diff --git a/docling_eval/benchmarks/constants.py b/docling_eval/benchmarks/constants.py index 8fd8bc6e..00abf95d 100644 --- a/docling_eval/benchmarks/constants.py +++ b/docling_eval/benchmarks/constants.py @@ -2,6 +2,8 @@ class BenchMarkColumns(str, Enum): + DOCLING_VERSION = "docling_version" + AZURE_VERSION = "azure_version" CONVERTER_TYPE = "converter_type" CONVERTER_VERSION = "converter_version" DOCLING_PIPELINE = "docling_pipeline" diff --git a/docling_eval/benchmarks/utils.py b/docling_eval/benchmarks/utils.py index b40848f4..7d549cc1 100644 --- a/docling_eval/benchmarks/utils.py +++ b/docling_eval/benchmarks/utils.py @@ -390,8 +390,6 @@ def save_shard_to_disk( batch = Dataset.from_list(items) # , features=features) output_file = dataset_path / f"shard_{thread_id:06}_{shard_id:06}.{shard_format}" - logging.info(f"Saved shard {shard_id} to {output_file} with {len(items)} documents") - if shard_format == "json": batch.to_json(output_file) @@ -401,6 +399,8 @@ def save_shard_to_disk( else: raise ValueError(f"Unsupported shard_format: {shard_format}") + logging.info(f"Saved shard {shard_id} to {output_file} with {len(items)} documents") + shard_id += 1 return shard_id, [], 0 diff --git a/docling_eval/cli/main.py b/docling_eval/cli/main.py index 996965dc..59bd505e 100644 --- a/docling_eval/cli/main.py +++ b/docling_eval/cli/main.py @@ -261,6 +261,9 @@ def evaluate( if not os.path.exists(idir): _log.error(f"Benchmark directory not found: {idir}") + # creare the output directories if they do not exist + os.makedirs(odir, exist_ok=True) + # Save the evaluation save_fn = odir / f"evaluation_{benchmark.value}_{modality.value}.json" diff --git a/docling_eval_next/dataset_builders/dataset_builder.py b/docling_eval_next/dataset_builders/dataset_builder.py index 4492e6a6..e336daa6 100644 --- a/docling_eval_next/dataset_builders/dataset_builder.py +++ b/docling_eval_next/dataset_builders/dataset_builder.py @@ -2,8 +2,9 @@ from abc import abstractmethod from io import BytesIO from pathlib import Path -from typing import Iterable, Optional, Union +from typing import Any, Iterable, Optional, Union +import ibm_boto3 from docling.utils.utils import chunkify from docling_core.types.io import DocumentStream from huggingface_hub import snapshot_download @@ -23,9 +24,80 @@ class HFSource(BaseModel): class S3Source(BaseModel): - # TBD - pass + endpoint: str + access_key: str + secret_key: str + cos_bucket: str # Bucket of interest inside of COS. + cos_dir: str # Path to dataset "directory" of interest in COS. + cos_resource: Optional[Any] = None + cos_client: Optional[Any] = None + overwrite_downloads: Optional[bool] = True + + + def __init__(self, **data): + super().__init__(**data) + self.cos_resource = self.initialize_s3_resource() + self.cos_client = self.initialize_s3_client() + + def initialize_s3_client(self): + """Initializes boto3 resource - s3 instance + Returns the s3 instance + """ + return ibm_boto3.client( + "s3", + endpoint_url=self.endpoint, + aws_access_key_id=self.access_key, + aws_secret_access_key=self.secret_key, + ) + + def initialize_s3_resource(self): + """Initializes boto3 resource - s3 instance + Returns the s3 instance + """ + + return ibm_boto3.resource( + "s3", + endpoint_url=self.endpoint, + aws_access_key_id=self.access_key, + aws_secret_access_key=self.secret_key, + ) + def download_objects(self, download_dir): + """Downloads the objects from the bucket to the given download directory.""" + print(f"Download objects from {self.cos_bucket}/{self.cos_dir} to {download_dir}") + paginator = self.cos_client.get_paginator("list_objects_v2") + pagination_params = { + "Bucket": self.cos_bucket, + "Prefix": self.cos_dir, + "MaxKeys": 100, + } + page_iterator = paginator.paginate(**pagination_params) + for page in page_iterator: + for file_meta in page["Contents"]: + # print(file_meta) + relative_path = file_meta["Key"][len(self.cos_dir) + 1:] + if len(relative_path) ==0: + continue + if file_meta["Size"] == 0: + continue + + # Identify the path to the file on disk. + local_file_path = os.path.join(download_dir, relative_path) + print(f"Download {file_meta['Key']} to {local_file_path}") + + # If the option to overwrite downloads is ON, and the file already exists, skip it. + if self.overwrite_downloads and os.path.exists(local_file_path): + print(f"File {local_file_path} already exists. Skipping.") + continue + + # Create the directories as required + local_dir = os.path.dirname(local_file_path) + if not os.path.exists(local_dir): + os.makedirs(local_dir) + + self.cos_resource.Bucket(self.cos_bucket).download_file(file_meta["Key"], local_file_path) + + return download_dir class BaseEvaluationDatasetBuilder: def __init__( @@ -65,6 +137,11 @@ def retrieve_input_dataset(self) -> Path: path = Path(path_str) elif isinstance(self.dataset_source, Path): path = self.dataset_source + elif isinstance(self.dataset_source, S3Source): + # Download the data from S3 bucket to the target folder + self.dataset_source.download_objects(self.target) + path = Path(self.target) + self.dataset_local_path = path else: raise RuntimeError( f"Unknown dataset_source type {type(self.dataset_source)}" @@ -103,13 +180,14 @@ def save_to_disk(self): "You must first retrieve the source dataset. Call retrieve_input_dataset()." ) - test_dir = self.target / "test" + test_dir = self.target / "intermediate_files" os.makedirs(test_dir, exist_ok=True) count = 0 for record_chunk in chunkify(self.iterate(), 80): record_chunk = [r.as_record_dict() for r in record_chunk] - save_shard_to_disk(items=record_chunk, dataset_path=test_dir) + shard_id = count # set the id based on the count of records.. + save_shard_to_disk(items=record_chunk, dataset_path=test_dir, shard_id=shard_id) count += len(record_chunk) write_datasets_info( diff --git a/docling_eval_next/dataset_builders/fintabnet_builder.py b/docling_eval_next/dataset_builders/fintabnet_builder.py new file mode 100644 index 00000000..b0656263 --- /dev/null +++ b/docling_eval_next/dataset_builders/fintabnet_builder.py @@ -0,0 +1,300 @@ +import glob +import io +import json +import os +from io import BytesIO +from pathlib import Path +from typing import Any, Dict, Iterable, List + +from datasets import load_dataset +from docling_core.types import DoclingDocument +from docling_core.types.doc import ( + BoundingBox, + CoordOrigin, + DocItemLabel, + ImageRef, + PageItem, + ProvenanceItem, + Size, + TableCell, + TableData, +) +from docling_core.types.io import DocumentStream +from PIL.Image import Image +from tqdm import tqdm + +from docling_eval.benchmarks.constants import BenchMarkColumns +from docling_eval.benchmarks.utils import ( + convert_html_table_into_docling_tabledata, + crop_bounding_box, + extract_images, + from_pil_to_base64uri, + get_binhash, +) +from docling_eval.converters.models.tableformer.tf_model_prediction import PageTokens +from docling_eval.visualisation.visualisations import save_comparison_html +from docling_eval_next.datamodels.dataset_record import DatasetRecord +from docling_eval_next.dataset_builders.dataset_builder import ( + BaseEvaluationDatasetBuilder, + HFSource, +) +from docling_eval_next.prediction_providers.prediction_provider import ( + BasePredictionProvider, +) + +TRUE_HTML_EXPORT_LABELS = { + DocItemLabel.TITLE, + DocItemLabel.DOCUMENT_INDEX, + DocItemLabel.SECTION_HEADER, + DocItemLabel.PARAGRAPH, + DocItemLabel.TABLE, + DocItemLabel.PICTURE, + DocItemLabel.FORMULA, + DocItemLabel.CHECKBOX_UNSELECTED, + DocItemLabel.CHECKBOX_SELECTED, + DocItemLabel.TEXT, + DocItemLabel.LIST_ITEM, + DocItemLabel.CODE, + DocItemLabel.REFERENCE, + # Additional + DocItemLabel.CAPTION, + DocItemLabel.PAGE_HEADER, + DocItemLabel.PAGE_FOOTER, + DocItemLabel.FOOTNOTE, +} + +PRED_HTML_EXPORT_LABELS = { + DocItemLabel.TITLE, + DocItemLabel.DOCUMENT_INDEX, + DocItemLabel.SECTION_HEADER, + DocItemLabel.PARAGRAPH, + DocItemLabel.TABLE, + DocItemLabel.PICTURE, + DocItemLabel.FORMULA, + DocItemLabel.CHECKBOX_UNSELECTED, + DocItemLabel.CHECKBOX_SELECTED, + DocItemLabel.TEXT, + DocItemLabel.LIST_ITEM, + DocItemLabel.CODE, + DocItemLabel.REFERENCE, + # Additional + DocItemLabel.PAGE_HEADER, + DocItemLabel.PAGE_FOOTER, + DocItemLabel.FOOTNOTE, +} + + + +class FintabnetDatasetBuilder(BaseEvaluationDatasetBuilder): + """ Base Fintabnet Dataset Builder that will pull dataset from Hugging face.""" + def __init__( + self, + name: str, + prediction_provider: BasePredictionProvider, + target: Path, + do_visualization: bool = True, + ): + super().__init__( + name=name, + dataset_source=HFSource(repo_id="ds4sd/FinTabNet_OTSL"), + prediction_provider=prediction_provider, + target=target, + ) + self.do_visualization = do_visualization + + +class FintabnetTableStructureDatasetBuilder(FintabnetDatasetBuilder): + """ Subclass of FintabnetDatasetBuilder that will define the "iterate" method on how to iterate + the table structure from the dataset.""" + def __init__( + self, + prediction_provider: BasePredictionProvider, + target: Path, + do_visualization: bool = True, + ): + super().__init__( + name="Fintabnet: table-structure", + prediction_provider=prediction_provider, + target=target, + do_visualization=do_visualization, + ) + + def create_page_tokens(self, data: List[Any], height: float, width: float) -> PageTokens: + """Needed for tableformer model only, where it additionally needs the page tokens for extraction. + TODO: Not needed?? - Remove for hyperscalers""" + tokens = [] + # text_lines = [] + + cnt = 0 + for i, row in enumerate(data): + for j, item in enumerate(row): + text = "".join(item["tokens"]) + + tokens.append( + { + "bbox": { + "l": item["bbox"][0], + # "t": height - item["bbox"][3], + "t": item["bbox"][1], + "r": item["bbox"][2], + # "b": height - item["bbox"][1], + "b": item["bbox"][3], + # "coord_origin": str(CoordOrigin.BOTTOMLEFT.value) + "coord_origin": str(CoordOrigin.TOPLEFT.value), + }, + "text": "".join(item["tokens"]), + "id": cnt, + } + ) + cnt += 1 + + result = {"tokens": tokens, "height": height, "width": width} + return PageTokens.parse_obj(result) + + def iterate(self) -> Iterable[DatasetRecord]: + """Iterate and yield each record of the dataset. + Prediction will be run on the yielded record in the calling function.""" + + if not self.retrieved: + raise RuntimeError( + "You must first retrieve the source dataset. Call retrieve_input_dataset()." + ) + + assert self.dataset_local_path is not None + + # Create the folders for saving the intermediate files (test) and visualizations + intermediate_dir = self.target / "intermediate_files" + viz_dir = self.target / "vizualisations" + for _ in [intermediate_dir, viz_dir]: + os.makedirs(_, exist_ok=True) + + # Use glob to find all .parquet files in the directory and clean up the intermediate files + parquet_files = glob.glob(os.path.join(str(intermediate_dir), "*.parquet")) + for file in parquet_files: + try: + os.remove(file) + print(f"Deleted: {file}") + except Exception as e: + print(f"Error deleting {file}: {e}") + + print(f"self.dataset_local_path={self.dataset_local_path}") + print(f"self.name={self.name}") + ds = load_dataset(os.path.join(self.dataset_local_path, "data"), split="test") # TODO - pass the split as argument? + + # TODO - Pass this as an argument? Do we need to run all items.. + max_items = -1 + if max_items == -1: + max_items = len(ds) + + # Iterate each of the record in the dataset + for i, item in tqdm( + enumerate(ds), + total=max_items, + ncols=128, + desc=f"create Fintabnet dataset", + ): + filename = item["filename"] + table_image = item["image"] + + # TODO - For now, process two files instead of the whole dataset + if filename not in ["HAL.2015.page_43.pdf_125177.png", "HAL.2009.page_77.pdf_125051.png"]: + continue + + print(f"\nProcessing file - [{filename}]...") + + true_page_images = [table_image] + # page_tokens = self.create_page_tokens( + # data=item["cells"], height=table_image.height, width=table_image.width + # ) + + # Create the Ground truth document + true_doc = DoclingDocument(name=f"ground-truth {filename}") + + page_index = 1 + + image_scale = 1.0 # TODO - pass as input argument? + + image_ref = ImageRef( + mimetype="image/png", + dpi=round(72 * image_scale), + size=Size(width=float(table_image.width), height=float(table_image.height)), + uri=from_pil_to_base64uri(table_image), + ) + page_item = PageItem( + page_no=page_index, + size=Size(width=float(table_image.width), height=float(table_image.height)), + image=image_ref, + ) + + html = "" + "".join(item["html"]) + "
" + table_data = convert_html_table_into_docling_tabledata( + html, text_cells=item["cells"][0] + ) + + l = 0.0 + b = 0.0 + r = table_image.width + t = table_image.height + if "table_bbox" in item: + l = item["table_bbox"][0] + b = table_image.height - item["table_bbox"][3] + r = item["table_bbox"][2] + t = table_image.height - item["table_bbox"][1] + + bbox = BoundingBox( + l=l, + r=r, + b=b, + t=t, + coord_origin=CoordOrigin.BOTTOMLEFT, + ) + + prov = ProvenanceItem(page_no=page_index, bbox=bbox, charspan=(0, 0)) + true_doc.pages[1] = page_item + + true_doc.add_table(data=table_data, caption=None, prov=prov) + + true_doc, _, true_page_images = extract_images( + document=true_doc, + pictures_column=BenchMarkColumns.GROUNDTRUTH_PICTURES.value, # pictures_column, + page_images_column=BenchMarkColumns.GROUNDTRUTH_PAGE_IMAGES.value, # page_images_column, + ) + + # In the dataset, item["image"] is a PIL Image. Convert it to bytes + bytes_io = io.BytesIO() + image = item["image"] + image.save(bytes_io, format="png") + image_bytes = bytes_io.getvalue() + image_stream = DocumentStream(name=filename, stream=BytesIO(image_bytes)) + record = DatasetRecord( + predictor_info=self.prediction_provider.info(), + doc_id=str(filename), + ground_truth_doc=true_doc, + doc_hash=get_binhash(image_bytes), + original=image_stream, + mime_type="image/png", + ) + + # Create the prediction, convert it to doclingDocument and update the dataset record + # Note: This saves the prediction and its doclingDocument as .json in the target directory + self.update_prediction(record) + + # Save the ground truth data as well - for debugging + output_dir = self.target / "microsoft" / "ground_truth_docling_document" + os.makedirs(output_dir, exist_ok=True) + docling_document_file_name = os.path.join(output_dir, f"{filename}.json") + with open(docling_document_file_name, 'w', encoding="utf-8") as f: + json.dump(true_doc.export_to_dict(), f, indent=2) + + # If visualization flag is set, run the visualizations and save them a well + if self.do_visualization and record.predicted_doc is not None: + save_comparison_html( + filename=viz_dir / f"{os.path.basename(filename)}.html", + true_doc=true_doc, + pred_doc=record.predicted_doc, + page_image=true_page_images[0], + true_labels=TRUE_HTML_EXPORT_LABELS, + pred_labels=PRED_HTML_EXPORT_LABELS, + ) + + yield record diff --git a/docling_eval_next/dataset_builders/fintabnet_cos_builder.py b/docling_eval_next/dataset_builders/fintabnet_cos_builder.py new file mode 100644 index 00000000..523356a5 --- /dev/null +++ b/docling_eval_next/dataset_builders/fintabnet_cos_builder.py @@ -0,0 +1,310 @@ +import glob +import io +import json +import os +from io import BytesIO +from pathlib import Path +from typing import Any, Dict, Iterable, List + +import jsonlines +from docling_core.types import DoclingDocument +from docling_core.types.doc import ( + BoundingBox, + CoordOrigin, + DocItemLabel, + ImageRef, + PageItem, + ProvenanceItem, + Size, + TableCell, + TableData, +) +from docling_core.types.io import DocumentStream +from PIL import Image +from tqdm import tqdm + +from docling_eval.benchmarks.constants import BenchMarkColumns +from docling_eval.benchmarks.utils import ( + convert_html_table_into_docling_tabledata, + crop_bounding_box, + extract_images, + from_pil_to_base64uri, + get_binhash, +) +from docling_eval.converters.models.tableformer.tf_model_prediction import PageTokens +from docling_eval.visualisation.visualisations import save_comparison_html +from docling_eval_next.datamodels.dataset_record import DatasetRecord +from docling_eval_next.dataset_builders.dataset_builder import ( + BaseEvaluationDatasetBuilder, + S3Source, +) +from docling_eval_next.prediction_providers.prediction_provider import ( + BasePredictionProvider, +) + +TRUE_HTML_EXPORT_LABELS = { + DocItemLabel.TITLE, + DocItemLabel.DOCUMENT_INDEX, + DocItemLabel.SECTION_HEADER, + DocItemLabel.PARAGRAPH, + DocItemLabel.TABLE, + DocItemLabel.PICTURE, + DocItemLabel.FORMULA, + DocItemLabel.CHECKBOX_UNSELECTED, + DocItemLabel.CHECKBOX_SELECTED, + DocItemLabel.TEXT, + DocItemLabel.LIST_ITEM, + DocItemLabel.CODE, + DocItemLabel.REFERENCE, + # Additional + DocItemLabel.CAPTION, + DocItemLabel.PAGE_HEADER, + DocItemLabel.PAGE_FOOTER, + DocItemLabel.FOOTNOTE, +} + +PRED_HTML_EXPORT_LABELS = { + DocItemLabel.TITLE, + DocItemLabel.DOCUMENT_INDEX, + DocItemLabel.SECTION_HEADER, + DocItemLabel.PARAGRAPH, + DocItemLabel.TABLE, + DocItemLabel.PICTURE, + DocItemLabel.FORMULA, + DocItemLabel.CHECKBOX_UNSELECTED, + DocItemLabel.CHECKBOX_SELECTED, + DocItemLabel.TEXT, + DocItemLabel.LIST_ITEM, + DocItemLabel.CODE, + DocItemLabel.REFERENCE, + # Additional + DocItemLabel.PAGE_HEADER, + DocItemLabel.PAGE_FOOTER, + DocItemLabel.FOOTNOTE, +} + + +class FintabnetCOSDatasetBuilder(BaseEvaluationDatasetBuilder): + """ Base Fintabnet Dataset Builder that will pull dataset from Hugging face.""" + def __init__( + self, + name: str, + prediction_provider: BasePredictionProvider, + target: Path, + do_visualization: bool = True, + ): + endpoint = os.environ.get("S3_ENDPOINT") + access_key = os.environ.get("S3_ACCESS_KEY") + secret_key = os.environ.get("S3_SECRET_KEY") + cos_bucket = os.environ.get("S3_COS_BUCKET") + + if not endpoint: + raise ValueError("Please set the S3_ENDPOINT environment variable") + if not access_key: + raise ValueError("Please set the S3_ACCESS_KEY environment variable") + if not secret_key: + raise ValueError("Please set the S3_SECRET_KEY environment variable") + if not cos_bucket: + raise ValueError("Please set the S3_COS_BUCKET environment variable") + + super().__init__( + name=name, + dataset_source=S3Source( + endpoint=endpoint, + access_key=access_key, + secret_key=secret_key, + cos_bucket=cos_bucket, + cos_dir="model_evaluation_artifacts/data/tables_quality_fintabnet_crops", + ), + prediction_provider=prediction_provider, + target=target, + ) + self.do_visualization = do_visualization + + +class FintabnetCOSTableStructureDatasetBuilder(FintabnetCOSDatasetBuilder): + """ Subclass of FintabnetDatasetBuilder that will define the "iterate" method on how to iterate + the table structure from the dataset.""" + def __init__( + self, + prediction_provider: BasePredictionProvider, + target: Path, + do_visualization: bool = True, + ): + super().__init__( + name="Fintabnet: table-structure", + prediction_provider=prediction_provider, + target=target, + do_visualization=do_visualization, + ) + + + def iterate(self) -> Iterable[DatasetRecord]: + """Iterate and yield each record of the dataset. + Prediction will be run on the yielded record in the calling function.""" + + if not self.retrieved: + raise RuntimeError( + "You must first retrieve the source dataset. Call retrieve_input_dataset()." + ) + + assert self.dataset_local_path is not None + + # Create the folders for saving the intermediate files (test) and visualizations + intermediate_dir = self.target / "intermediate_files" + viz_dir = self.target / "vizualisations" + for _ in [intermediate_dir, viz_dir]: + os.makedirs(_, exist_ok=True) + + # Use glob to find all .parquet files in the directory and clean up the intermediate files + parquet_files = glob.glob(os.path.join(str(intermediate_dir), "*.parquet")) + for file in parquet_files: + try: + os.remove(file) + print(f"Deleted: {file}") + except Exception as e: + print(f"Error deleting {file}: {e}") + + print(f"self.dataset_local_path={self.dataset_local_path}") + print(f"self.name={self.name}") + + # Get all image files + image_files_path = os.path.join(self.dataset_local_path, "images") + print(f"{image_files_path=}") + image_files = list(glob.glob(f"{image_files_path}/*")) + + # Read the ground truth into a dictionary structure + ground_truth_location = os.path.join(self.dataset_local_path, "gt/ftn_150_dpi_test_selection.jsonl") + ground_truth_per_filename = {} + with jsonlines.open(ground_truth_location, "r") as reader: + for line in reader: + filename = line["filename"] + # Each line is of the form + # { "filename": "xx", + # "split": "text", + # "imgid": "xx", + # "html": { + # "cells": [ + # { "tokens": ['char1', 'char2'], "bbox": []} + # ], + # "structure": { + # "tokens": + # [ "", " .."] + # } + # } + # } + html_structure = "" + "".join(line["html"]["structure"]["tokens"]) + "
" + ground_truth_per_filename[filename] = { "table_html": html_structure, + "table_cells": line["html"]["cells"] } + + # TODO - Pass this as an argument? Do we need to run all items.. + max_items = -1 + if max_items == -1: + max_items = len(image_files) + + # Iterate each of the record in the dataset + for i, item in tqdm( + enumerate(image_files), + total=max_items, + ncols=128, + desc=f"create Fintabnet dataset from cos", + ): + print(f"{item=}") + filename = os.path.basename(item) + table_image = Image.open(item) + + print(f"\nProcessing file - [{filename}]...") + + true_page_images = [table_image] + + # Create the Ground truth document + true_doc = DoclingDocument(name=f"ground-truth {filename}") + + page_index = 1 + + image_scale = 1.0 # TODO - pass as input argument? + + image_ref = ImageRef( + mimetype="image/png", + dpi=round(72 * image_scale), + size=Size(width=float(table_image.width), height=float(table_image.height)), + uri=from_pil_to_base64uri(table_image), + ) + page_item = PageItem( + page_no=page_index, + size=Size(width=float(table_image.width), height=float(table_image.height)), + image=image_ref, + ) + + table_data = convert_html_table_into_docling_tabledata( + table_html=ground_truth_per_filename[filename]["table_html"], + text_cells=ground_truth_per_filename[filename]["table_cells"], + ) + + l = 0.0 + b = 0.0 + r = table_image.width + t = table_image.height + if "table_bbox" in item: + l = item["table_bbox"][0] + b = table_image.height - item["table_bbox"][3] + r = item["table_bbox"][2] + t = table_image.height - item["table_bbox"][1] + + bbox = BoundingBox( + l=l, + r=r, + b=b, + t=t, + coord_origin=CoordOrigin.BOTTOMLEFT, + ) + + prov = ProvenanceItem(page_no=page_index, bbox=bbox, charspan=(0, 0)) + true_doc.pages[1] = page_item + + true_doc.add_table(data=table_data, caption=None, prov=prov) + + true_doc, _, true_page_images = extract_images( + document=true_doc, + pictures_column=BenchMarkColumns.GROUNDTRUTH_PICTURES.value, # pictures_column, + page_images_column=BenchMarkColumns.GROUNDTRUTH_PAGE_IMAGES.value, # page_images_column, + ) + + # In the dataset, item["image"] is a PIL Image. Convert it to bytes + bytes_io = io.BytesIO() + image = table_image + image.save(bytes_io, format="png") + image_bytes = bytes_io.getvalue() + image_stream = DocumentStream(name=filename, stream=BytesIO(image_bytes)) + record = DatasetRecord( + predictor_info=self.prediction_provider.info(), + doc_id=str(filename), + ground_truth_doc=true_doc, + doc_hash=get_binhash(image_bytes), + original=image_stream, + mime_type="image/png", + ) + + # Create the prediction, convert it to doclingDocument and update the dataset record + # Note: This saves the prediction and its doclingDocument as .json in the target directory + self.update_prediction(record) + + # Save the ground truth data as well - for debugging + output_dir = self.target / "microsoft" / "ground_truth_docling_document" + os.makedirs(output_dir, exist_ok=True) + docling_document_file_name = os.path.join(output_dir, f"{filename}.json") + with open(docling_document_file_name, 'w', encoding="utf-8") as f: + json.dump(true_doc.export_to_dict(), f, indent=2) + + # If visualization flag is set, run the visualizations and save them a well + if self.do_visualization and record.predicted_doc is not None: + save_comparison_html( + filename=viz_dir / f"{os.path.basename(filename)}.html", + true_doc=true_doc, + pred_doc=record.predicted_doc, + page_image=true_page_images[0], + true_labels=TRUE_HTML_EXPORT_LABELS, + pred_labels=PRED_HTML_EXPORT_LABELS, + ) + + yield record diff --git a/docling_eval_next/prediction_providers/azure_prediction_provider.py b/docling_eval_next/prediction_providers/azure_prediction_provider.py new file mode 100644 index 00000000..7df71810 --- /dev/null +++ b/docling_eval_next/prediction_providers/azure_prediction_provider.py @@ -0,0 +1,216 @@ +import json +import os +from pathlib import Path +from typing import Dict + +from docling_core.types import DoclingDocument +from docling_core.types.doc.base import BoundingBox, CoordOrigin, Size +from docling_core.types.doc.document import ( + DoclingDocument, + PageItem, + ProvenanceItem, + TableCell, + TableData, +) +from docling_core.types.io import DocumentStream + +from docling_eval_next.prediction_providers.prediction_provider import BasePredictionProvider +#from docling_core.types.doc.labels import DocItemLabel + + +class AzureDocIntelligencePredictionProvider(BasePredictionProvider): + """Provider that calls the Microsoft Azure Document Intelligence API for predicting the tables in document.""" + def __init__( + self, **kwargs + ): # could be the docling converter options, the remote credentials for MS/Google, etc. + super().__init__(**kwargs) + + # TODO - Need a temp directory to save Azure outputs + # Validate the required library + try: + from azure.ai.formrecognizer import AnalysisFeature, DocumentAnalysisClient + from azure.core.credentials import AzureKeyCredential + except ImportError: + raise ImportError("azure-ai-formrecognizer library is not installed..") + + # Validate the required endpoints to call the API + endpoint = os.getenv("AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT") + key = os.getenv("AZURE_DOCUMENT_INTELLIGENCE_KEY") + + if not endpoint or not key: + raise ValueError( + "AZURE_DOCUMENT_INTELLIGENCE_ENDPOINT and AZURE_DOCUMENT_INTELLIGENCE_KEY must be set in environment variables." + ) + + self.doc_intelligence_client = DocumentAnalysisClient(endpoint, AzureKeyCredential(key)) + + # Save the flags for intermediate results and processing + self.skip_api_if_prediction_is_present = bool(kwargs.get("skip_api_if_prediction_is_present", False) is True) + self.predictions_dir = kwargs.get("predictions_dir") + os.makedirs(self.predictions_dir, exist_ok=True) + + def extract_bbox_from_polygon(self, polygon): + """Helper function to extract bbox coordinates from polygon data.""" + if not polygon or not isinstance(polygon, list): + return {"l": 0, "t": 0, "r": 0, "b": 0} + + # Handle flat array format: [x1, y1, x2, y2, x3, y3, x4, y4] + if len(polygon) >= 8 and all(isinstance(p, (int, float)) for p in polygon): + return {"l": polygon[0], "t": polygon[1], "r": polygon[4], "b": polygon[5]} + # Handle array of point objects: [{x, y}, {x, y}, ...] + elif len(polygon) >= 4 and all( + isinstance(p, dict) and "x" in p and "y" in p for p in polygon + ): + return { + "l": polygon[0]["x"], + "t": polygon[0]["y"], + "r": polygon[2]["x"], + "b": polygon[2]["y"], + } + else: + return {"l": 0, "t": 0, "r": 0, "b": 0} + + def convert_azure_output_to_docling(self, analyze_result, filename) -> DoclingDocument: + """Converts Azure Document Intelligence output to DoclingDocument format.""" + doc = DoclingDocument(name=filename) + + for page in analyze_result.get("pages", []): + page_no = page.get("page_number", 1) + + page_width = page.get("width") + page_height = page.get("height") + doc.pages[page_no] = PageItem( + size=Size(width=float(page_width), height=float(page_height)), + page_no=page_no, + ) + + for word in page.get("words", []): + polygon = word.get("polygon", []) + bbox = self.extract_bbox_from_polygon(polygon) + + text_content = word.get("content", "") + + bbox_obj = BoundingBox( + l=bbox["l"], + t=bbox["t"], + r=bbox["r"], + b=bbox["b"], + coord_origin=CoordOrigin.TOPLEFT, + ) + + prov = ProvenanceItem( + page_no=page_no, bbox=bbox_obj, charspan=(0, len(text_content)) + ) + + # doc.add_text(label=DocItemLabel.TEXT, text=text_content, prov=prov) + + for table in analyze_result.get("tables", []): + page_no = table.get("page_range", {}).get("first_page_number", 1) + row_count = table.get("row_count", 0) + col_count = table.get("column_count", 0) + + table_polygon = table.get("bounding_regions", [{}])[0].get("polygon", []) + table_bbox = self.extract_bbox_from_polygon(table_polygon) + + table_bbox_obj = BoundingBox( + l=table_bbox["l"], + t=table_bbox["t"], + r=table_bbox["r"], + b=table_bbox["b"], + coord_origin=CoordOrigin.TOPLEFT, + ) + + table_prov = ProvenanceItem(page_no=page_no, bbox=table_bbox_obj, charspan=(0, 0)) + + table_cells = [] + + for cell in table.get("cells", []): + + cell_text = cell.get("content", "").strip() + row_index = cell.get("row_index", 0) + col_index = cell.get("column_index", 0) + row_span = cell.get("row_span", 1) + col_span = cell.get("column_span", 1) + + cell_polygon = cell.get("bounding_regions", [{}])[0].get("polygon", []) + cell_bbox = self.extract_bbox_from_polygon(cell_polygon) + + table_cell = TableCell( + bbox=BoundingBox( + l=cell_bbox["l"], + t=cell_bbox["t"], + r=cell_bbox["r"], + b=cell_bbox["b"], + coord_origin=CoordOrigin.TOPLEFT, + ), + row_span=row_span, + col_span=col_span, + start_row_offset_idx=row_index, + end_row_offset_idx=row_index + row_span, + start_col_offset_idx=col_index, + end_col_offset_idx=col_index + col_span, + text=cell_text, + column_header=False, + row_header=False, + row_section=False, + ) + + table_cells.append(table_cell) + + table_data = TableData( + table_cells=table_cells, num_rows=row_count, num_cols=col_count + ) + + doc.add_table(prov=table_prov, data=table_data, caption=None) + + return doc + + + def predict(self, stream: DocumentStream, **extra_args) -> DoclingDocument: + """For the given document stream (single document), run the API and create the doclingDocument.""" + + print(f"Creating prediction for file - {stream.name}..") + stream_file_basename = Path(stream.name).stem + + prediction_file_name = os.path.join(self.predictions_dir, f"{stream_file_basename}.json") + print(f"{prediction_file_name=}") + prediction_file_exists = False + # Check if the prediction exists, if so - reuse it + if (self.skip_api_if_prediction_is_present and os.path.exists(prediction_file_name)): + prediction_file_exists = True + print(f"Skipping Azure API call and re-using existing prediction from [{prediction_file_name}].") + with open(prediction_file_name, "r", encoding="utf-8") as f: + result_json = json.load(f) + result_json + else: + # Call the Azure API by passing in the image for prediction + poller = self.doc_intelligence_client.begin_analyze_document( + "prebuilt-layout", stream.stream, features=[] + ) + result = poller.result() + result_json = result.to_dict() + print(f"Successfully processed [{stream.name}] using Azure API..!!") + + # Convert the prediction to doclingDocument + pred_docling_doc = self.convert_azure_output_to_docling( + result_json, stream.name + ) + + # save both the prediction json as well as converted docling_document into the subfolders underneath + if not prediction_file_exists: + with open(prediction_file_name, 'w', encoding="utf-8") as f: + json.dump(result_json, f, indent=2) + print(f"Saved Prediction output to - {prediction_file_name}") + + # Directory for storing docling_document output + output_dir = os.path.join(self.predictions_dir, "docling_document") + os.makedirs(output_dir, exist_ok=True) + docling_document_file_name = os.path.join(output_dir, f"{stream.name}.json") # include full name + with open(docling_document_file_name, 'w', encoding="utf-8") as f: + json.dump(pred_docling_doc.export_to_dict(), f, indent=2) + print(f"Saved Docling Document output of prediction to - {docling_document_file_name}") + + return pred_docling_doc + + def info(self) -> Dict: + return {"asset": "Azure AI Document Intelligence", "version": "1.0.0"} diff --git a/docling_eval_next/prediction_providers/prediction_provider.py b/docling_eval_next/prediction_providers/prediction_provider.py index 0e641b93..50fc2233 100644 --- a/docling_eval_next/prediction_providers/prediction_provider.py +++ b/docling_eval_next/prediction_providers/prediction_provider.py @@ -1,3 +1,5 @@ +import os +from pathlib import Path from abc import abstractmethod from typing import Dict @@ -7,6 +9,17 @@ from docling_eval.benchmarks.utils import docling_version +from docling_core.types.doc.base import BoundingBox, CoordOrigin, Size +from docling_core.types.doc.document import ( + DoclingDocument, + PageItem, + ProvenanceItem, + TableCell, + TableData, + TableItem, +) +from docling_core.types.doc.labels import DocItemLabel +from PIL import Image class BasePredictionProvider: def __init__( @@ -42,3 +55,4 @@ def predict(self, stream: DocumentStream, **extra_args) -> DoclingDocument: def info(self) -> Dict: return {"asset": "Docling", "version": docling_version()} + diff --git a/docs/examples/run_fintabnet_builder_example.py b/docs/examples/run_fintabnet_builder_example.py new file mode 100644 index 00000000..24bcab14 --- /dev/null +++ b/docs/examples/run_fintabnet_builder_example.py @@ -0,0 +1,45 @@ +from pathlib import Path + +from docling_eval.benchmarks.constants import BenchMarkNames, EvaluationModality +from docling_eval.cli.main import evaluate +from docling_eval_next.dataset_builders.fintabnet_builder import FintabnetTableStructureDatasetBuilder +from docling_eval_next.prediction_providers.azure_prediction_provider import ( + AzureDocIntelligencePredictionProvider, +) + + +def main(): + """Main function that will run Fintabnet Table Structure Benchmark. + Pulls the 'fintabnet' dataset from HF and saves it to disk. + """ + # Define the place where the temporary output has to be saved + target_path = Path("./output/FinTabNet_OTSL/") + + # Define the predictor that needs to be run on each item of the dataset + provider = AzureDocIntelligencePredictionProvider() # Microsoft Azure Document Intelligence API Provider + + # 1. Create the dataset builder + dataset = FintabnetTableStructureDatasetBuilder( + prediction_provider=provider, + target=target_path, + ) + + # 2. Download the dataset + downloaded_path = dataset.retrieve_input_dataset() # fetches the source dataset from HF + print(f"Dataset downloaded to {downloaded_path}") + + # 3. Run prediction and save the output in parquet format locally; Note that this saved data will have both ground truth and prediction + dataset.save_to_disk() # does all the job of iterating the dataset, making GT+prediction records, and saving them in shards as parquet. + + # 4. Run evaluation using the saved data in step 3 above + evaluate( + modality=EvaluationModality.TABLE_STRUCTURE, + benchmark=BenchMarkNames.FINTABNET, + idir=target_path, + odir=target_path / "teds", + split="intermediate_files" + ) + + +if __name__ == "__main__": + main() diff --git a/docs/examples/run_fintabnet_cos_builder_example.py b/docs/examples/run_fintabnet_cos_builder_example.py new file mode 100644 index 00000000..4063ca7d --- /dev/null +++ b/docs/examples/run_fintabnet_cos_builder_example.py @@ -0,0 +1,49 @@ +from pathlib import Path + +from docling_eval.benchmarks.constants import BenchMarkNames, EvaluationModality +from docling_eval.cli.main import evaluate +from docling_eval_next.dataset_builders.fintabnet_cos_builder import ( + FintabnetCOSTableStructureDatasetBuilder, +) +from docling_eval_next.prediction_providers.azure_prediction_provider import ( + AzureDocIntelligencePredictionProvider, +) + + +def main(): + """Main function that will run Fintabnet Table Structure Benchmark. + Pulls the 'fintabnet' dataset from HF and saves it to disk. + """ + # Define the place where the temporary output has to be saved + target_path = Path("./output/tables_quality_fintabnet_crops/") + + # Define the predictor that needs to be run on each item of the dataset + provider_args = { "skip_api_if_prediction_is_present": True, + "predictions_dir": target_path / "microsoft" } + provider = AzureDocIntelligencePredictionProvider(**provider_args) # Microsoft Azure Document Intelligence API Provider + + # 1. Create the dataset builder + dataset = FintabnetCOSTableStructureDatasetBuilder( + prediction_provider=provider, + target=target_path, + ) + + # 2. Download the dataset + downloaded_path = dataset.retrieve_input_dataset() # fetches the source dataset from HF + print(f"Dataset downloaded to {downloaded_path}") + + # 3. Run prediction and save the output in parquet format locally; Note that this saved data will have both ground truth and prediction + dataset.save_to_disk() # does all the job of iterating the dataset, making GT+prediction records, and saving them in shards as parquet. + + # 4. Run evaluation using the saved data in step 3 above + evaluate( + modality=EvaluationModality.TABLE_STRUCTURE, + benchmark=BenchMarkNames.FINTABNET, + idir=target_path, + odir=target_path / "teds", + split="intermediate_files" + ) + + +if __name__ == "__main__": + main() diff --git a/poetry.lock b/poetry.lock index f9f14816..c4137f10 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. [[package]] name = "accelerate" @@ -6,6 +6,8 @@ version = "1.5.2" description = "Accelerate" optional = false python-versions = ">=3.9.0" +groups = ["main"] +markers = "(sys_platform != \"darwin\" or platform_machine != \"x86_64\") and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "accelerate-1.5.2-py3-none-any.whl", hash = "sha256:68a3b272f6a6ffebb457bdc138581a2bf52efad6a5e0214dc46675f3edd98792"}, {file = "accelerate-1.5.2.tar.gz", hash = "sha256:a1cf39473edc0e42772a9d9a18c9eb1ce8ffd9e1719dc0ab80670f5c1fd4dc43"}, @@ -37,6 +39,8 @@ version = "2.6.1" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8"}, {file = "aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558"}, @@ -48,6 +52,8 @@ version = "3.11.14" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "aiohttp-3.11.14-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:e2bc827c01f75803de77b134afdbf74fa74b62970eafdf190f3244931d7a5c0d"}, {file = "aiohttp-3.11.14-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e365034c5cf6cf74f57420b57682ea79e19eb29033399dd3f40de4d0171998fa"}, @@ -151,6 +157,8 @@ version = "1.3.2" description = "aiosignal: a list of registered asynchronous callbacks" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5"}, {file = "aiosignal-1.3.2.tar.gz", hash = "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54"}, @@ -165,6 +173,8 @@ version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, @@ -176,6 +186,8 @@ version = "0.1.4" description = "Disable App Nap on macOS >= 10.9" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "(python_version >= \"3.12\" or python_version <= \"3.11\") and platform_system == \"Darwin\"" files = [ {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"}, {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"}, @@ -187,6 +199,8 @@ version = "1.0.3" description = "APTED algorithm for the Tree Edit Distance" optional = false python-versions = "*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "apted-1.0.3-py3-none-any.whl", hash = "sha256:74193369d023649d335269e67c4df07f922959e5ac2597de1b79af4e694150e8"}, {file = "apted-1.0.3.tar.gz", hash = "sha256:befa5181e2d4457fa88e54995a82604ee048bb2fbc781ea97d8e1856b4715ce9"}, @@ -198,6 +212,8 @@ version = "2.15.8" description = "An abstract syntax tree for Python with inference support." optional = false python-versions = ">=3.7.2" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "astroid-2.15.8-py3-none-any.whl", hash = "sha256:1aa149fc5c6589e3d0ece885b4491acd80af4f087baafa3fb5203b113e68cd3c"}, {file = "astroid-2.15.8.tar.gz", hash = "sha256:6c107453dffee9055899705de3c9ead36e74119cee151e5a9aaf7f0b0e020a6a"}, @@ -207,8 +223,8 @@ files = [ lazy-object-proxy = ">=1.4.0" typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} wrapt = [ - {version = ">=1.11,<2", markers = "python_version < \"3.11\""}, {version = ">=1.14,<2", markers = "python_version >= \"3.11\""}, + {version = ">=1.11,<2", markers = "python_version < \"3.11\""}, ] [[package]] @@ -217,6 +233,8 @@ version = "3.0.0" description = "Annotate AST trees with source code positions" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2"}, {file = "asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7"}, @@ -232,6 +250,8 @@ version = "5.0.1" description = "Timeout context manager for asyncio programs" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version < \"3.11\"" files = [ {file = "async_timeout-5.0.1-py3-none-any.whl", hash = "sha256:39e3809566ff85354557ec2398b55e096c8364bacac9405a7a1fa429e77fe76c"}, {file = "async_timeout-5.0.1.tar.gz", hash = "sha256:d9321a7a3d5a6a5e187e824d2fa0793ce379a202935782d555d6e9d2735677d3"}, @@ -243,6 +263,8 @@ version = "25.3.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"}, {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"}, @@ -262,6 +284,8 @@ version = "2.2.0" description = "A tool that automatically formats Python code to conform to the PEP 8 style guide" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "autopep8-2.2.0-py2.py3-none-any.whl", hash = "sha256:05418a981f038969d8bdcd5636bf15948db7555ae944b9f79b5a34b35f1370d4"}, {file = "autopep8-2.2.0.tar.gz", hash = "sha256:d306a0581163ac29908280ad557773a95a9bede072c0fafed6f141f5311f43c1"}, @@ -271,12 +295,67 @@ files = [ pycodestyle = ">=2.11.0" tomli = {version = "*", markers = "python_version < \"3.11\""} +[[package]] +name = "azure-ai-formrecognizer" +version = "3.3.3" +description = "Microsoft Azure Form Recognizer Client Library for Python" +optional = false +python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "azure-ai-formrecognizer-3.3.3.tar.gz", hash = "sha256:9fc09788bbb65866630fa870cca1933bfd7298b8055236530bcc0e40d81fcccf"}, + {file = "azure_ai_formrecognizer-3.3.3-py3-none-any.whl", hash = "sha256:81fc1abda8bd898426ee3bbc1b9c6bd164514201ce282129a31d4664f9d1f3bc"}, +] + +[package.dependencies] +azure-common = ">=1.1" +azure-core = ">=1.23.0" +msrest = ">=0.6.21" +typing-extensions = ">=4.0.1" + +[[package]] +name = "azure-common" +version = "1.1.28" +description = "Microsoft Azure Client Library for Python (Common)" +optional = false +python-versions = "*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "azure-common-1.1.28.zip", hash = "sha256:4ac0cd3214e36b6a1b6a442686722a5d8cc449603aa833f3f0f40bda836704a3"}, + {file = "azure_common-1.1.28-py2.py3-none-any.whl", hash = "sha256:5c12d3dcf4ec20599ca6b0d3e09e86e146353d443e7fcc050c9a19c1f9df20ad"}, +] + +[[package]] +name = "azure-core" +version = "1.32.0" +description = "Microsoft Azure Core Library for Python" +optional = false +python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "azure_core-1.32.0-py3-none-any.whl", hash = "sha256:eac191a0efb23bfa83fddf321b27b122b4ec847befa3091fa736a5c32c50d7b4"}, + {file = "azure_core-1.32.0.tar.gz", hash = "sha256:22b3c35d6b2dae14990f6c1be2912bf23ffe50b220e708a28ab1bb92b1c730e5"}, +] + +[package.dependencies] +requests = ">=2.21.0" +six = ">=1.11.0" +typing-extensions = ">=4.6.0" + +[package.extras] +aio = ["aiohttp (>=3.0)"] + [[package]] name = "backports-tarfile" version = "1.2.0" description = "Backport of CPython tarfile module" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\"" files = [ {file = "backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34"}, {file = "backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991"}, @@ -292,6 +371,8 @@ version = "4.13.3" description = "Screen-scraping library" optional = false python-versions = ">=3.7.0" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "beautifulsoup4-4.13.3-py3-none-any.whl", hash = "sha256:99045d7d3f08f91f0d656bc9b7efbae189426cd913d830294a15eefa0ea4df16"}, {file = "beautifulsoup4-4.13.3.tar.gz", hash = "sha256:1bd32405dacc920b42b83ba01644747ed77456a65760e285fbc47633ceddaf8b"}, @@ -314,6 +395,8 @@ version = "24.10.0" description = "The uncompromising code formatter." optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "black-24.10.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6668650ea4b685440857138e5fe40cde4d652633b1bdffc62933d0db4ed9812"}, {file = "black-24.10.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:1c536fcf674217e87b8cc3657b81809d3c085d7bf3ef262ead700da345bfa6ea"}, @@ -356,12 +439,27 @@ d = ["aiohttp (>=3.10)"] jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] uvloop = ["uvloop (>=0.15.2)"] +[[package]] +name = "cachetools" +version = "5.5.2" +description = "Extensible memoizing collections and decorators" +optional = false +python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"}, + {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"}, +] + [[package]] name = "certifi" version = "2025.1.31" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "certifi-2025.1.31-py3-none-any.whl", hash = "sha256:ca78db4565a652026a4db2bcdf68f2fb589ea80d0be70e03929ed730746b84fe"}, {file = "certifi-2025.1.31.tar.gz", hash = "sha256:3d5da6925056f6f18f119200434a4780a94263f10d1c21d032a6f6b2baa20651"}, @@ -373,6 +471,8 @@ version = "1.17.1" description = "Foreign Function Interface for Python calling C code." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "(python_version >= \"3.12\" or python_version <= \"3.11\") and (implementation_name == \"pypy\" or sys_platform == \"linux\") and (implementation_name == \"pypy\" or platform_python_implementation != \"PyPy\")" files = [ {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"}, {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"}, @@ -452,6 +552,8 @@ version = "3.4.0" description = "Validate configuration and produce human readable error messages." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"}, {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"}, @@ -463,6 +565,8 @@ version = "3.4.1" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." optional = false python-versions = ">=3.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "charset_normalizer-3.4.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:91b36a978b5ae0ee86c394f5a54d6ef44db1de0815eb43de826d41d21e4af3de"}, {file = "charset_normalizer-3.4.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7461baadb4dc00fd9e0acbe254e3d7d2112e7f92ced2adc96e54ef6501c5f176"}, @@ -564,6 +668,8 @@ version = "8.1.8" description = "Composable command line interface toolkit" optional = false python-versions = ">=3.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "click-8.1.8-py3-none-any.whl", hash = "sha256:63c132bbbed01578a06712a2d1f497bb62d9c1c0d329b7903a866228027263b2"}, {file = "click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a"}, @@ -578,6 +684,8 @@ version = "0.4.0" description = "Logging integration for Click" optional = false python-versions = "*" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "click-log-0.4.0.tar.gz", hash = "sha256:3970f8570ac54491237bcdb3d8ab5e3eef6c057df29f8c3d1151a51a9c23b975"}, {file = "click_log-0.4.0-py2.py3-none-any.whl", hash = "sha256:a43e394b528d52112af599f2fc9e4b7cf3c15f94e53581f74fa6867e68c91756"}, @@ -592,10 +700,12 @@ version = "0.4.6" description = "Cross-platform colored terminal text." optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +groups = ["main", "dev"] files = [ {file = "colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6"}, {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"}, ] +markers = {main = "(python_version >= \"3.12\" or python_version <= \"3.11\") and platform_system == \"Windows\"", dev = "python_version <= \"3.11\" or python_version >= \"3.12\""} [[package]] name = "comm" @@ -603,6 +713,8 @@ version = "0.2.2" description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "comm-0.2.2-py3-none-any.whl", hash = "sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3"}, {file = "comm-0.2.2.tar.gz", hash = "sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e"}, @@ -620,6 +732,8 @@ version = "1.3.1" description = "Python library for calculating contours of 2D quadrilateral grids" optional = false python-versions = ">=3.10" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "contourpy-1.3.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a045f341a77b77e1c5de31e74e966537bba9f3c4099b35bf4c2e3939dd54cdab"}, {file = "contourpy-1.3.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:500360b77259914f7805af7462e41f9cb7ca92ad38e9f94d6c8641b089338124"}, @@ -693,6 +807,8 @@ version = "44.0.2" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." optional = false python-versions = "!=3.9.0,!=3.9.1,>=3.7" +groups = ["dev"] +markers = "sys_platform == \"linux\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "cryptography-44.0.2-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:efcfe97d1b3c79e486554efddeb8f6f53a4cdd4cf6086642784fa31fc384e1d7"}, {file = "cryptography-44.0.2-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:29ecec49f3ba3f3849362854b7253a9f59799e3763b0c9d0826259a88efa02f1"}, @@ -750,6 +866,8 @@ version = "0.12.1" description = "Composable style cycles" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "cycler-0.12.1-py3-none-any.whl", hash = "sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30"}, {file = "cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c"}, @@ -761,13 +879,15 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"] [[package]] name = "datasets" -version = "3.4.0" +version = "3.4.1" description = "HuggingFace community-driven open-source library of datasets" optional = false python-versions = ">=3.9.0" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "datasets-3.4.0-py3-none-any.whl", hash = "sha256:35ef5182bddd38f7aa774d9f33c3e8b8e9c9c7ea41b4b7969fde431919cb556b"}, - {file = "datasets-3.4.0.tar.gz", hash = "sha256:f3defae5d9c79ff586db3b17389fdde01704ffea015293a050d7e8ab6816bad8"}, + {file = "datasets-3.4.1-py3-none-any.whl", hash = "sha256:b91cf257bd64132fa9d953dd4768ab6d63205597301f132a74271cfcce8b5dd3"}, + {file = "datasets-3.4.1.tar.gz", hash = "sha256:e23968da79bc014ef9f7540eeb7771c6180eae82c86ebcfcc10535a03caf08b5"}, ] [package.dependencies] @@ -807,6 +927,8 @@ version = "1.8.13" description = "An implementation of the Debug Adapter Protocol for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "debugpy-1.8.13-cp310-cp310-macosx_14_0_x86_64.whl", hash = "sha256:06859f68e817966723ffe046b896b1bd75c665996a77313370336ee9e1de3e90"}, {file = "debugpy-1.8.13-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:cb56c2db69fb8df3168bc857d7b7d2494fed295dfdbde9a45f27b4b152f37520"}, @@ -842,6 +964,8 @@ version = "5.2.1" description = "Decorators for Humans" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "decorator-5.2.1-py3-none-any.whl", hash = "sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a"}, {file = "decorator-5.2.1.tar.gz", hash = "sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360"}, @@ -853,6 +977,8 @@ version = "0.3.8" description = "serialize all of Python" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "dill-0.3.8-py3-none-any.whl", hash = "sha256:c36ca9ffb54365bdd2f8eb3eff7d2a21237f8452b57ace88b1ac615b7e815bd7"}, {file = "dill-0.3.8.tar.gz", hash = "sha256:3ebe3c479ad625c4553aca177444d89b486b1d84982eeacded644afc0cf797ca"}, @@ -868,6 +994,8 @@ version = "0.1.3" description = "Utilities for comparing sequences" optional = false python-versions = "*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "Distance-0.1.3.tar.gz", hash = "sha256:60807584f5b6003f5c521aa73f39f51f631de3be5cccc5a1d67166fcbf0d4551"}, ] @@ -878,6 +1006,8 @@ version = "0.3.9" description = "Distribution utilities" optional = false python-versions = "*" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "distlib-0.3.9-py2.py3-none-any.whl", hash = "sha256:47f8c22fd27c27e25a65601af709b38e4f0a45ea4fc2e710f65755fa8caaaf87"}, {file = "distlib-0.3.9.tar.gz", hash = "sha256:a60f20dea646b8a33f3e7772f74dc0b2d0772d2837ee1342a00645c81edf9403"}, @@ -889,6 +1019,8 @@ version = "2.26.0" description = "SDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications." optional = false python-versions = "<4.0,>=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "docling-2.26.0-py3-none-any.whl", hash = "sha256:0ddebcd4c258c8fa9e4f84801940ae3c4fce59ad8ff81bc10939f686073323a0"}, {file = "docling-2.26.0.tar.gz", hash = "sha256:db7fc425b876023e4ad42a1fdfc0f285f507c38bc8a24ee2ae00e2eb8af0120d"}, @@ -932,13 +1064,15 @@ vlm = ["accelerate (>=1.2.1,<2.0.0)", "transformers (>=4.42.0,<4.43.0)", "transf [[package]] name = "docling-core" -version = "2.23.1" +version = "2.23.3" description = "A python library to define and validate data types in Docling." optional = false python-versions = "<4.0,>=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "docling_core-2.23.1-py3-none-any.whl", hash = "sha256:4a3f7bcc55a735a070d69d74cf1278f7e40cb403c5059d4149672c7ca163992f"}, - {file = "docling_core-2.23.1.tar.gz", hash = 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coordinates from programmatic PDFs" optional = false python-versions = "<4.0,>=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "docling_parse-3.4.0-cp310-cp310-macosx_13_0_x86_64.whl", hash = "sha256:96e95e63ab722dfe5340fcb04d0e07bd1c0a0ba2f62e93c91ac26dda0a312a44"}, {file = "docling_parse-3.4.0-cp310-cp310-macosx_14_0_arm64.whl", hash = "sha256:f9e14a7a0b92526d4dfd3f390f3d7e075f59d14d6b8a0a564fbc26299e56cd47"}, @@ -1039,6 +1177,8 @@ version = "0.21.2" description = "Docutils -- Python Documentation Utilities" optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "docutils-0.21.2-py3-none-any.whl", hash = "sha256:dafca5b9e384f0e419294eb4d2ff9fa826435bf15f15b7bd45723e8ad76811b2"}, {file = "docutils-0.21.2.tar.gz", hash = "sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f"}, @@ -1050,6 +1190,8 @@ version = 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+groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jaraco.context-6.0.1-py3-none-any.whl", hash = "sha256:f797fc481b490edb305122c9181830a3a5b76d84ef6d1aef2fb9b47ab956f9e4"}, {file = "jaraco_context-6.0.1.tar.gz", hash = "sha256:9bae4ea555cf0b14938dc0aee7c9f32ed303aa20a3b73e7dc80111628792d1b3"}, @@ -1763,6 +2210,8 @@ version = "4.1.0" description = "Functools like those found in stdlib" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jaraco.functools-4.1.0-py3-none-any.whl", hash = "sha256:ad159f13428bc4acbf5541ad6dec511f91573b90fba04df61dafa2a1231cf649"}, {file = "jaraco_functools-4.1.0.tar.gz", hash = "sha256:70f7e0e2ae076498e212562325e805204fc092d7b4c17e0e86c959e249701a9d"}, @@ -1785,6 +2234,8 @@ version = "0.19.2" description = "An autocompletion tool for Python that can be used for text editors." optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9"}, {file = "jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0"}, @@ -1804,6 +2255,8 @@ version = "0.9.0" description = "Low-level, pure Python DBus protocol wrapper." optional = false python-versions = ">=3.7" +groups = ["dev"] +markers = "sys_platform == \"linux\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "jeepney-0.9.0-py3-none-any.whl", hash = "sha256:97e5714520c16fc0a45695e5365a2e11b81ea79bba796e26f9f1d178cb182683"}, {file = "jeepney-0.9.0.tar.gz", hash = "sha256:cf0e9e845622b81e4a28df94c40345400256ec608d0e55bb8a3feaa9163f5732"}, @@ -1819,6 +2272,8 @@ version = "3.1.6" description = "A very fast and expressive template engine." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67"}, {file = "jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d"}, @@ -1830,12 +2285,27 @@ MarkupSafe = ">=2.0" [package.extras] i18n = ["Babel (>=2.7)"] +[[package]] +name = "jmespath" +version = "0.10.0" +description = "JSON Matching Expressions" +optional = false +python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "jmespath-0.10.0-py2.py3-none-any.whl", hash = "sha256:cdf6525904cc597730141d61b36f2e4b8ecc257c420fa2f4549bac2c2d0cb72f"}, + {file = "jmespath-0.10.0.tar.gz", hash = "sha256:b85d0567b8666149a93172712e68920734333c0ce7e89b78b3e987f71e5ed4f9"}, +] + [[package]] name = "joblib" version = "1.4.2" description = "Lightweight pipelining with Python functions" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"}, {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"}, @@ -1847,6 +2317,8 @@ version = "3.1.0" description = "Library with helpers for the jsonlines file format" optional = false python-versions = ">=3.6" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jsonlines-3.1.0-py3-none-any.whl", hash = "sha256:632f5e38f93dfcb1ac8c4e09780b92af3a55f38f26e7c47ae85109d420b6ad39"}, {file = "jsonlines-3.1.0.tar.gz", hash = "sha256:2579cb488d96f815b0eb81629e3e6b0332da0962a18fa3532958f7ba14a5c37f"}, @@ -1861,6 +2333,8 @@ version = "1.1.0" description = "jsonref is a library for automatic dereferencing of JSON Reference objects for Python." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jsonref-1.1.0-py3-none-any.whl", hash = "sha256:590dc7773df6c21cbf948b5dac07a72a251db28b0238ceecce0a2abfa8ec30a9"}, {file = "jsonref-1.1.0.tar.gz", hash = "sha256:32fe8e1d85af0fdefbebce950af85590b22b60f9e95443176adbde4e1ecea552"}, @@ -1872,6 +2346,8 @@ version = "4.23.0" description = "An implementation of JSON Schema validation for Python" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jsonschema-4.23.0-py3-none-any.whl", hash = "sha256:fbadb6f8b144a8f8cf9f0b89ba94501d143e50411a1278633f56a7acf7fd5566"}, {file = "jsonschema-4.23.0.tar.gz", hash = "sha256:d71497fef26351a33265337fa77ffeb82423f3ea21283cd9467bb03999266bc4"}, @@ -1893,6 +2369,8 @@ version = "2024.10.1" description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jsonschema_specifications-2024.10.1-py3-none-any.whl", hash = "sha256:a09a0680616357d9a0ecf05c12ad234479f549239d0f5b55f3deea67475da9bf"}, {file = "jsonschema_specifications-2024.10.1.tar.gz", hash = "sha256:0f38b83639958ce1152d02a7f062902c41c8fd20d558b0c34344292d417ae272"}, @@ -1907,6 +2385,8 @@ version = "8.6.3" description = "Jupyter protocol implementation and client libraries" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jupyter_client-8.6.3-py3-none-any.whl", hash = "sha256:e8a19cc986cc45905ac3362915f410f3af85424b4c0905e94fa5f2cb08e8f23f"}, {file = "jupyter_client-8.6.3.tar.gz", hash = "sha256:35b3a0947c4a6e9d589eb97d7d4cd5e90f910ee73101611f01283732bd6d9419"}, @@ -1929,6 +2409,8 @@ version = "5.7.2" description = "Jupyter core package. A base package on which Jupyter projects rely." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jupyter_core-5.7.2-py3-none-any.whl", hash = "sha256:4f7315d2f6b4bcf2e3e7cb6e46772eba760ae459cd1f59d29eb57b0a01bd7409"}, {file = "jupyter_core-5.7.2.tar.gz", hash = "sha256:aa5f8d32bbf6b431ac830496da7392035d6f61b4f54872f15c4bd2a9c3f536d9"}, @@ -1949,6 +2431,8 @@ version = "3.0.13" description = "Jupyter interactive widgets for JupyterLab" optional = false python-versions = ">=3.7" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "jupyterlab_widgets-3.0.13-py3-none-any.whl", hash = "sha256:e3cda2c233ce144192f1e29914ad522b2f4c40e77214b0cc97377ca3d323db54"}, {file = "jupyterlab_widgets-3.0.13.tar.gz", hash = "sha256:a2966d385328c1942b683a8cd96b89b8dd82c8b8f81dda902bb2bc06d46f5bed"}, @@ -1960,6 +2444,8 @@ version = "25.6.0" description = "Store and access your passwords safely." optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "keyring-25.6.0-py3-none-any.whl", hash = "sha256:552a3f7af126ece7ed5c89753650eec89c7eaae8617d0aa4d9ad2b75111266bd"}, {file = "keyring-25.6.0.tar.gz", hash = "sha256:0b39998aa941431eb3d9b0d4b2460bc773b9df6fed7621c2dfb291a7e0187a66"}, @@ -1989,6 +2475,8 @@ version = "1.4.8" description = "A fast implementation of the Cassowary constraint solver" optional = false python-versions = ">=3.10" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "kiwisolver-1.4.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:88c6f252f6816a73b1f8c904f7bbe02fd67c09a69f7cb8a0eecdbf5ce78e63db"}, {file = "kiwisolver-1.4.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c72941acb7b67138f35b879bbe85be0f6c6a70cab78fe3ef6db9c024d9223e5b"}, @@ -2078,6 +2566,8 @@ version = "3.77.0" description = "Pure Python library for LaTeX to MathML conversion" optional = false python-versions = ">=3.8.1,<4.0.0" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "latex2mathml-3.77.0-py3-none-any.whl", hash = "sha256:5531e18a2a9eae7c24e257118b6a444cbba253cd27ff3e81f1bd6c41e88e786e"}, {file = "latex2mathml-3.77.0.tar.gz", hash = "sha256:e2f501d1878f2e489c3f6f12786bef74c62f712d2770f7f3c837eb20a55d0a1e"}, @@ -2089,6 +2579,8 @@ version = "0.4" description = "Makes it easy to load subpackages and functions on demand." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "lazy_loader-0.4-py3-none-any.whl", hash = "sha256:342aa8e14d543a154047afb4ba8ef17f5563baad3fc610d7b15b213b0f119efc"}, {file = "lazy_loader-0.4.tar.gz", hash = "sha256:47c75182589b91a4e1a85a136c074285a5ad4d9f39c63e0d7fb76391c4574cd1"}, @@ -2108,6 +2600,8 @@ version = "1.10.0" description = "A fast and thorough lazy object proxy." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "lazy-object-proxy-1.10.0.tar.gz", hash = "sha256:78247b6d45f43a52ef35c25b5581459e85117225408a4128a3daf8bf9648ac69"}, {file = "lazy_object_proxy-1.10.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:855e068b0358ab916454464a884779c7ffa312b8925c6f7401e952dcf3b89977"}, @@ -2154,6 +2648,8 @@ version = "0.14.1" description = "Lightning toolbox for across the our ecosystem." optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "lightning_utilities-0.14.1-py3-none-any.whl", hash = "sha256:badc40a70d8e933706aa0b4f63b12392dbf8208728743a40b55edb5e81797311"}, {file = "lightning_utilities-0.14.1.tar.gz", hash = "sha256:9fb56c76dc07a46c075e1f78594fcb161091eae5944b34c2b43258d23c202791"}, @@ -2175,6 +2671,8 @@ version = "5.3.1" description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API." optional = false python-versions = ">=3.6" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "lxml-5.3.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a4058f16cee694577f7e4dd410263cd0ef75644b43802a689c2b3c2a7e69453b"}, {file = "lxml-5.3.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:364de8f57d6eda0c16dcfb999af902da31396949efa0e583e12675d09709881b"}, @@ -2329,6 +2827,8 @@ version = "3.0.0" description = "Python port of markdown-it. Markdown parsing, done right!" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "markdown-it-py-3.0.0.tar.gz", hash = "sha256:e3f60a94fa066dc52ec76661e37c851cb232d92f9886b15cb560aaada2df8feb"}, {file = "markdown_it_py-3.0.0-py3-none-any.whl", hash = "sha256:355216845c60bd96232cd8d8c40e8f9765cc86f46880e43a8fd22dc1a1a8cab1"}, @@ -2353,6 +2853,8 @@ version = "2.1.2" description = "A markdown parser with high extensibility." optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "marko-2.1.2-py3-none-any.whl", hash = "sha256:c14aa7a77468aaaf53cf056dcd3d32398b9df4c3fb81f5e120dd37cbb9f8c859"}, {file = "marko-2.1.2.tar.gz", hash = "sha256:a9170006b879376e6845c91b1ae3dce2992772954b99b70175ff888537186011"}, @@ -2369,6 +2871,8 @@ version = "3.0.2" description = "Safely add untrusted strings to HTML/XML markup." optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "MarkupSafe-3.0.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7e94c425039cde14257288fd61dcfb01963e658efbc0ff54f5306b06054700f8"}, {file = "MarkupSafe-3.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9e2d922824181480953426608b81967de705c3cef4d1af983af849d7bd619158"}, @@ -2439,6 +2943,8 @@ version = "3.10.1" description = "Python plotting package" optional = false python-versions = ">=3.10" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "matplotlib-3.10.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:ff2ae14910be903f4a24afdbb6d7d3a6c44da210fc7d42790b87aeac92238a16"}, {file = "matplotlib-3.10.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:0721a3fd3d5756ed593220a8b86808a36c5031fce489adb5b31ee6dbb47dd5b2"}, @@ -2496,6 +3002,8 @@ version = "0.1.7" description = "Inline Matplotlib backend for Jupyter" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "matplotlib_inline-0.1.7-py3-none-any.whl", hash = "sha256:df192d39a4ff8f21b1895d72e6a13f5fcc5099f00fa84384e0ea28c2cc0653ca"}, {file = "matplotlib_inline-0.1.7.tar.gz", hash = "sha256:8423b23ec666be3d16e16b60bdd8ac4e86e840ebd1dd11a30b9f117f2fa0ab90"}, @@ -2510,6 +3018,8 @@ version = "0.7.0" description = "McCabe checker, plugin for flake8" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "mccabe-0.7.0-py2.py3-none-any.whl", hash = "sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e"}, {file = "mccabe-0.7.0.tar.gz", hash = "sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325"}, @@ -2521,6 +3031,8 @@ version = "0.1.2" description = "Markdown 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multiprocessing, but faster than multiprocessing" optional = false python-versions = "*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "mpire-2.10.2-py3-none-any.whl", hash = "sha256:d627707f7a8d02aa4c7f7d59de399dec5290945ddf7fbd36cbb1d6ebb37a51fb"}, {file = "mpire-2.10.2.tar.gz", hash = "sha256:f66a321e93fadff34585a4bfa05e95bd946cf714b442f51c529038eb45773d97"}, @@ -2550,8 +3066,8 @@ files = [ [package.dependencies] multiprocess = [ - {version = "*", optional = true, markers = "python_version < \"3.11\" and extra == \"dill\""}, {version = ">=0.70.15", optional = true, markers = "python_version >= \"3.11\" and extra == \"dill\""}, + {version = "*", optional = true, markers = "python_version < \"3.11\" and extra == \"dill\""}, ] pygments = ">=2.0" pywin32 = {version = ">=301", markers = "platform_system == \"Windows\""} @@ -2569,6 +3085,8 @@ version = "1.3.0" description = "Python library for arbitrary-precision floating-point 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Communication Library (NCCL) Runtime" optional = false python-versions = ">=3" +groups = ["main"] +markers = "platform_machine == \"x86_64\" and (python_version >= \"3.12\" or python_version <= \"3.11\") and platform_system == \"Linux\"" files = [ {file = "nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl", hash = "sha256:8579076d30a8c24988834445f8d633c697d42397e92ffc3f63fa26766d25e0a0"}, ] @@ -3178,6 +3767,8 @@ version = "12.4.127" description = "Nvidia JIT LTO Library" optional = false python-versions = ">=3" +groups = ["main"] +markers = "platform_machine == \"x86_64\" and (python_version >= \"3.12\" or python_version <= \"3.11\") and platform_system == \"Linux\"" files = [ {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:4abe7fef64914ccfa909bc2ba39739670ecc9e820c83ccc7a6ed414122599b83"}, {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = 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["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "pre_commit-3.8.0-py2.py3-none-any.whl", hash = "sha256:9a90a53bf82fdd8778d58085faf8d83df56e40dfe18f45b19446e26bf1b3a63f"}, {file = "pre_commit-3.8.0.tar.gz", hash = "sha256:8bb6494d4a20423842e198980c9ecf9f96607a07ea29549e180eef9ae80fe7af"}, @@ -3552,6 +4189,8 @@ version = "3.0.50" description = "Library for building powerful interactive command lines in Python" optional = false python-versions = ">=3.8.0" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "prompt_toolkit-3.0.50-py3-none-any.whl", hash = "sha256:9b6427eb19e479d98acff65196a307c555eb567989e6d88ebbb1b509d9779198"}, {file = "prompt_toolkit-3.0.50.tar.gz", hash = "sha256:544748f3860a2623ca5cd6d2795e7a14f3d0e1c3c9728359013f79877fc89bab"}, @@ -3566,6 +4205,8 @@ version = "0.3.0" description = "Accelerated property cache" optional = false python-versions = ">=3.9" +groups = 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false python-versions = ">=3.8.1" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "pyproject_flake8-6.1.0-py3-none-any.whl", hash = "sha256:86ea5559263c098e1aa4f866776aa2cf45362fd91a576b9fd8fbbbb55db12c4e"}, {file = "pyproject_flake8-6.1.0.tar.gz", hash = "sha256:6da8e5a264395e0148bc11844c6fb50546f1fac83ac9210f7328664135f9e70f"}, @@ -4154,6 +4889,8 @@ version = "7.4.4" description = "pytest: simple powerful testing with Python" optional = false python-versions = ">=3.7" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "pytest-7.4.4-py3-none-any.whl", hash = "sha256:b090cdf5ed60bf4c45261be03239c2c1c22df034fbffe691abe93cd80cea01d8"}, {file = "pytest-7.4.4.tar.gz", hash = "sha256:2cf0005922c6ace4a3e2ec8b4080eb0d9753fdc93107415332f50ce9e7994280"}, @@ -4176,6 +4913,8 @@ version = "3.6.1" description = "pytest xdist plugin for distributed testing, most importantly across multiple CPUs" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "pytest_xdist-3.6.1-py3-none-any.whl", hash = "sha256:9ed4adfb68a016610848639bb7e02c9352d5d9f03d04809919e2dafc3be4cca7"}, {file = "pytest_xdist-3.6.1.tar.gz", hash = "sha256:ead156a4db231eec769737f57668ef58a2084a34b2e55c4a8fa20d861107300d"}, @@ -4196,6 +4935,8 @@ version = "0.6.6" description = "Python Bidi layout wrapping the Rust crate unicode-bidi" optional = false python-versions = "*" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python_bidi-0.6.6-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:09d4da6b5851d0df01d7313a11d22f308fdfb0e12461f7262e0f55c521ccc0f1"}, {file = "python_bidi-0.6.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:493a844891e23264411b01df58ba77d5dbb0045da3787f4195f50a56bfb847d9"}, @@ -4317,6 +5058,8 @@ version = "2.9.0.post0" description = "Extensions to the standard Python datetime module" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, @@ -4331,6 +5074,8 @@ version = "1.1.2" description = "Create, read, and update Microsoft Word .docx files." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python_docx-1.1.2-py3-none-any.whl", hash = "sha256:08c20d6058916fb19853fcf080f7f42b6270d89eac9fa5f8c15f691c0017fabe"}, {file = "python_docx-1.1.2.tar.gz", hash = "sha256:0cf1f22e95b9002addca7948e16f2cd7acdfd498047f1941ca5d293db7762efd"}, @@ -4346,6 +5091,8 @@ version = "1.0.1" description = "Read key-value pairs from a .env file and set them as environment variables" optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python-dotenv-1.0.1.tar.gz", hash = "sha256:e324ee90a023d808f1959c46bcbc04446a10ced277783dc6ee09987c37ec10ca"}, {file = "python_dotenv-1.0.1-py3-none-any.whl", hash = "sha256:f7b63ef50f1b690dddf550d03497b66d609393b40b564ed0d674909a68ebf16a"}, @@ -4360,6 +5107,8 @@ version = "3.15.0" description = "Interact with GitLab API" optional = false python-versions = ">=3.7.0" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python-gitlab-3.15.0.tar.gz", hash = "sha256:c9e65eb7612a9fbb8abf0339972eca7fd7a73d4da66c9b446ffe528930aff534"}, {file = "python_gitlab-3.15.0-py3-none-any.whl", hash = "sha256:8f8d1c0d387f642eb1ac7bf5e8e0cd8b3dd49c6f34170cee3c7deb7d384611f3"}, @@ -4379,6 +5128,8 @@ version = "1.0.2" description = "Create, read, and update PowerPoint 2007+ (.pptx) files." optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python_pptx-1.0.2-py3-none-any.whl", hash = "sha256:160838e0b8565a8b1f67947675886e9fea18aa5e795db7ae531606d68e785cba"}, {file = "python_pptx-1.0.2.tar.gz", hash = "sha256:479a8af0eaf0f0d76b6f00b0887732874ad2e3188230315290cd1f9dd9cc7095"}, @@ -4396,6 +5147,8 @@ version = "7.34.6" description = "Automatic Semantic Versioning for Python projects" optional = false python-versions = "*" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "python-semantic-release-7.34.6.tar.gz", hash = "sha256:e9b8fb788024ae9510a924136d573588415a16eeca31cc5240f2754a80a2e831"}, {file = 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"sha256:c3e78706e4229b915a0821941a84e7ef420bf2b77e08c9dae3c76fd03fd2ae3d"}, @@ -4456,6 +5212,7 @@ files = [ {file = "pywin32-310-cp39-cp39-win32.whl", hash = "sha256:851c8d927af0d879221e616ae1f66145253537bbdd321a77e8ef701b443a9a1a"}, {file = "pywin32-310-cp39-cp39-win_amd64.whl", hash = "sha256:96867217335559ac619f00ad70e513c0fcf84b8a3af9fc2bba3b59b97da70475"}, ] +markers = {main = "(python_version >= \"3.12\" or python_version <= \"3.11\") and (platform_system == \"Windows\" or sys_platform == \"win32\")", dev = "sys_platform == \"win32\" and (python_version >= \"3.12\" or python_version <= \"3.11\") and platform_python_implementation != \"PyPy\""} [[package]] name = "pywin32-ctypes" @@ -4463,6 +5220,8 @@ version = "0.2.3" description = "A (partial) reimplementation of pywin32 using ctypes/cffi" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "sys_platform == \"win32\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = 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"python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "referencing-0.36.2-py3-none-any.whl", hash = "sha256:e8699adbbf8b5c7de96d8ffa0eb5c158b3beafce084968e2ea8bb08c6794dcd0"}, {file = "referencing-0.36.2.tar.gz", hash = "sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa"}, @@ -4676,6 +5443,8 @@ version = "2024.11.6" description = "Alternative regular expression module, to replace re." optional = false python-versions = ">=3.8" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"}, {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"}, @@ -4779,6 +5548,8 @@ version = "2.32.3" description = "Python HTTP for Humans." optional = false python-versions = ">=3.8" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"}, {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"}, @@ -4794,12 +5565,34 @@ urllib3 = ">=1.21.1,<3" socks = ["PySocks (>=1.5.6,!=1.5.7)"] use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] +[[package]] +name = "requests-oauthlib" +version = "2.0.0" +description = "OAuthlib authentication support for Requests." +optional = false +python-versions = ">=3.4" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "requests-oauthlib-2.0.0.tar.gz", hash = "sha256:b3dffaebd884d8cd778494369603a9e7b58d29111bf6b41bdc2dcd87203af4e9"}, + {file = "requests_oauthlib-2.0.0-py2.py3-none-any.whl", hash = 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\"3.12\"" files = [ {file = "rfc3986-2.0.0-py2.py3-none-any.whl", hash = "sha256:50b1502b60e289cb37883f3dfd34532b8873c7de9f49bb546641ce9cbd256ebd"}, {file = "rfc3986-2.0.0.tar.gz", hash = "sha256:97aacf9dbd4bfd829baad6e6309fa6573aaf1be3f6fa735c8ab05e46cecb261c"}, @@ -4828,6 +5623,8 @@ version = "13.9.4" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false python-versions = ">=3.8.0" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "rich-13.9.4-py3-none-any.whl", hash = "sha256:6049d5e6ec054bf2779ab3358186963bac2ea89175919d699e378b99738c2a90"}, {file = "rich-13.9.4.tar.gz", hash = "sha256:439594978a49a09530cff7ebc4b5c7103ef57baf48d5ea3184f21d9a2befa098"}, @@ -4847,6 +5644,8 @@ version = "0.23.1" description = "Python bindings to Rust's persistent data structures (rpds)" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "rpds_py-0.23.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:2a54027554ce9b129fc3d633c92fa33b30de9f08bc61b32c053dc9b537266fed"}, {file = "rpds_py-0.23.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b5ef909a37e9738d146519657a1aab4584018746a18f71c692f2f22168ece40c"}, @@ -4953,12 +5752,30 @@ files = [ {file = "rpds_py-0.23.1.tar.gz", hash = "sha256:7f3240dcfa14d198dba24b8b9cb3b108c06b68d45b7babd9eefc1038fdf7e707"}, ] +[[package]] +name = "rsa" +version = "4.9" +description = "Pure-Python RSA implementation" +optional = false +python-versions = ">=3.6,<4" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "rsa-4.9-py3-none-any.whl", hash = "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7"}, + {file = "rsa-4.9.tar.gz", hash = "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21"}, +] + +[package.dependencies] +pyasn1 = ">=0.1.3" + [[package]] name = "rtree" version = "1.4.0" description = "R-Tree spatial index for Python GIS" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "rtree-1.4.0-py3-none-macosx_10_9_x86_64.whl", hash = "sha256:4d1bebc418101480aabf41767e772dd2155d3b27b1376cccbd93e4509485e091"}, {file = "rtree-1.4.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:997f8c38d5dffa3949ea8adb4c8b291ea5cd4ef5ee69455d642dd171baf9991d"}, @@ -4978,6 +5795,8 @@ version = "0.5.3" description = "" optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "safetensors-0.5.3-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:bd20eb133db8ed15b40110b7c00c6df51655a2998132193de2f75f72d99c7073"}, {file = "safetensors-0.5.3-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:21d01c14ff6c415c485616b8b0bf961c46b3b343ca59110d38d744e577f9cce7"}, @@ -5019,6 +5838,8 @@ version = "0.25.2" description = "Image processing in Python" optional = false python-versions = ">=3.10" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "scikit_image-0.25.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d3278f586793176599df6a4cf48cb6beadae35c31e58dc01a98023af3dc31c78"}, {file = "scikit_image-0.25.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:5c311069899ce757d7dbf1d03e32acb38bb06153236ae77fcd820fd62044c063"}, @@ -5068,6 +5889,8 @@ version = "1.15.2" description = "Fundamental algorithms for scientific computing in Python" optional = false python-versions = ">=3.10" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "scipy-1.15.2-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:a2ec871edaa863e8213ea5df811cd600734f6400b4af272e1c011e69401218e9"}, {file = "scipy-1.15.2-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:6f223753c6ea76983af380787611ae1291e3ceb23917393079dcc746ba60cfb5"}, @@ -5131,6 +5954,8 @@ version = "3.3.3" description = "Python bindings to FreeDesktop.org Secret Service API" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "sys_platform == \"linux\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "SecretStorage-3.3.3-py3-none-any.whl", hash = "sha256:f356e6628222568e3af06f2eba8df495efa13b3b63081dafd4f7d9a7b7bc9f99"}, {file = "SecretStorage-3.3.3.tar.gz", hash = "sha256:2403533ef369eca6d2ba81718576c5e0f564d5cca1b58f73a8b23e7d4eeebd77"}, @@ -5146,6 +5971,8 @@ version = "2.2.2" description = "A fast and lightweight Python library for splitting text into semantically meaningful chunks." optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = 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">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "setuptools-76.0.0-py3-none-any.whl", hash = "sha256:199466a166ff664970d0ee145839f5582cb9bca7a0a3a2e795b6a9cb2308e9c6"}, - {file = "setuptools-76.0.0.tar.gz", hash = "sha256:43b4ee60e10b0d0ee98ad11918e114c70701bc6051662a9a675a0496c1a158f4"}, + {file = "setuptools-76.1.0-py3-none-any.whl", hash = "sha256:34750dcb17d046929f545dec9b8349fe42bf4ba13ddffee78428aec422dbfb73"}, + {file = "setuptools-76.1.0.tar.gz", hash = "sha256:4959b9ad482ada2ba2320c8f1a8d8481d4d8d668908a7a1b84d987375cd7f5bd"}, ] [package.extras] @@ -5192,6 +6023,8 @@ version = "2.0.7" description = "Manipulation and analysis of geometric objects" optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "shapely-2.0.7-cp310-cp310-macosx_10_9_x86_64.whl", hash = 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"sha256:10f205b923c04678f744a6d553f6f86c639c9ba6e714f6758d81af0678ba75dc"}, {file = "tifffile-2025.3.13.tar.gz", hash = "sha256:30fcc4584216937b5993d0568452b6fea8e12e61f9afb1a8e967c07c281faa06"}, @@ -5366,6 +6215,8 @@ version = "6.1.0" description = "A wrapper around the stdlib `tokenize` which roundtrips." optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tokenize_rt-6.1.0-py2.py3-none-any.whl", hash = "sha256:d706141cdec4aa5f358945abe36b911b8cbdc844545da99e811250c0cee9b6fc"}, {file = "tokenize_rt-6.1.0.tar.gz", hash = "sha256:e8ee836616c0877ab7c7b54776d2fefcc3bde714449a206762425ae114b53c86"}, @@ -5377,6 +6228,8 @@ version = "0.19.1" description = "" optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "sys_platform == \"darwin\" and platform_machine == \"x86_64\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = 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"python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, @@ -5567,6 +6424,8 @@ version = "0.13.2" description = "Style preserving TOML library" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tomlkit-0.13.2-py3-none-any.whl", hash = "sha256:7a974427f6e119197f670fbbbeae7bef749a6c14e793db934baefc1b5f03efde"}, {file = "tomlkit-0.13.2.tar.gz", hash = "sha256:fff5fe59a87295b278abd31bec92c15d9bc4a06885ab12bcea52c71119392e79"}, @@ -5578,6 +6437,8 @@ version = "2.6.0" description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration" optional = false python-versions = ">=3.9.0" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "torch-2.6.0-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:6860df13d9911ac158f4c44031609700e1eba07916fff62e21e6ffa0a9e01961"}, {file = "torch-2.6.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:c4f103a49830ce4c7561ef4434cc7926e5a5fe4e5eb100c19ab36ea1e2b634ab"}, @@ -5634,6 +6495,8 @@ version = "1.6.3" description = "PyTorch native Metrics" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "torchmetrics-1.6.3-py3-none-any.whl", hash = "sha256:034640d4e1c30b7d3488551b1ce3fc1f363070811e6b97b9cb6b60a9ec15e9f4"}, {file = "torchmetrics-1.6.3.tar.gz", hash = "sha256:be59ffe9e9abf12ac12c3ac4383b2fc7731ad2bf3748ae1b06e8dea34e9f8a65"}, @@ -5662,6 +6525,8 @@ version = "0.21.0" description = "image and video datasets and models for torch deep learning" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "torchvision-0.21.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:044ea420b8c6c3162a234cada8e2025b9076fa82504758cd11ec5d0f8cd9fa37"}, {file = "torchvision-0.21.0-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:b0c0b264b89ab572888244f2e0bad5b7eaf5b696068fc0b93e96f7c3c198953f"}, @@ -5700,6 +6565,8 @@ version = "6.4.2" description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_universal2.whl", hash = "sha256:e828cce1123e9e44ae2a50a9de3055497ab1d0aeb440c5ac23064d9e44880da1"}, {file = "tornado-6.4.2-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:072ce12ada169c5b00b7d92a99ba089447ccc993ea2143c9ede887e0937aa803"}, @@ -5720,6 +6587,8 @@ version = "4.67.1" description = "Fast, Extensible Progress Meter" optional = false python-versions = ">=3.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tqdm-4.67.1-py3-none-any.whl", hash = "sha256:26445eca388f82e72884e0d580d5464cd801a3ea01e63e5601bdff9ba6a48de2"}, {file = "tqdm-4.67.1.tar.gz", hash = "sha256:f8aef9c52c08c13a65f30ea34f4e5aac3fd1a34959879d7e59e63027286627f2"}, @@ -5741,6 +6610,8 @@ version = "5.14.3" description = "Traitlets Python configuration system" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f"}, {file = "traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7"}, @@ -5756,6 +6627,8 @@ version = "4.42.4" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" optional = false python-versions = ">=3.8.0" +groups = ["main"] +markers = "sys_platform == \"darwin\" and platform_machine == \"x86_64\" and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "transformers-4.42.4-py3-none-any.whl", hash = "sha256:6d59061392d0f1da312af29c962df9017ff3c0108c681a56d1bc981004d16d24"}, {file = "transformers-4.42.4.tar.gz", hash = "sha256:f956e25e24df851f650cb2c158b6f4352dfae9d702f04c113ed24fc36ce7ae2d"}, @@ -5824,6 +6697,8 @@ version = "4.49.0" description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow" optional = false python-versions = ">=3.9.0" +groups = ["main"] +markers = "(sys_platform != \"darwin\" or platform_machine != \"x86_64\") and (python_version >= \"3.12\" or python_version <= \"3.11\")" files = [ {file = "transformers-4.49.0-py3-none-any.whl", hash = "sha256:6b4fded1c5fee04d384b1014495b4235a2b53c87503d7d592423c06128cbbe03"}, {file = "transformers-4.49.0.tar.gz", hash = "sha256:7e40e640b5b8dc3f48743f5f5adbdce3660c82baafbd3afdfc04143cdbd2089e"}, @@ -5893,6 +6768,8 @@ version = "3.2.0" description = "A language and compiler for custom Deep Learning operations" optional = false python-versions = "*" +groups = ["main"] +markers = "platform_machine == \"x86_64\" and (python_version >= \"3.12\" or python_version <= \"3.11\") and platform_system == \"Linux\"" files = [ {file = "triton-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b3e54983cd51875855da7c68ec05c05cf8bb08df361b1d5b69e05e40b0c9bd62"}, {file = "triton-3.2.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8009a1fb093ee8546495e96731336a33fb8856a38e45bb4ab6affd6dbc3ba220"}, @@ -5912,6 +6789,8 @@ version = "3.8.0" description = "Collection of utilities for publishing packages on PyPI" optional = false python-versions = ">=3.6" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "twine-3.8.0-py3-none-any.whl", hash = "sha256:d0550fca9dc19f3d5e8eadfce0c227294df0a2a951251a4385797c8a6198b7c8"}, {file = "twine-3.8.0.tar.gz", hash = "sha256:8efa52658e0ae770686a13b675569328f1fba9837e5de1867bfe5f46a9aefe19"}, @@ -5935,6 +6814,8 @@ version = "0.12.5" description = "Typer, build great CLIs. Easy to code. Based on Python type hints." optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "typer-0.12.5-py3-none-any.whl", hash = "sha256:62fe4e471711b147e3365034133904df3e235698399bc4de2b36c8579298d52b"}, {file = "typer-0.12.5.tar.gz", hash = "sha256:f592f089bedcc8ec1b974125d64851029c3b1af145f04aca64d69410f0c9b722"}, @@ -5952,6 +6833,8 @@ version = "3.1.5.20250306" description = "Typing stubs for openpyxl" optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "types_openpyxl-3.1.5.20250306-py3-none-any.whl", hash = "sha256:f7733dac1dcb07c89ff5ffde8452ee8d272be638defed855f4c48b2990ce5aa7"}, {file = "types_openpyxl-3.1.5.20250306.tar.gz", hash = "sha256:aa7ad2425e8020ff46a31633becfe1f3c64114498d964c536199f654b464e6bc"}, @@ -5959,28 +6842,45 @@ files = [ [[package]] name = "types-pytz" -version = 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+markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "types_requests-2.32.0.20250306-py3-none-any.whl", hash = "sha256:25f2cbb5c8710b2022f8bbee7b2b66f319ef14aeea2f35d80f18c9dbf3b60a0b"}, - {file = "types_requests-2.32.0.20250306.tar.gz", hash = "sha256:0962352694ec5b2f95fda877ee60a159abdf84a0fc6fdace599f20acb41a03d1"}, + {file = "types-requests-2.31.0.6.tar.gz", hash = "sha256:cd74ce3b53c461f1228a9b783929ac73a666658f223e28ed29753771477b3bd0"}, + {file = "types_requests-2.31.0.6-py3-none-any.whl", hash = "sha256:a2db9cb228a81da8348b49ad6db3f5519452dd20a9c1e1a868c83c5fe88fd1a9"}, ] [package.dependencies] -urllib3 = ">=2" +types-urllib3 = "*" + +[[package]] +name = "types-urllib3" +version = "1.26.25.14" +description = "Typing stubs for urllib3" +optional = false +python-versions = "*" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" +files = [ + {file = "types-urllib3-1.26.25.14.tar.gz", hash = "sha256:229b7f577c951b8c1b92c1bc2b2fdb0b49847bd2af6d1cc2a2e3dd340f3bda8f"}, + {file = "types_urllib3-1.26.25.14-py3-none-any.whl", hash = "sha256:9683bbb7fb72e32bfe9d2be6e04875fbe1b3eeec3cbb4ea231435aa7fd6b4f0e"}, +] [[package]] name = "typing-extensions" @@ -5988,6 +6888,8 @@ version = "4.12.2" description = "Backported and Experimental Type Hints for Python 3.8+" optional = false python-versions = ">=3.8" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"}, {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"}, @@ -5999,6 +6901,8 @@ version = "2025.1" description = "Provider of IANA time zone data" optional = false python-versions = ">=2" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "tzdata-2025.1-py2.py3-none-any.whl", hash = "sha256:7e127113816800496f027041c570f50bcd464a020098a3b6b199517772303639"}, {file = "tzdata-2025.1.tar.gz", hash = "sha256:24894909e88cdb28bd1636c6887801df64cb485bd593f2fd83ef29075a81d694"}, @@ -6006,20 +6910,21 @@ files = [ [[package]] name = "urllib3" -version = "2.3.0" +version = "1.26.20" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false -python-versions = ">=3.9" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +groups = ["main", "dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ - {file = "urllib3-2.3.0-py3-none-any.whl", hash = "sha256:1cee9ad369867bfdbbb48b7dd50374c0967a0bb7710050facf0dd6911440e3df"}, - {file = "urllib3-2.3.0.tar.gz", hash = "sha256:f8c5449b3cf0861679ce7e0503c7b44b5ec981bec0d1d3795a07f1ba96f0204d"}, + {file = "urllib3-1.26.20-py2.py3-none-any.whl", hash = "sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e"}, + {file = "urllib3-1.26.20.tar.gz", hash = "sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32"}, ] [package.extras] -brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"] -h2 = ["h2 (>=4,<5)"] -socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] -zstd = ["zstandard (>=0.18.0)"] +brotli = ["brotli (==1.0.9)", "brotli (>=1.0.9)", "brotlicffi (>=0.8.0)", "brotlipy (>=0.6.0)"] +secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"] +socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] [[package]] name = "virtualenv" @@ -6027,6 +6932,8 @@ version = "20.29.3" description = "Virtual Python Environment builder" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "virtualenv-20.29.3-py3-none-any.whl", hash = "sha256:3e3d00f5807e83b234dfb6122bf37cfadf4be216c53a49ac059d02414f819170"}, {file = "virtualenv-20.29.3.tar.gz", hash = "sha256:95e39403fcf3940ac45bc717597dba16110b74506131845d9b687d5e73d947ac"}, @@ -6047,6 +6954,8 @@ version = "0.2.13" description = "Measures the displayed width of unicode strings in a terminal" optional = false python-versions = "*" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"}, {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"}, @@ -6058,6 +6967,8 @@ version = "0.45.1" description = "A built-package format for Python" optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "wheel-0.45.1-py3-none-any.whl", hash = "sha256:708e7481cc80179af0e556bbf0cc00b8444c7321e2700b8d8580231d13017248"}, {file = "wheel-0.45.1.tar.gz", hash = "sha256:661e1abd9198507b1409a20c02106d9670b2576e916d58f520316666abca6729"}, @@ -6072,6 +6983,8 @@ version = "4.0.13" description = "Jupyter interactive widgets for Jupyter Notebook" optional = false python-versions = ">=3.7" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "widgetsnbextension-4.0.13-py3-none-any.whl", hash = "sha256:74b2692e8500525cc38c2b877236ba51d34541e6385eeed5aec15a70f88a6c71"}, {file = "widgetsnbextension-4.0.13.tar.gz", hash = "sha256:ffcb67bc9febd10234a362795f643927f4e0c05d9342c727b65d2384f8feacb6"}, @@ -6083,6 +6996,8 @@ version = "1.17.2" description = "Module for decorators, wrappers and monkey patching." optional = false python-versions = ">=3.8" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = 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python_version >= \"3.12\"" files = [ {file = "xmltodict-0.14.2-py2.py3-none-any.whl", hash = "sha256:20cc7d723ed729276e808f26fb6b3599f786cbc37e06c65e192ba77c40f20aac"}, {file = "xmltodict-0.14.2.tar.gz", hash = "sha256:201e7c28bb210e374999d1dde6382923ab0ed1a8a5faeece48ab525b7810a553"}, @@ -6193,6 +7112,8 @@ version = "3.5.0" description = "Python binding for xxHash" optional = false python-versions = ">=3.7" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "xxhash-3.5.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:ece616532c499ee9afbb83078b1b952beffef121d989841f7f4b3dc5ac0fd212"}, {file = "xxhash-3.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3171f693dbc2cef6477054a665dc255d996646b4023fe56cb4db80e26f4cc520"}, @@ -6325,6 +7246,8 @@ version = "1.18.3" description = "Yet another URL library" optional = false python-versions = ">=3.9" +groups = ["main"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:7df647e8edd71f000a5208fe6ff8c382a1de8edfbccdbbfe649d263de07d8c34"}, {file = "yarl-1.18.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c69697d3adff5aa4f874b19c0e4ed65180ceed6318ec856ebc423aa5850d84f7"}, @@ -6421,6 +7344,8 @@ version = "3.21.0" description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" +groups = ["dev"] +markers = "python_version <= \"3.11\" or python_version >= \"3.12\"" files = [ {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, @@ -6435,6 +7360,6 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", type = ["pytest-mypy"] [metadata] -lock-version = "2.0" +lock-version = "2.1" python-versions = "^3.10" -content-hash = "059e0c343e9d3804eb5715ceabfcad3103a001deaf4d7bcf6cae5f4e3d01a571" +content-hash = "ac2b44c42486d3003e35cbd020dc6bae4310a404a45dfb09e3310b6ad2154528" diff --git a/pyproject.toml b/pyproject.toml index 2edf9e9b..15c44da0 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -26,12 +26,12 @@ packages = [{include = "docling_eval"}] ###################### python = "^3.10" docling-core = "^2.20.0" -pydantic = "^2.0.0" +pydantic = "2.9.2" lxml = "^5.3.0" datasets = "^3.2.0" apted = "^1.0.3" Distance = "^0.1.3" -docling = {extras = ["vlm"], version = "^2.26.0"} +docling = {extras = ["vlm"], version = "2.26.0"} matplotlib = "^3.10.0" torch = "^2.5.1" torchmetrics = "^1.6.0" @@ -41,7 +41,13 @@ tqdm = "^4.67.1" pillow = "^10.3.0" evaluate = "^0.4.3" nltk = "^3.9.1" +ibm-cos-sdk = "^2.1.40" +google-cloud-documentai = "^3.2.0" +azure-ai-formrecognizer = "^3.3.0" +azure-common = "^1.1.28" +azure-core = "^1.32.0" beautifulsoup4 = "^4.12.3" +urllib3 = "^1.24.2" [tool.poetry.group.dev.dependencies] black = {extras = ["jupyter"], version = "^24.4.2"}