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Write results to your S3 bucket. For each input, we write a markdown file and an images/ folder of screenshots. The markdown references images by filename.

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Discriminant

  • type: "bucket"

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Minimal config

{
  "output": {
    "type": "bucket",
    "bucket_name": "example-output-bucket",
    "prefix": "processed/"
  }
}
Field reference
  • bucket_name (string): Destination bucket.
  • prefix (string): Folder prefix under which results are written.
Delivery details For each input identifier, the response includes:
  • images (object): Map of image ids to { bucket, key } pointers.
  • markdown_delivery (object): { bucket, key } pointer for the markdown file.
Example delivery (truncated) 
{
  "s3://my-docs-bucket/docs/file.pdf": {
    "images": {
      "001": { "bucket": "example-output-bucket", "key": "processed/abc/001.png" }
    },
    "markdown_delivery": { "bucket": "example-output-bucket", "key": "processed/abc/file.md" }
  }
}

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Going deeper

  • For programmatic consumption, use the bucket and key from each pointer to construct full S3 URLs.
  • When checking job status, you can exclude inline markdown to reduce payload size using the SDK:
    • TypeScript: client.getJobStatus(jobId, { excludeMarkdown: true })
    • Python: client.get_job_status(job_id, exclude_markdown=True)