What the Data for This Category Looks Like
This category covers the entire coating line process for automotive, home appliances, construction machinery, and metal furniture. Data sources include coating supplier TDS/SDS, spray booth and oven operation data, colorimeters, film thickness gauges, environmental monitoring equipment, and MES systems. Daily documents include coating process cards, coating batch sheets, paint mixing records, film thickness and color difference reports, oven curves, defect repair orders, and VOCs logs. Data is updated per coating batch, per shift, or via continuous collection. Fields include coating batch number, film thickness value, color difference ΔE value, oven temperature, VOCs concentration, and other fields with corresponding standardized units.
This document is written for FastGPT v4.17.0.
What Constraints These Characteristics Impose on HTTP Interfaces and External Systems
Data update frequencies vary widely in coating scenarios. Bulk coating batch sheets and film thickness reports require interfaces to support large request bodies. Multi-source heterogeneous data requires interfaces to support different field formats and unit conversions. Continuously collected real-time spray booth data requires interfaces to respond with low latency. Compliance data such as VOCs logs requires guaranteed transmission integrity to avoid packet loss. Defect repair orders are linked to multi-stage data, so interfaces must support batch transfer of associated parameters. Additionally, locally deployed FastGPT services must adapt to internal system access domain names and port rules. Interface timeout settings must match the analysis and processing duration of coating data to prevent task interruptions caused by overly short default timeouts.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Request Timeout | 60–120 seconds | Coating process analysis and multi-link data association matching require a certain processing duration to avoid mid-task interruptions |
Authorization | Bearer {custom secret} | Secure access between external systems and FastGPT interfaces, prevent unauthorized calls |
variables | Bind business fields such as coating batch number and film thickness value | Enable automatic associated transfer of interface parameters and coating business data |
responseData | Extract fields for defect type and rectification suggestions | Standardize the return of core results for coating defect analysis, adapt to downstream system parsing |
| Local Access Address | https://{deployment IP}:3000 | Match the default service port of locally deployed FastGPT, adapt to internal system calls |
| Request Body Format | application/json | Meet the transmission needs of structured data with multiple fields in coating scenarios |
Three Common Configuration Mistakes
- Phenomenon: An interface call returns a 401 unauthorized error, or the interface fails to receive business parameters. Cause: The
Authorizationparameter is not configured correctly, or the secret does not match the verification rules of the external system. - Phenomenon: The FastGPT interface cannot be accessed via the specified address during local deployment, and external systems cannot initiate requests. Cause: The firewall for the local deployment has not opened port 3000, or the access protocol is configured incorrectly.
- Phenomenon: Interface requests time out and interrupt, leading to failed transmission of bulk coating data. Cause: The timeout setting is not adjusted according to the time required for associated analysis of coating data, and the default short timeout threshold is used.
How to Verify Successful Configuration
- A test request containing the coating batch number and film thickness value is initiated, and the interface’s ability to correctly receive and bind the business fields in
variablesis verified. - The interface return result is reviewed, and confirmation is made that
responseDataincludes core fields such as preset defect types and rectification suggestions. - The local deployment access address is tested, and confirmation is made that external systems can normally connect to the FastGPT service port.
- A long-duration bulk data request is initiated, and confirmation is made that the interface timeout setting matches the processing duration of coating data, with no mid-task interruptions.
The values provided are common starting points and should be evaluated against samples specific to the deployment in use.