Vector Models and Indexes for Teacher Qualification Exams and Certification: Maintain Document Versions and Changes

Teacher Qualifications: review vector indexes for version tracking. Check source versions, input mappings and the values received by downstream nodes.

What this category's data looks like

Teacher qualification exams and certification involve written and interview registration forms, Mandarin proficiency certificates, medical examination forms, and other materials. Fields include name, ID number, exam subjects, score dates, certificate numbers, medical examination conclusions, and signatures. Material sources are exam institutions, certification institutions, and designated hospitals, and the update cadence changes with registration batches, certification announcements, and medical examination validity periods. When entering this function, the registration form serves as the main record providing identity and subject fields, while the Mandarin proficiency certificate and medical examination form serve as supporting materials providing levels, conclusions, and dates. Each generates a vector index, the original data is stored in the business database, and the index field records multiple vector identifiers for merging by identifier during retrieval.

Configuration and implementation checks

This step is executed by the indexing service and vector database, outputting vectors and index status (whether recall is possible and 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).

ObjectCheckVerification action
Written and interview registration formName, quantity, date, and signature must be consistent with the certification recordCheck the name, subject, date, and signature receipt in the registration form and certification record
Mandarin proficiency certificateLevel, number, and issue date must correspond to the registration formCheck whether the certificate level, number, and issue date match the registration form
Medical examination formMedical examination conclusion, date, and signature must match the certification batchCheck whether the medical examination conclusion, date, signature, and certification batch are consistent
Data row index fieldMultiple vector identifiers for one piece of data are all presentOpen a data row to check the index field, confirm the status is indexed, and view the rebuild task record

Three common errors

  • Symptom: The name and date for the same record do not match between the registration form and the medical examination form. Inspect the following: Materials are entered separately and not proofread against the same main record.
  • Symptom: The Mandarin proficiency certificate level has been updated, but the knowledge base still recalls the old version. Inspect the following: The version was not synchronized, and the index was not rebuilt when the material changed.
  • Symptom: The medical examination form lacks a signature or receipt, but retrieval still returns that entry. Inspect the following: The index only recognizes vectors and does not verify the completeness of signatures and receipts.

How to verify the setup

This function's acceptance check: sample a data row and look at the index field, confirm that multiple vector identifiers are all present and the status is indexed, then retrieve once to see whether the same group is merged; check defaultToken, maxToken, and the rebuild task record.

Business test: change one piece of content and see whether the version number and citations are updated synchronously; the number of citations is the array length, quoteMaxToken is the citation content budget, the two are not compared for equality, the citation upper limit checks the tokens of the citation text, and the array count is recorded separately.

  • In the knowledge base settings, check that the index model is consistent with the vector model actually used by the knowledge base. After changing the model, trigger a rebuild only for data that has already been indexed, and check the data range covered by the rebuild task.
  • Open a data row to check the index field, confirm that multiple vector identifiers for one piece of data are all present, that retrieval results have no duplicate entries, and that the data row has content and can be recalled.