What Data for This Category Looks Like
Data for this category originates from design drawings, material quality certificates, welding equipment parameters, filler metal inventories, non-destructive testing systems, and personnel qualification ledgers. Update frequency aligns with individual weld seams, each batch of materials, or each shift’s output. Daily documents include welding procedure qualifications, welding procedure specifications, filler metal issue records, welder qualification records, weld inspection reports, and repair orders. Corresponding fields across all documents cover weld seam numbers, filler metal batch numbers, welder qualification levels, non-destructive testing results, repair counts, and other relevant items. All fields adhere to the strict record requirements of manufacturing processes, with no additional custom units.
Constraints Imposed on Deployment and Upgrade
Data sources for this category are scattered, and update frequency is high. The deployment phase must support unified access configuration for multi-system data sources to prevent data synchronization delays. Multiple types of daily documents are used, and their fields meet strict manufacturing requirements. The upgrade phase must maintain compatibility with original document parsing rules to avoid historical data becoming unreadable after configuration changes. High-frequency updated weld-level data requires appropriate storage capacity and concurrency parameter configurations to ensure audit processes run without interruption. Given the severe consequences of quality failures, the deployment phase must enable full-link log retention configuration to support subsequent exception troubleshooting.
How to Set Configurations
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale for This Setting |
|---|---|---|
DB_MAX_LINK | 10–20 connections | Adapts to high-frequency weld data writes and queries per shift, avoids connection pool exhaustion |
MONGODB_URI | Connection string pointing to a locally deployed MongoDB instance | Stores unstructured documents including massive weld inspection reports and repair orders, adapts to high-frequency update requirements |
REDIS_URL | 600-second connection timeout, 1-hour cache validity period | Caches static data such as welder qualifications and filler metal inventories that are read frequently, reduces database query pressure |
STORAGE_S3_ENDPOINT | Configured per local storage node address, 1000 MB storage capacity limit | Stores large files including non-destructive testing images, meets document storage needs for welded structural component manufacturing |
FILE_TOKEN_KEY | Generated per internal enterprise key rules | Ensures access security for sensitive documents such as filler metal issue records that are uploaded |
ROOT_KEY | Generated initial key per official documentation | Configures initial system administrator permissions, ensures deployment permissions are controllable |
Three Common Misconfigurations
- Attempting to connect to a MongoDB instance started via Docker Desktop results in connection timeout or field parsing failure errors. Cause: Connection parameters for
MONGODB_URIare not correctly configured, and the correct database name and authentication information are not specified. - After upgrading to FastGPT v4.17.0, original proxy configurations no longer take effect, and interface calls fail. Cause: Proxy rules changed in the new version are not adapted, and the official recommended proxy configuration method is not switched to.
- Front-end interfaces show unresponsive status during high-frequency calls to audit interfaces, while system resource usage does not reach the upper limit. Cause: Reasonable
DB_MAX_LINKparameters are not configured, leading to database connection pool exhaustion and request queue timeouts.
How to Verify Proper Configuration
- Run upload and parsing tests for filler metal issue records, confirm that document fields are correctly identified, and no missing field prompts appear
- Submit multiple frequent weld inspection report query requests, confirm that no database connection exhaustion errors occur, and query responses align with business rhythm
- View system storage logs, confirm that the configured
STORAGE_S3_ENDPOINTnode can normally write and read large-volume testing image files - Verify that the initial administrator key can successfully log in to the system, with no permission anomaly prompts
The values provided are common starting points and should be measured against the reader's own samples.