PDF Processing

End-to-end guide to PDF ingestion in FastRouter chat completions, including plugin config, request examples, and billing details.

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Introduction

FastRouter supports PDF understanding in chat completions by attaching PDFs to messages and enabling the file-parser plugin with the mistral-ocr engine.

This allows you to ask questions about PDFs (including scanned/image PDFs) using your chosen chat model—FastRouter will OCR/parse the document and provide the extracted text to the model.

Pricing: PDF OCR via mistral-ocr is billed at $2 / 1,000 pages, in addition to normal model token usage.

Note: If you’re using a model with native document understanding (e.g., openai/gpt-4.1), you can leverage the model’s built-in document processing — no plugin may be needed.

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Endpoint

POST https://api.fastrouter.ai/api/v1/chat/completions

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How PDF processing works

When you include a PDF in messages[].content[] and enable the plugin:

• FastRouter fetches/decodes the PDF (URL or base64)

• Runs mistral-ocr to extract text (works well on scanned pages and embedded images)

• Feeds the extracted content into the target model so it can answer your prompt

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Plugin configuration (required for OCR)

Enable PDF processing with the plugins parameter:

{
  "plugins": [
    {
      "id": "file-parser",
      "pdf": {
        "engine": "mistral-ocr"
      }
    }
  ]
}

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Sending PDFs in messages

Attach PDFs inside a message’s content array using type: "file":

{
  "type": "file",
  "file": {
    "filename": "document.pdf",
    "file_data": "https://example.com/document.pdf"
  }
}

Supported file_data formats

• Public URL (recommended): https://.../file.pdf

• Base64 data URL (for local/private docs): data:application/pdf;base64,JVBERi0xLjc...

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Example: PDF via public URL

cURL

curl https://api.fastrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $FASTROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-ai/glm-4.7",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Summarize this PDF in 5 bullets and list any key dates." },
          {
            "type": "file",
            "file": {
              "filename": "document.pdf",
              "file_data": "https://example.com/document.pdf"
            }
          }
        ]
      }
    ],
    "plugins": [
      {
        "id": "file-parser",
        "pdf": {
          "engine": "mistral-ocr"
        }
      }
    ]
  }'

Python

JavaScript

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Example: PDF via base64 (data URL)

Use base64 when the PDF is local or not publicly reachable.

cURL

curl https://api.fastrouter.ai/api/v1/chat/completions \
  -H "Authorization: Bearer $FASTROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-ai/glm-4.7",
    "messages": [
      {
        "role": "user",
        "content": [
          { "type": "text", "text": "Summarize this PDF in 5 bullets and list any key dates." },
          {
            "type": "file",
            "file": {
              "filename": "document.pdf",
              "file_data": "data:application/pdf;base64,..."
            }
          }
        ]
      }
    ],
    "plugins": [
      {
        "id": "file-parser",
        "pdf": {
          "engine": "mistral-ocr"
        }
      }
    ]
  }'

Python

Node.js

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Pricing

• mistral-ocr: $2 / 1,000 pages processed

• Model tokens: billed normally for the model you select

• Prefer URLs for large PDFs to avoid request size limits and base64 overhead.

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