What This Category of Data Looks Like
Data for the spraying and coating scenario covers the entire coating process. Daily documents include coating process cards, paint batch sheets, paint mixing records, film thickness and color difference reports, oven curves, defect repair orders, and VOCs ledgers. Data sources are paint supplier TDS/SDS documents, real-time collection data from spray booths and ovens, colorimeters, film thickness gauges, environmental monitoring equipment, and factory MES systems. Update frequency follows per paint batch and per shift schedules. Some device data is collected continuously. Fields include film thickness (unit μm), color difference ΔE value, oven temperature (unit ℃), VOCs concentration (unit mg/m³), and others. Most document structures fall into two categories: structured forms and time-series curves. Some documents require linking to batch and work order information.
What Constraints These Characteristics Impose on the Deployment and Upgrade Phase
Data sources for this scenario cover equipment, testing instruments, business systems, and external supplier documents. The formats and update rhythms of multi-source data vary widely. Continuously collected real-time data from spray booths and ovens generates high-frequency write requests, which imposes clear limits on database connection counts. Storing multiple batches of paint documents alongside real-time testing data requires the knowledge base to support mixed retrieval of structured fields and time-series curves. VOCs ledgers are compliance-related business data. Deployment must include clear storage permission and encryption configurations. During upgrades, compatibility must be maintained with the original block rules of coating process cards, existing retrieval matching logic must not be disrupted, and adaptation must be made to different versions of device data reporting formats.
How to Set the Configurations
These configurations are formulated based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 connections | Adapt to high-frequency device data write requests, avoid exhausting database connections |
MONGODB_URI | Fill in the database connection address for the factory MES system and testing instruments, calibrated based on actual measurements | Access multi-source structured business data, cover full-process coating documents and device logs |
REDIS_URL | Configure as the local cache service address, set cache expiration time to 300 seconds | Cache high-frequency queried color difference and film thickness detection data, reduce database read pressure |
STORAGE_S3_ENDPOINT | Fill in the endpoint address of the enterprise's internal object storage | Store external documents such as coating process cards, TDS/SDS files, and batch inspection reports |
ROOT_KEY | Generate a key according to the enterprise's internal permission control rules | Control the highest access permission of the knowledge base, ensure the security of compliance-related business data |
Three Common Mistakes
- Phenomenon: Local debugging operates normally, but Docker image packaging results in database connection failure. Cause: Database connection parameters such as
MONGODB_URIare not correctly injected during image construction, leading to failure to read external database configurations within the container. - Phenomenon: Search results only display single user query content, and no matching search term list is shown. Cause: Multi-search term optimization configuration is not enabled, or the response template logic is not updated synchronously after upgrading FastGPT.
- Phenomenon: Local deployment fails to load the local coating document library. Cause: Local storage path is not configured, or offline-dependent model files and document resources are not fully packaged into the deployment image.
How to Confirm Successful Configuration
- Log in to the FastGPT management backend, view the knowledge base data source list, confirm that access configurations for coating-related business systems, testing instruments, and external documents have been added.
- Perform local debugging and Docker image startup tests, verify database connection status, confirm no connection failure error reports.
- Submit a query related to spraying and coating equipment inspection, check whether the response result includes matching search terms and relevant document fragments.
- View system operation logs, confirm that high-frequency device data write requests do not trigger database connection over-limit alarms.
The values provided are common starting points and should be measured against the reader's own samples.