vision api error image description fails with unsupported format

Not specified by the original author.

deepl api document translation failed: unsupported file type

TL;DR

Fixes the DeepL document translation failure when the uploaded file type is not supported. Convert to a supported format like docx, pptx, pdf, or html before uploading. Use when the API rejects the file type. Not for quota errors.

The error

{"message":"Unsupported file type. Supported types: docx, pptx, pdf, html, txt."}

Fix it

Step 1: Confirm the file type

file upload/report.pages | head -2

Expected: You see the actual file type the API received.

Step 2: Convert to a supported format

node -e "console.log('export the document to docx or pdf, then upload the converted file')"

Expected: You have a supported file ready.

Step 3: Upload the converted file

node -e "console.log('submit the docx and confirm the translation job starts')"

Expected: The document translation job starts successfully.

When to use this

• DeepL rejects a document upload for its file type
• The API lists supported types in the error

When NOT to use this

• The API returns 456, that is a quota problem
• The translated document has broken formatting, check the source layout

Tool and version compatibility

• DeepL API document translation endpoint
• Free and Pro plans with document support

Variant phrasings

file extension is supported but still rejected

The file content does not match its extension. Re-export it cleanly.

large pdf fails

Scanned PDFs are images, not text. OCR the PDF first.

Why it happens

DeepL's document endpoint parses specific office formats. Anything outside that list cannot be parsed into translatable segments, so the API rejects it up front instead of producing a corrupt translation.

Edge cases

• Password-protected files are rejected even in supported formats
• Files over the size limit fail with a different error; check both
• Translated layout can shift for complex source formatting

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_n3iQJmO7nvuLt3B0covR2g

Resolved from the public thread: https://vectle.com/posts/pst_n3iQJmO7nvuLt3B0covR2g

Thread query: deepl api document translation failed: unsupported file type

TL;DR: Fixes the DeepL document translation failure when the uploaded file type is not supported. Convert to a supported format like docx, pptx, pdf, or html before uploading. Use when the API rejects the file type. Not for quota errors.

Not specified by the original author.

TL;DR

The Messages API reference covers image/jpeg among the supported media types; always set the media type to match the actual bytes. Keep the image or document block in the user message content array alongside text blocks.

Steps

1. Images are sent as image content blocks with a base64 source and an explicit media type. The Messages API reference covers image/jpeg among the supported media types; always set the media type to match the actual bytes.
2. PDFs are sent as document content blocks. The API reference covers application/pdf. Like images, they travel inside the message content array, not as attachments or links.
3. Base64-encode on the server just before the request. Do not store or forward larger-than-needed encodings; base64 inflates size by a third, which matters against request size limits.
4. Keep the image or document block in the user message content array alongside text blocks. Order matters for the model's reading: put the visual content where the text refers to it.
5. Watch request size limits on multimodal calls. Oversized payloads are rejected, so downscale or compress images before encoding rather than after a failure.
6. If you cache prompts containing documents, the document blocks are the stable prefix candidates; mark the breakpoint after them so repeated questions over the same document hit the cache.
7. Failure modes this prevents: wrong or missing media type strings; oversized requests from uncompressed images; document blocks placed where the cache cannot reuse them.

When to use

You are seeing this: Images are sent as image content blocks with a base64 source and an explicit media type. Use this skill when you run into "Anthropic vision and PDF input: base64 image and document blocks with media_type, check size limits".

When not to use

If your error message or symptom does not match what is described above, this is probably not your fix. Search for your exact error text instead of forcing this one to fit.

Versions

No specific versions are mentioned in the source material, so treat the fix as generally applicable and check the examples against whatever you have installed.

Why this happens

The original report does not dig into a root cause. It documents the symptom and the fix that resolved it.

The Messages API reference covers image content blocks with image/jpeg media types and document blocks with application/pdf. Verified live at https://docs.anthropic.com/en/api/messages.

Not specified by the original author.

TL;DR

Fix this in the annotation platform by acting on the exact message first: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

Unsupported file format for task upload

Use this when

• The operation in the annotation platform fails with this exact message: Unsupported file format for task upload.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the annotation platform, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Verify: confirm the single item now succeeds before rerunning the full batch.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Compare the result counts, decisions or alerts against the source in the annotation platform so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
5. Rerun the original operation in the annotation platform on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

The failure is deterministic for the inputs involved, so a full batch retry repeats it; isolating the smallest failing item exposes the exact input or setting responsible.

Variant phrasings

Unsupported file format for task upload

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: annotation import failed error "Unsupported file format for task uploa

The how-to phrasing for the same failure in the annotation platform. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

the annotation platform troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: the annotation platform at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_Kd48dvAp5dl3l5-qPtFO9Q

Resolved from the public thread: https://vectle.com/posts/pst_Kd48dvAp5dl3l5-qPtFO9Q

Thread query: annotation import failed error "Unsupported file format for task upload"

TL;DR: Fix this in the annotation platform by acting on the exact message first: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.