What the data for this category looks like
Data sources for production ledger data in metal cutting machining include product drawings and 3D models, CAPP/CAM systems, machine tool collection terminals, tool management systems, MES systems, and measurement and inspection tool data. Data updates trigger based on work orders, individual workpieces, sampling batches, or tool changes. Daily documents cover process routes, operation cards, tool lists, CNC programs, first-piece inspection records, patrol inspection forms, and measuring tool calibration records. Fields include dedicated machining parameters such as operation number, tool life (minutes), workpiece dimensional deviation (micrometers), and machine tool runtime (hours).
What constraints these characteristics impose during deployment and upgrade
Ledger data for this category comes from multiple dispersed sources and updates frequently. During deployment, adapt to multi-system integration requirements and configure stable database and cache connections. Document types include large files such as 3D models and CNC programs. Configure a dedicated storage path separately to avoid occupying business database resources. Fields include dedicated parameters for precision machining. Ensure metadata extraction rules match the document structure of this category during deployment. During upgrades, maintain compatibility with the interface format of existing workshop systems to avoid interrupting the real-time summary process of production ledgers. Verify the processing efficiency of newly added configurations for high-frequency updated data.
How to set the configurations
The following configurations apply to FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Metal cutting machining ledger data updates frequently, with multiple records generated per work order. Sufficient database connections must be maintained to avoid timeouts |
MONGODB_URI | For local deployment: mongodb://localhost:27017/fastgpt_metalcut; For private deployment: Intranet-accessible cluster address | Ledger data requires persistent storage, and must match the workshop intranet network environment |
REDIS_URL | redis://:custom_password@localhost:6379/0 | Cache frequently accessed tool lists and operation card metadata to reduce database load |
STORAGE_S3_ENDPOINT | For local deployment: http://localhost:9000; For private deployment: Intranet MinIO or object storage address | Store large files such as CNC programs and 3D models, complying with the requirement that workshop data does not leave the factory |
FILE_TOKEN_KEY | Random 32-character string | Used to encrypt file upload tokens, preventing unauthorized access to sensitive workshop process documents |
ROOT_KEY | Configured according to enterprise intranet security policies | Manages the highest system permissions, restricting only operation and maintenance personnel from modifying ledger configurations |
Three common mistakes
- Issue:
permission denied while trying to connect toerror occurs when starting FastGPT. Cause: The FastGPT process has not been assigned file permissions to access the intranet database and object storage, or the correct local storage directory has not been mounted during container deployment. - Issue: Corresponding content cannot be retrieved after uploading process documents, or a prompt indicates that the file failed to upload. Cause:
STORAGE_S3_ENDPOINTis not configured correctly, resulting in an unexpected file storage path, orFILE_TOKEN_KEYis not configured, causing token verification to fail. - Issue: Calling ledger report generation via voice input fails, with a prompt indicating that the inference service is unresponsive. Cause: The correct address of the local inference service was not specified during deployment, or
REDIS_URLwas not configured to cache inference sessions, resulting in a timeout.
How to confirm the configuration is complete
- Run the database connection test command to verify that the addresses configured in
MONGODB_URIandREDIS_URLcan connect normally. - Upload a CNC program file, and confirm through the FastGPT file management module that the file storage location meets the workshop intranet storage requirements.
- Import a simulated operation card document and generate a ledger report, confirming that dedicated metal cutting machining fields such as operation number and tool life can be extracted.
- Log in to the system backend, verifying that the
ROOT_KEYconfiguration only authorizes operation and maintenance accounts to modify core system configurations.
The values provided here are common starting points, and should be evaluated against the reader's own samples.