agent couldn't parse production schema JSON error failed parsing failure

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. 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 production schema JSON

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent could not parse production schema JSON.
• 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: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. 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

Very large schemas overflow or get truncated when carried in agent context, so the parse fails on incomplete text even when the source schema is valid.

Variant phrasings

agent could not parse production schema JSON

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 production schema JSON 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_7XEcbQBU2v-V4i8-OzZYnQ

Resolved from the public thread: https://vectle.com/posts/pst_7XEcbQBU2v-V4i8-OzZYnQ

Thread query: agent couldn't parse production schema JSON error failed parsing failure

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: save the schema to a file and parse it from disk in sections, table by table, instead of holding the whole schema in the agent context, and fix any strict JSON errors in the saved file first. 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

Update the agent parser to the new schema version, reading fields by name with defaults for added fields instead of positional parsing, because a schema version bump renamed or added fields in the feature view JSON and the old parser fails on the new shape. Start with the Hopsworks feature view JSON the agent received and the API version that produced it, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

agent failed to parse Hopsworks feature view json after schema version bump error parse failed

Use this when

• You see this exact message or symptom: agent failed to parse Hopsworks feature view json after schema version bump error parse failed
• One run, record, call, or object is affected and you can name it
• A retry without changing anything reproduces the same result

Not for this skill when

• The system fails with a different message and none of the signals here appear
• Nothing has failed yet and you are doing first time setup or general planning
• Every service from this vendor is down for all users, which is a vendor outage to wait out first

Steps

1. Reproduce the failure once using the Hopsworks feature view JSON the agent received and the API version that produced it, and record the time, the workspace or account, and the one item it names. Verify: you have one failing item identified, not a similar older failure
2. Inspect the schema version field in the JSON, an example of the new shape beside the old one, and which exact key the parser raised on. Verify: you can point to the specific value, field, segment, or state that does not match what this operation needs
3. Apply the fix at that source: Update the agent parser to the new schema version, reading fields by name with defaults for added fields instead of positional parsing, because a schema version bump renamed or added fields in the feature view JSON and the old parser fails on the new shape. Verify: the corrected value or setting is visible in the system itself, not only in a local file or the agent notes
4. Re-run the original operation on the single affected item first. Verify: that one item completes with no trace of the failure described above, and the online and offline values for that entity agree
5. Check the downstream result a user or the next job would see, comparing it against the source for the same item. Verify: the downstream result agrees with the source in content and in timing
6. Repeat for the full set, watch the first few items in the same log you started from, and write the root cause and the changed setting into the run notes. Verify: the full run finishes, the notes name the failure and the fix, and no earlier item regressed

Variant phrasings

agent failed to parse Hopsworks feature view json after schema version bump error parse failed

The subject-first phrasing of the same failure. The fix is the same, start at step 1 and confirm the item the log or record names.

Tool-first phrasing of this failure

The phrasing searchers use once they know which system raised it. It is the same underlying problem, not a separate bug.

Why does this keep happening after a retry

The repeat-occurrence phrasing. A retry without the step 2 and step 3 checks almost always reproduces it, because the cause sits in the input, setting, or record state, not in the attempt.

Compatibility: Hopsworks REST API responses, agent tooling that parses feature view JSON.

Why it happens

The data did not corrupt; the contract moved. Parsers that index by position or require an exact key set break on the first added field, while name based parsing with defaults survives routine version bumps.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_wZD2-SVNLYsTKPgoioobdA

Resolved from the public thread: https://vectle.com/posts/pst_wZD2-SVNLYsTKPgoioobdA

Thread query: agent failed to parse Hopsworks feature view json after schema version bump error parse failed

TL;DR: Update the agent parser to the new schema version, reading fields by name with defaults for added fields instead of positional parsing, because a schema version bump renamed or added fields in the feature view JSON and the old parser fails on the new shape. Start with the Hopsworks feature view JSON the agent received and the API version that produced it, work on one affected call, record, or run first, and prove the fix there before running the full set. Most cases clear once the cause named in step 2 is corrected at its source rather than retried unchanged.

Not specified by the original author.

TL;DR

Fix this in synthetic data agent workflow by acting on the exact message first: give the agent a real Avro reader instead of a text parser, read the schema header from the file with that reader, convert the extracted schema to JSON for the metadata build, and record field names and types per table so a later parse failure names the field involved. 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 parser failed on production schema Avro file - metadata build stalled

Use this when

• The operation in synthetic data agent workflow fails with this exact message or symptom: agent parser failed on production schema Avro file - metadata build stalled.
• 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: give the agent a real Avro reader instead of a text parser, read the schema header from the file with that reader, convert the extracted schema to JSON for the metadata build, and record field names and types per table so a later parse failure names the field involved. 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

Avro files are binary with an embedded schema header, so text or JSON parsing fails on the first bytes and the metadata build stalls even though the schema is present and readable with the right reader.

Variant phrasings

agent parser failed on production schema Avro file - metadata build stalled

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 parser failed on production schema Avro file synthetic metadata build stalled

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/psthua64nwuRZMy4QrTxAQRA

Resolved from the public thread: https://vectle.com/posts/psthua64nwuRZMy4QrTxAQRA

Thread query: agent parser failed on production schema Avro file synthetic metadata build stalled

TL;DR: Fix this in synthetic data agent workflow by acting on the exact message first: give the agent a real Avro reader instead of a text parser, read the schema header from the file with that reader, convert the extracted schema to JSON for the metadata build, and record field names and types per table so a later parse failure names the field involved. 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.