7 +895,8 @@ class WorkflowService:
             "nodes": config.nodes,
             "edges": config.edges,
             "variables": config.variables,
-            "execution_config": config.execution_config
+            "execution_config": config.execution_config,
+            "features": feature_configs
         }
 
         try: