What data for this category looks like
This category of data primarily originates from the Chinese Center for Disease Control and Prevention Information System, medical institution HIS systems, infectious disease reporting systems, and laboratory testing systems. It updates daily. Daily documents include infectious disease report cards, epidemic analysis reports, case correction records, clustered epidemic reports, and epidemiological investigation reports. The document structure centers on case identifiers, diagnostic information, reporting time limits, correction status, and monitoring statistical fields. Most fields link to legally mandated reporting specifications, with no additional custom extended fields.
What constraints these characteristics impose on the model access and configuration link
When calling models, multiple and scattered data sources require unified interface docking across multiple systems to avoid data docking deviations. High-frequency daily updated data requires configuration that supports near-real-time synchronization, to prevent data lag from affecting monitoring and early warning efficiency. Fixed document structure and field links to legal requirements require limiting model output to only match preset fields, to prevent generation of non-compliant content. The sensitivity of case data requires configuring strict access control and data desensitization rules, while ensuring that model call token consumption complies with system resource limits.
How to set the configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Daily documents are mostly single or multiple associated reports. The context length must cover complete case and monitoring data to avoid context overflow |
maxTokens | 2000–3000 token | Standardized report or early warning content must be generated, matching the conventional output length requirements of legally mandated reporting documents |
quoteMaxToken | 1500–2000 token | Original report cards or test data must be cited as a basis, ensuring cited content is complete and does not exceed context limits |
temperature | 0.1–0.3 | Rigorous content compliant with legally mandated reporting specifications must be generated, avoiding arbitrary generation of non-compliant fields or redundant information |
AIPROXY_API_ENDPOINT | Fill in the dedicated interface address according to the deployment environment | Ensure model calls point to compliant proxy services, ensuring data transmission security and authentication effectiveness |
AIPROXY_API_TOKEN | Fill in the dedicated authentication token | Implement identity verification for interface calls, preventing unauthorized access and data leaks |
Three common mistakes
- Issue: The model cannot parse incoming image files, even after embedding images into a PDF document. Cause: The
visionparameter is not enabled, or model rules adapted for visual parsing are not configured. - Issue: Authentication failure or interface timeout occurs when calling the deepseek-R1 model. Cause: The
AIPROXY_API_TOKENis filled incorrectly, orAIPROXY_API_ENDPOINTdoes not point to the correct proxy service address. - Issue: A prompt indicating unexpected token consumption appears during the conversation. Cause: The
maxContextandmaxTokensparameters are not set reasonably, and the maximum token length for context references is not limited.
How to confirm the configuration is complete
- Initiate a test call for a single standard infectious disease report card, and check whether the model output matches the preset fields in the document.
- Upload a test document with embedded images, and check whether the model can correctly identify and extract information associated with the images.
- View the model call logs to confirm that the authentication request returns a normal status with no error messages.
- Adjust the
temperatureparameter and initiate a test, compare the rigor of the output content, and confirm that it meets business specification requirements.
The values provided 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.