What data for this category looks like
Typical entities include color printing, label, carton, flexible packaging, and pharmaceutical packaging enterprises. Daily documents cover pre-press files, imposition sheets, printing process sheets, ink color matching records, first article sign-off samples, barcode inspection, die-cutting and lamination records. Data sources include customer manuscripts, color management systems, printing press data, ink and substrate batch records, spectrometers, and barcode detectors. Update frequency follows per order, per batch, or per plate change. Document fields include plate version number, ink batch number, barcode verification value, die-cutting tool parameters, lamination temperature and pressure, and others. Some data comes from unstructured files exported by equipment, with no unified standard format.
What constraints these characteristics impose on deployment and upgrade
This category has high-frequency document updates and scattered data sources. During deployment, support must be added for rapid import and index updates of multi-source heterogeneous data. The volume of single-batch documents varies with order scale, so high-concurrency database connection configuration must be supported. Documents contain production process parameters and customer-sensitive manuscripts, so strict access permission control must be configured during deployment. Plate errors can spread rapidly, so version comparison and real-time verification logic must be integrated during deployment to avoid batch scrap risks. The system must also be compatible with unstructured data exported by devices including spectrometers and barcode detectors. Data format adaptation interfaces must be reserved during the deployment phase to ensure detection data from all sources can be unified into the cross-review workflow.
The following configurations are adapted for FastGPT v4.17.0.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | mongodb://fastgpt:yourpassword@db-host:27017/fastgpt_db?authSource=admin | This category requires isolated storage of technical documents by order batch. A database instance with independent authentication must be configured to ensure data isolation and access security |
REDIS_URL | redis://:redispass@redis-host:6379/0 | High-frequency updated imposition sheets and first article sign-off sample verification results need to be cached to reduce repeated calculation overhead and adapt to order-level update rhythms |
STORAGE_S3_ENDPOINT | Fill in according to the node address of the enterprise's own S3-compatible storage service provider | This category needs to store original detection data from spectrometers and barcode detectors. S3 protocol-compatible object storage is required to meet multi-source data storage needs |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Temporary access tokens must be generated for sensitive documents such as pre-press files and customer manuscripts to prevent unauthorized access, which aligns with production document security requirements |
DB_MAX_LINK | 800–1200 concurrent connections | This category has large single-batch document volumes and high concurrent access volumes. High-concurrency database connections must be adapted to avoid request blocking |
ROOT_KEY | Generated only during initial deployment, not exposed externally | This category's technical documents contain production process parameters. The scope of super administrator permissions must be restricted to prevent accidental modification of core configurations |
Three common configuration mistakes
- Phenomenon: After starting docker-compose, an error prompt indicates undefined environment variables, and document storage configuration fails to load. Cause: Corresponding environment variables were not added to the compose file, and
STORAGE_S3_ENDPOINTorFILE_TOKEN_KEYconfiguration items were omitted. - Phenomenon: After a Windows device restarts, all configured models and document verification rules are lost. Cause: Database and cache directories were not mounted to persistent storage. Temporary storage inside the container was used by default, and temporary storage contents are cleared after restart.
- Phenomenon: Workflow debugging returns an error containing "Dangerous behavior". Cause:
FILE_TOKEN_KEYwas not configured or configured incorrectly, causing sensitive document access permission verification to fail and triggering the security interception mechanism.
How to verify successful configuration
- Review the service startup log to confirm the database instance configured with
MONGODB_URIestablishes a normal connection, with no connection timeout or authentication failure prompts. - Upload a pre-press file, generate a temporary access link, and confirm the link accesses the file normally with no permission errors, verifying the
FILE_TOKEN_KEYconfiguration is active. - Access the service management interface, check the cache service status, and confirm the cache service configured with
REDIS_URLruns normally with no connection exceptions. - A super administrator account attempts to modify core configuration items, and unauthorized operations are intercepted, confirming the
ROOT_KEYpermission control is active.
The values provided are common starting points and should be measured against the operator's own samples.