What the data for this category looks like
Data for this category comes from the health supervision information system, medical institution electronic registration system, complaint and reporting platform, and law enforcement inspection records. The update frequency is monthly. Daily documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Data centers on individual medical institutions to associate multiple types of law enforcement documents. Fields include institution qualification number, practice scope, rectification items, penalty basis, and more. The dataset includes both structured number fields and unstructured content such as on-site inspection descriptions and rectification requirements.
What constraints these characteristics impose on deployment and upgrade
Data sources for this category are scattered and have fixed update cycles. Deployment requires adapting to database interface connections across multiple systems, and configuring multi-source data synchronization rules. Document types are diverse, and include both structured and unstructured content. Upgrade requires compatibility with parsing formats for historical law enforcement documents, to avoid damaging existing retrieval indexes. The monthly update feature requires configuring incremental synchronization mechanisms during deployment, to reduce resource consumption from full synchronization. Fields include both structured numbers and unstructured descriptions. Deployment requires balancing precise field retrieval and full-text semantic retrieval. Additionally, since error consequences involve institutional penalties and practice risks, deployment requires configuring failure log retention and abnormal alert mechanisms.
How to set configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
DB_MAX_LINK | 10–15 | Adapt to concurrent access across multiple health system data sources, avoid exhausting database connections |
PG_URL | Configure according to the database address of the health supervision information system | Connect to structured qualification data sources |
MONGODB_URI | Configure according to the storage address of law enforcement records | Connect to unstructured law enforcement document data |
STORAGE_S3_ENDPOINT | Configure according to the local object storage | Store law enforcement documents and parsed vector data |
FILE_TOKEN_KEY | Calibrate based on actual measurements | Ensure permission security for document parsing and retrieval |
REDIS_URL | Configure according to the local cache service address | Cache law enforcement record data for high-frequency retrieval, improve response speed |
Three common mistakes
Reference only; verify against the target FastGPT release and deployment documentation.
- The pg container fails to start, with the prompt "role "postgres" does not exist". Cause: The postgres database role was not initialized after upgrading the version, or the mounted volume did not retain the original database configuration.
- Vector retrieval results cannot match institution qualification numbers in supervision inspection forms. Cause: Multi-source database synchronization rules are not configured, or retrieval configuration for structured fields is not optimized.
How to confirm the configuration is complete
- Execute a local model connection test, verify that response fields can be extracted normally, and set thresholds based on actual model measurements.
- Check the pg container logs, confirm there are no role missing or connection timeout errors.
- Upload a supervision inspection form, retrieve the institution qualification number, confirm the number of results aligns with expectations.
- Trigger the monthly data synchronization task, verify that documents from multiple data sources can be properly imported into the vector database.
The values provided are common starting points, and should be evaluated against samples from the respective deployment environments.
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.