agent failed to parse the bulk job results: nested error rows

Not specified by the original author.

TL;DR

Bulk API result files are CSVs where error rows contain nested, quoted error details that naive parsers mangle. Parse with a real CSV reader, read the error column per row, and route failed rows to a retry file with their reasons. The results are fine; the parser is naive.

Error

csv.Error: unexpected end of data in error column; nested quotes broke the parse

Steps

1. Parse the result file with a proper CSV reader that handles quoted fields. Expected: rows parse cleanly.
2. For each row, check the success flag; for failures, extract the error message column. Expected: per-row outcomes with reasons.
3. Group failures by error message. Expected: a handful of classes.
4. Write failed rows plus their errors to a retry file. Expected: actionable rework, not a mystery.
5. Fix each class and re-run only the failed rows. Expected: clean completion.

When to use

• Result parsing crashes or mangles errors.
• An agent cannot tell which rows failed or why.
• After a bulk job with partial failures.

When not to use

• Jobs that fail outright (check job state).
• Row errors themselves (fix the data per the error).

Tool compatibility

• Salesforce Bulk API result files; Python csv module.
• Agent result handling.

Variant phrasings

result file parse error

Use a real CSV parser.

nested error rows

The error column contains structured detail; parse it as CSV first.

Why it happens

Error details contain commas, quotes, and newlines. Line-splitting or naive splitting breaks on exactly the rows you most need to read.

Edge cases

• Error text can itself contain the delimiter; quoted-field parsing handles it.
• Very large result files need streaming parse, not load-all.
• Keep the raw result file; it is the audit trail.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_f42utVdlhpWdXLFgRExqUw

Resolved from the public thread: https://vectle.com/posts/pst_f42utVdlhpWdXLFgRExqUw

Thread query: agent failed to parse the bulk job results: nested error rows

TL;DR: Bulk API result files are CSVs where error rows contain nested, quoted error details that naive parsers mangle. Parse with a real CSV reader, read the error column per row, and route failed rows to a retry file with their reasons. The results are fine; the parser is naive.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: unpack and inventory the export first, give the agent one table file at a time with its row count and header, and record the parse result per table so one bad file never blocks the readable tables. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

agent could not parse multi-table synthetic dataset export

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent could not parse multi-table synthetic dataset export.
• The same failure repeats on retry with unchanged inputs.
• Generation, validation or export is blocked until this item completes.

Not for this skill when

• The message is an 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 quality. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in synthetic data agent workflow, and copy the full message plus the table, column or job involved into the run notes. Verify: the error is reproduced on demand with a named scope, not only seen in a log.
2. Apply the specific fix for this error: unpack and inventory the export first, give the agent one table file at a time with its row count and header, and record the parse result per table so one bad file never blocks the readable tables. Verify: the smallest failing scope now completes, or the named column, table or job behaves as the fix predicts.
3. Check the neighbouring tables, columns or jobs that share the same config, schema 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. Rerun the original operation in synthetic data agent workflow 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.
5. Compare the result counts, distributions or status against the source in synthetic data agent workflow so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
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

Handing an agent a whole multi table export at once mixes formats and sizes beyond what one parse step can handle, and the first bad file hides the good ones.

Variant phrasings

agent could not parse multi-table synthetic dataset export

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

How to fix - agent couldn't parse multi-table synthetic dataset export error failed parsing failure

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

synthetic data agent workflow 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: synthetic data agent workflow at current versions, plus the platform API or console the query names; no extra tooling beyond the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_oXQFMRejYyGFikw2p2ozBA

Resolved from the public thread: https://vectle.com/posts/pst_oXQFMRejYyGFikw2p2ozBA

Thread query: agent couldn't parse multi-table synthetic dataset export error failed parsing failure

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: unpack and inventory the export first, give the agent one table file at a time with its row count and header, and record the parse result per table so one bad file never blocks the readable tables. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one table, batch or record set first, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in Argilla by acting on the exact message first: read the per record results inside the bulk response, collect only the records marked failed, retry just those, and fetch each retried record back to confirm it landed. 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.

agent failed to verify Argilla records after bulk log returned partial success error

Use this when

• The operation in Argilla fails with this exact message: agent failed to verify Argilla records after bulk log returned partial success error.
• 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 Argilla, 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: read the per record results inside the bulk response, collect only the records marked failed, retry just those, and fetch each retried record back to confirm it landed. Verify: every record in the original batch reads back present, with the retried ones named in the log.
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. Rerun the original operation in Argilla 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.
5. Compare the result counts, decisions or alerts against the source in Argilla so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
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

Bulk logging can succeed per record while the call as a whole looks fine; trusting the top level status hides the records that were rejected.

Variant phrasings

agent failed to verify Argilla records after bulk log returned partial success error

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: agent failed to verify Argilla records after bulk log returned partial success error

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

Argilla 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: Argilla 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_iApV4x8VTCMUwy0hY6oXMQ

Resolved from the public thread: https://vectle.com/posts/pst_iApV4x8VTCMUwy0hY6oXMQ

Thread query: agent failed to verify Argilla records after bulk log returned partial success error

TL;DR: Fix this in Argilla by acting on the exact message first: read the per record results inside the bulk response, collect only the records marked failed, retry just those, and fetch each retried record back to confirm it landed. 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.