What the data for this category looks like
Data for this category comes from formal internal expense management documents of central state-owned enterprises and public sector in China. This includes general reimbursement policies, special category rules, and temporary supplementary provisions. Update frequency follows policy adjustments or annual system revisions. Full rule entries are updated in a single batch. Documents are primarily structured clauses, with fields such as applicable positions, reimbursement categories, amount limits, voucher requirements, and approval nodes. Units mostly use standardized financial measurement units including yuan, workdays, and person-times.
Constraints imposed on vector models and indexing
The structured clause property of this category requires chunking to retain the complete semantic boundary of a single rule. Do not split content across core clauses, as this will cause semantic breaks during retrieval. The fixed-cycle update schedule of this category is compatible with scheduled full-update mode, which reduces computing resource consumption. The multi-field financial professional attributes require the vector model to support financial term embeddings. This ensures that semantic associations for information such as amount limits and approval nodes are correctly captured. Exclusive rules for different departments must be associated with indexes via metadata fields. This avoids retrieval result deviations caused by confusion of cross-department rules.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Single clause length for reimbursement rules mostly ranges from 500-1000 characters. This retains complete semantics and avoids in-block redundancy |
| Chunk Overlap Length | 100–200 characters | Covers associated information at the start and end of cross-chunk clauses, avoiding semantic fragmentation |
| Similarity Threshold | 0.72–0.85, calibrated via actual testing | Filters low-match irrelevant rules while retaining retrieval results for cross-category similar rules |
| Single Search Limit | Top 8 entries | Retrieval results for reimbursement rules do not need to be excessive. 8 entries cover rule entries for common reimbursement scenarios |
maxToken | 8192 | Adapts to the context window limit of Meta/Llama-3.1-8B-instruct model, ensuring retrieval results can be fully included in conversations |
defaultToken | 2048 | Balances the length of retrieval results and the fluency of conversation responses, meeting information needs for regular reimbursement inquiries |
Three Common Mistakes
- Phenomenon: Vector index construction progress shows no movement, and index status remains unchanged for a long time on the interface. Cause: Chunk parameters are not adjusted for the long clauses of reimbursement rules. Incomplete in-block semantics cause model embedding failures, which triggers index construction interruption.
- Phenomenon: Returned reimbursement rules in retrieval are completely unrelated to user queries. Cause: Similarity threshold is set too low, causing low-match irrelevant rules to be included in retrieval results, or metadata is not associated with department rules leading to incorrect recall of cross-department rules.
- Phenomenon: A quick error with a timeout prompt returns after index construction is triggered. Cause: Scheduled full-update mode adapted to this category is not used. Attempting to index full reimbursement rule documents at one time exceeds the time limit of a single system calculation.
How to Confirm Configuration is Correct
- Upload a single complete reimbursement rule document, perform manual indexing, and check if chunk previews retain complete clause semantics without cross-clause splitting.
- Input a simulated reimbursement inquiry question, initiate retrieval, verify whether the matching degree of returned results conforms to preset logic, and adjust parameters until requirements are met.
- Trigger a scheduled indexing task, wait for the task to complete, and check the index update log to confirm there are no abnormal errors or progress stagnation.
- Test retrieval of reimbursement rules for different departments, confirm that only rules for the corresponding department are recalled, and the metadata filtering function works normally.
Note: The configuration values listed above are common starting points. Adjust them based on your own specific samples and use cases.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.