What the data for this category looks like
This category's data primarily comes from the national student financial aid management information system, school student registration system, civil affairs low-income and extremely impoverished household data, and financial payment system. Daily documents include family economic hardship certification forms, financial aid application forms, scholarship and grant review forms, disbursement lists, and public notification materials. Data is updated per semester. Core fields cover family economic status descriptions, student registration IDs, financial aid application categories, disbursement amounts, and receiving bank card information. Each document covers the full chain of application qualification verification, review processes, and fund disbursement.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Reference only; verify against the target FastGPT release and deployment documentation.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Covers the total length of a single semester’s policy documents and typical application materials, to avoid truncating critical verification information |
chatId | Bind to the current semester business batch ID | Isolates dialogue contexts across different batches, to prevent cross-cycle data mixing |
variables | Pre-set "current semester", "business entity", "application category" | Limits retrieval scope, reduces recall of unrelated policies and historical data |
| Maximum multi-turn dialogue rounds | 5–7 rounds | Matches the typical verification process for student financial aid review, to avoid context overflow from overly long dialogues |
| Number of single-prompt recall entries | Top 10–15 entries | Adapts to the professional term matching accuracy of policy documents, balances recall accuracy and recall volume |
Three common mistakes
- Phenomenon: Some dialogues return empty results when concurrent call volume is high. Cause: The system fails to bind independent session contexts via
chatId, leading to overwriting of thevariablesparameter for multiple concurrent requests and disorganized retrieval scopes. - Phenomenon: Variable results in dialogue outputs show content overlap, with previous round’s replies mixed into the current round. Cause: Session history isolation for
messagesis not properly configured, and expired dialogue context cache is not cleared. - Phenomenon: Input guidance and a thesaurus are configured, but expected guidance questions do not appear in the dialogue interface. Cause: Multi-turn dialogue’s pre-prompt loading is not enabled, or the thesaurus matching threshold is set too high, leading to failure to recall guidance content.
How to confirm correct configuration
- Submit a single test application, check that the dialogue context only includes current semester policies and business data, with no expired content.
- Send concurrent test requests, verify that sessions with different
chatIddo not interfere with each other, and variable results do not overlap. - Enable input guidance configuration, confirm that the preset guidance questions load in the interface, and thesaurus matching results meet expectations.
- View system logs, confirm that the
messagesparameter for multi-turn dialogue fully records session history, with no truncation or loss.
The values provided here are common starting points, and should be evaluated against local deployment 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.