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upstage-document-parse

Parse documents (PDF, images, DOCX, PPTX, XLSX, HWP) using Upstage Document Parse API. Extracts text, tables, figures, and layout elements with bounding boxes. Use when user asks to parse, extract, or analyze document content, convert documents to markdown/HTML, or extract structured data from PDFs and images.

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Kernel8901/ai-agent-skills-classification
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2026年4月4日 15:26
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SKILL.md
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name
upstage-document-parse
description
Parse documents (PDF, images, DOCX, PPTX, XLSX, HWP) using Upstage Document Parse API. Extracts text, tables, figures, and layout elements with bounding boxes. Use when user asks to parse, extract, or analyze document content, convert documents to markdown/HTML, or extract structured data from PDFs and images.
homepage
https://console.upstage.ai/api/document-digitization/document-parsing
metadata
{"openclaw":{"emoji":"📑","requires":{"bins":"[Truncated]","env":"[Truncated]"},"primaryEnv":"UPSTAGE_API_KEY"}}
# Upstage Document Parse Extract structured content from documents using Upstage's Document Parse API. ## Supported Formats PDF (up to 1000 pages with async), PNG, JPG, JPEG, TIFF, BMP, GIF, WEBP, DOCX, PPTX, XLSX, HWP ## Installation ```bash clawhub install upstage-document-parse ``` ## API Key Setup 1. Get your API key from [Upstage Console](https://console.upstage.ai) 2. Configure the API key: ```bash openclaw config set skills.entries.upstage-document-parse.apiKey "your-api-key" ``` Or add to `~/.openclaw/openclaw.json`: ```json5 { "skills": { "entries": { "upstage-document-parse": { "apiKey": "your-api-key" } } } } ``` ## Usage Examples Just ask the agent to parse your document: ``` "Parse this PDF: ~/Documents/report.pdf" "Parse: ~/Documents/report.jpg" ``` --- ## Sync API (Small Documents) For small documents (recommended < 20 pages). ### Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `model` | string | required | Use `document-parse` (latest) or `document-parse-nightly` | | `document` | file | required | Document file to parse | | `mode` | string | `standard` | `standard` (text-focused), `enhanced` (complex tables/images), `auto` | | `ocr` | string | `auto` | `auto` (images only) or `force` (always OCR) | | `output_formats` | string | `['html']` | `text`, `html`, `markdown` (array format) | | `coordinates` | boolean | `true` | Include bounding box coordinates | | `base64_encoding` | string | `[]` | Elements to base64: `["table"]`, `["figure"]`, etc. | | `chart_recognition` | boolean | `true` | Convert charts to tables (Beta) | | `merge_multipage_tables` | boolean | `false` | Merge tables across pages (Beta, max 20 pages if true) | ### Basic Parsing ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@/path/to/file.pdf" \ -F "model=document-parse" ``` ### Extract Markdown ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@report.pdf" \ -F "model=document-parse" \ -F "output_formats=['markdown']" ``` ### Enhanced Mode for Complex Documents ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@complex.pdf" \ -F "model=document-parse" \ -F "mode=enhanced" \ -F "output_formats=['html', 'markdown']" ``` ### Force OCR for Scanned Documents ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@scan.pdf" \ -F "model=document-parse" \ -F "ocr=force" ``` ### Extract Table Images as Base64 ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@invoice.pdf" \ -F "model=document-parse" \ -F "base64_encoding=['table']" ``` --- ## Response Structure ```json { "api": "2.0", "model": "document-parse-251217", "content": { "html": "<h1>...</h1>", "markdown": "# ...", "text": "..." }, "elements": [ { "id": 0, "category": "heading1", "content": { "html": "...", "markdown": "...", "text": "..." }, "page": 1, "coordinates": [{"x": 0.06, "y": 0.05}, ...] } ], "usage": { "pages": 1 } } ``` ### Element Categories `paragraph`, `heading1`, `heading2`, `heading3`, `list`, `table`, `figure`, `chart`, `equation`, `caption`, `header`, `footer`, `index`, `footnote` --- ## Async API (Large Documents) For documents up to 1000 pages. Documents are processed in batches of 10 pages. ### Submit Request ```bash curl -X POST "https://api.upstage.ai/v1/document-digitization/async" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" \ -F "document=@large.pdf" \ -F "model=document-parse" \ -F "output_formats=['markdown']" ``` Response: ```json {"request_id": "uuid-here"} ``` ### Check Status & Get Results ```bash curl "https://api.upstage.ai/v1/document-digitization/requests/{request_id}" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" ``` Response includes `download_url` for each batch (available for 30 days). ### List All Requests ```bash curl "https://api.upstage.ai/v1/document-digitization/requests" \ -H "Authorization: Bearer $UPSTAGE_API_KEY" ``` ### Status Values - `submitted`: Request received - `started`: Processing in progress - `completed`: Ready for download - `failed`: Error occurred (check `failure_message`) ### Notes - Results stored for 30 days - Download URLs expire after 15 minutes (re-fetch status to get new URLs) - Documents split into batches of up to 10 pages --- ## Python Usage ```python import requests api_key = "up_xxx" # Sync with open("doc.pdf", "rb") as f: response = requests.post( "https://api.upstage.ai/v1/document-digitization", headers={"Authorization": f"Bearer {api_key}"}, files={"document": f}, data={"model": "document-parse", "output_formats": "['markdown']"} ) print(response.json()["content"]["markdown"]) # Async for large docs with open("large.pdf", "rb") as f: r = requests.post( "https://api.upstage.ai/v1/document-digitization/async", headers={"Authorization": f"Bearer {api_key}"}, files={"document": f}, data={"model": "document-parse"} ) request_id = r.json()["request_id"] # Poll for results import time while True: status = requests.get( f"https://api.upstage.ai/v1/document-digitization/requests/{request_id}", headers={"Authorization": f"Bearer {api_key}"} ).json() if status["status"] == "completed": break time.sleep(5) ``` ## LangChain Integration ```python from langchain_upstage import UpstageDocumentParseLoader loader = UpstageDocumentParseLoader( file_path="document.pdf", output_format="markdown", ocr="auto" ) docs = loader.load() ``` --- ## Environment Variable (Alternative) You can also set the API key as an environment variable: ```bash export UPSTAGE_API_KEY="your-api-key" ``` --- ## Tips - Use `mode=enhanced` for complex tables, charts, images - Use `mode=auto` to let API decide per page - Use async API for documents > 20 pages - Use `ocr=force` for scanned PDFs or images - `merge_multipage_tables=true` combines split tables (max 20 pages with enhanced mode) - Results from async API available for 30 days - Server-side timeout: 5 minutes per request (sync API) - Standard documents process in ~3 seconds
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