What the data for this category looks like
Reference only; verify against the target FastGPT release and deployment documentation.
Constraints imposed by these characteristics on the "model integration and configuration" link
Dispersed data sources and irregular update cycles require configurations that support dynamic access to multi-source heterogeneous databases, to prevent content lag caused by fixed indexing. Documents include multiple types of related materials, so sufficient context carrying capacity must be configured to fully cover relevant review basis. Review work requires comparison between higher-level laws and authority basis, so the model must accurately match hierarchical regulatory content. Irrelevant content interference must also be limited to avoid review deviations. A single review involves multiple documents, so context and output length must be properly configured to ensure full coverage of information across all review steps.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
AIPROXY_API_ENDPOINT | Fill in the corresponding node address according to the deployment environment | Adapt to the access requirements of multi-source regulatory databases |
AIPROXY_API_TOKEN | Bind a dedicated access key | Ensure access permission security for review data |
maxContext | 8000–12000 token | Cover the complete content of multiple related documents such as regulatory document drafts and solicited opinion summaries |
maxTokens | 2000–3000 token | Ensure complete output of legality review opinions, avoid content truncation |
quoteMaxToken | 1500 token | Accurately intercept relevant clauses of higher-level laws and departmental policies as review basis |
temperature | 0.1–0.3 | Maintain the rigor of review conclusions, avoid subjective deviations |
Three common mistakes
- Attempting to directly view the table model structure of the connected database fails to obtain valid field information. The cause is failure to obtain metadata through the FastGPT data source configuration module, and calling underlying interfaces directly leads to insufficient permissions.
- Model call returns a timeout error, and logs show the request duration exceeds the preset limit. The cause is failure to properly set the
maxContextandmaxTokensparameters, leading to excessive time consumption for the model to process multiple related documents. - Random deviations appear in review results after configuration is saved, and the matching degree with regulatory basis is unstable. The cause is that the
temperatureparameter is set too high, leading to lack of rigor in model output.
How to confirm successful configuration
- Test the combination of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENto confirm the interface returns a normal status code. - Upload a small regulatory document draft, check that
maxContextfully loads all related material content without truncation. - Run a single review process, verify the rigor of the output result, and confirm that the
temperaturevalue meets review requirements. - Check the data source configuration module to confirm that metadata information from the regulatory rule base and higher-level law database has been successfully synchronized.
The values listed here are common starting points, and should be validated against local test 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.