mistral-ocr

📁 parlamento-ai/parlamento-ai 📅 Jan 29, 2026
39
总安装量
39
周安装量
#5275
全站排名
安装命令
npx skills add https://github.com/parlamento-ai/parlamento-ai --skill mistral-ocr

Agent 安装分布

claude-code 23
opencode 22
gemini-cli 16
codex 16
github-copilot 12
cursor 12

Skill 文档

Mistral OCR

Extract text from images and PDFs using Mistral’s dedicated OCR API. No external dependencies required.

Requirements

This skill requires a Mistral API key. If you don’t have one, follow the guide in reference/getting-started.md.

API Key

The user must provide their Mistral API key. Ask for it if not available.

Option 1 (Recommended for AI agents): User provides key directly in message:

"Use this Mistral key: aBc123XyZ..."
"Convert this PDF to markdown, my API key is aBc123XyZ..."

Option 2: Environment variable $MISTRAL_API_KEY

Option 3: Claude Code settings (~/.claude/settings.json)

If no key is available, guide the user to get one at console.mistral.ai.


API Endpoint

Use the dedicated OCR endpoint for all document processing:

POST https://api.mistral.ai/v1/ocr

Model: mistral-ocr-latest


Features

1. PDF → Markdown (Direct, no conversion needed!)

curl -s "https://api.mistral.ai/v1/ocr" \
  -H "Authorization: Bearer $MISTRAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-ocr-latest",
    "document": {
      "type": "document_url",
      "document_url": "https://example.com/document.pdf"
    }
  }'

2. Image → Text

Works with JPG, PNG, WEBP, GIF:

curl -s "https://api.mistral.ai/v1/ocr" \
  -H "Authorization: Bearer $MISTRAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-ocr-latest",
    "document": {
      "type": "image_url",
      "image_url": "https://example.com/image.jpg"
    }
  }'

3. Local Files (Base64 Data URL)

For local PDFs or images, encode as base64 and use a data URL.

ALWAYS use curl (works on all platforms including Windows via Git Bash):

# For local PDF
BASE64=$(base64 -w0 document.pdf)
curl -s "https://api.mistral.ai/v1/ocr" \
  -H "Authorization: Bearer $MISTRAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-ocr-latest",
    "document": {
      "type": "document_url",
      "document_url": "data:application/pdf;base64,'"$BASE64"'"
    }
  }'

# For local images (PNG, JPG, etc.)
BASE64=$(base64 -w0 image.png)
curl -s "https://api.mistral.ai/v1/ocr" \
  -H "Authorization: Bearer $MISTRAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistral-ocr-latest",
    "document": {
      "type": "image_url",
      "image_url": "data:image/png;base64,'"$BASE64"'"
    }
  }'

MIME types:

  • PDF: data:application/pdf;base64,...
  • PNG: data:image/png;base64,...
  • JPG: data:image/jpeg;base64,...
  • WEBP: data:image/webp;base64,...

4. Structured JSON Output

For invoices, forms, tables – ask for JSON in a follow-up or use Document AI annotations.


Response Format

The API returns markdown directly:

{
  "pages": [
    {
      "index": 0,
      "markdown": "# Document Title\n\nExtracted content here...",
      "images": [],
      "tables": [],
      "dimensions": {"dpi": 200, "height": 842, "width": 595}
    }
  ],
  "model": "mistral-ocr-latest",
  "usage_info": {"pages_processed": 1, "doc_size_bytes": 12345}
}

Workflow

User requests OCR from image or PDF

  1. Get API key – Ask user if not in environment
  2. Determine input type (URL or local file)
  3. For local files, ALWAYS use temp file approach (avoids “Argument list too long” error):
# Cross-platform temp directory
TMPDIR="${TMPDIR:-${TEMP:-/tmp}}"

# Step 1: Encode file to base64
base64 -w0 "document.pdf" > "$TMPDIR/b64.txt"

# Step 2: Create JSON request file
echo '{"model":"mistral-ocr-latest","document":{"type":"document_url","document_url":"data:application/pdf;base64,'$(cat "$TMPDIR/b64.txt")'"}}' > "$TMPDIR/request.json"

# Step 3: Call API with -d @file (use actual key, not variable)
curl -s "https://api.mistral.ai/v1/ocr" \
  -H "Authorization: Bearer YOUR_API_KEY_HERE" \
  -H "Content-Type: application/json" \
  -d @"$TMPDIR/request.json" > "$TMPDIR/response.json"

# Step 4: Extract markdown with node (NOT jq - not available on all systems)
node -e "const fs=require('fs'); const r=JSON.parse(fs.readFileSync('$TMPDIR/response.json')); console.log(r.pages.map(p=>p.markdown).join('\n\n---\n\n'))"
  1. Save to .md file using Write tool
  2. Confirm file location to user

IMPORTANT: Cross-Platform Compatibility

  • ALWAYS use curl (works on Windows via Git Bash)
  • ALWAYS use -d @file for request body (handles large files)
  • NEVER use jq – use node instead to parse JSON
  • Use ${TMPDIR:-${TEMP:-/tmp}} for temp files (works on all systems)
  • Copy response.json to user directory before parsing with node on Windows

Usage Examples

When the user says:

User Request Action
“Convert this PDF to markdown” OCR the PDF, save as .md file
“Extract text from this image” OCR the image, return text
“Give me a .md of this document” OCR and save as .md file
“What does this PDF say?” OCR and summarize content
“OCR this receipt” Extract text, optionally structure as JSON

Error Handling

Error Cause Solution
401 Unauthorized Invalid API key Verify key, guide to getting-started.md
400 Bad Request Invalid document Check format and URL accessibility
3310 File fetch error URL not accessible Use base64 for local files
Rate limit Too many requests Wait and retry

Supported Formats

Format Support
PDF ✅ Direct (no conversion)
PNG ✅ Direct
JPG/JPEG ✅ Direct
WEBP ✅ Direct
GIF ✅ Direct

No external dependencies required! Unlike other OCR solutions, Mistral OCR handles PDFs directly without needing pdftoppm, ImageMagick, or any other tools.


Pricing

As of 2025, Mistral OCR pricing:

  • $2 per 1,000 pages
  • 50% discount with Batch API

Check current rates at mistral.ai/pricing


References


Skill by Parlamento AI