What the data for this category looks like
The core data for this category comes from the national basic catalog of government service items, administrative licensing item lists, and local government service item databases, and is typically updated monthly. Daily maintained documents include the basic catalog of government service items, implementation lists, service guides, standard material directories, flowcharts, and frequently asked questions. A single service guide usually contains structured fields such as item name, acceptance conditions, application materials, and processing procedures. Some documents also include cross-level item association information.
What constraints these characteristics bring to the "Model Access and Configuration" step
Data for this category comes from scattered sources and is updated monthly. Multi-source catalog data must be synchronized regularly. Model access must adapt to scenarios requiring batch data verification. Service guides have numerous fields and high structured requirements. Model processing must balance field integrity verification and cross-level item association comparison. The monthly update rhythm requires that the batch processing efficiency of the configuration matches the synchronization cycle, to avoid update interruptions caused by model call timeouts. Due to compliance requirements for government affairs, model calls must ensure consistent result standards, and avoid deviations between online and offline service standards.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | The total length of service guides and associated documents is usually large, so context content from multiple catalogs and guides must be accommodated, calibrated based on actual testing |
maxTokens | 2000–3000 token | Single-round output for ledger summary and report generation must cover item lists, verification results, and other content, to avoid exceeding the model's output limit |
quoteMaxToken | 500 token | Key fields from service guides must be extracted as quoted content to avoid exceeding the quoted length limit |
temperature | 0.1–0.3 | Consistency of item verification and summary results must be ensured, to avoid generating content with randomly deviated standards |
AIPROXY_API_ENDPOINT | Government-specific model deployment address | Models adapted for the government affairs domain must be used to ensure data security and call stability |
AIPROXY_API_TOKEN | Key bound with exclusive permissions | Government data involves sensitive information, so exclusive keys must be used to restrict call permissions and prevent data leaks |
Three common configuration mistakes
- After connecting a reranker model offline, a
rerank errorprompt appears. This is caused by failure to configure the model's access permissions, or the deployment address not matching theAIPROXY_API_ENDPOINTparameter value. - When calling a vision model, image upload succeeds but the button cannot be triggered. This is caused by failure to enable the configuration switch for the
visionparameter, or the front-end call logic not binding the model loading status. - When using the
bge-m3vector model, the semantic retrieval value is abnormally large. This is caused by failure to calibrate the model's matching logic, or failure to correctly align item field formats during batch data import.
How to confirm the configuration is complete
- Call the model interface corresponding to
AIPROXY_API_ENDPOINT, initiate a verification request using test government service item documents, and check whether the returned result includes field integrity prompts. - View the model call log to confirm that the parameter values of
maxContextandmaxTokensare correctly passed in the request, with no truncation or over-limit errors. - Simulate the monthly update batch data import process, and check whether the batch quantity processed by the model matches the configured batch limit.
- Call the same verification task multiple times, and verify whether the returned results remain consistent after the
temperatureparameter is set.
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.