Structure of this category of data
Data for this category comes from the centralized treasury payment system, integrated budget management system, electronic invoice platform, and contract management system. Daily processed documents include payment applications, fund use plans, invoices, contracts, acceptance receipts, reimbursement approval forms, and payment vouchers. Data updates daily. Each document contains budget indicator identifiers, economic classification fields, payment amounts, contract associated numbers, acceptance node information, and other details. Single data entries center on a single fund payment application, covering all full-process execution steps from fund use plan to final payment voucher.
Constraints on model access and configuration
This category of data is multi-sourced and updates daily. This requires model access configuration to support unified indexing logic across multiple systems, ensuring policy basis Q&A can link to the latest fiscal execution data. Single payment-related documents focus on a single fund application, with fields centered on core compliance items such as budget indicators and economic classification. This requires limiting the scope of context-associated fields in configuration to avoid interference from irrelevant information. Additionally, payment compliance audit errors have clear consequences. This requires configuring high-confidence retrieval and generation logic to ensure accurate matching of policy basis.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | This category of documents centers on a single payment application, and requires linking corresponding policy basis and full-process documents. Context length must cover core compliance fields and reference materials. |
maxTokens | 2000–3000 token | Policy and regulatory basis Q&A needs to produce clear audit conclusions. Output length must match the information density of a single audit scenario. |
quoteMaxToken | 1500–2000 token | Compliance snippets from documents such as invoices, contracts, and acceptance receipts must be accurately cited. Limiting total cited snippet length avoids redundant content. |
temperature | 0.1–0.3 | This scenario requires strict alignment with policy and document compliance requirements. A low temperature value improves response accuracy and consistency. |
AIPROXY_API_ENDPOINT | Official access address of the corresponding model service provider | Ensures connectivity for model calls, and supports interaction requirements across multiple systems. |
AIPROXY_API_TOKEN | Valid key assigned by the service provider | Completes identity verification for model access, and ensures legitimate call permissions. |
Three common misconfigurations
- Symptom: The knowledge base can retrieve matching documents and policy materials, but the model generates no output or fails to reference compliance basis. Cause: The
maxContextparameter is not configured correctly. Retrieved document snippets cannot be included in the context, so the model cannot link to policy basis. - Symptom: Offline model reconfiguration fails, and the interface displays a connection timeout error. Cause: The
AIPROXY_API_ENDPOINTparameter is not set correctly. The access address does not match the model service provider’s deployment environment, interrupting the call chain. - Symptom: The model’s generated audit conclusion does not match document fields, with incorrect economic classification judgments. Cause: The
temperatureparameter is set too high. Generated content deviates from strict compliance requirements for policies and documents, introducing irrelevant information.
How to verify successful configuration
- Run a policy basis Q&A test for a single payment application. Enter the corresponding application number and compliance query question, and verify that retrieved document snippets match the test payment application, contract, and other documents.
- Check model call logs to confirm there are no format errors or connection issues for the
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfigurations. - Adjust the
temperatureparameter, compare the consistency of generated conclusions, and confirm that response compliance matching meets expectations at the low temperature value. - Trigger a manual knowledge base update, and confirm that Q&A results synchronize the latest document information after the update.
The values provided here are common starting points, and should be evaluated against the test samples relevant to the specific deployment.
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.