deepset-ai/haystack · error · TypeError

Unsupported data source type: {type(source).__name__}

Error message

Unsupported data source type: {type(source).__name__}

What it means

FileTypeRouter.run accepts only str, Path, and ByteStream sources; any other type raises this TypeError identifying the offending type name.

Source

Thrown at haystack/components/routers/file_type_router.py:176

        for source, meta_dict in zip(sources, meta_list, strict=True):
            if isinstance(source, str):
                source = Path(source)

            if isinstance(source, Path):
                if not source.exists():
                    if self._raise_on_failure:
                        raise FileNotFoundError(f"File not found: {source}")
                    logger.warning("File not found: {source}. Skipping it.", source=source)
                    mime_types["failed"].append(source)
                    continue

                mime_type = _guess_mime_type(source)

            elif isinstance(source, ByteStream):
                mime_type = source.mime_type
            else:
                raise TypeError(f"Unsupported data source type: {type(source).__name__}")

            # If we have metadata, we convert the source to ByteStream and add the metadata
            if meta_dict:
                try:
                    source = get_bytestream_from_source(source)
                except Exception as e:
                    if self._raise_on_failure:
                        raise e
                    logger.warning("Could not read {source}. Skipping it. Error: {error}", source=source, error=e)
                    mime_types["failed"].append(source)
                    continue

                source.meta.update(meta_dict)

            matched = False
            if mime_type:
                # Try exact equality first so MIMEs containing regex metacharacters (e.g. the `+` in
                # `image/svg+xml`) match themselves before the regex fallback gets a chance to misread them.

View on GitHub (pinned to e318778c9b)

Solutions

1. Convert the source to a Path/str for file paths, or wrap bytes in ByteStream(data=..., mime_type=...)
2. Check the type reported in the message and adapt upstream code to yield supported types

Example fix

# before
router.run(sources=[b"raw pdf bytes"])
# after
from haystack.dataclasses import ByteStream
router.run(sources=[ByteStream(data=b"raw pdf bytes", mime_type="application/pdf")])

from haystack.dataclasses import ByteStream
from pathlib import Path
bad = [s for s in sources if not isinstance(s, (str, Path, ByteStream))]

def is_valid_source(source) -> bool:
    from haystack.dataclasses import ByteStream
    from pathlib import Path
    return isinstance(source, (str, Path, ByteStream))

try:
    result = router.run(sources=sources)
except TypeError as e:
    if "Unsupported data source type" in str(e):
        sources = [s if is_valid_source(s) else ByteStream(data=bytes(s)) for s in sources]
        result = router.run(sources=sources)
    else:
        raise

When it happens

Trigger: run(sources=[b'bytes']) or run(sources=[{'path': 'f.pdf'}]) — passing raw bytes, dicts, or other objects instead of str/Path/ByteStream.

Common situations: Confusing raw file contents with file paths; passing Document objects from other Haystack components instead of ByteStream; integrating with code that yields different source types.

Related errors

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• Invalid template for condition: {condition_value}
• Invalid template for output: {output!r} (type: {type(output)
• Invalid template for output: {output}

AI-assisted analysis of deepset-ai/haystack@e318778c9b (2026-08-30). Data as JSON: /api/errors/ff965a44eb41f837. Report an issue: GitHub.