What this category's data looks like
Data for this category comes from the national student funding management information system, school student status system, civil affairs minimum living security and special assistance datasets, and fiscal payment systems. Updates occur once per semester. Daily processed documents include family economic hardship assessment forms, aid application forms, scholarship and grant review forms, disbursement lists, and public notice materials. Document fields include recipient student identity information, hardship assessment level, aid amount, bank card number, and other details. The core covers full process records for subsidy eligibility and fund disbursement.
What constraints these characteristics impose on model access and configuration
Cross-system data sources require model access to support cross-data source field matching verification. Semester-level batch updates require adaptation to large-capacity context processing capabilities. Documents contain sensitive identity and fund information, so output scope must be strictly restricted to prevent data leaks. The verification process relies on cross-system data such as student status and minimum living security records, so precise tool call rules must be configured. Fixed format requirements for disbursement lists and public notice materials require limiting the model's output typesetting and ensuring content completeness.
How to set the configuration
Reference configuration items for FastGPT v4.17.0 are listed below:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Must accommodate cross-system student aid-related documents to avoid context overflow and content loss |
maxTokens | 2000–3000 token | Must fully output review results, disbursement lists, and other content to prevent output truncation |
quoteMaxToken | 500 token | Must accurately reference key fields from assessment forms and public notice materials to avoid redundant content interfering with review judgments |
toolChoice | auto | Must automatically call verification tools for multiple data sources to adapt to dynamic cross-system data verification needs |
temperature | 0.1–0.3 | Must ensure consistency of aid review results to avoid subjective bias affecting eligibility determination |
AIPROXY_API_TOKEN | Bind a dedicated service key | Must ensure identity verification security for interface calls to prevent unauthorized access |
Three common mistakes
- Symptom: Model outputs streaming segmented content that cannot be directly embedded into fixed-format public notice materials. Cause: Non-streaming output mode is not configured, resulting in segmented result returns.
- Symptom: Markdown disbursement list tables generated by the model are truncated, with
...[hide 38432 chardisplayed at the end. Cause:maxTokensvalue is too low, failing to reserve sufficient output space for complete list and remark information. - Symptom: Tool calls fail during cross-system data verification, returning empty results. Cause:
toolChoiceis configured for fixed call mode, failing to adapt to dynamic verification needs for multiple data sources.
How to confirm proper configuration
- Submit batch-tested family economic hardship assessment form data, check the match between the model's hardship level determination results and original document fields, and adjust relevant parameters to meet business requirements.
- Generate a Markdown document containing a complete disbursement list, verify that content is not truncated, and adjust the
maxTokensvalue to ensure full content output. - Call the interface to test the output mode, confirm that a single request returns a complete review result with no segmented returns.
- Verify automatic recall of cross-data source fields, confirm that the model can correctly associate student identity information from the student status system and civil affairs system.
The values provided are common starting points and should be evaluated against the reader's own samples.
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.