feat: 增强 AI-Core 文档解析器

- 添加 VLM 客户端支持
- 优化解析器配置
- 添加配置示例文件
- 生成新的 gRPC protobuf 文件

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

ai-core/config.example.yaml

@@ -0,0 +1,18 @@
+# AI-Core 配置文件示例
+# 复制此文件为 config.yaml 并填入实际配置
+
+# VLM 配置（可选）
+# 如果配置了 VLM，图片文件会自动使用 VLM 解析
+vlm:
+  enabled: false  # 是否启用 VLM
+  provider: "openai"  # openai / anthropic / qwen
+  model: "gpt-4o"  # 模型名称
+  api_key: ""  # API Key
+  base_url: ""  # 自定义 API 地址（可选）
+  prompt: ""  # 自定义提示词（可选）
+
+# 服务配置
+server:
+  port: 50051
+  max_workers: 10
+  log_level: INFO

ai-core/parser/config.py

@@ -0,0 +1,84 @@
+"""
+配置管理模块
+"""
+import os
+import yaml
+import logging
+from typing import Optional, Dict, Any
+
+logger = logging.getLogger(__name__)
+
+# 默认配置
+DEFAULT_CONFIG = {
+    "vlm": {
+        "enabled": False,
+        "provider": "openai",
+        "model": "gpt-4o",
+        "api_key": "",
+        "base_url": "",
+        "prompt": ""
+    },
+    "server": {
+        "port": 50051,
+        "max_workers": 10,
+        "log_level": "INFO"
+    }
+}
+
+
+def load_config(config_path: Optional[str] = None) -> Dict[str, Any]:
+    """加载配置文件"""
+    if config_path is None:
+        # 默认查找 config.yaml
+        base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+        config_path = os.path.join(base_dir, "config.yaml")
+
+    # 环境变量覆盖
+    vlm_api_key = os.environ.get("VLM_API_KEY", "")
+    if vlm_api_key:
+        DEFAULT_CONFIG["vlm"]["api_key"] = vlm_api_key
+        DEFAULT_CONFIG["vlm"]["enabled"] = True
+        logger.info("VLM enabled via environment variable")
+
+    vlm_provider = os.environ.get("VLM_PROVIDER", "")
+    if vlm_provider:
+        DEFAULT_CONFIG["vlm"]["provider"] = vlm_provider
+
+    vlm_model = os.environ.get("VLM_MODEL", "")
+    if vlm_model:
+        DEFAULT_CONFIG["vlm"]["model"] = vlm_model
+
+    # 尝试加载配置文件
+    if os.path.exists(config_path):
+        try:
+            with open(config_path, 'r', encoding='utf-8') as f:
+                file_config = yaml.safe_load(f)
+                if file_config:
+                    # 合并配置
+                    for key in file_config:
+                        if key in DEFAULT_CONFIG:
+                            DEFAULT_CONFIG[key].update(file_config[key])
+                    logger.info(f"Loaded config from {config_path}")
+        except Exception as e:
+            logger.warning(f"Failed to load config: {e}")
+
+    # 检查 VLM 是否有效
+    if DEFAULT_CONFIG["vlm"]["enabled"] and not DEFAULT_CONFIG["vlm"]["api_key"]:
+        logger.warning("VLM enabled but API key is empty, disabling VLM")
+        DEFAULT_CONFIG["vlm"]["enabled"] = False
+
+    return DEFAULT_CONFIG
+
+
+def get_vlm_config() -> Optional[Dict[str, Any]]:
+    """获取 VLM 配置"""
+    config = load_config()
+    if config.get("vlm", {}).get("enabled") and config["vlm"].get("api_key"):
+        return config["vlm"]
+    return None
+
+
+def get_server_config() -> Dict[str, Any]:
+    """获取服务器配置"""
+    config = load_config()
+    return config.get("server", DEFAULT_CONFIG["server"])

ai-core/parser/parser.py

@@ -1,39 +1,68 @@
 import logging
 import os
 import tempfile
-from typing import Optional
+from typing import Optional, Dict, Any
 from markitdown import MarkItDown
 
+from .vlm_client import VLMClient
+from .config import get_vlm_config
+
 logger = logging.getLogger(__name__)
 
 
 class Parser:
-    """基于 MarkItDown 的统一文档解析器
-    
+    """基于 MarkItDown + VLM 的统一文档解析器
+
     支持格式：PDF、DOCX、DOC、PPTX、PPT、XLSX、XLS、CSV、图片、网页、Markdown 等
+
+    VLM 解析：
+    - 方式一：启动时配置（config.yaml 或环境变量）
+    - 方式二：gRPC 请求时传入 VLM 配置（优先级更高）
     """
 
     def __init__(self):
         self.markitdown = MarkItDown()
-        logger.info("Parser initialized with MarkItDown")
+        self.vlm_client: Optional[VLMClient] = None
 
-    def parse(self, file_path: str, file_type: Optional[str] = None) -> dict:
+        # 尝试加载配置的 VLM
+        vlm_config = get_vlm_config()
+        if vlm_config:
+            self.vlm_client = VLMClient(vlm_config)
+            logger.info(f"VLM enabled: provider={vlm_config.get('provider')}, model={vlm_config.get('model')}")
+        else:
+            logger.info("VLM not configured, using MarkItDown only")
+
+    def set_vlm_config(self, config: Dict[str, Any]) -> None:
+        """手动设置 VLM 配置（优先级高于全局配置）"""
+        if config and config.get("enabled") and config.get("api_key"):
+            self.vlm_client = VLMClient(config)
+            logger.info(f"VLM enabled: provider={config.get('provider')}, model={config.get('model')}")
+        else:
+            self.vlm_client = None
+            logger.info("VLM disabled")
+
+    def parse(self, file_path: str, file_type: Optional[str] = None, vlm_config: Optional[Dict[str, Any]] = None) -> dict:
         """解析文档为 Markdown
-        
+
         Args:
             file_path: 文件路径或 URL
             file_type: 文件类型（可选，MarkItDown 会自动检测）
-            
+            vlm_config: VLM 配置（可选，优先级高于全局配置）
+
         Returns:
             dict: 包含 markdown 内容和元数据
         """
+        # 如果有 VLM 配置，覆盖全局配置
+        if vlm_config:
+            self.set_vlm_config(vlm_config)
+
         try:
             logger.info(f"Parsing file: {file_path}")
-            
+
             result = self.markitdown.convert(file_path)
-            
+
             logger.info(f"Parse successful: {len(result.text_content)} characters")
-            
+
             return {
                 "success": True,
                 "content": result.text_content,
@@ -49,29 +78,40 @@ class Parser:
                 "error": str(e)
             }
 
-    def parse_bytes(self, content: bytes, file_name: str, file_type: Optional[str] = None) -> dict:
+    def parse_bytes(self, content: bytes, file_name: str, file_type: Optional[str] = None, vlm_config: Optional[Dict[str, Any]] = None) -> dict:
         """解析字节内容为 Markdown
-        
+
         Args:
             content: 文件字节内容
             file_name: 文件名
             file_type: 文件类型（可选）
-            
+            vlm_config: VLM 配置（可选，优先级高于全局配置）
+
         Returns:
             dict: 包含 markdown 内容和元数据
         """
+        # 如果有 VLM 配置，覆盖全局配置
+        if vlm_config:
+            self.set_vlm_config(vlm_config)
+
         try:
             logger.info(f"Parsing bytes: {file_name}, size: {len(content)} bytes")
-            
+
+            # 检查是否应该使用 VLM（根据文件名自动判断）
+            if self._should_use_vlm(file_name):
+                logger.info("Using VLM for parsing")
+                return self._parse_with_vlm(content, file_name)
+
+            # 否则使用 MarkItDown
             with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file_name)[1] or '') as temp_file:
                 temp_file.write(content)
                 temp_path = temp_file.name
-            
+
             try:
                 result = self.markitdown.convert(temp_path)
-                
+
                 logger.info(f"Parse successful: {len(result.text_content)} characters")
-                
+
                 return {
                     "success": True,
                     "content": result.text_content,
@@ -89,10 +129,69 @@ class Parser:
                 "error": str(e)
             }
 
+    def _should_use_vlm(self, file_name: str) -> bool:
+        """判断是否应该使用 VLM"""
+        if not self.vlm_client:
+            return False
+
+        # 图片文件使用 VLM
+        image_exts = ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.webp', '.tiff']
+        ext = os.path.splitext(file_name)[1].lower()
+        return ext in image_exts
+
+    def _parse_with_vlm(self, content: bytes, file_name: str) -> dict:
+        """使用 VLM 解析"""
+        if not self.vlm_client:
+            return {
+                "success": False,
+                "content": "",
+                "content_length": 0,
+                "error": "VLM not configured"
+            }
+
+        # 确定 MIME 类型
+        ext = os.path.splitext(file_name)[1].lower()
+        mime_types = {
+            '.jpg': 'image/jpeg',
+            '.jpeg': 'image/jpeg',
+            '.png': 'image/png',
+            '.gif': 'image/gif',
+            '.bmp': 'image/bmp',
+            '.webp': 'image/webp',
+            '.tiff': 'image/tiff',
+        }
+        mime_type = mime_types.get(ext, 'image/png')
+
+        try:
+            result = self.vlm_client.analyze_image(content, mime_type)
+
+            if result.get("success"):
+                return {
+                    "success": True,
+                    "content": result["content"],
+                    "content_length": len(result["content"]),
+                    "metadata": {"vlm_used": True}
+                }
+            else:
+                return {
+                    "success": False,
+                    "content": "",
+                    "content_length": 0,
+                    "error": result.get("error", "VLM parsing failed")
+                }
+        except Exception as e:
+            logger.error(f"VLM parsing error: {e}")
+            return {
+                "success": False,
+                "content": "",
+                "content_length": 0,
+                "error": str(e)
+            }
+
 
 if __name__ == "__main__":
     parser = Parser()
-    
+
     # 测试
     test_url = "https://example.com"
     result = parser.parse(test_url)

ai-core/parser/vlm_client.py

@@ -0,0 +1,209 @@
+"""
+VLM 客户端 - 用于调用 VLM 模型进行文档理解
+"""
+import logging
+import base64
+import requests
+from typing import Optional, Dict, Any
+
+logger = logging.getLogger(__name__)
+
+
+class VLMClient:
+    """VLM 客户端，支持多种提供商"""
+
+    def __init__(self, config: Dict[str, Any]):
+        """
+        初始化 VLM 客户端
+
+        Args:
+            config: VLM 配置，包含 provider, model, api_key, base_url, prompt 等
+        """
+        self.config = config
+        self.provider = config.get("provider", "openai")
+        self.model = config.get("model", "gpt-4o")
+        self.api_key = config.get("api_key", "")
+        self.base_url = config.get("base_url", "")
+        self.prompt = config.get("prompt", "") or self._default_prompt()
+
+        logger.info(f"VLMClient initialized: provider={self.provider}, model={self.model}")
+
+    def _default_prompt(self) -> str:
+        """默认提示词"""
+        return """请分析这张图片中的文档内容，并将其转换为 Markdown 格式。
+要求：
+1. 保持原文的格式和结构
+2. 表格用 Markdown 表格格式
+3. 标题用 # ## ### 标记
+4. 代码块用 ``` 标记
+5. 尽量保留原文的所有信息"""
+
+    def analyze_image(self, image_data: bytes, mime_type: str = "image/png") -> Dict[str, Any]:
+        """
+        使用 VLM 分析图片
+
+        Args:
+            image_data: 图片二进制数据
+            mime_type: 图片 MIME 类型
+
+        Returns:
+            包含分析结果的字典
+        """
+        if self.provider == "openai":
+            return self._call_openai(image_data, mime_type)
+        elif self.provider == "anthropic":
+            return self._call_anthropic(image_data, mime_type)
+        elif self.provider == "qwen":
+            return self._call_qwen(image_data, mime_type)
+        else:
+            return {
+                "success": False,
+                "content": "",
+                "error": f"Unsupported provider: {self.provider}"
+            }
+
+    def _call_openai(self, image_data: bytes, mime_type: str) -> Dict[str, Any]:
+        """调用 OpenAI GPT-4o API"""
+        try:
+            url = (self.base_url or "https://api.openai.com/v1") + "/chat/completions"
+
+            # Base64 编码图片
+            image_base64 = base64.b64encode(image_data).decode("utf-8")
+            data_url = f"data:{mime_type};base64,{image_base64}"
+
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json"
+            }
+
+            payload = {
+                "model": self.model,
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {"type": "text", "text": self.prompt},
+                            {"type": "image_url", "image_url": {"url": data_url}}
+                        ]
+                    }
+                ],
+                "max_tokens": 4096
+            }
+
+            response = requests.post(url, headers=headers, json=payload, timeout=120)
+            response.raise_for_status()
+
+            result = response.json()
+            content = result["choices"][0]["message"]["content"]
+
+            return {
+                "success": True,
+                "content": content,
+                "usage": result.get("usage", {})
+            }
+        except Exception as e:
+            logger.error(f"OpenAI API error: {e}")
+            return {
+                "success": False,
+                "content": "",
+                "error": str(e)
+            }
+
+    def _call_anthropic(self, image_data: bytes, mime_type: str) -> Dict[str, Any]:
+        """调用 Anthropic Claude API"""
+        try:
+            url = (self.base_url or "https://api.anthropic.com/v1") + "/messages"
+
+            image_base64 = base64.b64encode(image_data).decode("utf-8")
+
+            headers = {
+                "x-api-key": self.api_key,
+                "anthropic-version": "2023-06-01",
+                "Content-Type": "application/json"
+            }
+
+            # Anthropic 支持 image 类型
+            payload = {
+                "model": self.model,
+                "max_tokens": 4096,
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {"type": "text", "text": self.prompt},
+                            {
+                                "type": "image",
+                                "source": {
+                                    "type": "base64",
+                                    "media_type": mime_type,
+                                    "data": image_base64
+                                }
+                            }
+                        ]
+                    }
+                ]
+            }
+
+            response = requests.post(url, headers=headers, json=payload, timeout=120)
+            response.raise_for_status()
+
+            result = response.json()
+            content = result["content"][0]["text"]
+
+            return {
+                "success": True,
+                "content": content,
+                "usage": result.get("usage", {})
+            }
+        except Exception as e:
+            logger.error(f"Anthropic API error: {e}")
+            return {
+                "success": False,
+                "content": "",
+                "error": str(e)
+            }
+
+    def _call_qwen(self, image_data: bytes, mime_type: str) -> Dict[str, Any]:
+        """调用阿里 Qwen VL API"""
+        try:
+            url = (self.base_url or "https://dashscope.aliyuncs.com/compatible-mode/v1") + "/chat/completions"
+
+            image_base64 = base64.b64encode(image_data).decode("utf-8")
+
+            headers = {
+                "Authorization": f"Bearer {self.api_key}",
+                "Content-Type": "application/json"
+            }
+
+            # Qwen 格式
+            payload = {
+                "model": self.model,
+                "messages": [
+                    {
+                        "role": "user",
+                        "content": [
+                            {"type": "text", "text": self.prompt},
+                            {"type": "image_url", "image_url": {"url": f"data:{mime_type};base64,{image_base64}"}}
+                        ]
+                    }
+                ]
+            }
+
+            response = requests.post(url, headers=headers, json=payload, timeout=120)
+            response.raise_for_status()
+
+            result = response.json()
+            content = result["choices"][0]["message"]["content"]
+
+            return {
+                "success": True,
+                "content": content,
+                "usage": {}
+            }
+        except Exception as e:
+            logger.error(f"Qwen API error: {e}")
+            return {
+                "success": False,
+                "content": "",
+                "error": str(e)
+            }

ai-core/proto/document_parser.proto

@@ -16,6 +16,18 @@ message ParseRequest {
   string file_type = 3;
   string parser_engine = 4;
   map<string, string> engine_overrides = 5;
+
+  // VLM 配置（可选）
+  VLMConfig vlm_config = 6;
+}
+
+message VLMConfig {
+  bool enabled = 1;              // 是否启用 VLM
+  string provider = 2;            // VLM 提供商: openai, anthropic, local 等
+  string model = 3;               // 模型名称
+  string api_key = 4;             // API Key
+  string base_url = 5;            // 自定义 API 地址
+  string prompt = 6;              // 自定义提示词
 }
 
 message ParseResponse {
@@ -44,4 +56,4 @@ message EngineInfo {
   repeated string supported_file_types = 3;
   bool available = 4;
   string unavailable_reason = 5;
-}
+}

ai-core/proto/document_parser_pb2.py

@@ -24,7 +24,7 @@ _sym_db = _symbol_database.Default()
 
 
 
-DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x15\x64ocument_parser.proto\x12\tdocparser\"\xdd\x01\n\x0cParseRequest\x12\x10\n\x08\x66ile_url\x18\x01 \x01(\t\x12\x11\n\tfile_name\x18\x02 \x01(\t\x12\x11\n\tfile_type\x18\x03 \x01(\t\x12\x15\n\rparser_engine\x18\x04 \x01(\t\x12\x46\n\x10\x65ngine_overrides\x18\x05 \x03(\x0b\x32,.docparser.ParseRequest.EngineOverridesEntry\x1a\x36\n\x14\x45ngineOverridesEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"\x84\x01\n\rParseResponse\x12\x0f\n\x07success\x18\x01 \x01(\x08\x12\x0f\n\x07\x63ontent\x18\x02 \x01(\t\x12\x0f\n\x07message\x18\x03 \x01(\t\x12\x16\n\x0e\x63ontent_length\x18\x04 \x01(\x05\x12\x11\n\tfile_type\x18\x05 \x01(\t\x12\x15\n\rparser_engine\x18\x06 \x01(\t\"\x07\n\x05\x45mpty\"\xca\x01\n\x18SupportedFormatsResponse\x12\x12\n\nfile_types\x18\x01 \x03(\t\x12]\n\x16\x66ile_type_descriptions\x18\x02 \x03(\x0b\x32=.docparser.SupportedFormatsResponse.FileTypeDescriptionsEntry\x1a;\n\x19\x46ileTypeDescriptionsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"9\n\x0f\x45nginesResponse\x12&\n\x07\x65ngines\x18\x01 \x03(\x0b\x32\x15.docparser.EngineInfo\"|\n\nEngineInfo\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x02 \x01(\t\x12\x1c\n\x14supported_file_types\x18\x03 \x03(\t\x12\x11\n\tavailable\x18\x04 \x01(\x08\x12\x1a\n\x12unavailable_reason\x18\x05 \x01(\t2\xde\x01\n\x0e\x44ocumentParser\x12\x42\n\rParseDocument\x12\x17.docparser.ParseRequest\x1a\x18.docparser.ParseResponse\x12L\n\x13GetSupportedFormats\x12\x10.docparser.Empty\x1a#.docparser.SupportedFormatsResponse\x12:\n\nGetEngines\x12\x10.docparser.Empty\x1a\x1a.docparser.EnginesResponseB\x1aZ\x18x-agents/proto/docparserb\x06proto3')
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x15\x64ocument_parser.proto\x12\tdocparser\"\x87\x02\n\x0cParseRequest\x12\x10\n\x08\x66ile_url\x18\x01 \x01(\t\x12\x11\n\tfile_name\x18\x02 \x01(\t\x12\x11\n\tfile_type\x18\x03 \x01(\t\x12\x15\n\rparser_engine\x18\x04 \x01(\t\x12\x46\n\x10\x65ngine_overrides\x18\x05 \x03(\x0b\x32,.docparser.ParseRequest.EngineOverridesEntry\x12(\n\nvlm_config\x18\x06 \x01(\x0b\x32\x14.docparser.VLMConfig\x1a\x36\n\x14\x45ngineOverridesEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"p\n\tVLMConfig\x12\x0f\n\x07\x65nabled\x18\x01 \x01(\x08\x12\x10\n\x08provider\x18\x02 \x01(\t\x12\r\n\x05model\x18\x03 \x01(\t\x12\x0f\n\x07\x61pi_key\x18\x04 \x01(\t\x12\x10\n\x08\x62\x61se_url\x18\x05 \x01(\t\x12\x0e\n\x06prompt\x18\x06 \x01(\t\"\x84\x01\n\rParseResponse\x12\x0f\n\x07success\x18\x01 \x01(\x08\x12\x0f\n\x07\x63ontent\x18\x02 \x01(\t\x12\x0f\n\x07message\x18\x03 \x01(\t\x12\x16\n\x0e\x63ontent_length\x18\x04 \x01(\x05\x12\x11\n\tfile_type\x18\x05 \x01(\t\x12\x15\n\rparser_engine\x18\x06 \x01(\t\"\x07\n\x05\x45mpty\"\xca\x01\n\x18SupportedFormatsResponse\x12\x12\n\nfile_types\x18\x01 \x03(\t\x12]\n\x16\x66ile_type_descriptions\x18\x02 \x03(\x0b\x32=.docparser.SupportedFormatsResponse.FileTypeDescriptionsEntry\x1a;\n\x19\x46ileTypeDescriptionsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"9\n\x0f\x45nginesResponse\x12&\n\x07\x65ngines\x18\x01 \x03(\x0b\x32\x15.docparser.EngineInfo\"|\n\nEngineInfo\x12\x0c\n\x04name\x18\x01 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x02 \x01(\t\x12\x1c\n\x14supported_file_types\x18\x03 \x03(\t\x12\x11\n\tavailable\x18\x04 \x01(\x08\x12\x1a\n\x12unavailable_reason\x18\x05 \x01(\t2\xde\x01\n\x0e\x44ocumentParser\x12\x42\n\rParseDocument\x12\x17.docparser.ParseRequest\x1a\x18.docparser.ParseResponse\x12L\n\x13GetSupportedFormats\x12\x10.docparser.Empty\x1a#.docparser.SupportedFormatsResponse\x12:\n\nGetEngines\x12\x10.docparser.Empty\x1a\x1a.docparser.EnginesResponseB\x1aZ\x18x-agents/proto/docparserb\x06proto3')
 
 _globals = globals()
 _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@@ -37,21 +37,23 @@ if not _descriptor._USE_C_DESCRIPTORS:
   _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._loaded_options = None
   _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._serialized_options = b'8\001'
   _globals['_PARSEREQUEST']._serialized_start=37
-  _globals['_PARSEREQUEST']._serialized_end=258
-  _globals['_PARSEREQUEST_ENGINEOVERRIDESENTRY']._serialized_start=204
-  _globals['_PARSEREQUEST_ENGINEOVERRIDESENTRY']._serialized_end=258
-  _globals['_PARSERESPONSE']._serialized_start=261
-  _globals['_PARSERESPONSE']._serialized_end=393
-  _globals['_EMPTY']._serialized_start=395
-  _globals['_EMPTY']._serialized_end=402
-  _globals['_SUPPORTEDFORMATSRESPONSE']._serialized_start=405
-  _globals['_SUPPORTEDFORMATSRESPONSE']._serialized_end=607
-  _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._serialized_start=548
-  _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._serialized_end=607
-  _globals['_ENGINESRESPONSE']._serialized_start=609
-  _globals['_ENGINESRESPONSE']._serialized_end=666
-  _globals['_ENGINEINFO']._serialized_start=668
-  _globals['_ENGINEINFO']._serialized_end=792
-  _globals['_DOCUMENTPARSER']._serialized_start=795
-  _globals['_DOCUMENTPARSER']._serialized_end=1017
+  _globals['_PARSEREQUEST']._serialized_end=300
+  _globals['_PARSEREQUEST_ENGINEOVERRIDESENTRY']._serialized_start=246
+  _globals['_PARSEREQUEST_ENGINEOVERRIDESENTRY']._serialized_end=300
+  _globals['_VLMCONFIG']._serialized_start=302
+  _globals['_VLMCONFIG']._serialized_end=414
+  _globals['_PARSERESPONSE']._serialized_start=417
+  _globals['_PARSERESPONSE']._serialized_end=549
+  _globals['_EMPTY']._serialized_start=551
+  _globals['_EMPTY']._serialized_end=558
+  _globals['_SUPPORTEDFORMATSRESPONSE']._serialized_start=561
+  _globals['_SUPPORTEDFORMATSRESPONSE']._serialized_end=763
+  _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._serialized_start=704
+  _globals['_SUPPORTEDFORMATSRESPONSE_FILETYPEDESCRIPTIONSENTRY']._serialized_end=763
+  _globals['_ENGINESRESPONSE']._serialized_start=765
+  _globals['_ENGINESRESPONSE']._serialized_end=822
+  _globals['_ENGINEINFO']._serialized_start=824
+  _globals['_ENGINEINFO']._serialized_end=948
+  _globals['_DOCUMENTPARSER']._serialized_start=951
+  _globals['_DOCUMENTPARSER']._serialized_end=1173
 # @@protoc_insertion_point(module_scope)

ai-core/requirements.txt

@@ -6,8 +6,9 @@ grpcio-tools>=1.60.0
 grpcio-reflection>=1.60.0
 protobuf>=4.25.0
 
-# HTTP 请求
+# 配置文件解析
+pyyaml>=6.0
 requests>=2.31.0
 
-# 文档解析
-markitdown>=0.0.1
+# 文档解析 - markitdown 及其所有依赖
+markitdown[pdf,docx,pptx,xlsx,all]>=0.0.1

ai-core/service/grpc_server.py

@@ -75,6 +75,21 @@ class DocumentParserServicer:
                     content_length=0,
                 )
 
+            # 提取 VLM 配置
+            vlm_config = None
+            if hasattr(request, 'vlm_config') and request.vlm_config:
+                vlm_cfg = request.vlm_config
+                if vlm_cfg.enabled:
+                    vlm_config = {
+                        "enabled": vlm_cfg.enabled,
+                        "provider": vlm_cfg.provider,
+                        "model": vlm_cfg.model,
+                        "api_key": vlm_cfg.api_key,
+                        "base_url": vlm_cfg.base_url,
+                        "prompt": vlm_cfg.prompt,
+                    }
+                    logger.info(f"VLM config: provider={vlm_cfg.provider}, model={vlm_cfg.model}")
+
             logger.info("Downloading file from URL: %s", file_url)
 
             try:
@@ -95,9 +110,9 @@ class DocumentParserServicer:
                     content_length=0,
                 )
 
-            logger.info("Parsing file with MarkItDown")
+            logger.info("Parsing file with MarkItDown + VLM")
 
-            result = self.parser.parse_bytes(content, file_name)
+            result = self.parser.parse_bytes(content, file_name, vlm_config=vlm_config)
 
             if not result.get("success", False):
                 logger.warning("Parser returned failure: %s", result.get("error", "Unknown error"))