What the Data for This Category Looks Like
The data for this category mainly comes from the unified budget management system, department staff establishment system, prior-year final accounts, project repository, and the Ministry of Finance's annual budget formulation notice. The update frequency is annual. Daily processed documents include department budget drafts, project application letters, performance target forms, personnel expense calculation forms, budget approvals, and similar items. Document fields cover project codes, expense amounts, staff establishment numbers, performance indicators, and similar items. Common units are ten thousand yuan, persons, items, and similar units. The data structure is relatively fixed, but individual document volumes are large.
Constraints on Model Access and Configuration
Annual updated data sources require that model access adapts to batch historical data import logic, and frequent real-time incremental synchronization should be avoided. The scenario of mixing multiple types of structured documents requires configuration to support multi-format parsing adaptation, covering different document types such as budget drafts and application letters. Data sources involve internal interfaces of fiscal systems, so access permissions must be strictly limited to ensure data security. The large volume of budget data processed in a single run has clear requirements for context window capacity. Budget formulation has rigid time nodes, so model call stability must be ensured to avoid timeouts that affect the overall process.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the batch context length of annual budget documents, avoiding truncation of key data such as core expenses and establishment numbers |
maxTokens | 4000 token | Controls the output length of single-round budget analysis, ensuring that the review process can fully view calculation and review results |
temperature | 0.3–0.5 | Maintains the rigor of budget calculations, avoiding generated results that do not comply with fiscal regulations such as floating values or non-standardized outcomes |
AIPROXY_API_ENDPOINT | Exclusive internally deployed interface address | Adapts to the internal network restrictions of fiscal systems, ensuring that data transmission does not exceed authorized scope |
AIPROXY_API_TOKEN | Bound to department-specific permission tokens | Limits access scope, complies with the permission control requirements of fiscal systems, and prevents unauthorized access |
quoteMaxToken | 1500 token | Restricts the length of single content referenced by the knowledge base, adapting to the field specifications and review requirements of budget documents |
Three Common Misconfigurations
- Symptom: No abnormal entries referenced from the knowledge base are returned after running the workflow, only general conclusions are generated. Cause: The model's verification logic for referenced content is not configured, and the dedicated knowledge base source related to budget formulation is not bound.
- Symptom: A browser version restriction error is returned when calling the model, and requests cannot be initiated normally. Cause: The adapted browser environment is not specified, or the interface does not open public access permissions, only allowing access from internally designated terminals.
- Symptom: An error is reported when calling the locally deployed model, prompting that the model UID is invalid. Cause: The general large model type required for the budget formulation scenario is not correctly matched, or the deployment parameters are not adapted to batch data processing needs.
How to Verify Successful Configuration
- Upload a single annual department budget draft, check whether the model can fully parse fields such as expenses and establishment numbers in the document and generate compliant calculation content.
- Initiate a single-round model call, verify that the returned result context is not truncated and complies with the
maxContextsetting range. - Check the permission configuration, confirm that only authorized department internal accounts can access this model configuration interface.
- Run the preset verification workflow, verify whether the model can identify and mark unreasonable content referenced by the knowledge base.
The values provided are common starting points and should be measured 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.