What This Category's Data Looks Like
Data originates from slab or billet batches, heating furnaces, mill automation controls, online thickness and width gauges, surface inspection systems, and MES systems. Daily documents include rolling plans, heating schedules, rolling procedures, shape and thickness records, surface quality reports, and quality certificates. Updates occur in real time per coil or individual steel billet. Document fields include batch identifiers, temperature parameters, thickness and width values, surface defect grades, and mechanical performance indicators, using standard industrial units of measurement.
What Constraints These Characteristics Impose During Deployment and Upgrade
The data is updated in real time per coil or individual steel billet, and comes from multiple industrial production systems. During deployment, access logic for multi-source heterogeneous data must be adapted. General document parsing workflows cannot be used directly. Bid document preparation requires combining real-time rolling parameters and historical batch data. As a result, vector database and database configurations must support high-frequency, small-batch data synchronization and querying. Professional industrial documents such as rolling procedures and quality certificates require vector modeling logic adapted to industry-specific terminology. During upgrades, existing connected MES system interfaces must remain uninterrupted to avoid disrupting real-time production data synchronization. Data errors can lead to coil downgrading, equipment damage, and other negative outcomes. Deployment stability requirements are therefore high, and complete failure retry and data validation mechanisms must be configured.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Adapts to real-time data connection counts per steel coil, avoiding database connection exhaustion |
PG_URL | postgresql://username:password@server_address:5432/steel_roll_db | Stores structured industrial documents including rolling procedures and quality certificates, plus bid history data |
REDIS_URL | redis://:custom_password@server_address:6379/0 | Caches real-time rolling batch data and session states, supporting high-frequency, small-batch data updates |
STORAGE_S3_ENDPOINT | Configured per the enterprise's internal object storage service address | Stores large industrial documents such as rolling records and surface inspection reports |
ROOT_KEY | Generate a random string per platform security specifications | Used for internal platform interface authentication, preventing unauthorized access to the deployed system |
FILE_TOKEN_KEY | Encryption key matching the object storage service | Used to generate document access tokens, ensuring secure access to industrial documents |
Three Common Misconfigurations
- After modifying frontend-related configurations, the platform frontend cannot load the available model list. The cause is incorrect
ROOT_KEYconfiguration, leading to backend interface authentication failure and failure to return model information. - Connection errors appear after a newly deployed quick trial version starts. The cause is incorrect connection parameters for
PG_URLorREDIS_URL, with mismatched database username, password, and port. - The service throws an exception after running
docker run --gpus all -itd -p 7231:7231to start the marker_images container. The cause is failure to correctly mount the local industrial document directory to the container, or a mismatch between the CUDA version inside the container and the host driver.
How to Verify Proper Configuration
- Log in to the FastGPT v4.17.0 management backend, run the database connection test tool, and confirm that the configured
PG_URLandREDIS_URLcan establish normal connections. - Upload a rolling quality report document to verify that the storage service configured via
STORAGE_S3_ENDPOINTcan complete normal file upload and download. - Use the configured
ROOT_KEYto send an internal interface request, and confirm that the authentication process operates without errors. - Simulate data synchronization requests for multiple steel coil batches, and check that the database connection count does not exceed the
DB_MAX_LINKsetting threshold.
The values provided here are common starting points and should be measured against the reader's own samples.