What this category's data looks like
Training institution course scheduling and course consumption scenarios involve materials including timetables, course consumption records, course change applications, signed receipts, and multilingual reference drafts. The course name, number of class hours, date, and signature status of the same lesson are often scattered across different versions, and multilingual materials further introduce differences in translated names and terminology. After materials enter the vector model and indexing stage, timetables and course consumption records are stored as raw data rows in the business database, multilingual reference drafts and terminology glossaries are used as text to be retrieved to generate vectors, and signed receipts participate in recall as attachments or descriptions in the index. The update rhythm changes with course changes, supplementary signatures, and translation revisions. The field characteristics are course number, date, class hours, signature status, translated name, and version number. It is necessary to ensure that the same terminology is consistent throughout the entire text and that translated names can refer back to the original text.
Configuration and implementation checks
This stage is executed by the indexing service and the vector database, outputting vectors and index status (whether recall is possible, whether data in the same group is merged). "Unified terminology glossary and reference drafts" is then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials). Vectors are stored in the vector database, raw data is stored in data tables in the business database, and index fields record the corresponding multiple vector identifiers; retrieval first recalls vectors, then merges back to the raw data by identifier, and for the same group of data the highest score is taken.
| Object | Check | Verification action |
|---|---|---|
| Timetable | The course number, date, class hours, signature status, and translated name are consistent across versions and can refer back to the original text | Open a timetable data row and check the index field to confirm that multiple vector identifiers are all present; retrieve that course number and see whether data in the same group is merged |
| Course consumption record | The name, quantity, and date of the same lesson match in the two materials; missing signatures or receipts must be marked | Check whether the fields of the course consumption record and the timetable are consistent; view the data range covered by the rebuild task and confirm whether data that has already been indexed after a model change has been rebuilt |
| Course change application | The date, class hours, and signed receipt after the course change are synchronized to the timetable and course consumption record, and the version number is consistent | Compare the date and signature of the course change application with the timetable and course consumption record; sample three terms and check whether their spelling is consistent throughout the entire text |
| Index model | Consistent with the vector model actually used by the knowledge base, with status indexed or a rebuild task record | Check the index model in the knowledge base settings; view the rebuild task record and confirm that after a model change, only data that has already been indexed is triggered |
Three common errors
- Symptom: The name, quantity, and date of the same lesson do not match between the timetable and the course consumption record. Inspect the following: Multilingual materials and terminology are not unified, raw data rows are not merged by the same course number.
- Symptom: The course change application has been updated, but the timetable and course consumption record are still the old version. Inspect the following: The version is not synchronized.
- Symptom: The course consumption record lacks a signature or receipt, and duplicate entries appear in retrieval results. Inspect the following: Multiple vector identifiers corresponding to the same group of data are not merged, and signed receipts do not participate in recall as index fields.
How to verify the setup
This feature acceptance: sample one data row and look at the index field to confirm that multiple vector identifiers are all present; then retrieve once and see whether data in the same group is merged and whether the highest score is taken.
Business test: sample three terms and check whether their spelling is consistent throughout the entire text, and whether translated names can refer back to the original text; check the number of citations and the quoteMaxToken budget, the tokens of the cited text are recorded separately, and array lengths are not compared for equality.
- Open a data row and check the index field to confirm that vector identifiers are complete under the
defaultTokenandmaxTokensettings, and that the status is indexed or a rebuild task record. - View the data range covered by the rebuild task; after a model change, only data that has already been indexed is triggered; sample three terms and check whether their spelling is consistent throughout the entire text.