What this category's data looks like
This category's data involves three types of materials for the formulation of talent cultivation programs in vocational colleges: talent cultivation programs, curriculum standards, and job competency analysis tables. The sources are the academic affairs office, secondary colleges, and professional teaching and research offices, and the update cadence advances with professional research, semester revisions, and signed receipts. Talent cultivation programs provide the major name, program length, cultivation objectives, and course structure; curriculum standards provide the course name, class hours and credits, assessment methods, and implementation date; job competency analysis tables provide the job name, competency items, quantity, and signature column. When the materials enter the vector model and indexing function, each plays a different role: talent cultivation programs and curriculum standards serve as text index sources, while job competency analysis tables can simultaneously produce text indexes and image description indexes. Field characteristics are concentrated in names, quantities, dates, and signatures, and version numbers and reference relationships need to be maintained in sync to avoid the same record failing to match across two materials.
Configuration and implementation checks
The indexing service and vector database only output vectors and index status (whether recall is possible, whether data in the same group is merged). The version ledger and change records must be handled next by subsequent AI nodes, code nodes, or manual work (retrieval and reference trimming only take supporting materials). Vectors are stored in the vector database, while the original data is stored in data tables in the business database, with index fields recording the corresponding multiple vector identifiers; retrieval first recalls vectors, then merges back to the original data by identifier, taking the highest score for the same group of data.
| Object | Check | Verification action |
|---|---|---|
| Index model | Consistent with the vector model actually used by the knowledge base; recall quality should not decline after changing models | Check the index model in the knowledge base settings, and view the data scope covered by the rebuild task |
| Index field of the data row | All multiple vector identifiers of one data row are present, and data in the same group can be merged during retrieval | Open a data row and check the index field, confirm the status is indexed and the rebuild task record is complete |
| Talent cultivation programs and curriculum standards | Names, quantities, dates, and signatures are consistent between the two types of materials, and the current version is unique | Compare the fields and signature columns of the two materials, and check whether the version number and references are in sync |
| Job competency analysis tables | Job names, competency item quantities, and dates are consistent with the program and curriculum standard definitions | Check the names, quantities, dates, and signed receipts of the analysis table against the program and curriculum standards |
Three common errors
- Symptom: duplicate entries appear in retrieval results. Inspect the following: multiple vector identifiers for the same group of data are not merged, or reference trimming related to
defaultTokenandmaxTokenis not recorded separately by array item count. - Symptom: the name, quantity, and date of the same record do not match across two materials. Inspect the following: versions are not synchronized, old-version materials are still referenced, and signatures or receipts are missing.
- Symptom: recall quality declines after changing models. Inspect the following: rebuilding is triggered only for data that has already been indexed and does not cover all data rows, causing some content to be unretrievable.
How to verify the setup
Acceptance for this feature: sample one data row and inspect the index field to confirm that multiple vector identifiers are present and the status is indexed; then run retrieval once to see whether the same group is merged, and check the coverage scope of the rebuild task record.
Business test: change one piece of content and see whether the version number and references are updated in sync; check the tokens of the reference text under the limit budgets, with array item counts recorded separately.
- Check the index model in the knowledge base settings, view the data scope covered by the rebuild task record, and confirm that after changing models, rebuilding is triggered only for data that has already been indexed.
- Open the data row and check the index field and the status value indexed, and verify whether the names, quantities, dates, and signatures of the talent cultivation programs, curriculum standards, and job competency analysis tables are consistent.