diff --git a/docker/Dockerfile.app b/docker/Dockerfile.app index fac4022a..38e12b06 100644 --- a/docker/Dockerfile.app +++ b/docker/Dockerfile.app @@ -1,5 +1,5 @@ # Build stage -FROM golang:1.24-bookworm AS builder +FROM golang:1.26-bookworm AS builder WORKDIR /app diff --git a/docreader/README.md b/docreader/README.md index dfe6f201..baf4b843 100644 --- a/docreader/README.md +++ b/docreader/README.md @@ -84,30 +84,9 @@ docreader: - `DOCREADER_PDF_RENDER_DPI`: 扫描 PDF 渲染 DPI（默认：200） - `DOCREADER_PDF_JPEG_QUALITY`: 扫描 PDF 输出 JPEG 质量（默认：90，范围会自动限制在 1-95） -### OCR 配置 +### OCR / VLM -- `OCR_BACKEND`: OCR 引擎后端，可选值： - - `paddle`: 使用 PaddleOCR（默认） - - `no_ocr`: 禁用 OCR 功能 - - `api`: 使用外部 OCR API -- `OCR_API_BASE_URL`: 外部 OCR API 的基础 URL -- `OCR_API_KEY`: 外部 OCR API 的密钥 -- `OCR_MODEL`: OCR 模型名称 - -**示例**：禁用 OCR 功能 -```yaml -environment: - - OCR_BACKEND=no_ocr -``` - -### VLM（视觉语言模型）配置 - -用于图像理解和描述生成： - -- `VLM_MODEL_BASE_URL`: VLM 模型的 API 地址 -- `VLM_MODEL_NAME`: VLM 模型名称 -- `VLM_MODEL_API_KEY`: VLM 模型的 API 密钥 -- `VLM_INTERFACE_TYPE`: 接口类型，可选值：`openai`（默认）或 `ollama` +DocReader 自身不再内置 OCR 与 VLM 后端。扫描 PDF 会被渲染为 JPEG 图片后交由 Go App 侧调用 OCR/VLM 服务处理，相关配置请参考主项目文档。 ### 存储配置 @@ -167,7 +146,7 @@ docreader: - MAX_FILE_SIZE_MB=50 ``` -### 高级配置（启用 MinerU + 自定义 OCR） +### 高级配置（启用 MinerU） ```yaml docreader: @@ -176,10 +155,6 @@ docreader: - MINIO_PUBLIC_ENDPOINT=http://192.168.1.100:9000 - MINERU_ENDPOINT=http://mineru:8080 - MAX_FILE_SIZE_MB=100 - - OCR_BACKEND=paddle - - VLM_MODEL_BASE_URL=http://ollama:11434 - - VLM_MODEL_NAME=llava - - VLM_INTERFACE_TYPE=ollama ``` ### 使用腾讯云 COS @@ -214,12 +189,7 @@ docreader: ### 1. DocReader 服务无法启动？ -如果日志中出现 PaddleOCR 相关错误，可以尝试禁用 OCR： - -```yaml -environment: - - OCR_BACKEND=no_ocr -``` +检查容器日志中是否存在依赖缺失或权限相关错误，必要时确认 `MINIO_ENDPOINT` / 存储相关环境变量是否正确配置。 ### 2. 图片无法显示？ diff --git a/docreader/ocr/__init__.py b/docreader/ocr/__init__.py deleted file mode 100644 index 692dceb0..00000000 --- a/docreader/ocr/__init__.py +++ /dev/null @@ -1,37 +0,0 @@ -import logging -import threading -from typing import Dict - -from docreader.ocr.base import DummyOCRBackend, OCRBackend -from docreader.ocr.paddle import PaddleOCRBackend -from docreader.ocr.vlm import VLMOCRBackend - -logger = logging.getLogger(__name__) - - -class OCREngine: - """OCR Engine factory class for managing different OCR backend instances""" - - _instances: Dict[str, OCRBackend] = {} - _lock = threading.Lock() - - @classmethod - def get_instance(cls, backend_type: str) -> OCRBackend: - backend_type = (backend_type or "dummy").lower() - - with cls._lock: - inst = cls._instances.get(backend_type) - if inst is not None: - return inst - - logger.info(f"Creating OCR engine instance for backend: {backend_type}") - - if backend_type == "paddle": - inst = PaddleOCRBackend() - elif backend_type == "vlm": - inst = VLMOCRBackend() - else: - inst = DummyOCRBackend() - - cls._instances[backend_type] = inst - return inst diff --git a/docreader/ocr/base.py b/docreader/ocr/base.py deleted file mode 100644 index 4c6fb073..00000000 --- a/docreader/ocr/base.py +++ /dev/null @@ -1,31 +0,0 @@ -import logging -from abc import ABC, abstractmethod -from typing import Union - -from PIL import Image - -logger = logging.getLogger(__name__) - - -class OCRBackend(ABC): - """Base class for OCR backends""" - - @abstractmethod - def predict(self, image: Union[str, bytes, Image.Image]) -> str: - """Extract text from an image - - Args: - image: Image file path, bytes, or PIL Image object - - Returns: - Extracted text - """ - pass - - -class DummyOCRBackend(OCRBackend): - """Dummy OCR backend implementation""" - - def predict(self, image: Union[str, bytes, Image.Image]) -> str: - logger.warning("Dummy OCR backend is used") - return "" diff --git a/docreader/ocr/paddle.py b/docreader/ocr/paddle.py deleted file mode 100644 index 249bebc2..00000000 --- a/docreader/ocr/paddle.py +++ /dev/null @@ -1,175 +0,0 @@ -import io -import logging -import os -import platform -import subprocess -from typing import Union - -import numpy as np -from PIL import Image - -from docreader.ocr.base import OCRBackend - -logger = logging.getLogger(__name__) - - -class PaddleOCRBackend(OCRBackend): - """PaddleOCR backend implementation""" - - def __init__(self): - """Initialize PaddleOCR backend""" - self.ocr = None - try: - import paddle - - # Set PaddlePaddle to use CPU and disable GPU - os.environ["CUDA_VISIBLE_DEVICES"] = "" - paddle.device.set_device("cpu") - - # Try to detect if CPU supports AVX instruction set - # 尝试检测CPU是否支持AVX指令集 - try: - # Detect if CPU supports AVX - # 检测CPU是否支持AVX - if platform.system() == "Linux": - try: - result = subprocess.run( - ["grep", "-o", "avx", "/proc/cpuinfo"], - capture_output=True, - text=True, - timeout=5, - ) - has_avx = "avx" in result.stdout.lower() - if not has_avx: - logger.warning( - "CPU does not support AVX instructions, " - "using compatibility mode" - ) - # Further restrict instruction set usage - # 进一步限制指令集使用 - os.environ["FLAGS_use_avx2"] = "0" - os.environ["FLAGS_use_avx"] = "1" - except ( - subprocess.TimeoutExpired, - FileNotFoundError, - subprocess.SubprocessError, - ): - logger.warning( - "Could not detect AVX support, using compatibility mode" - ) - os.environ["FLAGS_use_avx2"] = "0" - os.environ["FLAGS_use_avx"] = "1" - except Exception as e: - logger.warning( - f"Error detecting CPU capabilities: {e}, using compatibility mode" - ) - os.environ["FLAGS_use_avx2"] = "0" - os.environ["FLAGS_use_avx"] = "1" - - from paddleocr import PaddleOCR - - # OCR configuration with text orientation classification enabled - ocr_config = { - "use_gpu": False, - "text_det_limit_type": "max", - "text_det_limit_side_len": 960, - "use_doc_orientation_classify": True, # Enable document orientation classification / 启用文档方向分类 - "use_doc_unwarping": False, - "use_textline_orientation": True, # Enable text line orientation detection / 启用文本行方向检测 - "text_recognition_model_name": "PP-OCRv4_server_rec", - "text_detection_model_name": "PP-OCRv4_server_det", - "text_det_thresh": 0.3, - "text_det_box_thresh": 0.6, - "text_det_unclip_ratio": 1.5, - "text_rec_score_thresh": 0.0, - "ocr_version": "PP-OCRv4", - "lang": "ch", - "show_log": False, - "use_dilation": True, # improves accuracy - "det_db_score_mode": "slow", # improves accuracy - } - - self.ocr = PaddleOCR(**ocr_config) - logger.info("PaddleOCR engine initialized successfully") - - except ImportError as e: - logger.error( - f"Failed to import paddleocr: {str(e)}. " - "Please install it with 'pip install paddleocr'" - ) - except OSError as e: - if "Illegal instruction" in str(e) or "core dumped" in str(e): - logger.error( - f"PaddlePaddle crashed due to CPU instruction set incompatibility:" - f"{e}" - ) - logger.error( - "This happens when the CPU doesn't support AVX instructions. " - "Try install CPU-only version of PaddlePaddle, " - "or use a different OCR backend." - ) - else: - logger.error( - f"Failed to initialize PaddleOCR due to OS error: {str(e)}" - ) - except Exception as e: - logger.error(f"Failed to initialize PaddleOCR: {str(e)}") - - def predict(self, image: Union[str, bytes, Image.Image]) -> str: - """Extract text from an image - - Args: - image: Image file path, bytes, or PIL Image object - - Returns: - Extracted text - """ - if isinstance(image, str): - image = Image.open(image) - elif isinstance(image, bytes): - image = Image.open(io.BytesIO(image)) - - if not isinstance(image, Image.Image): - raise TypeError("image must be a string, bytes, or PIL Image object") - - return self._predict(image) - - def _predict(self, image: Image.Image) -> str: - """Perform OCR recognition on the image - - Args: - image: Image object (PIL.Image or numpy array) - - Returns: - Extracted text string - """ - if self.ocr is None: - logger.error("PaddleOCR engine not initialized") - return "" - try: - # Ensure image is in RGB format - if image.mode != "RGB": - image = image.convert("RGB") - - # Convert to numpy array for PaddleOCR processing - image_array = np.array(image) - - # Perform OCR recognition - ocr_result = self.ocr.ocr(image_array, cls=False) - - # Extract and concatenate text from OCR results - ocr_text = "" - if ocr_result and ocr_result[0]: - text = [ - line[1][0] if line and len(line) >= 2 and line[1] else "" - for line in ocr_result[0] - ] - text = [t.strip() for t in text if t] - ocr_text = " ".join(text) - - logger.info(f"OCR extracted {len(ocr_text)} characters") - return ocr_text - - except Exception as e: - logger.error(f"OCR recognition error: {str(e)}") - return "" diff --git a/docreader/ocr/vlm.py b/docreader/ocr/vlm.py deleted file mode 100644 index 9f4e25d0..00000000 --- a/docreader/ocr/vlm.py +++ /dev/null @@ -1,87 +0,0 @@ -import logging -from typing import Union - -from openai import OpenAI -from PIL import Image - -from docreader.config import CONFIG -from docreader.ocr.base import OCRBackend -from docreader.utils import endecode - -logger = logging.getLogger(__name__) - - -class VLMOCRBackend(OCRBackend): - """VLM OCR backend implementation using OpenAI API format""" - - def __init__(self): - """Initialize VLM OCR backend - - Args: - api_key: API key for OpenAI API - base_url: Base URL for OpenAI API - model: Model name - """ - self.model = CONFIG.ocr_model - self.client = OpenAI( - api_key=CONFIG.ocr_api_key, - base_url=CONFIG.ocr_api_base_url, - timeout=30, - ) - self.temperature = 0.0 - self.max_tokens = 5000 - - # Prompt for OCR text extraction with specific formatting requirements - self.prompt = "提取文档图片中正文的所有信息用markdown格式表示，" - "其中页眉、页脚部分忽略，" - "表格用html格式表达，" - "文档中公式用latex格式表示，" - "按照阅读顺序组织进行解析。" - - def predict(self, image: Union[str, bytes, Image.Image]) -> str: - """Extract text from an image using VLM OCR - - Args: - image: Image file path, bytes, or PIL Image object - - Returns: - Extracted text - """ - if self.client is None: - logger.error("VLM OCR client not initialized") - return "" - - try: - # Encode image to base64 format for API transmission - img_base64 = endecode.decode_image(image) - if not img_base64: - return "" - - # Call VLM OCR API using OpenAI-compatible format - logger.info(f"Calling VLM OCR API with model: {self.model}") - response = self.client.chat.completions.create( - model=self.model, - messages=[ - { - "role": "user", - "content": [ - { - "type": "image_url", - "image_url": { - "url": f"data:image/png;base64,{img_base64}" - }, - }, - { - "type": "text", - "text": self.prompt, - }, - ], - } - ], - temperature=self.temperature, - max_tokens=self.max_tokens, - ) - return response.choices[0].message.content or "" - except Exception as e: - logger.error(f"VLM OCR prediction error: {str(e)}") - return "" diff --git a/docreader/parser/storage.py b/docreader/parser/storage.py deleted file mode 100644 index 9ecff0cb..00000000 --- a/docreader/parser/storage.py +++ /dev/null @@ -1,419 +0,0 @@ -# -*- coding: utf-8 -*- -import io -import logging -import os -import traceback -import uuid -from abc import ABC, abstractmethod -from typing import Dict, Optional - -from minio import Minio -from qcloud_cos import CosConfig, CosS3Client - -try: - import oss2 -except ImportError: - oss2 = None # type: ignore[assignment] - -from docreader.utils import endecode - -logger = logging.getLogger(__name__) - - -def _cfg(storage_config: Optional[Dict], key: str, *env_keys: str, default: str = "") -> str: - """Read a value from storage_config dict, falling back to env vars.""" - if storage_config: - v = storage_config.get(key, "") - if v: - return str(v) - for ek in env_keys: - v = os.environ.get(ek, "") - if v: - return v - return default - - -class Storage(ABC): - """Abstract base class for object storage operations""" - - @abstractmethod - def upload_file(self, file_path: str) -> str: - pass - - @abstractmethod - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - pass - - -class CosStorage(Storage): - """Tencent Cloud COS storage implementation""" - - def __init__(self, storage_config: Optional[Dict] = None): - self.storage_config = storage_config - self.client, self.bucket_name, self.region, self.prefix = ( - self._init_cos_client() - ) - - def _init_cos_client(self): - try: - sc = self.storage_config - secret_id = _cfg(sc, "access_key_id", "COS_SECRET_ID") - secret_key = _cfg(sc, "secret_access_key", "COS_SECRET_KEY") - region = _cfg(sc, "region", "COS_REGION") - bucket_name = _cfg(sc, "bucket_name", "COS_BUCKET_NAME") - appid = _cfg(sc, "app_id", "COS_APP_ID") - prefix = _cfg(sc, "path_prefix", "COS_PATH_PREFIX") - enable_old_domain = os.environ.get("COS_ENABLE_OLD_DOMAIN", "").lower() in ("1", "true", "yes") - - if not all([secret_id, secret_key, region, bucket_name, appid]): - logger.error( - "Incomplete COS configuration: " - "secret_id=%s, region=%s, bucket=%s, appid=%s", - bool(secret_id), region, bucket_name, appid, - ) - return None, None, None, None - - logger.info("Initializing COS client: region=%s, bucket=%s", region, bucket_name) - config = CosConfig( - Appid=appid, - Region=region, - SecretId=secret_id, - SecretKey=secret_key, - EnableOldDomain=enable_old_domain, - ) - client = CosS3Client(config) - return client, bucket_name, region, prefix - except Exception as e: - logger.error("Failed to initialize COS client: %s", e) - return None, None, None, None - - def _get_download_url(self, bucket_name, region, object_key): - return f"https://{bucket_name}.cos.{region}.myqcloud.com/{object_key}" - - def upload_file(self, file_path: str) -> str: - try: - if not self.client: - return "" - file_ext = os.path.splitext(file_path)[1] - object_key = f"{self.prefix}/images/{uuid.uuid4().hex}{file_ext}" - self.client.upload_file( - Bucket=self.bucket_name, - LocalFilePath=file_path, - Key=object_key, - ) - file_url = self._get_download_url(self.bucket_name, self.region, object_key) - logger.info("COS upload_file ok: %s", file_url) - return file_url - except Exception as e: - logger.error("COS upload_file failed: %s", e) - return "" - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - try: - if not self.client: - return "" - object_key = ( - f"{self.prefix}/images/{uuid.uuid4().hex}{file_ext}" - if self.prefix - else f"images/{uuid.uuid4().hex}{file_ext}" - ) - self.client.put_object( - Bucket=self.bucket_name, Body=content, Key=object_key - ) - file_url = self._get_download_url(self.bucket_name, self.region, object_key) - logger.info("COS upload_bytes ok: %s", file_url) - return file_url - except Exception as e: - logger.error("COS upload_bytes failed: %s", e) - traceback.print_exc() - return "" - - -class MinioStorage(Storage): - """MinIO storage implementation""" - - def __init__(self, storage_config: Optional[Dict] = None): - self.storage_config = storage_config - self.client, self.bucket_name, self.use_ssl, self.endpoint, self.path_prefix = ( - self._init_minio_client() - ) - - def _init_minio_client(self): - try: - sc = self.storage_config - access_key = _cfg(sc, "access_key_id", "MINIO_ACCESS_KEY_ID") - secret_key = _cfg(sc, "secret_access_key", "MINIO_SECRET_ACCESS_KEY") - bucket_name = _cfg(sc, "bucket_name", "MINIO_BUCKET_NAME") - path_prefix_raw = _cfg(sc, "path_prefix", "MINIO_PATH_PREFIX") - path_prefix = path_prefix_raw.strip().strip("/") if path_prefix_raw else "" - endpoint = _cfg(sc, "endpoint", "MINIO_ENDPOINT") - use_ssl = os.environ.get("MINIO_USE_SSL", "").lower() in ("1", "true", "yes") - - if not all([endpoint, access_key, secret_key, bucket_name]): - logger.error("Incomplete MinIO configuration") - return None, None, None, None, None - - client = Minio( - endpoint, access_key=access_key, secret_key=secret_key, secure=use_ssl - ) - - found = client.bucket_exists(bucket_name) - if not found: - client.make_bucket(bucket_name) - policy = ( - "{" - '"Version":"2012-10-17",' - '"Statement":[' - '{"Effect":"Allow","Principal":{"AWS":["*"]},' - '"Action":["s3:GetObject"],' - '"Resource":["arn:aws:s3:::%s/*"]}' - "]}" % (bucket_name) - ) - client.set_bucket_policy(bucket_name, policy) - - return client, bucket_name, use_ssl, endpoint, path_prefix - except Exception as e: - logger.error("Failed to initialize MinIO client: %s", e) - return None, None, None, None, None - - def _get_download_url(self, object_key: str): - public_endpoint = os.environ.get("MINIO_PUBLIC_ENDPOINT", "") - if public_endpoint: - return f"{public_endpoint}/{self.bucket_name}/{object_key}" - scheme = "https" if self.use_ssl else "http" - return f"{scheme}://{self.endpoint}/{self.bucket_name}/{object_key}" - - def upload_file(self, file_path: str) -> str: - try: - if not self.client: - return "" - file_name = os.path.basename(file_path) - object_key = ( - f"{self.path_prefix}/images/{uuid.uuid4().hex}{os.path.splitext(file_name)[1]}" - if self.path_prefix - else f"images/{uuid.uuid4().hex}{os.path.splitext(file_name)[1]}" - ) - with open(file_path, "rb") as file_data: - file_size = os.path.getsize(file_path) - self.client.put_object( - bucket_name=self.bucket_name or "", - object_name=object_key, - data=file_data, - length=file_size, - content_type="application/octet-stream", - ) - file_url = self._get_download_url(object_key) - logger.info("MinIO upload_file ok: %s", file_url) - return file_url - except Exception as e: - logger.error("MinIO upload_file failed: %s", e) - return "" - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - try: - if not self.client: - return "" - object_key = ( - f"{self.path_prefix}/images/{uuid.uuid4().hex}{file_ext}" - if self.path_prefix - else f"images/{uuid.uuid4().hex}{file_ext}" - ) - self.client.put_object( - self.bucket_name or "", - object_key, - data=io.BytesIO(content), - length=len(content), - content_type="application/octet-stream", - ) - file_url = self._get_download_url(object_key) - logger.info("MinIO upload_bytes ok: %s", file_url) - return file_url - except Exception as e: - logger.error("MinIO upload_bytes failed: %s", e) - traceback.print_exc() - return "" - - -class OssStorage(Storage): - """Alibaba Cloud OSS storage implementation""" - - def __init__(self, storage_config: Optional[Dict] = None): - self.storage_config = storage_config - self.bucket, self.endpoint, self.prefix = self._init_oss_bucket() - - def _init_oss_bucket(self): - if oss2 is None: - logger.error("oss2 package not installed. Install with: pip install oss2") - return None, None, None - try: - sc = self.storage_config - access_key = _cfg(sc, "access_key", "OSS_ACCESS_KEY") - secret_key = _cfg(sc, "secret_key", "OSS_SECRET_KEY") - endpoint_raw = _cfg(sc, "endpoint", "OSS_ENDPOINT") - bucket_name = _cfg(sc, "bucket_name", "OSS_BUCKET_NAME") - prefix_raw = _cfg(sc, "path_prefix", "OSS_PATH_PREFIX") - - if not all([access_key, secret_key, endpoint_raw, bucket_name]): - logger.error( - "Incomplete OSS configuration: " - "access_key=%s, endpoint=%s, bucket=%s", - bool(access_key), endpoint_raw, bucket_name, - ) - return None, None, None - - # oss2 requires endpoint to include the scheme (http:// or https://) - if not endpoint_raw.startswith(("http://", "https://")): - endpoint_raw = f"https://{endpoint_raw}" - - auth = oss2.Auth(access_key, secret_key) - bucket = oss2.Bucket(auth, endpoint_raw, bucket_name) - - # Verify bucket exists; do NOT auto-create to avoid unintended public-read buckets - try: - bucket.get_bucket_info() - except oss2.exceptions.NoSuchBucket: - logger.error( - "OSS bucket %s does not exist. Please create it manually in the console.", - bucket_name, - ) - return None, None, None - - prefix = prefix_raw.strip().strip("/") if prefix_raw else "" - return bucket, endpoint_raw, prefix - - except Exception as e: - logger.error("Failed to initialize OSS client: %s", e) - return None, None, None - - def _get_download_url(self, object_key: str) -> str: - # Use virtual-hosted style URL: https://{bucket}.{endpoint_without_scheme}/{key} - endpoint_no_scheme = self.endpoint.removeprefix("https://").removeprefix("http://") - return f"https://{self.bucket.bucket_name}.{endpoint_no_scheme}/{object_key}" - - def upload_file(self, file_path: str) -> str: - try: - if not self.bucket: - return "" - file_ext = os.path.splitext(file_path)[1] - object_key = ( - f"{self.prefix}/images/{uuid.uuid4().hex}{file_ext}" - if self.prefix - else f"images/{uuid.uuid4().hex}{file_ext}" - ) - self.bucket.put_object_from_file(object_key, file_path) - file_url = self._get_download_url(object_key) - logger.info("OSS upload_file ok: %s", file_url) - return file_url - except Exception as e: - logger.error("OSS upload_file failed: %s", e) - return "" - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - try: - if not self.bucket: - return "" - object_key = ( - f"{self.prefix}/images/{uuid.uuid4().hex}{file_ext}" - if self.prefix - else f"images/{uuid.uuid4().hex}{file_ext}" - ) - self.bucket.put_object(object_key, content) - file_url = self._get_download_url(object_key) - logger.info("OSS upload_bytes ok: %s", file_url) - return file_url - except Exception as e: - logger.error("OSS upload_bytes failed: %s", e) - traceback.print_exc() - return "" - - -class LocalStorage(Storage): - """Local file system storage implementation. - - Saves files under base_dir and returns web-accessible URL paths - (e.g. /files/images/uuid.jpg) so that the Go app can serve them. - """ - - def __init__(self, storage_config: Optional[Dict] = None): - sc = storage_config or {} - self.base_dir = ( - sc.get("base_dir") - or os.environ.get("LOCAL_STORAGE_BASE_DIR", "/data/files") - ) - path_prefix = (sc.get("path_prefix") or "").strip().strip("/") - if path_prefix: - self.image_dir = os.path.join(self.base_dir, path_prefix, "images") - else: - self.image_dir = os.path.join(self.base_dir, "images") - self.url_prefix = ( - sc.get("url_prefix") - or os.environ.get("LOCAL_STORAGE_URL_PREFIX", "/files") - ) - os.makedirs(self.image_dir, exist_ok=True) - - def _to_url(self, fpath: str) -> str: - if self.url_prefix: - rel = os.path.relpath(fpath, self.base_dir) - return f"{self.url_prefix}/{rel}" - return fpath - - def upload_file(self, file_path: str) -> str: - return file_path - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - fpath = os.path.join(self.image_dir, f"{uuid.uuid4()}{file_ext}") - with open(fpath, "wb") as f: - f.write(content) - url = self._to_url(fpath) - logger.info("Local storage saved: %s -> %s", fpath, url) - return url - - -class Base64Storage(Storage): - def upload_file(self, file_path: str) -> str: - return file_path - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - file_ext = file_ext.lstrip(".") - return f"data:image/{file_ext};base64,{endecode.decode_image(content)}" - - -class DummyStorage(Storage): - """Dummy storage — all uploads return empty string.""" - - def upload_file(self, file_path: str) -> str: - return "" - - def upload_bytes(self, content: bytes, file_ext: str = ".png") -> str: - return "" - - -def create_storage(storage_config: Optional[Dict[str, str]] = None) -> Storage: - """Create a storage instance based on storage_config dict. - - The ``provider`` key in storage_config determines the backend: - minio, cos, oss, local, base64. - Falls back to STORAGE_TYPE env var, then ``local``. - """ - storage_type = "" - if storage_config: - provider = str(storage_config.get("provider", "")).lower().strip() - if provider and provider not in ("unspecified", "storage_provider_unspecified"): - storage_type = provider - - if not storage_type: - storage_type = os.environ.get("STORAGE_TYPE", "local").lower().strip() - - logger.info("Creating %s storage instance", storage_type) - - if storage_type == "minio": - return MinioStorage(storage_config) - elif storage_type == "cos": - return CosStorage(storage_config) - elif storage_type == "oss": - return OssStorage(storage_config) - elif storage_type == "local": - return LocalStorage(storage_config) - elif storage_type == "base64": - return Base64Storage() - return DummyStorage() diff --git a/docreader/pyproject.toml b/docreader/pyproject.toml index b3d64c2f..c852c936 100644 --- a/docreader/pyproject.toml +++ b/docreader/pyproject.toml @@ -5,36 +5,20 @@ description = "Add your description here" readme = "README.md" requires-python = ">=3.10.18" dependencies = [ - "antiword>=0.1.0", - "asyncio>=4.0.0", "beautifulsoup4>=4.14.2", - "cos-python-sdk-v5>=1.9.42", - "goose3[all]>=3.1.20", "grpcio>=1.76.0", "grpcio-health-checking>=1.76.0", "grpcio-tools>=1.76.0", "lxml>=6.1.0", - "markdown>=3.10", - "markdownify>=1.2.0", "markitdown[docx,pdf,xls,xlsx]>=0.1.3", - "minio>=7.2.20", - "mistletoe>=1.5.0", - "ollama>=0.6.0", - "openai>=2.7.1", - 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- -def init_ocr_model(): - """Initialize PaddleOCR model to pre-download and cache models""" - try: - logger.info("Initializing PaddleOCR model for pre-download...") - - # 使用与代码中相同的配置 - ocr_config = { - "use_gpu": False, - "text_det_limit_type": "max", - "text_det_limit_side_len": 960, - "use_doc_orientation_classify": True, # 启用文档方向分类 - "use_doc_unwarping": False, - "use_textline_orientation": True, # 启用文本行方向检测 - "text_recognition_model_name": "PP-OCRv4_server_rec", - "text_detection_model_name": "PP-OCRv4_server_det", - "text_det_thresh": 0.3, - "text_det_box_thresh": 0.6, - "text_det_unclip_ratio": 1.5, - "text_rec_score_thresh": 0.0, - "ocr_version": "PP-OCRv4", - "lang": "ch", - "show_log": False, - "use_dilation": True, - "det_db_score_mode": "slow", - } - - # 初始化PaddleOCR，这会触发模型下载和缓存 - ocr = PaddleOCR(**ocr_config) - logger.info("PaddleOCR model initialization completed successfully") - - # 测试OCR功能以确保模型正常工作 - import numpy as np - from PIL import Image - - # 创建一个简单的测试图像 - test_image = np.ones((100, 300, 3), dtype=np.uint8) * 255 - 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