优化OCR解析

main-ocr.py

@@ -25,6 +25,12 @@ import sys
 import signal
 from pathlib import Path
 
+# 确保项目根目录在 sys.path 中
+_current_file = Path(__file__).resolve()
+_project_root = _current_file.parent.parent
+if str(_project_root) not in sys.path:
+    sys.path.insert(0, str(_project_root))
+
 import uvicorn
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware

ocr/__init__.py

@@ -20,12 +20,15 @@
 可以直接作为独立模块使用。
 
 使用方法：
-    from ocr import OCR
+    from ocr import OCR, SimplePdfParser
     import cv2
     
     ocr = OCR()
     img = cv2.imread("image.jpg")
     results = ocr(img)
+    
+    parser = SimplePdfParser()
+    result = parser.parse_pdf("document.pdf")
 """
 
 # 处理导入问题：支持直接运行和模块导入
@@ -35,3 +38,4 @@ from pathlib import Path
 
 __all__ = ['OCR', 'TextDetector', 'TextRecognizer', 'SimplePdfParser']
 
+

ocr/api.py

@@ -57,7 +57,7 @@ class ParseResponse(BaseModel):
     data: Optional[dict] = None
 
 
-@router.get(
+@ocr_router.get(
     "/health",
     summary="健康检查",
     description="检查OCR服务的健康状态和配置信息",
@@ -79,7 +79,7 @@ async def health_check():
     }
 
 
-@router.post(
+@ocr_router.post(
     "/parse",
     response_model=ParseResponse,
     summary="上传并解析PDF文件",
@@ -165,7 +165,7 @@ async def parse_pdf_endpoint(
                 logger.warning(f"Failed to delete temp file {temp_file}: {e}")
 
 
-@router.post(
+@ocr_router.post(
     "/parse/bytes",
     response_model=ParseResponse,
     summary="通过二进制数据解析PDF",
@@ -244,7 +244,7 @@ async def parse_pdf_bytes(
                 logger.warning(f"Failed to delete temp file {temp_file}: {e}")
 
 
-@router.post(
+@ocr_router.post(
     "/parse/path",
     response_model=ParseResponse,
     summary="通过文件路径解析PDF",
@@ -315,7 +315,7 @@ async def parse_pdf_path(
         )
 
 
-@router.post(
+@ocr_router.post(
     "/parse_into_bboxes",
     summary="解析PDF并返回边界框",
     description="解析PDF文件并返回文本边界框信息，用于文档结构化处理",
@@ -414,7 +414,7 @@ class RemoveTagResponse(BaseModel):
     text: Optional[str] = None
 
 
-@router.post(
+@ocr_router.post(
     "/remove_tag",
     response_model=RemoveTagResponse,
     summary="移除文本中的位置标签",
@@ -464,7 +464,7 @@ class ExtractPositionsResponse(BaseModel):
     positions: Optional[list] = None
 
 
-@router.post(
+@ocr_router.post(
     "/extract_positions",
     response_model=ExtractPositionsResponse,
     summary="从文本中提取位置信息",

ocr/client.py

@@ -0,0 +1,239 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+"""
+OCR HTTP 客户端工具类
+用于通过 HTTP 接口调用 OCR 服务
+"""
+
+import logging
+import os
+from typing import Optional, Callable, List, Tuple, Any
+
+try:
+    import httpx
+    HAS_HTTPX = True
+except ImportError:
+    HAS_HTTPX = False
+    import aiohttp
+
+logger = logging.getLogger(__name__)
+
+
+class OCRClient:
+    """OCR HTTP 客户端，用于调用 OCR API"""
+    
+    def __init__(self, base_url: Optional[str] = None, timeout: float = 300.0):
+        """
+        初始化 OCR 客户端
+        
+        Args:
+            base_url: OCR 服务的基础 URL，如果不提供则从环境变量 OCR_SERVICE_URL 获取，
+                      如果仍未设置则默认为 http://localhost:8000/api/v1/ocr
+            timeout: 请求超时时间（秒），默认 300 秒
+        """
+        self.base_url = base_url or os.getenv("OCR_SERVICE_URL", "http://localhost:8000/api/v1/ocr")
+        self.timeout = timeout
+        # 移除末尾的斜杠
+        if self.base_url.endswith('/'):
+            self.base_url = self.base_url.rstrip('/')
+    
+    async def _make_request(self, method: str, endpoint: str, **kwargs) -> dict:
+        """内部方法：发送 HTTP 请求"""
+        url = f"{self.base_url}{endpoint}"
+        
+        if HAS_HTTPX:
+            async with httpx.AsyncClient(timeout=self.timeout) as client:
+                response = await client.request(method, url, **kwargs)
+                response.raise_for_status()
+                return response.json()
+        else:
+            async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=self.timeout)) as session:
+                async with session.request(method, url, **kwargs) as response:
+                    response.raise_for_status()
+                    return await response.json()
+    
+    async def remove_tag(self, text: str) -> str:
+        """
+        移除文本中的位置标签
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            移除标签后的文本
+        """
+        response = await self._make_request(
+            "POST",
+            "/remove_tag",
+            json={"text": text}
+        )
+        if response.get("success") and response.get("text") is not None:
+            return response["text"]
+        raise Exception(f"移除标签失败: {response.get('message', '未知错误')}")
+    
+    def remove_tag_sync(self, text: str) -> str:
+        """
+        同步版本的 remove_tag（用于同步代码）
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            移除标签后的文本
+        """
+        import asyncio
+        try:
+            loop = asyncio.get_event_loop()
+            return loop.run_until_complete(self.remove_tag(text))
+        except RuntimeError:
+            # 如果没有事件循环，创建一个新的
+            return asyncio.run(self.remove_tag(text))
+    
+    async def extract_positions(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """
+        从文本中提取位置信息
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            位置信息列表，格式为 [(页码列表, left, right, top, bottom), ...]
+        """
+        response = await self._make_request(
+            "POST",
+            "/extract_positions",
+            json={"text": text}
+        )
+        if response.get("success") and response.get("positions") is not None:
+            # 将响应格式转换为原始格式
+            positions = []
+            for pos in response["positions"]:
+                positions.append((
+                    pos["page_numbers"],
+                    pos["left"],
+                    pos["right"],
+                    pos["top"],
+                    pos["bottom"]
+                ))
+            return positions
+        raise Exception(f"提取位置信息失败: {response.get('message', '未知错误')}")
+    
+    def extract_positions_sync(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """
+        同步版本的 extract_positions（用于同步代码）
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            位置信息列表
+        """
+        import asyncio
+        try:
+            loop = asyncio.get_event_loop()
+            return loop.run_until_complete(self.extract_positions(text))
+        except RuntimeError:
+            return asyncio.run(self.extract_positions(text))
+    
+    async def parse_into_bboxes(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """
+        解析 PDF 并返回边界框
+        
+        Args:
+            pdf_bytes: PDF 文件的二进制数据
+            callback: 进度回调函数 (progress: float, message: str) -> None
+            zoomin: 图像放大倍数（1-5，默认为3）
+            filename: 文件名（仅用于日志）
+            
+        Returns:
+            边界框列表
+        """
+        if HAS_HTTPX:
+            async with httpx.AsyncClient(timeout=self.timeout) as client:
+                # 注意：httpx 需要将文件和数据合并到 files 参数中
+                form_data = {"filename": filename, "zoomin": str(zoomin)}
+                form_files = {"pdf_bytes": (filename, pdf_bytes, "application/pdf")}
+                response = await client.post(
+                    f"{self.base_url}/parse_into_bboxes",
+                    files=form_files,
+                    data=form_data
+                )
+                response.raise_for_status()
+                result = response.json()
+        else:
+            async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=self.timeout)) as session:
+                form_data = aiohttp.FormData()
+                form_data.add_field('pdf_bytes', pdf_bytes, filename=filename, content_type='application/pdf')
+                form_data.add_field('filename', filename)
+                form_data.add_field('zoomin', str(zoomin))
+                
+                async with session.post(
+                    f"{self.base_url}/parse_into_bboxes",
+                    data=form_data
+                ) as response:
+                    response.raise_for_status()
+                    result = await response.json()
+        
+        if result.get("success") and result.get("data") and result["data"].get("bboxes"):
+            return result["data"]["bboxes"]
+        raise Exception(f"解析 PDF 失败: {result.get('message', '未知错误')}")
+    
+    def parse_into_bboxes_sync(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """
+        同步版本的 parse_into_bboxes（用于同步代码）
+        
+        Args:
+            pdf_bytes: PDF 文件的二进制数据
+            callback: 进度回调函数（注意：HTTP 调用中无法实时传递回调，此参数将被忽略）
+            zoomin: 图像放大倍数（1-5，默认为3）
+            filename: 文件名（仅用于日志）
+            
+        Returns:
+            边界框列表
+        """
+        if callback:
+            logger.warning("HTTP 调用中无法使用 callback，将忽略回调函数")
+        import asyncio
+        try:
+            loop = asyncio.get_event_loop()
+            return loop.run_until_complete(self.parse_into_bboxes(pdf_bytes, None, zoomin, filename))
+        except RuntimeError:
+            return asyncio.run(self.parse_into_bboxes(pdf_bytes, None, zoomin, filename))
+
+
+# 全局客户端实例（懒加载）
+_global_client: Optional[OCRClient] = None
+
+
+def get_ocr_client() -> OCRClient:
+    """获取全局 OCR 客户端实例（单例模式）"""
+    global _global_client
+    if _global_client is None:
+        _global_client = OCRClient()
+    return _global_client
+

ocr/service.py

@@ -0,0 +1,290 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+"""
+OCR 服务统一接口
+支持本地OCR模型和HTTP接口两种方式，可通过配置选择
+"""
+
+import logging
+import os
+from abc import ABC, abstractmethod
+from typing import Optional, Callable, List, Tuple, Any
+
+logger = logging.getLogger(__name__)
+
+
+class OCRService(ABC):
+    """OCR服务抽象接口"""
+    
+    @abstractmethod
+    async def remove_tag(self, text: str) -> str:
+        """
+        移除文本中的位置标签
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            清理后的文本
+        """
+        pass
+    
+    @abstractmethod
+    def remove_tag_sync(self, text: str) -> str:
+        """
+        同步版本的 remove_tag（用于同步代码）
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            清理后的文本
+        """
+        pass
+    
+    @abstractmethod
+    async def extract_positions(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """
+        从文本中提取位置信息
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            位置信息列表，格式为 [(页码列表, left, right, top, bottom), ...]
+        """
+        pass
+    
+    @abstractmethod
+    def extract_positions_sync(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """
+        同步版本的 extract_positions（用于同步代码）
+        
+        Args:
+            text: 包含位置标签的文本
+            
+        Returns:
+            位置信息列表
+        """
+        pass
+    
+    @abstractmethod
+    async def parse_into_bboxes(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """
+        解析 PDF 并返回边界框
+        
+        Args:
+            pdf_bytes: PDF 文件的二进制数据
+            callback: 进度回调函数 (progress: float, message: str) -> None
+            zoomin: 图像放大倍数（1-5，默认为3）
+            filename: 文件名（仅用于日志）
+            
+        Returns:
+            边界框列表
+        """
+        pass
+    
+    @abstractmethod
+    def parse_into_bboxes_sync(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """
+        同步版本的 parse_into_bboxes（用于同步代码）
+        
+        Args:
+            pdf_bytes: PDF 文件的二进制数据
+            callback: 进度回调函数（注意：HTTP 调用中无法实时传递回调，此参数将被忽略）
+            zoomin: 图像放大倍数（1-5，默认为3）
+            filename: 文件名（仅用于日志）
+            
+        Returns:
+            边界框列表
+        """
+        pass
+
+
+class LocalOCRService(OCRService):
+    """本地OCR服务实现（直接调用本地OCR模型）"""
+    
+    def __init__(self, parser_instance=None):
+        """
+        初始化本地OCR服务
+        
+        Args:
+            parser_instance: SimplePdfParser 实例，如果不提供则自动创建
+        """
+        if parser_instance is None:
+            from ocr import SimplePdfParser
+            from ocr.config import MODEL_DIR
+            logger.info(f"Initializing local OCR parser with model_dir={MODEL_DIR}")
+            self.parser = SimplePdfParser(model_dir=MODEL_DIR)
+        else:
+            self.parser = parser_instance
+    
+    async def remove_tag(self, text: str) -> str:
+        """使用本地解析器的静态方法移除标签"""
+        # SimplePdfParser.remove_tag 是静态方法，可以直接调用
+        return self.parser.remove_tag(text)
+    
+    def remove_tag_sync(self, text: str) -> str:
+        """同步版本的 remove_tag"""
+        return self.parser.remove_tag(text)
+    
+    async def extract_positions(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """使用本地解析器的静态方法提取位置"""
+        # SimplePdfParser.extract_positions 是静态方法，可以直接调用
+        return self.parser.extract_positions(text)
+    
+    def extract_positions_sync(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """同步版本的 extract_positions"""
+        return self.parser.extract_positions(text)
+    
+    async def parse_into_bboxes(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """使用本地解析器解析PDF"""
+        # 本地解析器可以直接接受BytesIO
+        import asyncio
+        from io import BytesIO
+        
+        # 在后台线程中运行同步方法
+        loop = asyncio.get_event_loop()
+        bboxes = await loop.run_in_executor(
+            None,
+            lambda: self.parser.parse_into_bboxes(BytesIO(pdf_bytes), callback=callback, zoomin=zoomin)
+        )
+        return bboxes
+    
+    def parse_into_bboxes_sync(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """同步版本的 parse_into_bboxes"""
+        from io import BytesIO
+        # 本地解析器可以直接接受BytesIO
+        return self.parser.parse_into_bboxes(BytesIO(pdf_bytes), callback=callback, zoomin=zoomin)
+
+
+class HTTPOCRService(OCRService):
+    """HTTP OCR服务实现（通过HTTP接口调用OCR服务）"""
+    
+    def __init__(self, base_url: Optional[str] = None, timeout: float = 300.0):
+        """
+        初始化HTTP OCR服务
+        
+        Args:
+            base_url: OCR 服务的基础 URL，如果不提供则从环境变量 OCR_SERVICE_URL 获取
+            timeout: 请求超时时间（秒），默认 300 秒
+        """
+        from ocr.client import OCRClient
+        self.client = OCRClient(base_url=base_url, timeout=timeout)
+    
+    async def remove_tag(self, text: str) -> str:
+        """通过HTTP接口移除标签"""
+        return await self.client.remove_tag(text)
+    
+    def remove_tag_sync(self, text: str) -> str:
+        """同步版本的 remove_tag"""
+        return self.client.remove_tag_sync(text)
+    
+    async def extract_positions(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """通过HTTP接口提取位置"""
+        return await self.client.extract_positions(text)
+    
+    def extract_positions_sync(self, text: str) -> List[Tuple[List[int], float, float, float, float]]:
+        """同步版本的 extract_positions"""
+        return self.client.extract_positions_sync(text)
+    
+    async def parse_into_bboxes(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """通过HTTP接口解析PDF"""
+        return await self.client.parse_into_bboxes(pdf_bytes, callback, zoomin, filename)
+    
+    def parse_into_bboxes_sync(
+        self,
+        pdf_bytes: bytes,
+        callback: Optional[Callable[[float, str], None]] = None,
+        zoomin: int = 3,
+        filename: str = "document.pdf"
+    ) -> List[dict]:
+        """同步版本的 parse_into_bboxes"""
+        return self.client.parse_into_bboxes_sync(pdf_bytes, callback, zoomin, filename)
+
+
+# 全局服务实例（懒加载）
+_global_service: Optional[OCRService] = None
+
+
+def get_ocr_service() -> OCRService:
+    """
+    获取全局 OCR 服务实例（单例模式）
+    根据环境变量 OCR_MODE 选择使用本地或HTTP方式：
+    - OCR_MODE=local 或未设置：使用本地OCR模型
+    - OCR_MODE=http：使用HTTP接口
+    
+    也可以通过环境变量 OCR_SERVICE_URL 配置HTTP服务的地址（仅在OCR_MODE=http时生效）
+    
+    Returns:
+        OCRService 实例
+    """
+    global _global_service
+    if _global_service is None:
+        ocr_mode = os.getenv("OCR_MODE", "local").lower()
+        
+        if ocr_mode == "http":
+            base_url = os.getenv("OCR_SERVICE_URL", "http://localhost:8000/api/v1/ocr")
+            logger.info(f"Initializing HTTP OCR service with URL: {base_url}")
+            _global_service = HTTPOCRService(base_url=base_url)
+        else:
+            logger.info("Initializing local OCR service")
+            _global_service = LocalOCRService()
+    
+    return _global_service
+
+
+# 为了向后兼容，保留 get_ocr_client 函数（但重定向到 get_ocr_service）
+def get_ocr_client() -> OCRService:
+    """
+    获取OCR服务实例（向后兼容函数）
+    建议使用 get_ocr_service() 替代
+    
+    Returns:
+        OCRService 实例
+    """
+    return get_ocr_service()
+

rag/flow/hierarchical_merger/hierarchical_merger.py

@@ -22,7 +22,7 @@ import trio
 
 from api.utils import get_uuid
 from api.utils.base64_image import id2image, image2id
-from deepdoc.parser.pdf_parser import RAGFlowPdfParser
+from ocr.service import get_ocr_service
 from rag.flow.base import ProcessBase, ProcessParamBase
 from rag.flow.hierarchical_merger.schema import HierarchicalMergerFromUpstream
 from rag.nlp import concat_img
@@ -170,14 +170,17 @@ class HierarchicalMerger(ProcessBase):
                 cks.append(txt)
                 images.append(img)
 
-            cks = [
-                {
-                    "text": RAGFlowPdfParser.remove_tag(c),
+            ocr_service = get_ocr_service()
+            processed_cks = []
+            for c, img in zip(cks, images):
+                cleaned_text = await ocr_service.remove_tag(c)
+                positions = await ocr_service.extract_positions(c)
+                processed_cks.append({
+                    "text": cleaned_text,
                     "image": img,
-                    "positions": RAGFlowPdfParser.extract_positions(c),
-                }
-                for c, img in zip(cks, images)
-            ]
+                    "positions": positions,
+                })
+            cks = processed_cks
             async with trio.open_nursery() as nursery:
                 for d in cks:
                     nursery.start_soon(image2id, d, partial(STORAGE_IMPL.put), get_uuid())

rag/flow/parser/parser.py

@@ -29,7 +29,8 @@ from api.db.services.llm_service import LLMBundle
 from api.utils import get_uuid
 from api.utils.base64_image import image2id
 from deepdoc.parser import ExcelParser
-from deepdoc.parser.pdf_parser import PlainParser, RAGFlowPdfParser, VisionParser
+from deepdoc.parser.pdf_parser import PlainParser, VisionParser
+from ocr.service import get_ocr_service
 from rag.app.naive import Docx
 from rag.flow.base import ProcessBase, ProcessParamBase
 from rag.flow.parser.schema import ParserFromUpstream
@@ -204,7 +205,9 @@ class Parser(ProcessBase):
         self.set_output("output_format", conf["output_format"])
 
         if conf.get("parse_method").lower() == "deepdoc":
-            bboxes = RAGFlowPdfParser().parse_into_bboxes(blob, callback=self.callback)
+            # 注意：HTTP 调用中无法传递 callback，callback 将被忽略
+            ocr_service = get_ocr_service()
+            bboxes = ocr_service.parse_into_bboxes_sync(blob, callback=self.callback, filename=name)
         elif conf.get("parse_method").lower() == "plain_text":
             lines, _ = PlainParser()(blob)
             bboxes = [{"text": t} for t, _ in lines]

rag/flow/splitter/splitter.py

@@ -19,7 +19,7 @@ import trio
 
 from api.utils import get_uuid
 from api.utils.base64_image import id2image, image2id
-from deepdoc.parser.pdf_parser import RAGFlowPdfParser
+from ocr.service import get_ocr_service
 from rag.flow.base import ProcessBase, ProcessParamBase
 from rag.flow.splitter.schema import SplitterFromUpstream
 from rag.nlp import naive_merge, naive_merge_with_images
@@ -96,14 +96,18 @@ class Splitter(ProcessBase):
             deli,
             self._param.overlapped_percent,
         )
-        cks = [
-            {
-                "text": RAGFlowPdfParser.remove_tag(c),
+        ocr_service = get_ocr_service()
+        cks = []
+        for c, img in zip(chunks, images):
+            if not c.strip():
+                continue
+            cleaned_text = await ocr_service.remove_tag(c)
+            positions = await ocr_service.extract_positions(c)
+            cks.append({
+                "text": cleaned_text,
                 "image": img,
-                "positions": [[pos[0][-1]+1, *pos[1:]] for pos in RAGFlowPdfParser.extract_positions(c)],
-            }
-            for c, img in zip(chunks, images) if c.strip()
-        ]
+                "positions": [[pos[0][-1]+1, *pos[1:]] for pos in positions],
+            })
         async with trio.open_nursery() as nursery:
             for d in cks:
                 nursery.start_soon(image2id, d, partial(STORAGE_IMPL.put), get_uuid())

rag/nlp/__init__.py

@@ -578,7 +578,8 @@ def hierarchical_merge(bull, sections, depth):
 
 
 def naive_merge(sections: str | list, chunk_token_num=128, delimiter="\n。；！？", overlapped_percent=0):
-    from deepdoc.parser.pdf_parser import RAGFlowPdfParser
+    from ocr.service import get_ocr_service
+    ocr_service = get_ocr_service()
     if not sections:
         return []
     if isinstance(sections, str):
@@ -598,7 +599,7 @@ def naive_merge(sections: str | list, chunk_token_num=128, delimiter="\n。；
         # Ensure that the length of the merged chunk does not exceed chunk_token_num
         if cks[-1] == "" or tk_nums[-1] > chunk_token_num * (100 - overlapped_percent)/100.:
             if cks:
-                overlapped = RAGFlowPdfParser.remove_tag(cks[-1])
+                overlapped = ocr_service.remove_tag_sync(cks[-1])
                 t = overlapped[int(len(overlapped)*(100-overlapped_percent)/100.):] + t
             if t.find(pos) < 0:
                 t += pos
@@ -625,7 +626,8 @@ def naive_merge(sections: str | list, chunk_token_num=128, delimiter="\n。；
 
 
 def naive_merge_with_images(texts, images, chunk_token_num=128, delimiter="\n。；！？", overlapped_percent=0):
-    from deepdoc.parser.pdf_parser import RAGFlowPdfParser
+    from ocr.service import get_ocr_service
+    ocr_service = get_ocr_service()
     if not texts or len(texts) != len(images):
         return [], []
     cks = [""]
@@ -642,7 +644,7 @@ def naive_merge_with_images(texts, images, chunk_token_num=128, delimiter="\n。
         # Ensure that the length of the merged chunk does not exceed chunk_token_num
         if cks[-1] == "" or tk_nums[-1] > chunk_token_num * (100 - overlapped_percent)/100.:
             if cks:
-                overlapped = RAGFlowPdfParser.remove_tag(cks[-1])
+                overlapped = ocr_service.remove_tag_sync(cks[-1])
                 t = overlapped[int(len(overlapped)*(100-overlapped_percent)/100.):] + t
             if t.find(pos) < 0:
                 t += pos