What this category of data looks like
Data sources include design BOM, silicon steel sheet and insulating material procurement data, vacuum drying equipment operation logs, oil test reports, and partial discharge and withstand voltage test results from high-voltage test stations. Updates are performed per single product batch or per batch of materials. Daily documents include winding and core assembly records, vacuum drying records, insulating oil test reports, partial discharge and withstand voltage test reports, and nameplate parameter tables. Fields cover insulating structure parameters, lead connection information, tap positions, test values, and more. There is no unified batch format, and the size of single-unit documents varies significantly.
What constraints do these characteristics impose on deployment and upgrade
This category of data characteristics imposes three core constraints on the deployment and upgrade link. First, the independent update rhythm of single products or per-batch materials requires that deployments support incremental synchronization mechanisms. This avoids fully repeated processing of historical data and reduces storage and computing load. Second, multi-source heterogeneous data (equipment operation logs, oil test reports, high-voltage test data) requires configuring index rules adapted to multi-format parsing. This ensures unified field mapping for different types of documents. Third, the large variation in single-unit document size and the focus of core fields on insulation and high-voltage test parameters requires adjusting the vector storage sharding threshold. This avoids index exceptions caused by overly large single data entries.
How to configure the settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 120–180 connections | Adapt to scenarios of concurrent reading of multiple documents for a single product, and avoid exhausting the database connection pool |
MONGODB_URI | Point to a dedicated database instance for insulation test and oil test data | Separate core business data from general knowledge base data to improve retrieval efficiency and data security |
REDIS_URL | Configure as the locally deployed Redis service address, set the cache expiration time to 1800–3600 seconds | Cache frequently queried insulation parameters and test data to reduce the load of repeated database reads |
ROOT_KEY | Generate a random key that complies with enterprise security specifications | Ensure the security of administrator permissions, and avoid unauthorized access to the deployed system |
STORAGE_S3_ENDPOINT | Point to the enterprise's internal industrial data storage node | Adapt to the unified storage requirements of multi-source heterogeneous documents, and ensure the stability of data access |
Three common configuration errors
- Phenomenon: After upgrading to FastGPT v4.17.0, the knowledge base can retrieve matching test reports, but the large language model cannot output complete process drafting content. Cause: After the upgrade, the
FILE_TOKEN_KEYparameter was not regenerated and configured, causing access token verification after document parsing to fail, and the model cannot pull complete context data. - Phenomenon: After Docker deployment, the 3000 port page cannot be loaded, while the 3001 port can be accessed normally. Cause: The port mapping parameter for
FE_DOMAINwas not correctly configured, and the port binding of the front-end main service was not exposed to the host's 3000 port, causing external access to fail. - Phenomenon: After Docker deployment in a Linux environment, modifying the configuration file inside the container does not take effect for specified parameters. Cause: Parameters were not modified by mounting an external configuration volume. Directly modifying files inside the container will be reset after the container restarts, or the container was not restarted to load the new configuration content.
How to verify successful configuration
- Perform a database connection test to verify that the number of connections configured by
DB_MAX_LINKcan support the concurrent reading requirements of current business, and confirm that the connection pool is not exhausted. - Upload an insulating test report for a single transformer to verify that the storage node configured by
STORAGE_S3_ENDPOINTcan normally store and read documents without access errors. - Restart the deployment service, log in to the system using the administrator account corresponding to
ROOT_KEY, and verify that the permission verification process works normally without error prompts. - Trigger an incremental synchronization task to confirm that the cache service configured by
REDIS_URLcan normally cache frequently queried test parameter data without cache failure logs.
The values provided are common starting points and should be measured against the reader's own samples.