Sold by: UpstageÂ
Overview
Upstage Document Parse is a powerful API designed to automatically convert any document to HTML. It detects layout elements such as paragraphs, tables, images, equations, charts and more to determine the structure of the document. The API then serializes the elements according to reading order, and finally converts the document into HTML.
Highlights
- ### Key Features **Text Recognition** detects text via OCR or PDF parsing, excelling in English and CJK documents, including digital-born PDFs. **Layout Element Detection (LED)** identifies paragraphs, figures, tables, and captions, arranging them in human reading order - great for complex layouts. **Table Structure Recognition (TSR)** converts complex tables to HTML, handling merged cells and hidden gridlines.
- ### Key Applications The Upstage Document Parse model enhances LLM-based document processing and information retrieval by preserving contextual information better than traditional OCR. It is valuable for scenarios where LLMs process documents, integrating RAG with Layout Analysis via embedding techniques. It excels in information extraction and recognizing document structures across various templates, making it ideal for handling the same type of documents in different formats.
- ### Key Tasks - Document OCR - Document Parsing - Layout Analysis - Information Extraction - Layout Element Detection - Table Structure Recognition
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.12xlarge Inference (Batch) Recommended | Model inference on the ml.m5.12xlarge instance type, batch mode | $15.00 |
ml.g6.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g6.xlarge instance type, real-time mode | $15.00 |
ml.p3.2xlarge Inference (Real-Time) | Model inference on the ml.p3.2xlarge instance type, real-time mode | $15.00 |
ml.g6.2xlarge Inference (Real-Time) | Model inference on the ml.g6.2xlarge instance type, real-time mode | $15.00 |
ml.g5.xlarge Inference (Real-Time) | Model inference on the ml.g5.xlarge instance type, real-time mode | $15.00 |
ml.g5.2xlarge Inference (Real-Time) | Model inference on the ml.g5.2xlarge instance type, real-time mode | $15.00 |
ml.g4dn.xlarge Inference (Real-Time) | Model inference on the ml.g4dn.xlarge instance type, real-time mode | $15.00 |
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We do not support any refunds currently.
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
âť— Important Notice It requires NVIDIA Driver version 525.0 or later and is optimized for ml.g6 instances. For users running ml.g5 instances, please use version 250404c.3 for compatibility.
🚀 Updates
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Support for various form types has been significantly improved, enabling more accurate parsing across diverse document layouts.
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Tables split across multiple pages are now automatically linked and merged into a single coherent structure.
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Rotated documents are now handled correctly without requiring manual adjustments, improving robustness in real-world scenarios.
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Patchify has been optimized for better performance and accuracy when processing long vertical images.
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Added safeguards to prevent infinite loops, improving system stability.
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Fixed an issue where errors incorrectly returned a 200 OK response, ensuring accurate HTTP status reporting.
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Improved GPU memory management for resource efficiency.
Additional details
Inputs
- Summary
Provide input data in multipart form data View more detailed description hereÂ
- Input MIME type
- multipart/form-data
https://console.upstage.ai/_next/image?url=%2Fassets%2Fimages%2Fdocs%2Finvoice.png&w=1920&q=75
BATCH INFERENCE IS NOT SUPPORTED NOW
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