What the data for this category looks like
Ledger data for nuclear power operations originates from three main sources: reactor operation monitoring systems, equipment inspection terminals, and safety verification systems. There are two data update schedules: core operation parameters are synchronized every 15 minutes, while equipment inspection and safety verification ledgers are updated in batches per 8-hour shift. A single ledger document includes fields such as unique equipment identifier, cumulative operating duration, abnormal trigger count, and last verification date, with units of hours, count, and YYYY-MM-DD format respectively. Some ledgers include binary-format inspection photo attachments.
What constraints these characteristics impose on deployment and upgrade
Real-time synchronized operation parameters require the database connection pool to support high-concurrency writes, so the maximum connection count must be adjusted. The volume of batch-updated ledger data grows with the number of operating nuclear power equipment, so sufficient persistent storage capacity must be configured. Attached inspection photo attachments require enabling an object storage service to avoid occupying local server disk resources. During the upgrade process, data synchronization must not be interrupted, so a rolling upgrade strategy must be used. A full offline backup of all ledger data must be completed before upgrading to prevent data loss from upgrade exceptions.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 30–50 connections | Matches the concurrent write requests from real-time parameters synchronized every 15 minutes, prevents connection exhaustion that interrupts synchronization |
MONGODB_URI | Cluster connection address with read-write separation suffix | Stores batch-updated ledger documents and inspection attachment metadata; cluster architecture ensures read performance |
REDIS_URL | Cluster address with memory no less than 8000 MB | Caches temporary calculation results of real-time operation parameters, reduces database access pressure |
STORAGE_S3_ENDPOINT | Endpoint address adapted to nuclear power intranet compliant storage | Stores binary attachments such as inspection photos, complies with intranet data storage regulatory requirements |
ROOT_KEY | Randomly generated 32-bit string | Configures system administrator access permissions, ensures background operation security of ledger data |
Three common mistakes
- Symptom: After upgrading to FastGPT v4.17.0, the model thinking process for private deployments is not displayed separately in the interface, and the content is directly mixed into the reply body. Cause:
FILE_TOKEN_KEYfor identifying model output thinking tags was not configured correctly, or this configuration item was not migrated synchronously during the upgrade. - Symptom: The server reports a database connection exhaustion error, and the ledger synchronization task is interrupted. Cause: The value of
DB_MAX_LINKis too low to support concurrent write requests for real-time parameters. - Symptom: Inspection photo attachments fail to load normally or display as blank. Cause: The storage endpoint configured in
STORAGE_S3_ENDPOINThas insufficient permissions, and read-write permissions for ledger data are not enabled.
How to confirm the configuration is complete
- Run the database connection test script to verify that the connection count configured in
DB_MAX_LINKcan be established and maintained normally, and no connection exhaustion errors are triggered. - Upload a simulated inspection photo attachment, and verify normal writing and reading through the system storage interface to confirm that the
STORAGE_S3_ENDPOINTconfiguration takes effect. - Trigger a batch ledger synchronization task, and check that the task log has no records of database connection exhaustion or storage write failures.
- Call the model to generate a ledger report, and verify that the thinking content and body of the model output are separated, meeting the configuration requirements.
The values given 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.