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docs: Describe examples (#2262)

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* Update .py examples with clearer guidance,
update out of date imports and calls

Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com>

* Fix minimal.py string error, fix ruff format error

Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com>

* fix more CI issues

Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com>

---------

Signed-off-by: Mingxuan Zhao <43148277+mingxzhao@users.noreply.github.com>
This commit is contained in:
Mingxuan Zhao
2025-09-16 10:00:38 -04:00
committed by GitHub
parent 0e95171dd6
commit ff351fd40c
21 changed files with 608 additions and 85 deletions
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37
docs/examples/rapidocr_with_custom_models.py vendored
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@@ -1,25 +1,46 @@
# %% [markdown]
# Use RapidOCR with custom ONNX models to OCR a PDF page and print Markdown.
#
# What this example does
# - Downloads RapidOCR models from Hugging Face via ModelScope.
# - Configures `RapidOcrOptions` with explicit det/rec/cls model paths.
# - Runs the PDF pipeline with RapidOCR and prints Markdown output.
#
# Prerequisites
# - Install Docling, `modelscope`, and have network access to download models.
# - Ensure your environment can import `docling` and `modelscope`.
#
# How to run
# - From the repo root: `python docs/examples/rapidocr_with_custom_models.py`.
# - The script prints the recognized text as Markdown to stdout.
#
# Notes
# - The default `source` points to an arXiv PDF URL; replace with a local path if desired.
# - Model paths are derived from the downloaded snapshot directory.
# - ModelScope caches downloads (typically under `~/.cache/modelscope`); set a proxy
# or pre-download models if running in a restricted network environment.
# %%
import os
from modelscope import snapshot_download
from docling.datamodel.base_models import InputFormat
from docling.datamodel.document import ConversionResult
from docling.datamodel.pipeline_options import PdfPipelineOptions, RapidOcrOptions
from docling.document_converter import (
ConversionResult,
DocumentConverter,
InputFormat,
PdfFormatOption,
)
from docling.document_converter import DocumentConverter, PdfFormatOption
def main():
# Source document to convert
source = "https://arxiv.org/pdf/2408.09869v4"
# Download RappidOCR models from HuggingFace
# Download RapidOCR models from Hugging Face
print("Downloading RapidOCR models")
download_path = snapshot_download(repo_id="RapidAI/RapidOCR")
# Setup RapidOcrOptions for english detection
# Setup RapidOcrOptions for English detection
det_model_path = os.path.join(
download_path, "onnx", "PP-OCRv5", "det", "ch_PP-OCRv5_server_det.onnx"
)