Reference only; verify against the target FastGPT release and deployment documentation.
What this category of data looks like
This category of data mainly comes from the low-income population dynamic monitoring platform and resident family economic status verification system within the civil affairs system, as well as cross-department shared data from public security, human resources and social security, medical insurance, housing and urban-rural development, tax and other departments. Daily processed documents include minimum living security application forms, family economic status verification reports, household survey forms, democratic appraisal records, public notice materials, assistance approval forms and other materials. The data update frequency is monthly. Core fields focus on family economic status, member relationships and assistance qualification related information. No additional custom statistical values are included.
What constraints do these characteristics impose on the model access and configuration link
Differences in format across cross-department, multi-source data require that model access must adapt to structured and semi-structured document formats exported by different systems, to avoid field parsing errors. The monthly update frequency requires configuring scheduled knowledge base synchronization tasks to ensure the timeliness of policies and data. The accuracy of core fields such as family economic status and member relationships is directly linked to assistance qualification judgment. This requires limiting unsubstantiated inferences in model output, and only generating responses based on uploaded official documents and verification data. At the same time, the risk of incorrect or missed assistance coverage requires that Q&A results must be linked to specific document fragments, and content cannot be generated without relying on data sources.
How to set the configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Must accommodate content from multiple cross-department, multi-source documents such as verification reports and application forms, to ensure complete context |
temperature | 0.1–0.3 | Ensures the rigor of responses, and avoids generating subjective inferences beyond policy basis |
quoteMaxToken | 2000–3000 token | Fully reference core document fragments such as family economic status verification reports and public notice materials, to support the basis for assistance qualification judgment |
maxTokens | 4000–6000 token | Limits the length of single-round responses, and avoids redundant content beyond business requirements |
toolChoice | auto | Automatically select whether to call the knowledge base retrieval tool based on queries, and prioritize generating responses based on official documents |
AIPROXY_API_ENDPOINT | Fill in according to the internal proxy address of the deployment environment | Adapt to the internal network environment, and ensure the security of cross-department data transmission |
Three common configuration errors
- Phenomenon: Knowledge base retrieval response times out, and the interface displays a request timeout status code. Cause: The index structure of cross-department, multi-source data is not adapted, leading to an overly large retrieval scope that exceeds hardware carrying capacity.
- Phenomenon: Q&A results are not linked to specific document fragments, and the reference field is empty. Cause: The
quoteMaxTokenparameter is not configured, and there is no mandatory requirement to generate responses based on official documents. - Phenomenon: Q&A generated content deviates from policy basis, and subjective inferences appear. Cause: The
temperatureparameter is set too high, leading the model to generate unsubstantiated extended content.
How to confirm the configuration is complete
- Upload one standard family economic status verification report, initiate a query related to "minimum living security application qualification judgment", and confirm that the response links to specific fragments of the uploaded document.
- Adjust the
temperatureparameter to 0.2, initiate a vague policy query, and confirm that the response content is rigorous and has no subjective speculative statements. - Configure a monthly knowledge base synchronization task, and verify that retrieval results can be updated after cross-department shared data is updated.
- Check the
AIPROXY_API_ENDPOINTconfiguration, initiate a test request, and confirm that the network connection is normal and there are no access errors.
The values given 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.