What Data for This Category Looks Like
Data for this category comes from product digital models and GD&T specifications, process route documents, coordinate measuring machine data, on-site trial feedback, and metrology system records. Daily generated documents include fixture requirement documents, positioning datum schemes, fixture drawings, gauge operation manuals, acceptance reports, calibration records, and change histories. Data updates occur during single project cycles, each product change, and regular calibration nodes. Data fields include positioning datum parameters, clamping force requirements, measurement tolerance values, calibration cycles, and more. Some documents include geometric dimension annotations in engineering drawing format.
Constraints for Deployment and Upgrade
Multi-source professional data and non-standard update cycles for this category create clear constraints for deployment and upgrade. First, daily documents include engineering drawings such as fixture drawings and gauge operation manuals. Configure preprocessing rules that support engineering document parsing during deployment. Second, data updates trigger with project changes and calibration nodes, with no fixed schedule. Reserve configuration space for incremental data synchronization. Third, data includes professional fields such as GD&T tolerances and coordinate measuring machine readings. Adapt vector mapping rules for professional engineering semantics during deployment. Allocate sufficient storage resources for large-capacity drawings and measurement records. When upgrading, retain version associations for historical change histories to prevent data connection breaks.
How to Configure Settings
The following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://<user>:<pass>@<host>:27017/fastgpt?authSource=admin | Documents and measurement data for this category require persistent storage. The standard MongoDB connection format supports batch writes for multi-source data. |
REDIS_URL | redis://:<password>@<host>:6379/0 | Caches frequently queried process specification content to reduce database load. The default port 6379 works for standard deployment environments. |
STORAGE_S3_ENDPOINT | http://<minio-host>:9000 (or corresponding cloud storage endpoint) | This category includes large-capacity engineering drawings and coordinate measuring machine data. Configure an S3-compatible storage service to support large file uploads. |
FILE_TOKEN_KEY | Random 32-character string | Encrypts access tokens for engineering documents to prevent unauthorized access to sensitive fixture design data. |
ROOT_KEY | Custom complex string, avoid default values | Prevents default keys from being scanned in bulk, ensuring system security after deployment. |
DB_MAX_LINK | 200–300 | Query frequency for multi-source data in this category fluctuates with project progress. Set a reasonable connection pool upper limit to avoid exhausting database connections. |
Three Common Mistakes
- After logging into the system, the root account password is automatically reset to 123456, and the issue repeats every 24 hours. The cause is failure to modify the default
ROOT_KEYconfiguration. The system uses the default key to trigger the built-in default password reset mechanism. - The frontend page returns a 500 error after loading, with a prompt stating URI malformed. The cause is that the
FE_DOMAINconfiguration item contains special characters or an improperly escaped domain address, causing routing parsing failure. - The container starts successfully but the frontend page cannot be accessed. The cause is a mismatch between
FE_DOMAINand the backend service network configuration, or incorrect port mapping that fails to open the port, preventing the frontend from connecting to the backend interface.
How to Verify Successful Configuration
- Log into the system, modify the root account password, and check if the password is automatically reset within 24 hours. Verify that
ROOT_KEYuses a custom value. - Upload a fixture drawing document, check that the parsed text and metadata are complete. Confirm that the storage service configured via
STORAGE_S3_ENDPOINTcan read and write files normally. - Access the frontend page and attempt to send a process specification query request. Check that the backend interface returns a normal status code. Confirm that there are no network issues with the
REDIS_URLand database connection configurations. - Run an incremental data synchronization test, upload an updated gauge calibration record, and check that the data is successfully written to storage and the database. Confirm that the connection pool configured via
DB_MAX_LINKcan normally handle write requests.
The values provided are common starting points and should be evaluated against deployment-specific samples.