diff --git a/.gitignore b/.gitignore index 996925b96..7a49b1481 100644 --- a/.gitignore +++ b/.gitignore @@ -155,3 +155,6 @@ src/**/server/static/ # App generated files extralit-server/src/extralit_server/static extralit/site + +# Development files +*.db \ No newline at end of file diff --git a/extralit-server/.env.dev b/extralit-server/.env.dev index 9617b610b..fd993b7d0 100644 --- a/extralit-server/.env.dev +++ b/extralit-server/.env.dev @@ -1,7 +1,7 @@ OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES # Needed by RQ to work with forked processes on MacOS ALEMBIC_CONFIG=src/extralit_server/alembic.ini EXTRALIT_AUTH_SECRET_KEY=8VO7na5N/jQx+yP/N+HlE8q51vPdrxqlh6OzoebIyko= # With this we avoid using a different key every time the server is reloaded -EXTRALIT_DATABASE_URL=sqlite+aiosqlite:///${HOME}/.extralit/extralit-dev.db?check_same_thread=False +EXTRALIT_DATABASE_URL=sqlite+aiosqlite:///./extralit-dev.db?check_same_thread=False HF_HUB_DISABLE_TELEMETRY=1 # S3 Configuration (skipped to use LocalFileStorage) @@ -20,3 +20,13 @@ EXTRALIT_ELASTICSEARCH=http://localhost:9200 # Redis configuration EXTRALIT_REDIS_URL=redis://localhost:6379/0 + +# PDF Preprocessing +PREPROCESSING_ENABLED=true +PREPROCESSING_ENABLE_ANALYSIS=true +PREPROCESSING_ROTATE_PAGES=true +PREPROCESSING_ROTATE_PAGES_THRESHOLD=2.0 +PREPROCESSING_CLEAN=false +PREPROCESSING_SKIP_TEXT=true +PREPROCESSING_TESSERACT_TIMEOUT=0 +PREPROCESSING_QUIET=false diff --git a/extralit-server/pdm.lock b/extralit-server/pdm.lock index 86777a985..0de71f798 100644 --- a/extralit-server/pdm.lock +++ b/extralit-server/pdm.lock @@ -5,10 +5,10 @@ groups = ["default", "postgresql", "test"] strategy = [] lock_version = "4.5.0" -content_hash = "sha256:9ff6bc1261cec9c0bdce741c04a63bf63a0a8e194e380d560c5032a6aef76b11" +content_hash = "sha256:02264c865d9bc17964c0abbd121810947822b6ff067ac8fcd0cbcb1ef46de191" [[metadata.targets]] -requires_python = ">=3.9" +requires_python = ">=3.10" [[package]] name = "aiofiles" @@ -102,21 +102,6 @@ files 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"huggingface-hub>=0.26.2", "Jinja2>=3.1.4", # Used by huggingface-hub to render dataset card templates # For file storage "minio>=7.2.7", + # For document processing + "ocrmypdf>=16.10.4", + "pdf2image>=1.17.0", + "opencv-python>=4.11.0.86", ] [project.optional-dependencies] @@ -182,8 +187,9 @@ worker = { cmd = "python -m extralit_server worker" } server-dev.composite = [ "migrate", "cli database users create_default", - "server", + "server-and-worker", ] +server-and-worker = { shell = "pdm run server & pdm run worker & wait" } test = { cmd = "pytest --verbosity=1 --disable-warnings", env_file = ".env.test" } test-cov = { cmd = "pytest tests --cov=extralit_server --cov-report=term --cov-report=xml --verbosity=0 --disable-warnings", env_file = ".env.test" } diff --git a/extralit-server/src/extralit_server/api/schemas/v1/document/preprocessing.py b/extralit-server/src/extralit_server/api/schemas/v1/document/preprocessing.py new file mode 100644 index 000000000..5448b90ca --- /dev/null +++ b/extralit-server/src/extralit_server/api/schemas/v1/document/preprocessing.py @@ -0,0 +1,29 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + +from typing import Dict, List, Optional +from pydantic import BaseModel + + +class PDFMetadata(BaseModel): + """ + Metadata for PDF processing results. + """ + + filename: str + processing_time: float + page_count: Optional[int] = None + language_detected: Optional[List[str]] = None + processing_settings: Optional[Dict] = None + analysis_results: Optional[Dict] = None diff --git a/extralit-server/src/extralit_server/api/schemas/v1/document/segments.py b/extralit-server/src/extralit_server/api/schemas/v1/document/segments.py new file mode 100644 index 000000000..f22da6284 --- /dev/null +++ b/extralit-server/src/extralit_server/api/schemas/v1/document/segments.py @@ -0,0 +1,122 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + +import uuid +from typing import Optional, Any, List, Union + +from pydantic import BaseModel, Field, validator + +""" +This is deprecated code that is outdated and should be used for reference only. +We may want to switch to using LlamaIndexDocument or other document models in the future. +""" + + +class Segments(BaseModel): + items: List[Union["TextSegment", "TableSegment", "FigureSegment"]] = Field( + default_factory=list, + description="List of segments in the reading order of the document", + ) + + def get(self, id: str, header: str | None = None, default=None): + for item in self.items: + if item.id == id or (header and item.header == header): + return item + + return default + + def __repr_str__(self, join_str: str) -> str: + return "\n " + f"{join_str}\n ".join(f"{type(item).__name__}({item})" for item in self.items) + + @validator("items", pre=True, each_item=True) + def parse_segments(cls, v): + if not isinstance(v, dict): + v = v.dict() + + segment_type = v.get("type", "").lower() + if segment_type in {"figure", "image"}: + return FigureSegment(**v) + elif segment_type == "table" or "html" in v: + return TableSegment(**v) + else: + return TextSegment(**v) + + def __getitem__(self, index): + return self.items[index] + + def __len__(self): + return len(self.items) + + +class Coordinates(BaseModel): + points: List[List[float]] = Field( + ..., description="List of 4 points, e.g. [[x1, y1], [x2, y1], [x1, y2], [x2, y2]]" + ) + layout_width: Optional[int] = Field(None, description="Width of the layout") + layout_height: Optional[int] = Field(None, description="Height of the layout") + system: Optional[str] = Field(description="System of coordinates") + + def __repr_str__(self, join_str: str) -> str: + return "" + + +class TextSegment(BaseModel): + id: str = Field( + default_factory=lambda: str(uuid.uuid4()), description="Unique identifier of the segment", repr=False + ) + + header: Optional[str] = Field( + None, + description="Header of the element", + ) + text: str = Field(..., description="Content as plain text", repr=False) + summary: Optional[str] = Field(None, description="Summary of the content") + page_number: Optional[int] = Field(None, description="Page number of the segment") + coordinates: Optional["Coordinates"] = Field( + None, description="Coordinates of the element in the document", repr=False + ) + level: Optional[int] = Field(None, description="Level of the header") + source: Optional[str] = Field(None, description="Source of the element", repr=False) + type: Optional[str] = Field("text", description="Type of the element", repr=False) + original: Optional[Any] = Field( + None, exclude=True, description="Original object from which the segment was extracted", repr=False + ) + + def text_cleaned(self): + return self.text.replace(" | ", " ").replace("---", "").strip() + + def __repr_str__(self, join_str: str) -> str: + return join_str.join( + repr(v) + if a is None + else ( + f'{a}="{v[:100]}...{v[-100:]}"'.replace("\n", "") + if isinstance(v, str) and len(v) > 200 + else f"{a}={v!r}" + ) + for a, v in self.__repr_args__() + if v and a not in {"INCLUDE_METADATA_KEYS"} + ) + + +class TableSegment(TextSegment): + footer: Optional[str] = Field(None, description="Footer of the table or figure, to explain variable acronyms.") + html: Optional[str] = Field(None, description="Content as HTML structured", repr=False) + image: Optional[str] = Field(None, description="URL/filepath of the element's image", repr=False) + probability: Optional[float] = Field(None, description="Probability or confidence of the segment's extraction") + type: Optional[str] = Field("table", description="Type of the element", repr=False) + + +class FigureSegment(TableSegment): + type: Optional[str] = Field("figure", description="Type of the element", repr=False) diff --git a/extralit-server/src/extralit_server/api/schemas/v1/imports.py b/extralit-server/src/extralit_server/api/schemas/v1/imports.py index 654fff606..837a004cf 100644 --- a/extralit-server/src/extralit_server/api/schemas/v1/imports.py +++ b/extralit-server/src/extralit_server/api/schemas/v1/imports.py @@ -68,7 +68,7 @@ class DataframeSchema(BaseModel): class DataframeData(BaseModel): """Tabular dataframe representation for generalized import support.""" - schema: DataframeSchema = Field(..., description="Schema definition with fields and primary key") + schema_: DataframeSchema = Field(..., alias="schema", description="Schema definition with fields and primary key") data: List[Dict[str, Any]] = Field(..., description="List of data rows as dictionaries") diff --git a/extralit-server/src/extralit_server/cli/__init__.py b/extralit-server/src/extralit_server/cli/__init__.py index b0ad568f3..0e75fb520 100644 --- a/extralit-server/src/extralit_server/cli/__init__.py +++ b/extralit-server/src/extralit_server/cli/__init__.py @@ -1,18 +1,30 @@ -# Copyright 2021-present, the Recognai S.L. team. +# Copyright 2024-present, Extralit Labs, Inc. # -# 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 +# 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 +# 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. +# 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. -from .__main__ import app +import typer + +from .database import app as database_app +from .search_engine import app as search_engine_app +from .start import start +from .worker import worker + +app = typer.Typer(help="Commands for Extralit server management", no_args_is_help=True) + +app.add_typer(database_app, name="database") +app.add_typer(search_engine_app, name="search-engine") +app.command(name="worker", help="Starts rq workers")(worker) +app.command(name="start", help="Starts the Extralit server")(start) if __name__ == "__main__": app() diff --git a/extralit-server/src/extralit_server/cli/__main__.py b/extralit-server/src/extralit_server/cli/__main__.py index 3c98db185..7d7ff85aa 100644 --- a/extralit-server/src/extralit_server/cli/__main__.py +++ b/extralit-server/src/extralit_server/cli/__main__.py @@ -12,21 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. -import typer - -from .database import app as database_app -from .search_engine import app as search_engine_app -from .start import start -from .worker import worker - -app = typer.Typer(help="Commands for Extralit server management", no_args_is_help=True) - - -app.add_typer(database_app, name="database") -app.add_typer(search_engine_app, name="search-engine") -app.command(name="worker", help="Starts rq workers")(worker) -app.command(name="start", help="Starts the Extralit server")(start) - +from extralit_server.cli import app if __name__ == "__main__": app() diff --git a/extralit-server/src/extralit_server/contexts/document/__init__.py b/extralit-server/src/extralit_server/contexts/document/__init__.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/document/__init__.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/contexts/document/analysis.py b/extralit-server/src/extralit_server/contexts/document/analysis.py new file mode 100644 index 000000000..5b3008db8 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/document/analysis.py @@ -0,0 +1,186 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + +from pdfminer.pdfpage import PDFPage +from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter +from pdfminer.converter import PDFPageAggregator +from pdfminer.layout import LAParams, LTTextBox, LTChar +from typing import Dict, List +from io import BytesIO + + +class PDFOCRLayerDetector: + def __init__(self): + self.resource_manager = PDFResourceManager() + self.laparams = LAParams() + self.device = PDFPageAggregator(self.resource_manager, laparams=self.laparams) + self.interpreter = PDFPageInterpreter(self.resource_manager, self.device) + + def has_ocr_text_layer(self, pdf_bytes: bytes, threshold: float = 0.5, verbose=False) -> bool: + """ + Detect if PDF has OCR text layer by analyzing font resources per page. + Returns True if more than 50% of pages have font resources (indicating searchable text). + + Args: + pdf_bytes: PDF file content as bytes + + Returns: + bool: True if PDF has OCR text layer, False otherwise + """ + page_info = self._check_font_resources_per_page(pdf_bytes) + + if not page_info: + return False + + if verbose: + print(f"Total pages: {len(page_info)}") + print(page_info) + + pages_with_fonts = sum(1 for page in page_info if page.get("has_fonts", False)) + total_pages = len(page_info) + + # Return True if more than 50% of pages have fonts + return pages_with_fonts > (total_pages * threshold) + + def _check_font_resources_per_page(self, pdf_bytes: bytes) -> List[Dict]: + """ + Check each page for font resources - indicates searchable text + """ + page_info = [] + + pdf_stream = BytesIO(pdf_bytes) + for page_num, page in enumerate(PDFPage.get_pages(pdf_stream)): + page_data = { + "page_number": page_num + 1, + "has_fonts": False, + "font_count": 0, + "has_images": False, + "resource_types": [], + } + + if hasattr(page, "resources") and page.resources: + resources = page.resources + + if "Font" in resources: + page_data["has_fonts"] = True + font_resource = resources["Font"] + try: + page_data["font_count"] = len(font_resource) # type: ignore + except (TypeError, AttributeError): + page_data["font_count"] = 1 + + if "XObject" in resources: + page_data["has_images"] = True + + page_data["resource_types"] = list(resources.keys()) + + page_info.append(page_data) + + return page_info + + def analyze_character_quality(self, pdf_bytes: bytes) -> Dict: + char_stats = { + "total_chars": 0, + "font_variations": set(), + "suspicious_patterns": 0, + "ocr_artifacts": 0, + "avg_char_size": 0, + "size_variations": [], + } + + pdf_stream = BytesIO(pdf_bytes) + for page in PDFPage.get_pages(pdf_stream): + self.interpreter.process_page(page) + layout = self.device.get_result() + + for element in layout: + if isinstance(element, LTTextBox): + for line in element: + for char in line: + if isinstance(char, LTChar): + char_stats["total_chars"] += 1 + + if self._is_ocr_artifact(char): + char_stats["ocr_artifacts"] += 1 + + if self._is_suspicious_char(char): + char_stats["suspicious_patterns"] += 1 + + char_stats["ocr_quality_score"] = self._calculate_quality_score(char_stats) + + return char_stats + + def _is_ocr_artifact(self, char: LTChar) -> bool: + if "hidden" in char.fontname.lower() or "ocr" in char.fontname.lower(): + return True + + char_text = char.get_text() + if len(char_text) == 1: + # Look for replacement characters or unusual Unicode + if ord(char_text) > 65535 or char_text in ["�", "□", "▯"]: + return True + + return False + + def _is_suspicious_char(self, char: LTChar) -> bool: + char_text = char.get_text() + + # Single character that's not alphanumeric or common punctuation + if len(char_text) == 1 and not (char_text.isalnum() or char_text in ".,!?;: "): + return True + + # Very small font size (might indicate hidden text) + if char.size < 1.0: + return True + + return False + + def _calculate_quality_score(self, char_stats: Dict) -> float: + if char_stats["total_chars"] == 0: + return 0.0 + + score = 1.0 + + # Penalize OCR artifacts + artifact_ratio = char_stats["ocr_artifacts"] / char_stats["total_chars"] + score -= artifact_ratio * 0.5 + + # Penalize suspicious patterns + suspicious_ratio = char_stats["suspicious_patterns"] / char_stats["total_chars"] + score -= suspicious_ratio * 0.3 + + return max(0.0, min(1.0, score)) + + +if __name__ == "__main__": + import sys + from pathlib import Path + + if len(sys.argv) != 2: + print("Usage: python analysis.py ") + sys.exit(1) + + pdf_path = sys.argv[1] + if not Path(pdf_path).is_file(): + print(f"File not found: {pdf_path}") + sys.exit(1) + + with open(pdf_path, "rb") as f: + pdf_bytes = f.read() + + ocr_detector = PDFOCRLayerDetector() + has_ocr = ocr_detector.has_ocr_text_layer(pdf_bytes) + print(f"PDF has_ocr_text_layer: {has_ocr}") + ocr_quality = ocr_detector.analyze_character_quality(pdf_bytes) + print(f"PDF analyze_character_quality: {ocr_quality}") diff --git a/extralit-server/src/extralit_server/contexts/document/margin.py b/extralit-server/src/extralit_server/contexts/document/margin.py new file mode 100644 index 000000000..dbcfb87a9 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/document/margin.py @@ -0,0 +1,470 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + +import logging +import os + +from typing import Dict, List, Optional, Tuple, TYPE_CHECKING +import numpy as np + +import lazy_loader as lazy + +os.environ["OPENCV_VIDEOIO_PRIORITY_MSMF"] = "0" +os.environ["OPENCV_VIDEOIO_PRIORITY_INTEL_MFX"] = "0" + +try: + cv2 = lazy.load("cv2") + # Set OpenCV to use CPU-only mode to avoid OpenGL issues + cv2.setUseOptimized(False) # type: ignore + cv2.setNumThreads(1) # type: ignore +except Exception as e: + _LOGGER = logging.getLogger(__name__) + _LOGGER.warning(f"OpenCV not available or failed to load: {e}") + +pdf2image = lazy.load("pdf2image") +PIL = lazy.load("PIL") + +if TYPE_CHECKING: + from PIL.Image import Image + +_LOGGER = logging.getLogger(__name__) + + +def pil_to_cv(image: "Image") -> np.ndarray: + """Convert PIL Image to OpenCV format.""" + return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) # type: ignore + + +def classify_and_draw_layout_regions( + reference: "Image", mask: "Image", min_area: int = 5000, label: bool = True +) -> Tuple["Image", List[Dict]]: + """ + Classify and optionally draw layout regions using contour detection. + + Returns: + Tuple of (annotated image, list of detected regions) + """ + + mask_np = np.array(mask.convert("L")) + h, w = mask_np.shape + + # Clean up the mask using morphological operations + kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)) # type: ignore + cleaned = cv2.morphologyEx(mask_np, cv2.MORPH_CLOSE, kernel) # type: ignore + + contours, _ = cv2.findContours(cleaned, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # type: ignore + + img = reference.copy() if label else reference + regions = [] + + if label: + draw = PIL.ImageDraw.Draw(img) # type: ignore + + for cnt in contours: + x, y, rw, rh = cv2.boundingRect(cnt) # type: ignore + area = rw * rh + + if area < min_area: + continue + + cx, cy = x + rw // 2, y + rh // 2 + + # Classify region based on position + if cy < h * 0.25: + region = "header" + elif cy > h * 0.75: + region = "footer" + elif cx < w * 0.15: + region = "left_margin" + elif cx > w * 0.85: + region = "right_margin" + else: + region = "body" + + region_data = { + "type": region, + "x": x, + "y": y, + "width": rw, + "height": rh, + "area": area, + "center_x": cx, + "center_y": cy, + } + regions.append(region_data) + + if label: + draw.rectangle([x, y, x + rw, y + rh], outline="green", width=2) + draw.text((x, y - 10), region, fill="green") + + return img, regions + + +def find_horizontal_bands(mask: "Image", min_height: int = 15, min_ratio: float = 0.95) -> List[Tuple[int, int]]: + """Find horizontal bands of similar content across pages.""" + mask_np = np.array(mask.convert("L")) + h, w = mask_np.shape + + row_sums = np.sum(mask_np == 255, axis=1) / w # white = same + same_rows = row_sums >= min_ratio + + bands = [] + start = None + for i, val in enumerate(same_rows): + if val and start is None: + start = i + elif not val and start is not None: + if i - start >= min_height: + bands.append((start, i)) + start = None + if start is not None and h - start >= min_height: + bands.append((start, h)) + + return bands + + +class PDFAnalyzer: + def analyze_pdf_layout(self, pdf_data: bytes, filename: str) -> Dict: + """ + Analyze PDF layout to extract margin and region information. + + Args: + pdf_data: PDF file data as bytes + filename: Filename for logging + + Returns: + Dictionary containing layout analysis metadata + """ + + try: + images = pdf2image.convert_from_bytes(pdf_data, dpi=150) # type: ignore + if not images: + return {"analysis_available": False, "error": "No pages found"} + + _LOGGER.info(f"Analyzing layout for {filename} with {len(images)} pages") + + # Analyze layout + layout_data = self._analyze_page_layout(images) + + return { + "analysis_available": True, + "total_pages": len(images), + "page_dimensions": {"width": images[0].size[0], "height": images[0].size[1]} if images else {}, + **layout_data, + } + + except Exception as e: + _LOGGER.error(f"PDF layout analysis failed for {filename}: {e}") + return {"analysis_available": False, "error": str(e)} + + def _analyze_page_layout(self, images: List["Image"]) -> Dict: + """ + Analyze page layout by comparing pages to find common regions. + """ + if len(images) < 2: + return self._analyze_single_page(images[0]) if images else {} + + # Use first page as reference, compare with others + reference_img = images[0].convert("RGB") + margin_data = [] + + for i in range(1, min(len(images), 5)): # Analyze up to 5 pages for efficiency + compare_img = images[i].convert("RGB") + page_margins = self._compare_pages_for_margins(reference_img, compare_img) + if page_margins: + margin_data.append(page_margins) + + # Aggregate margin data + if margin_data: + return self._aggregate_margin_data(margin_data, reference_img.size) + else: + return self._analyze_single_page(reference_img) + + def _compare_pages_for_margins(self, reference: "Image", compare: "Image") -> Optional[Dict]: + """ + Compare two pages to identify common regions using advanced CV2 techniques. + """ + try: + # Ensure same size + if reference.size != compare.size: + _LOGGER.debug(f"Resizing page to match reference size") + compare = compare.resize(reference.size) + + # Step 1: Compute difference and invert so white = same + diff = PIL.ImageChops.difference(reference, compare) # type: ignore + sameness_mask = PIL.ImageChops.invert(diff.convert("L")) # type: ignore + + # Step 2: Threshold the mask (keep high-sameness pixels) + # Create a lookup table for thresholding + threshold = 30 + lut = [255 if i > threshold else 0 for i in range(256)] + sameness_mask.point(lut).convert("1") + + # Step 3: Find horizontal bands (potential headers/footers) + horizontal_bands = find_horizontal_bands(sameness_mask) + + # Step 4: Use contour-based region classification + annotated_img, detected_regions = classify_and_draw_layout_regions( + reference, sameness_mask, min_area=5000, label=False + ) + + # Step 5: Classify and aggregate results + regions = self._classify_regions_advanced(horizontal_bands, detected_regions, reference.size) + + return regions + + except Exception as e: + _LOGGER.debug(f"Page comparison failed: {e}") + return None + + def _classify_regions_advanced( + self, bands: List[Tuple[int, int]], detected_regions: List[Dict], page_size: Tuple[int, int] + ) -> Dict: + """ + Advanced region classification combining horizontal bands and contour detection. + """ + width, height = page_size + regions = { + "header_bands": [], + "footer_bands": [], + "detected_regions": detected_regions, + "estimated_margins": {}, + } + + # Process horizontal bands + for start_y, end_y in bands: + band_center = (start_y + end_y) / 2 + band_height = end_y - start_y + + # Classify based on position + if band_center < height * 0.25: # Top 25% + regions["header_bands"].append({"start_y": start_y, "end_y": end_y, "height": band_height}) + elif band_center > height * 0.75: # Bottom 25% + regions["footer_bands"].append({"start_y": start_y, "end_y": end_y, "height": band_height}) + + # Estimate margins using both techniques + regions["estimated_margins"] = self._estimate_margins_advanced(regions, detected_regions, page_size) + + return regions + + def _estimate_margins_advanced( + self, regions: Dict, detected_regions: List[Dict], page_size: Tuple[int, int] + ) -> Dict: + """ + Advanced margin estimation using both band and contour information. + """ + width, height = page_size + margins = { + "top": 0, + "bottom": 0, + "left": 50, # Default estimates + "right": 50, + } + + # Calculate top margin from header regions + header_sources = [] + if regions["header_bands"]: + header_sources.append(max(band["end_y"] for band in regions["header_bands"])) + + # Add header regions from contour detection + header_regions = [r for r in detected_regions if r["type"] == "header"] + if header_regions: + header_sources.append(max(r["y"] + r["height"] for r in header_regions)) + + if header_sources: + margins["top"] = max(header_sources) + + # Calculate bottom margin from footer regions + footer_sources = [] + if regions["footer_bands"]: + footer_sources.append(min(band["start_y"] for band in regions["footer_bands"])) + + # Add footer regions from contour detection + footer_regions = [r for r in detected_regions if r["type"] == "footer"] + if footer_regions: + footer_sources.append(min(r["y"] for r in footer_regions)) + + if footer_sources: + margins["bottom"] = height - min(footer_sources) + + # Calculate left/right margins from contour detection + left_regions = [r for r in detected_regions if r["type"] == "left_margin"] + if left_regions: + margins["left"] = max(r["x"] + r["width"] for r in left_regions) + + right_regions = [r for r in detected_regions if r["type"] == "right_margin"] + if right_regions: + margins["right"] = width - min(r["x"] for r in right_regions) + + # Convert to relative percentages for consistency + return { + "top_px": margins["top"], + "bottom_px": margins["bottom"], + "left_px": margins["left"], + "right_px": margins["right"], + "top_percent": (margins["top"] / height) * 100 if height > 0 else 0, + "bottom_percent": (margins["bottom"] / height) * 100 if height > 0 else 0, + "left_percent": (margins["left"] / width) * 100 if width > 0 else 0, + "right_percent": (margins["right"] / width) * 100 if width > 0 else 0, + } + + def _classify_regions(self, bands: List[Tuple[int, int]], page_size: Tuple[int, int]) -> Dict: + """ + Classify horizontal bands into headers, footers, and margins. + """ + width, height = page_size + regions = {"header_bands": [], "footer_bands": [], "estimated_margins": {}} + + for start_y, end_y in bands: + band_center = (start_y + end_y) / 2 + band_height = end_y - start_y + + # Classify based on position + if band_center < height * 0.25: # Top 25% + regions["header_bands"].append({"start_y": start_y, "end_y": end_y, "height": band_height}) + elif band_center > height * 0.75: # Bottom 25% + regions["footer_bands"].append({"start_y": start_y, "end_y": end_y, "height": band_height}) + + # Estimate margins based on bands + regions["estimated_margins"] = self._estimate_margins_from_bands(regions, page_size) + + return regions + + def _estimate_margins_from_bands(self, regions: Dict, page_size: Tuple[int, int]) -> Dict: + """ + Estimate page margins based on detected bands. + """ + width, height = page_size + margins = { + "top": 0, + "bottom": 0, + "left": 50, # Default estimates + "right": 50, + } + + # Calculate top margin from header bands + if regions["header_bands"]: + max_header_end = max(band["end_y"] for band in regions["header_bands"]) + margins["top"] = max_header_end + + # Calculate bottom margin from footer bands + if regions["footer_bands"]: + min_footer_start = min(band["start_y"] for band in regions["footer_bands"]) + margins["bottom"] = height - min_footer_start + + # Convert to relative percentages for consistency + return { + "top_px": margins["top"], + "bottom_px": margins["bottom"], + "left_px": margins["left"], + "right_px": margins["right"], + "top_percent": (margins["top"] / height) * 100, + "bottom_percent": (margins["bottom"] / height) * 100, + "left_percent": (margins["left"] / width) * 100, + "right_percent": (margins["right"] / width) * 100, + } + + def _aggregate_margin_data(self, margin_data: List[Dict], page_size: Tuple[int, int]) -> Dict: + """ + Aggregate margin data from multiple page comparisons. + """ + # Average the margin estimates + all_margins = [data.get("estimated_margins", {}) for data in margin_data if data.get("estimated_margins")] + + if not all_margins: + return self._analyze_single_page_size(page_size) + + # Calculate average margins + avg_margins = {} + for key in [ + "top_px", + "bottom_px", + "left_px", + "right_px", + "top_percent", + "bottom_percent", + "left_percent", + "right_percent", + ]: + values = [m.get(key, 0) for m in all_margins if key in m] + avg_margins[key] = sum(values) / len(values) if values else 0 + + # Collect all bands and regions + all_header_bands = [] + all_footer_bands = [] + all_detected_regions = [] + + for data in margin_data: + all_header_bands.extend(data.get("header_bands", [])) + all_footer_bands.extend(data.get("footer_bands", [])) + all_detected_regions.extend(data.get("detected_regions", [])) + + # Aggregate detected regions by type + region_stats = {} + for region in all_detected_regions: + region_type = region["type"] + if region_type not in region_stats: + region_stats[region_type] = [] + region_stats[region_type].append(region) + + return { + "layout_analysis": { + "header_bands": all_header_bands, + "footer_bands": all_footer_bands, + "detected_regions": all_detected_regions, + "region_statistics": { + region_type: { + "count": len(regions), + "avg_area": sum(r["area"] for r in regions) / len(regions) if regions else 0, + "total_area": sum(r["area"] for r in regions), + } + for region_type, regions in region_stats.items() + }, + "estimated_margins": avg_margins, + "analysis_method": "multi_page_comparison_advanced", + } + } + + def _analyze_single_page(self, image: "Image") -> Dict: + """ + Analyze a single page when comparison isn't possible. + """ + return self._analyze_single_page_size(image.size) + + def _analyze_single_page_size(self, page_size: Tuple[int, int]) -> Dict: + """ + Provide default margin estimates for single page analysis. + """ + width, height = page_size + + # Use common academic paper margins as defaults + default_margins = { + "top_px": int(height * 0.1), # 10% top margin + "bottom_px": int(height * 0.1), # 10% bottom margin + "left_px": int(width * 0.1), # 10% left margin + "right_px": int(width * 0.1), # 10% right margin + "top_percent": 10.0, + "bottom_percent": 10.0, + "left_percent": 10.0, + "right_percent": 10.0, + } + + return { + "layout_analysis": { + "header_bands": [], + "footer_bands": [], + "estimated_margins": default_margins, + "analysis_method": "default_estimates", + } + } diff --git a/extralit-server/src/extralit_server/contexts/document/preprocessing.py b/extralit-server/src/extralit_server/contexts/document/preprocessing.py new file mode 100644 index 000000000..b467eed3e --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/document/preprocessing.py @@ -0,0 +1,270 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + +"""Document preprocessing utilities.""" + +import logging +import os +import tempfile +import time +from io import BytesIO +from typing import List +from dataclasses import dataclass +from uuid import uuid4 + +import lazy_loader as lazy +from pydantic import Field +from pydantic_settings import BaseSettings +from extralit_server.contexts.document.margin import PDFAnalyzer +from extralit_server.api.schemas.v1.document.preprocessing import PDFMetadata + + +ocrmypdf = lazy.load("ocrmypdf") + +_LOGGER = logging.getLogger(__name__) + + +@dataclass +class PDFProcessingResponse: + """ + Result of PDF preprocessing containing both processed data and analysis metadata. + """ + + processed_data: bytes + metadata: PDFMetadata + + +class PDFPreprocessingSettings(BaseSettings): + """ + PDF preprocessing settings that can be configured via environment variables. + + All settings have the PREPROCESSING_ prefix. + """ + + class Config: + env_prefix = "PREPROCESSING_" + + enabled: bool = Field( + default=True, description="Enable PDF preprocessing with OCRmyPDF. Set to False to disable all processing." + ) + + enable_analysis: bool = Field(default=True, description="Enable PDF layout analysis and margin detection") + + language: List[str] = Field( + default=["eng"], description="List of languages for OCR processing (e.g., ['eng', 'spa', 'fra'])" + ) + + rotate_pages: bool = Field(default=True, description="Auto-rotate pages with horizontal text") + + rotate_pages_threshold: float = Field( + default=2.0, + description="Threshold for auto-rotation", + ) + + deskew: bool = Field(default=False, description="Fix skewed text") + + clean: bool = Field(default=True, description="Use `unpaper` to clean up artifacts") + + optimize: int = Field( + default=1, description="Optimize output file size (0=none, 1=lossless, 2=lossy, 3=aggressive)" + ) + + pdf_renderer: str = Field(default="hocr", description="PDF renderer: 'auto', 'hocr', 'sandwich'") + + force_ocr: bool = Field(default=False, description="Force OCR on all pages, even if they already have text") + + skip_text: bool = Field(default=True, description="Skip text-based operations (OCR only for images)") + + redo_ocr: bool = Field(default=False, description="Redo OCR on pages that already have OCR") + + tesseract_timeout: int = Field( + default=0, description="Timeout for Tesseract OCR processing in seconds (0 to skip Tesseract OCR)" + ) + + progress_bar: bool = Field(default=False, description="Show progress bar during processing") + + output_type: str = Field( + default="pdf", + description="Output type for OCRmyPDF. Set to 'pdf' to skip PDF/A conversion.", + ) + + fast_web_view: int = Field( + default=999999, + description="Fast web view optimization. Set to 999999 to disable fast web view optimization.", + ) + + skip_big: float = Field( + default=100.0, + description="Image size threshold in MB to skip OCR processing.", + ) + + jobs: int = Field( + default=1, + description="Number of worker processes to use for OCR. Set to 1 for Docker containers with limited CPU to avoid oversubscription.", + ) + + def get_ocrmypdf_args(self) -> dict: + """ + Get OCRmyPDF arguments as a dictionary for use with **kwargs. + + Returns: + Dictionary of OCRmyPDF arguments excluding input/output parameters. + """ + return { + "language": self.language, + "rotate_pages": self.rotate_pages, + "rotate_pages_threshold": self.rotate_pages_threshold, + "deskew": self.deskew, + "clean": self.clean, + "optimize": self.optimize, + "pdf_renderer": self.pdf_renderer, + "force_ocr": self.force_ocr, + "skip_text": self.skip_text, + "tesseract_timeout": self.tesseract_timeout, + "redo_ocr": self.redo_ocr, + "progress_bar": self.progress_bar, + "output_type": self.output_type, + "fast_web_view": self.fast_web_view, + "skip_big": self.skip_big, + "jobs": self.jobs, + } + + +settings = PDFPreprocessingSettings() + + +class PDFPreprocessor: + """ + PDF preprocessor that uses OCRmyPDF for rotation, OCR, and optimization. + Also performs layout analysis to extract margin and structure information. + + Can be configured with environment variables using the PDFPreprocessingSettings. + """ + + def __init__(self, settings: PDFPreprocessingSettings = settings): + """ + Initialize the PDF preprocessor. + + Args: + settings: Optional PDFPreprocessingSettings instance. If None, loads from environment. + """ + self.settings = settings + + if self.settings.enable_analysis: + self.analyzer = PDFAnalyzer() + else: + self.analyzer = None + + def preprocess(self, file_data: bytes, filename: str) -> PDFProcessingResponse: + """ + Preprocess PDF with OCRmyPDF and analyze layout structure. + + Args: + file_data: PDF file data as bytes + filename: Original filename for logging purposes + + Returns: + PDFProcessingResult containing processed data and layout analysis metadata + """ + # Initialize metadata variables + analysis_results = None + processing_time = 0.0 + processed_data = file_data + + # Handle non-PDF files + if not filename.lower().endswith(".pdf"): + pass # Use default values + + # Handle disabled preprocessing + elif not self.settings.enabled: + if self.analyzer: + analysis_results = self.analyzer.analyze_pdf_layout(file_data, filename) + + # Handle PDF processing + else: + try: + start_time = time.time() + + # Step 1: Analyze original PDF layout (if enabled) + if self.analyzer: + analysis_results = self.analyzer.analyze_pdf_layout(file_data, filename) + + # Step 2: OCR preprocessing + try: + input_buffer = BytesIO(file_data) + output_buffer = BytesIO() + + ocrmypdf.ocr(input_buffer, output_buffer, **self.settings.get_ocrmypdf_args()) # type: ignore + + processed_data = output_buffer.getvalue() + output_buffer.close() + input_buffer.close() + + except Exception as buffer_error: + _LOGGER.debug(f"BytesIO approach failed for {filename}, falling back to temp files: {buffer_error}") + processed_data = self._preprocess_with_temp_files(file_data, filename) + + processing_time = time.time() - start_time + print(filename, analysis_results) + + except Exception: + # Use default values on error + pass + + # Single PDFMetadata initialization for all code paths + metadata = PDFMetadata(filename=filename, processing_time=processing_time, analysis_results=analysis_results) + + return PDFProcessingResponse(processed_data=processed_data, metadata=metadata) + + def _preprocess_with_temp_files(self, file_data: bytes, filename: str) -> bytes: + """ + Fallback implementation using unique temporary files to avoid concurrency issues. + """ + input_temp_file = None + output_temp_file = None + + try: + unique_id = str(uuid4()) + temp_dir = tempfile.gettempdir() + + input_temp_file = tempfile.NamedTemporaryFile( + suffix=".pdf", prefix=f"ocr_input_{unique_id}_", dir=temp_dir, delete=False + ) + input_temp_file.write(file_data) + input_temp_file.flush() + input_temp_file.close() + + output_temp_file = tempfile.NamedTemporaryFile( + suffix=".pdf", prefix=f"ocr_output_{unique_id}_", dir=temp_dir, delete=False + ) + output_temp_file.close() + + ocrmypdf.ocr(input_temp_file.name, output_temp_file.name, **self.settings.get_ocrmypdf_args()) # type: ignore + + with open(output_temp_file.name, "rb") as f: + processed_data = f.read() + + return processed_data + + finally: + for temp_file in [input_temp_file, output_temp_file]: + if temp_file is not None: + try: + if hasattr(temp_file, "name"): + os.unlink(temp_file.name) + except OSError as e: + _LOGGER.warning(f"Failed to clean up temp file: {e}") + + +preprocessor = PDFPreprocessor() diff --git a/extralit-server/src/extralit_server/contexts/embeddings/__init__.py b/extralit-server/src/extralit_server/contexts/embeddings/__init__.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/embeddings/__init__.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/contexts/hub.py b/extralit-server/src/extralit_server/contexts/hub.py index 8f8ceb981..9d8fbf1a9 100644 --- a/extralit-server/src/extralit_server/contexts/hub.py +++ b/extralit-server/src/extralit_server/contexts/hub.py @@ -19,16 +19,23 @@ from uuid import uuid4 from pathlib import Path -from typing import Any, Optional, List +from typing import Any, Optional, List, TYPE_CHECKING from typing_extensions import Self from tempfile import TemporaryDirectory -from PIL import Image +import lazy_loader as lazy + +datasets = lazy.load("datasets") +PIL = lazy.load("PIL") + from sqlalchemy.orm import selectinload from sqlalchemy.ext.asyncio import AsyncSession from pydantic import BaseModel from huggingface_hub import HfApi, DatasetCard, DatasetCardData -from datasets import Dataset as HFDataset, NamedSplit, load_dataset, features + +if TYPE_CHECKING: + from PIL import Image + from datasets import Dataset as HFDataset from extralit_server.contexts import info from extralit_server.database import get_sync_db @@ -62,7 +69,7 @@ class HubDataset: def __init__(self, name: str, subset: str, split: str, mapping: HubDatasetMapping): - self.dataset: HFDataset = load_dataset(path=name, name=subset, split=split, streaming=True) # type: ignore + self.dataset: "HFDataset" = datasets.load_dataset(path=name, name=subset, split=split, streaming=True) # type: ignore self.split = split self.mapping = mapping self.mapping_feature_names = mapping.sources @@ -121,14 +128,14 @@ def _batch_index_to_row(self, batch: dict, index: int) -> dict: return row def _cast_feature_value(self, feature: Any, value: Any) -> Any: - if isinstance(feature, features.ClassLabel): + if isinstance(feature, datasets.features.ClassLabel): # type: ignore if value == FEATURE_CLASS_LABEL_NO_LABEL: return None else: return feature.int2str(value) - elif isinstance(feature, features.Sequence): + elif isinstance(feature, datasets.features.Sequence): # type: ignore return [self._cast_feature_value(feature.feature, v) for v in value] - elif isinstance(feature, features.Image) and isinstance(value, Image.Image): + elif isinstance(feature, datasets.features.Image) and isinstance(value, PIL.Image.Image): # type: ignore return pil_image_to_data_url(value) else: return value @@ -231,7 +238,9 @@ def __init__(self, dataset: Dataset): self.cache_version = uuid4() def export_to(self, name: str, subset: str, split: str, private: bool, token: str) -> None: - hf_dataset: HFDataset = HFDataset.from_generator(self._rows_generator, split=NamedSplit(split)) # type: ignore + hf_dataset: "HFDataset" = datasets.Dataset.from_generator( + self._rows_generator, split=datasets.NamedSplit(split) + ) # type: ignore hf_dataset.push_to_hub( repo_id=name, config_name=subset, @@ -285,7 +294,7 @@ def _row_fields(self, record: Record) -> dict: feature_value = record.fields.get(field.name) if field.is_image and feature_value is not None and feature_value.startswith("data:"): - row_fields[feature_name] = Image.open(io.BytesIO(data_url_to_bytes(feature_value))) + row_fields[feature_name] = PIL.Image.open(io.BytesIO(data_url_to_bytes(feature_value))) # type: ignore else: row_fields[feature_name] = feature_value @@ -474,7 +483,7 @@ def _create_readme_file(self, directory: str, repo_id: str) -> None: card.save(os.path.join(directory, "README.md")) -def pil_image_to_data_url(image: Image.Image): +def pil_image_to_data_url(image: "Image"): buffer = io.BytesIO() image_format = image.format or DATA_URL_DEFAULT_IMAGE_FORMAT diff --git a/extralit-server/src/extralit_server/contexts/imports.py b/extralit-server/src/extralit_server/contexts/imports.py index 6520d8acc..21a2f1ae9 100644 --- a/extralit-server/src/extralit_server/contexts/imports.py +++ b/extralit-server/src/extralit_server/contexts/imports.py @@ -37,7 +37,7 @@ ImportHistoryCreate, ImportHistoryCreateResponse, ) -from extralit_server.jobs.document_jobs import upload_reference_documents_job +from extralit_server.jobs.document_jobs import upload_and_preprocess_documents_job _LOGGER = logging.getLogger(__name__) @@ -385,12 +385,11 @@ async def process_bulk_upload( if not doc.associated_files: # Create a reference-based job for documents without files job = DEFAULT_QUEUE.enqueue( - upload_reference_documents_job, + upload_and_preprocess_documents_job, reference=reference, reference_data=doc.document_create.model_dump(), file_data_list=[], user_id=user_id, - job_timeout=None, # No timeout for large uploads ) # Store job ID mapped to reference key for frontend tracking @@ -436,7 +435,7 @@ async def process_bulk_upload( # Create a reference-based job for multiple files job = DEFAULT_QUEUE.enqueue( - upload_reference_documents_job, + upload_and_preprocess_documents_job, reference=reference, reference_data=doc.document_create.model_dump(), file_data_list=file_data_list, diff --git a/extralit-server/src/extralit_server/contexts/ocr/__init__.py b/extralit-server/src/extralit_server/contexts/ocr/__init__.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/ocr/__init__.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/contexts/ocr/figures.py b/extralit-server/src/extralit_server/contexts/ocr/figures.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/ocr/figures.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/contexts/ocr/tables.py b/extralit-server/src/extralit_server/contexts/ocr/tables.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/ocr/tables.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/contexts/ocr/text.py b/extralit-server/src/extralit_server/contexts/ocr/text.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/contexts/ocr/text.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/src/extralit_server/jobs/document_jobs.py b/extralit-server/src/extralit_server/jobs/document_jobs.py index 2389e1be4..6a248c000 100644 --- a/extralit-server/src/extralit_server/jobs/document_jobs.py +++ b/extralit-server/src/extralit_server/jobs/document_jobs.py @@ -22,16 +22,18 @@ from rq import Retry from rq.decorators import job + from extralit_server.database import AsyncSessionLocal from extralit_server.jobs import DEFAULT_QUEUE, JOB_TIMEOUT_DISABLED from extralit_server.api.schemas.v1.documents import DocumentCreate from extralit_server.contexts import files, imports +from extralit_server.contexts.document import preprocessing _LOGGER = logging.getLogger(__name__) @job(DEFAULT_QUEUE, timeout=JOB_TIMEOUT_DISABLED, retry=Retry(max=3, interval=[10, 30, 60])) -async def upload_reference_documents_job( +async def upload_and_preprocess_documents_job( reference: str, reference_data: Dict[str, Any], file_data_list: List[Tuple[str, bytes]], # List of (filename, file_data) tuples @@ -129,15 +131,22 @@ async def upload_reference_documents_job( continue try: + # Preprocess PDF files with OCRmyPDF for rotation and OCR, plus layout analysis + preprocessing_result = preprocessing.preprocessor.preprocess( + file_data=file_data, filename=filename + ) + processed_file_data = preprocessing_result.processed_data + + # Store preprocessing metadata in file metadata + file_metadata.update({"preprocessing": preprocessing_result.metadata}) + file_url = files.put_document_file( client=client, workspace_name=workspace.name, document_id=file_document_create.id, # type: ignore - file_data=file_data, + file_data=processed_file_data, filename=filename, - # metadata=file_document_create.model_dump( - # include={"file_name": True, "pmid": True, "doi": True} - # ), + metadata=file_metadata, ) if file_url: @@ -152,6 +161,7 @@ async def upload_reference_documents_job( # Create document in database try: + file_document_create.metadata = file_metadata document = await imports.create_document(db, file_document_create) _LOGGER.info(f"Document created successfully for file {filename} with ID {document.id}") file_result.update({"success": True, "document_id": str(document.id), "status": "created"}) @@ -173,7 +183,7 @@ async def upload_reference_documents_job( results["success"] = results["failed_files"] == 0 except Exception as e: - error_msg = f"Error in upload_reference_documents_job for reference {reference}: {str(e)}" + error_msg = f"Error uploading documents for reference {reference}: {str(e)}" _LOGGER.error(error_msg) results["success"] = False results["errors"].append(str(e)) diff --git a/extralit-server/src/extralit_server/jobs/ocr_jobs.py b/extralit-server/src/extralit_server/jobs/ocr_jobs.py new file mode 100644 index 000000000..fb5dffc96 --- /dev/null +++ b/extralit-server/src/extralit_server/jobs/ocr_jobs.py @@ -0,0 +1,14 @@ +# Copyright 2024-present, Extralit Labs, Inc. +# +# 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. + diff --git a/extralit-server/tests/unit/jobs/test_document_jobs.py b/extralit-server/tests/unit/jobs/test_document_jobs.py index a47cb17e6..ca70ca4ac 100644 --- a/extralit-server/tests/unit/jobs/test_document_jobs.py +++ b/extralit-server/tests/unit/jobs/test_document_jobs.py @@ -16,7 +16,7 @@ from unittest.mock import patch, MagicMock from uuid import uuid4 -from extralit_server.jobs.document_jobs import upload_reference_documents_job +from extralit_server.jobs.document_jobs import upload_and_preprocess_documents_job from tests.factories import WorkspaceFactory, UserFactory @@ -70,7 +70,7 @@ async def test_upload_reference_documents_job_success(self, mock_imports, mock_d mock_model_dump.return_value = {"file_name": "test.pdf", "pmid": None, "doi": "10.1234/test.doi"} # Execute job - result = await upload_reference_documents_job(reference, document_data, file_data_list, user.id) + result = await upload_and_preprocess_documents_job(reference, document_data, file_data_list, user.id) # Debug: print the actual result print(f"DEBUG: result = {result}") @@ -107,7 +107,7 @@ async def test_upload_reference_documents_job_workspace_not_found(self): # Use non-existent workspace ID - the job will handle the lookup internally # Execute job - result = await upload_reference_documents_job(reference, document_data, file_data_list, user.id) + result = await upload_and_preprocess_documents_job(reference, document_data, file_data_list, user.id) # Verify result assert result["success"] is False @@ -165,7 +165,7 @@ async def test_upload_reference_documents_job_partial_failure(self, mock_imports mock_model_dump.return_value = {"file_name": "test.pdf", "pmid": None, "doi": "10.1234/test.doi"} # Execute job - result = await upload_reference_documents_job(reference, document_data, file_data_list, user.id) + result = await upload_and_preprocess_documents_job(reference, document_data, file_data_list, user.id) # Debug: print the actual result print(f"DEBUG: result = {result}") diff --git a/extralit/pdm.lock b/extralit/pdm.lock index 37cb4cf1a..fef71b678 100644 --- a/extralit/pdm.lock +++ b/extralit/pdm.lock @@ -5,7 +5,7 @@ groups = ["default", "dev"] strategy = [] lock_version = "4.5.0" -content_hash = "sha256:70ce069646b7109d8dc4217449d7053c16b14700891f5b9902207ac35ba7943c" +content_hash = "sha256:4eed977ec0ae819f547f71e5131d350c7686fa2a8399a998cb62994db78d442c" [[metadata.targets]] requires_python = ">=3.9.2,<3.14" @@ -2130,6 +2130,18 @@ files = [ {file = "language_data-1.3.0.tar.gz", hash = "sha256:7600ef8aa39555145d06c89f0c324bf7dab834ea0b0a439d8243762e3ebad7ec"}, ] +[[package]] +name = "lazy-loader" +version = "0.4" +summary = "" +dependencies = [ + "packaging", +] +files = [ + {file = "lazy_loader-0.4-py3-none-any.whl", hash = "sha256:342aa8e14d543a154047afb4ba8ef17f5563baad3fc610d7b15b213b0f119efc"}, + {file = "lazy_loader-0.4.tar.gz", hash = "sha256:47c75182589b91a4e1a85a136c074285a5ad4d9f39c63e0d7fb76391c4574cd1"}, +] + [[package]] name = "llama-cloud" version = "0.1.23" diff --git a/extralit/pyproject.toml b/extralit/pyproject.toml index 328c37fb4..e2865f785 100644 --- a/extralit/pyproject.toml +++ b/extralit/pyproject.toml @@ -23,6 +23,7 @@ dependencies = [ "pillow>=9.5.0", "standardwebhooks>=1.0.0", "typer>=0.9.0", + "lazy-loader>=0.4", # for environment variables "python-dotenv~=1.1.0", @@ -49,6 +50,7 @@ dependencies = [ "fastparquet >= 2023.10.0; python_version < '3.13'", "fastparquet >= 2024.4.0; python_version >= '3.13'", "tiktoken ~= 0.9.0", + "bibtexparser>=1.4.3", # for llama-index "llama-index ~= 0.10.68", @@ -61,7 +63,6 @@ dependencies = [ # for weaviate vector db "weaviate-client >= 4", "llama-index-vector-stores-weaviate ~= 1.0.0", - "bibtexparser>=1.4.3", ] nlp = [ "textdescriptives", diff --git a/extralit/src/extralit/_helpers/_media.py b/extralit/src/extralit/_helpers/_media.py index 01a7edc02..09c0ceb72 100644 --- a/extralit/src/extralit/_helpers/_media.py +++ b/extralit/src/extralit/_helpers/_media.py @@ -16,9 +16,14 @@ import io import warnings from pathlib import Path -from typing import Union, Optional +from typing import Union, Optional, TYPE_CHECKING -from PIL import Image +import lazy_loader as lazy + +PIL = lazy.load("PIL") + +if TYPE_CHECKING: + from PIL.Image import Image def pil_to_data_uri(image_object: Optional["Image"]) -> Optional[str]: @@ -30,7 +35,7 @@ def pil_to_data_uri(image_object: Optional["Image"]) -> Optional[str]: """ if image_object is None: return None - if not isinstance(image_object, Image.Image): + if not isinstance(image_object, PIL.Image.Image): # type: ignore raise ValueError("The image_object must be a PIL Image object.") image_format = image_object.format @@ -82,28 +87,28 @@ def cast_image(image: Union["Image", str, Path]) -> str: return filepath_to_data_uri(image) elif isinstance(image, Path): return filepath_to_data_uri(image) - elif isinstance(image, Image.Image): + elif isinstance(image, PIL.Image.Image): # type: ignore return pil_to_data_uri(image) else: raise ValueError("The image must be a data URI string, a file path, or a PIL Image object.") -def uncast_image(image: str) -> "Image": +def uncast_image(image: Union[str, "Image"]) -> "Image": """Convert a base64 data URI string to a PIL image.""" - if isinstance(image, Image.Image): + if isinstance(image, PIL.Image.Image): # type: ignore return image elif not isinstance(image, str): raise ValueError("The image must be a data URI string.") elif image.startswith("data:image"): try: image_data = base64.b64decode(image.split(",")[1]) - image = Image.open(io.BytesIO(image_data)) + image = PIL.Image.open(io.BytesIO(image_data)) # type: ignore except Exception as e: raise ValueError("An error occurred while converting the data URI to a PIL image.") from e return image elif image.startswith("http"): return image elif Path(image).exists(): - return Image.open(image) + return PIL.Image.open(image) # type: ignore else: raise ValueError("The image must be a data URI string.") diff --git a/extralit/src/extralit/cli/documents/import_bib.py b/extralit/src/extralit/cli/documents/import_bib.py index 3f597e791..8084d48eb 100644 --- a/extralit/src/extralit/cli/documents/import_bib.py +++ b/extralit/src/extralit/cli/documents/import_bib.py @@ -38,16 +38,19 @@ import pandas as pd import typer -import bibtexparser from rich.console import Console from rich.progress import Progress, SpinnerColumn, TextColumn from rich.table import Table +import lazy_loader as lazy from extralit.workspaces._resource import Workspace from extralit.client import Extralit from extralit.cli.rich import get_themed_panel +bibtexparser = lazy.load("bibtexparser") + + def _clean_bibtex_field(value: str) -> str: """Clean BibTeX field by removing braces and extra whitespace.""" if not value: diff --git a/extralit/src/extralit/datasets/_io/_hub.py b/extralit/src/extralit/datasets/_io/_hub.py index 15851ae4d..00a5ded4c 100644 --- a/extralit/src/extralit/datasets/_io/_hub.py +++ b/extralit/src/extralit/datasets/_io/_hub.py @@ -19,10 +19,8 @@ from tempfile import TemporaryDirectory from typing import TYPE_CHECKING, Any, Dict, Optional, Type, Union, Literal from uuid import UUID +import lazy_loader as lazy -from datasets import DatasetDict -from datasets.data_files import EmptyDatasetError -from PIL import Image from extralit._exceptions import ImportDatasetError from extralit._exceptions._api import UnprocessableEntityError @@ -34,6 +32,9 @@ from extralit.records._mapping import IngestedRecordMapper from extralit.responses import Response +datasets = lazy.load("datasets") +PIL = lazy.load("PIL") + if TYPE_CHECKING: from datasets import Dataset as HFDataset @@ -143,7 +144,8 @@ def from_hub( A `Dataset` loaded from the Hugging Face Hub. """ from extralit.settings import Settings - from datasets import load_dataset + + # load_dataset is accessed via lazy loaded datasets module from huggingface_hub import snapshot_download settings = settings or "ui" @@ -194,15 +196,15 @@ def from_hub( if with_records: try: - hf_dataset = load_dataset( + hf_dataset = datasets.load_dataset( # type: ignore path=repo_id, split=split, name=subset, **kwargs, - ) # type: ignore + ) hf_dataset = cls._get_dataset_split(hf_dataset=hf_dataset, split=split, **kwargs) cls._log_dataset_records(hf_dataset=hf_dataset, dataset=dataset) - except EmptyDatasetError: + except datasets.data_files.EmptyDatasetError: # type: ignore warnings.warn( message="Trying to load a dataset `with_records=True` but dataset does not contain any records.", category=UserWarning, @@ -298,7 +300,7 @@ def _get_dataset_split(hf_dataset: "HFDataset", split: Optional[str] = None, **k HFDataset: The single dataset. """ - if isinstance(hf_dataset, DatasetDict) and split is None: + if isinstance(hf_dataset, datasets.DatasetDict) and split is None: # type: ignore split = next(iter(hf_dataset.keys())) if len(hf_dataset.keys()) > 1: warnings.warn( @@ -326,7 +328,7 @@ def _get_sample_hf_record(hf_dataset: "HFDataset") -> Dict: json.dumps(value) sample_huggingface_record[key] = value except TypeError: - if isinstance(value, Image.Image): + if isinstance(value, PIL.Image.Image): # type: ignore sample_huggingface_record[key] = pil_to_data_uri(value) else: sample_huggingface_record[key] = "Record value is not serializable" diff --git a/extralit/src/extralit/records/_dataset_records.py b/extralit/src/extralit/records/_dataset_records.py index 4c9b3fe15..1bfae04f6 100644 --- a/extralit/src/extralit/records/_dataset_records.py +++ b/extralit/src/extralit/records/_dataset_records.py @@ -24,13 +24,14 @@ from extralit._models import RecordModel from extralit._exceptions import RecordsIngestionError from extralit.client import Extralit -from extralit.records._io import GenericIO, HFDataset, HFDatasetsIO, JsonIO +from extralit.records._io import GenericIO, HFDatasetsIO, JsonIO from extralit.records._mapping import IngestedRecordMapper from extralit.records._resource import Record from extralit.records._search import Query if TYPE_CHECKING: from extralit.datasets import Dataset + from datasets import Dataset as HFDataset class RecordErrorHandling(Enum): @@ -246,7 +247,7 @@ def __repr__(self) -> str: def log( self, - records: Union[List[dict], List[Record], HFDataset], + records: Union[List[dict], List[Record], "HFDataset"], mapping: Optional[Dict[str, Union[str, Sequence[str]]]] = None, user_id: Optional[UUID] = None, batch_size: int = DEFAULT_BATCH_SIZE, @@ -403,7 +404,7 @@ def from_json(self, path: Union[Path, str]) -> List[Record]: records = JsonIO._records_from_json(path=path) return self.log(records=records) - def to_datasets(self) -> HFDataset: + def to_datasets(self) -> "HFDataset": """ Export the records to a HFDataset. @@ -420,7 +421,7 @@ def to_datasets(self) -> HFDataset: def _ingest_records( self, - records: Union[List[Dict[str, Any]], List[Record], HFDataset], + records: Union[List[Dict[str, Any]], List[Record], "HFDataset"], mapping: Optional[Dict[str, Union[str, Sequence[str]]]] = None, user_id: Optional[UUID] = None, on_error: RecordErrorHandling = RecordErrorHandling.RAISE, diff --git a/extralit/src/extralit/records/_io/__init__.py b/extralit/src/extralit/records/_io/__init__.py index 206b7a71d..398ce4a30 100644 --- a/extralit/src/extralit/records/_io/__init__.py +++ b/extralit/src/extralit/records/_io/__init__.py @@ -15,4 +15,3 @@ from extralit.records._io._datasets import HFDatasetsIO # noqa: F401 from extralit.records._io._generic import GenericIO # noqa: F401 from extralit.records._io._json import JsonIO # noqa: F401 -from extralit.records._io._datasets import HFDataset # noqa: F401 diff --git a/extralit/src/extralit/records/_io/_datasets.py b/extralit/src/extralit/records/_io/_datasets.py index 9de0afddb..2432ca65e 100644 --- a/extralit/src/extralit/records/_io/_datasets.py +++ b/extralit/src/extralit/records/_io/_datasets.py @@ -14,14 +14,17 @@ import warnings from typing import TYPE_CHECKING, Any, Dict, List, Union, Optional, Tuple - -from datasets import Dataset as HFDataset, Sequence -from datasets import Image, ClassLabel, Value +import lazy_loader as lazy from extralit._helpers._media import pil_to_data_uri, uncast_image from extralit.records._io._generic import GenericIO +datasets = lazy.load("datasets") + + if TYPE_CHECKING: + from datasets import Dataset as HFDataset, ClassLabel + from extralit.records import Record from extralit.datasets import Dataset from extralit.records._mapping import IngestedRecordMapper @@ -41,7 +44,7 @@ def _cast_images_as_urls(hf_dataset: "HFDataset", columns: List[str]) -> "HFData for column in columns: # make an updated features object with the new column type features = hf_dataset.features.copy() - features[column] = Value("string") + features[column] = datasets.Value("string") # type: ignore # cast the column in batches hf_dataset = hf_dataset.map( function=lambda batch: {column: [pil_to_data_uri(sample) for sample in batch]}, @@ -55,7 +58,7 @@ def _cast_images_as_urls(hf_dataset: "HFDataset", columns: List[str]) -> "HFData return hf_dataset -def _int2class_name(feature: ClassLabel, value: int) -> Optional[str]: +def _int2class_name(feature: "ClassLabel", value: int) -> Optional[str]: try: return feature.int2str(value) except Exception as ex: @@ -73,7 +76,7 @@ def map2str_list(x: dict, column_name: str, features: dict): for column in columns: features = hf_dataset.features.copy() - features[column] = Sequence(Value("string")) + features[column] = datasets.Sequence(datasets.Value("string")) # type: ignore hf_dataset = hf_dataset.map( map2str_list, fn_kwargs={"column_name": column, "features": hf_dataset.features}, @@ -103,7 +106,7 @@ def label_column2str(x: dict, column: str, features: dict) -> Dict[str, Union[st for column in columns: features = hf_dataset.features.copy() - features[column] = Value("string") + features[column] = datasets.Value("string") # type: ignore hf_dataset = hf_dataset.map( label_column2str, fn_kwargs={"column": column, "features": hf_dataset.features}, features=features ) @@ -126,7 +129,7 @@ def _uncast_uris_as_images(hf_dataset: "HFDataset", columns: List[str]) -> "HFDa for column in columns: features = hf_dataset.features.copy() - features[column] = Image() + features[column] = datasets.Image() # type: ignore casted_hf_dataset = hf_dataset.map( function=lambda batch: {column: [uncast_image(sample) for sample in batch]}, with_indices=False, @@ -162,7 +165,7 @@ def _uncast_label_questions_as_classlabels(hf_dataset: "HFDataset", columns: Lis continue values = list(hf_dataset.unique(column)) features = hf_dataset.features.copy() - features[column] = ClassLabel(names=values) + features[column] = datasets.ClassLabel(names=values) # type: ignore hf_dataset = hf_dataset.map( function=lambda batch: {column: [values.index(sample) for sample in batch]}, with_indices=False, @@ -191,10 +194,10 @@ def _is_hf_dataset(dataset: Any) -> bool: Returns: bool: True if the object is a Hugging Face dataset, False otherwise. """ - return isinstance(dataset, HFDataset) + return isinstance(dataset, datasets.Dataset) # type: ignore @staticmethod - def to_datasets(records: List[Union["Record", Tuple["Record", float]]], dataset: "Dataset") -> HFDataset: + def to_datasets(records: List[Union["Record", Tuple["Record", float]]], dataset: "Dataset") -> "HFDataset": """ Export the records to a Hugging Face dataset. @@ -202,7 +205,7 @@ def to_datasets(records: List[Union["Record", Tuple["Record", float]]], dataset: The dataset containing the records. """ record_dicts = GenericIO.to_dict(records, flatten=True) - hf_dataset = HFDataset.from_dict(record_dicts) + hf_dataset = datasets.Dataset.from_dict(record_dicts) # type: ignore hf_dataset = HFDatasetsIO._uncast_argilla_attributes_to_datasets(hf_dataset, dataset.schema) return hf_dataset @@ -277,11 +280,11 @@ def to_argilla(hf_dataset: "HFDataset", mapper: "IngestedRecordMapper") -> "HFDa class_label_sequence_columns = [] for name, feature in hf_dataset.features.items(): - if isinstance(feature, Image): + if isinstance(feature, datasets.Image): # type: ignore image_columns.append(name) - elif isinstance(feature, ClassLabel): + elif isinstance(feature, datasets.ClassLabel): # type: ignore class_label_columns.append(name) - elif isinstance(feature, Sequence) and isinstance(feature.feature, ClassLabel): + elif isinstance(feature, datasets.Sequence) and isinstance(feature.feature, datasets.ClassLabel): # type: ignore class_label_sequence_columns.append(name) if image_columns: