Data characteristics of this category
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. Daily processed documents include infectious disease reporting cards, epidemic analysis reports, case correction records, clustered epidemic reports, and epidemiological investigation reports. The data update frequency is daily. Document fields include basic case information, diagnosis results, reporting time limits, correction status, laboratory test results, and similar items. Common units are case counts, dates, institution codes, and no additional custom units are used.
Constraints imposed on the "model access and configuration" link by these characteristics
This category of data is updated daily. Model access configuration must match the daily data synchronization rhythm to avoid retrieving outdated information. A mix of multiple types of structured and semi-structured documents requires adaptation to the field rules of different documents. During configuration, the retrieval weight of different documents must be clearly specified. Data sources cover multiple business systems, so configuration must support format conversion for multi-source data. As this involves statutory infectious disease reporting rules, model output must strictly align with policy basis. Generation flexibility must be limited to avoid deviating from statutory requirements. Additionally, data fields include key information such as case diagnosis and reporting time limits. Configuration must ensure that retrieved content is accurately linked to policy clauses.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to batch retrieval of multiple daily updated documents, avoiding truncation of key policy basis and case data |
temperature | 0.1–0.3 | Ensures rigor in policy Q&A, reduces randomness of generated content, and complies with statutory reporting rule requirements |
AIPROXY_API_ENDPOINT | Fill in the compliant large model service address based on deployment | Connects to model services that meet health data security requirements |
maxTokens | 2000–3000 token | Limits the output length of a single round of Q&A, ensuring that integrated results of policy clauses and case information are clear and traceable |
toolChoice | Auto | Enables policy clause matching tools to accurately retrieve statutory provisions corresponding to infectious disease reports |
AIPROXY_API_TOKEN | Fill in the secret key provided by the service | Ensures identity verification and data transmission security for model calls |
Three common configuration errors
- A 404 error occurs when calling a third-party model service. This is caused by incorrect configuration of
AIPROXY_API_ENDPOINTorAIPROXY_API_TOKEN, or a mismatch between the model service address and the secret key. - The Q&A function fails to load normally after enabling a custom model. This is caused by failing to complete configuration of the corresponding model in the platform-supported model access list, or the access format not meeting platform requirements.
- Large discrepancies appear in classification results for policy Q&A. This is caused by an excessively high
temperaturevalue, which leads to excessive randomness in model-generated content and prevents stable matching of policy basis and case information correspondence rules.
How to confirm successful configuration
- Initiate a single policy Q&A test, and verify whether the returned result includes matching statutory clauses for infectious disease reports and corresponding case data.
- View the platform's model call logs to confirm that there are no abnormal errors in call requests for
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKEN. - Test the retrieval effect of daily incremental data, confirming that the number of retrieved documents and update frequency match daily synchronization requirements.
- Adjust the
temperatureparameter to the 0.1–0.3 range, and verify consistency of three consecutive Q&A results to avoid excessive random fluctuations.
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.