What Data for This Category Looks Like
Data for this category comes from China’s Center for Disease Control and Prevention Information System, hospital HIS and infectious disease reporting systems, and laboratory testing systems. Daily generated documents include infectious disease report cards, epidemic analysis reports, case correction records, clustered outbreak reports, and epidemiological investigation reports. Data is updated daily. Document structures include fixed fields such as basic case information, diagnosis classification, reporting time limit, and correction notes. All content must match official template formats. No custom extended fields are allowed. Field values must strictly follow statutory reporting rules.
Constraints Imposed on Model Integration and Configuration Workflows
Data sources are scattered. Daily updates from multiple systems must be synchronized. This requires the model integration proxy channel to support stable batch requests.
Document fields are fixed. They must strictly match official templates. Configured model outputs must not generate undefined extra fields or content.
Data updates occur daily. The configured context window must handle processing needs for full daily case data. This avoids timeouts caused by overly long single requests.
Statutory reporting accuracy requirements are high. The model’s free generation space must be limited. This ensures output content complies with official rules.
How to Set Configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Supports context requirements for full daily case data and historical reports, prevents processing interruptions caused by context overflow |
maxTokens | 2000–3000 characters | Matches the standard output length of a single infectious disease report card or epidemic analysis report, ensures complete generation of document content |
temperature | 0.1–0.3 | Reduces generation randomness, ensures output content strictly complies with the fixed format and rules of statutory reports |
toolChoice | none | Disables tool calling, prevents the model from generating extra operational content beyond the preset document scope |
AIPROXY_API_ENDPOINT | Fill in the exclusive address provided by the platform | Ensures model requests pass through compliant proxy channels, adapts to data security and access permission requirements for disease control scenarios |
AIPROXY_API_TOKEN | Fill in the exclusive key assigned by the platform | Verifies request legitimacy, ensures security of data transmission and calls |
Three Common Configuration Errors
- A
401 Unauthorizederror occurs, or model calls produce no response. The cause is incorrect configuration ofAIPROXY_API_TOKEN, or confusion between general proxy and AIPROXY exclusive channel configuration, with other keys entered in the exclusive proxy configuration item. - Generated documents contain undefined extra fields, or deviate from official template formats. The cause is a
temperaturevalue that is too high, leading the model to generate free content beyond preset requirements. - Timeout interruptions appear during batch processing of multiple reports. The cause is a
maxContextvalue that is too small, unable to support context requirements for batch data, resulting in request truncation.
How to Verify Successful Configuration
- Call the test interface, input sample data for a single infectious disease report card, and check if returned result fields fully match the official template.
- View proxy channel call logs, confirm that
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENconfiguration items are correctly loaded, with no empty values or incorrect characters. - Set
maxTokensto a low value, test generating a short case correction record, and confirm output length meets expectations and has no format errors. - Simulate daily batch requests, check if the system can stably process multiple case data without timeouts or errors.
The values provided are common starting points, and should be evaluated against the user’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.