Skills Guide

Convertisseur de documents Datalab

Convertissez des documents (PDF, EPUB, PPTX, DOCX, XLSX, HTML, images) en Markdown via l'API cloud Datalab. Idéal pour un traitement basé sur le cloud avec options OCR et LLM.

Spar Skills Guide Bot
Data & IAIntermédiaire
15009/03/2026
Claude CodeCursorCopilot
#document-conversion#api-integration#markdown#ocr#cloud-processing

name: datalab description: Convert documents (PDF, EPUB, PPTX, DOCX, XLSX, HTML, images) to Markdown using Datalab cloud API. Use when user wants to use Datalab API for document conversion, or prefers cloud-based processing over local marker CLI.

Datalab Document Converter

Convert PDF, EPUB, PPTX, DOCX, XLSX, HTML, and image files to Markdown using the Datalab cloud API.

Prerequisites

# Install Datalab Python SDK
uv pip install datalab-python-sdk

# Set API key (get from https://www.datalab.to)
export DATALAB_API_KEY="your_api_key_here"

Python SDK Usage

Basic Conversion

from datalab_sdk import DatalabClient

client = DatalabClient()  # Uses DATALAB_API_KEY env var

# Convert document to markdown
result = client.convert("document.pdf")
print(result.markdown)

# Save output
result = client.convert(
    "document.pdf",
    save_output="./output/document"
)
# Creates: output/document.md, output/document_meta.json, output/*.png

With Options

from datalab_sdk import DatalabClient, ConvertOptions

client = DatalabClient()

options = ConvertOptions(
    output_format="markdown",  # markdown, json, html, chunks
    force_ocr=False,           # Force OCR on all pages
    paginate=True,             # Add page separators
    use_llm=True,              # Use LLM for better accuracy
    disable_image_extraction=True,  # Plain text only
    page_range="0,5-10,20"     # Specific pages
)

result = client.convert("document.pdf", options=options)

Async Client (Better Performance)

import asyncio
from datalab_sdk import AsyncDatalabClient, ConvertOptions

async def convert_document():
    async with AsyncDatalabClient() as client:
        result = await client.convert(
            "document.pdf",
            options=ConvertOptions(output_format="markdown")
        )
        return result.markdown

markdown = asyncio.run(convert_document())
print(markdown)

OCR Only

from datalab_sdk import DatalabClient

client = DatalabClient()

# OCR a document
ocr_result = client.ocr("document.pdf")
print(ocr_result.pages)  # Get all text

REST API Usage

Submit Document for Conversion

import requests

url = "https://www.datalab.to/api/v1/marker"
headers = {"X-API-Key": "YOUR_API_KEY"}

with open("document.pdf", "rb") as f:
    files = {"file": ("document.pdf", f, "application/pdf")}
    data = {
        "output_format": (None, "markdown"),
        "force_ocr": (None, "false"),
        "use_llm": (None, "false"),
        "disable_image_extraction": (None, "true")
    }
    response = requests.post(url, headers=headers, files=files, data=data)

result = response.json()
print(f"Request ID: {result['request_id']}")
print(f"Check URL: {result['request_check_url']}")

Poll for Results

import requests
import time

check_url = result['request_check_url']
headers = {"X-API-Key": "YOUR_API_KEY"}

while True:
    response = requests.get(check_url, headers=headers)
    status = response.json()

    if status.get('status') == 'complete':
        print(status['markdown'])
        break
    elif status.get('status') == 'failed':
        print(f"Error: {status.get('error')}")
        break

    time.sleep(2)  # Poll every 2 seconds

Using curl

# Submit document
curl -X POST "https://www.datalab.to/api/v1/marker" \
  -H "X-API-Key: $DATALAB_API_KEY" \
  -F "file=@document.pdf" \
  -F "output_format=markdown" \
  -F "disable_image_extraction=true"

# Check status
curl "https://www.datalab.to/api/v1/marker/{request_id}" \
  -H "X-API-Key: $DATALAB_API_KEY"

API Options

| Parameter | Type | Description | | -------------------------- | ------- | ------------------------------------ | | output_format | string | markdown, json, html, chunks | | force_ocr | boolean | Force OCR on all pages | | paginate | boolean | Add page separators | | use_llm | boolean | Use LLM for better accuracy | | strip_existing_ocr | boolean | Remove existing OCR and re-process | | disable_image_extraction | boolean | Plain text only | | page_range | string | Specific pages, e.g., "0,5-10,20" | | max_pages | integer | Maximum pages to convert |

Batch Processing

import asyncio
from pathlib import Path
from datalab_sdk import AsyncDatalabClient, ConvertOptions

async def batch_convert(files: list[Path], output_dir: Path):
    output_dir.mkdir(parents=True, exist_ok=True)

    options = ConvertOptions(
        output_format="markdown",
        disable_image_extraction=True
    )

    async with AsyncDatalabClient() as client:
        tasks = [
            client.convert(
                file_path=f,
                options=options,
                save_output=output_dir / f.stem
            )
            for f in files
        ]
        results = await asyncio.gather(*tasks, return_exceptions=True)

    for f, result in zip(files, results):
        if isinstance(result, Exception):
            print(f"✗ {f.name}: {result}")
        elif result.success:
            print(f"✓ {f.name}: {result.page_count} pages")
        else:
            print(f"✗ {f.name}: {result.error}")

# Usage
files = list(Path("documents").glob("*.pdf"))
asyncio.run(batch_convert(files, Path("output")))

Error Handling

from datalab_sdk import (
    DatalabClient,
    DatalabAPIError,
    DatalabTimeoutError,
    DatalabFileError
)

client = DatalabClient()

try:
    result = client.convert("document.pdf", max_polls=60, poll_interval=2)

    if result.success:
        print(result.markdown)
    else:
        print(f"Conversion failed: {result.error}")

except DatalabAPIError as e:
    if e.status_code == 401:
        print("Authentication failed - check API key")
    elif e.status_code == 429:
        print("Rate limit exceeded - wait before retrying")
    else:
        print(f"API Error: {e}")

except DatalabTimeoutError:
    print("Operation timed out - try increasing max_polls")

except DatalabFileError as e:
    print(f"File error: {e}")

Datalab vs Marker CLI

| Feature | Datalab API | Marker CLI | | ------------ | ------------------ | ------------------- | | Processing | Cloud-based | Local | | GPU Required | No | Yes (recommended) | | Setup | API key only | Python + PyTorch | | Speed | Fast (cloud GPU) | Depends on hardware | | Privacy | Data sent to cloud | Local processing | | Cost | API credits | Free |

Instructions

  1. Confirm the input file path exists

  2. Check if $DATALAB_API_KEY environment variable is set

  3. Use AskUserQuestion tool to ask user preferences:

    Question 1 - Processing Method:

    • Header: "Method"
    • Question: "使用哪种方式调用 Datalab API？"
    • Options:
      • "Python SDK (Recommended)": 使用 datalab-python-sdk，更简洁
      • "REST API": 使用 requests 直接调用 API
      • "curl": 使用命令行 curl

    Question 2 - Image Extraction:

    • Header: "Images"
    • Question: "是否需要提取文档中的图片？"
    • Options:
      • "No (Recommended)": 仅提取文本，生成纯 Markdown
      • "Yes": 提取图片并保存

  4. Generate and run the appropriate code based on user's choice

  5. Report the output file location and any extraction notes

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