What data this category involves
This category uses data from medical insurance intelligent monitoring systems, fund supervision rule libraries, medical insurance settlement data, pharmaceutical and consumable traceability codes, and complaint leads. Daily processed documents include supervision audit notices, inspection work papers, suspicious item lists, interview records, decision letters, and rectification reports. Most documents contain fields for supervision subject, violation circumstances, and involved amount, with units mostly being yuan and person-times. Data updates occur monthly, and document batches to be processed synchronously are generated in batches alongside monthly supervision audit tasks.
What constraints these characteristics impose on deployment and upgrade
Monthly updated batch data requires deploying storage and computing resources adapted to high-volume synchronization to avoid single synchronization timeouts. Differences in fields across multiple document types require the system to support flexible parsing rules to ensure correct field mapping for different supervision audit documents. The monthly update rhythm requires configuring scheduled synchronization tasks to ensure the timeliness of policy rules and business data. Supervision-related documents involve sensitive regulatory information, so a permission isolation mechanism must be configured during deployment to prevent unauthorized access. Medical insurance settlement data and traceability code data volumes are large, so sufficient database and cache resources must be reserved to support storage and query operations.
Configuration Settings
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
REDIS_URL | redis://:your_secure_password@your_host:6379/0 | Cache frequently accessed policy rules and supervision audit suspicious item data to reduce database access pressure |
MONGODB_URI | mongodb://db_user:db_pass@your_host:27017/fastgpt?authSource=admin | Store unstructured documents such as medical insurance settlement data and complaint leads, adapting to large field storage requirements |
DB_MAX_LINK | 20–30 | Adapt to peak database connections during monthly batch synchronization to avoid connection pool exhaustion |
ROOT_KEY | Custom high-strength random string | Ensure the security of system administrator access permissions and prevent unauthorized operations |
STORAGE_S3_ENDPOINT | http://local-storage:9000 (local deployment scenario) | Store attachment files such as supervision audit notices and rectification reports, adapting to large-capacity document storage requirements. Reserve at least 1000 GB of storage space |
Three Common Misconfigurations
- Symptom: The model service on port 3005 is inaccessible after Docker deployment, while the base service on port 3000 works normally. Cause: Environment variable configurations in docker-compose.yml were not modified correctly, causing the port bound by the model service to not match the actual access port.
- Symptom: Workflow response is slow after deployment on an 8-core 32G machine. Cause: Database connection pool and cache configurations were not adjusted, leading to underutilized resources and inability to support batch supervision audit data processing and query operations.
- Symptom: The bge-reranker model fails to function after Docker deployment. Cause: Model-related configurations were not added to the environment field in docker-compose.yml, causing the system to fail to load the reranking model normally.
How to Verify Configurations
- Run the
docker pscommand to confirm all relevant containers are running and port mapping configurations match the configuration files. - Call the system's built-in cache connectivity test interface to verify that the
REDIS_URLconfiguration can connect normally and perform read/write operations on data. - Upload a standard supervision audit notice document to verify that the
MONGODB_URIconfiguration can store and read document content normally. - Log in to the system administrator backend and complete identity verification using the configured
ROOT_KEYto confirm that the administrator permission configuration takes effect.
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.