What this category's data looks like
In the off-campus training compliance filing and penalty response scenario, materials revolve around three axes: school operating licenses, course filing materials, and fee disclosure. Sources are mostly receipts from education administrative departments, internal institutional approval documents, and disclosure archives. The update cadence is driven by license renewal, course adjustments, and fee changes, and field characteristics center on names, quantities, dates, and signature fields. School operating licenses provide subject qualification and validity period, course filing materials provide course names, class hours, and instructors, and fee disclosures provide items, standards, and disclosure dates. When the three types of materials enter the knowledge base, each plays a different role: licenses are used for subject verification, course filings for content comparison, and fee disclosures for checking external messaging. The vector model and indexing step are only responsible for converting the segmented text of materials into a recallable state; they do not generate ledgers. Ledgers are completed by subsequent nodes or manual organization.
Configuration and implementation checks
This step is executed by the indexing service and vector database, outputting vectors and index status (whether recall is possible, whether data in the same group is merged). The "version ledger and change records" are then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials).
| Object | Check | Verification action |
|---|---|---|
| School operating license | Verify whether the subject name, validity period, issuance date, and signature field are consistent with the filing records | Check the indexing model in the knowledge base settings; open a data row to check the index field, confirm that multiple vector identifiers are present, and check whether the status is indexed |
| Course filing materials | Verify whether the course name, number of class hours, instructors, and filing date correspond between the two materials | Search the same course keyword and see whether data in the same group is merged; if duplicate entries appear, trace back to the data row index field and rebuild task records |
| Fee disclosure | Verify whether the fee items, standards, disclosure date, and receipt signature are complete | After changing the model, trigger rebuild only for data that has already been indexed, check the data scope covered by the rebuild task, and verify whether the defaultToken and maxToken budgets are sufficient |
| Version ledger | Verify that the current version is unique, old versions are traceable, and citations are synchronized | After changing one piece of content, search the citations and confirm that the version number and citations are updated in sync; record the citation count separately and do not compare it for equality with its text tokens |
Three common errors
- Symptom: the name, quantity, and date of the same record do not match between the two materials. Inspect the following: the school operating license and course filing materials were entered separately, fields were not aligned, and versions were not synchronized.
- Symptom: duplicate entries appear in search results. Inspect the following: compare the relevant source fields, document versions and downstream processing records.
- Symptom: the fee disclosure lacks a signature or receipt, yet retrieval still hits it. Inspect the following: indexing only reflects the text recallable state; a missing signature field is a matter of material completeness and must be manually rechecked in the ledger.
How to verify the setup
Acceptance for this feature: sample one data row and check the index field to confirm that multiple vector identifiers are present; then search once more to see whether data in the same group is merged and whether the highest score is taken.
Business test: change one piece of content and see whether the version number and citations are updated in sync; record the citation count separately and check whether the cited text tokens exceed the budget.
- Check in the knowledge base settings that the indexing model is consistent with the vector model actually used by the knowledge base; open a data row to check the index field and confirm that the status is indexed.
- Check the rebuild task records to confirm that after changing the model, rebuild is triggered only for data that has already been indexed, and verify
limit, and the citation count records.