What the Data for This Category Looks Like
Core data for this category comes from the entire production process of injection molded parts. Daily documents include injection molding process cards, raw material drying records, mold history logs, first-piece inspection reports, patrol inspection records, and material change and machine cleaning records. Data sources include resin batch and property sheets, injection molding machine parameters, mold temperature controllers, MES systems, and dimensional and appearance inspection equipment. Data is updated for each production batch, each mold or material change, and each shift patrol. Fields cover filling, holding pressure, and cooling window parameters, raw material drying and recycle ratio, and defect records such as shrinkage, short shots, flash, and warping. Units include industrial standard units such as temperature, pressure, time, and weight.
Constraints Imposed by These Characteristics During Deployment and Upgrade
Injection molding data sources are scattered and updated frequently. During deployment, connect to multiple types of industrial equipment and systems, and configure synchronization rules adapted to multi-source data. Enable a caching mechanism for frequently updated process data during deployment to avoid repeated reads and meet the low latency requirements of real-time Q&A. Industrial attributes of document fields are strong; knowledge base chunking must match the fixed field structure of process cards, otherwise accurate recall of relevant production content is not possible. Retain the mapping relationship of original process data during upgrades to avoid Q&A failure due to configuration changes, and prepare a rollback plan to handle exceptions after upgrades.
Configuration Settings
This guidance is based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | Connection string using local intranet IP and default port | Injection molding process data is stored in a local industrial database, and intranet connection ensures data security |
REDIS_URL | Local Redis instance on port 6379 | Frequently updated process parameters and patrol records need caching to reduce database read pressure |
FILE_TOKEN_KEY | Randomly generated 32-bit string | Protect access permissions for sensitive production documents such as process documents and mold images |
DB_MAX_LINK | 20–30 | Matches the concurrent connection limit of injection molding equipment and MES systems to avoid exhausting database resources |
STORAGE_S3_ENDPOINT | Intranet address of the local MinIO instance | Offline deployment requires local storage of process documents and inspection images without relying on external cloud services |
Three Common Misconfigurations
- No response from SSO connection after local deployment: Symptoms include no popup when clicking the authentication button or authentication failure. The cause is that
FE_DOMAINis not configured as the callback domain of the enterprise SSO, resulting in cross-domain requests being blocked. - Knowledge base image loading failure: Symptoms include image placeholders or 404 errors displayed on the interface. The cause is that
FILE_TOKEN_KEYis not configured correctly or the storage path mapping is incorrect, resulting in the inability to generate valid file access links. - Abnormal knowledge base query results after offline upgrade: Symptoms include the large model outputting unorganized raw data. The cause is that incremental data of injection molding process cards was not resynchronized after the upgrade, or the
DB_MAX_LINKconfiguration exceeds the database concurrent limit, resulting in data reading failure.
How to Confirm Valid Configuration
- Run a
curlcommand to test the connection toMONGODB_URI, and confirm that the fields of the injection molding process card can be read normally. - Upload an image of an injection mold, and verify that the access link generated via
FILE_TOKEN_KEYcan load the image normally. - Initiate a Q&A request related to process parameters, and confirm that the returned results include matching injection molding process fields and corresponding parameters.
- Restart the FastGPT service, check the connection status of
REDIS_URL, and confirm that the caching service is running normally.
The values provided are common starting points and should be measured against the reader's own samples.