This document is written based on FastGPT v4.17.0.
What Data for This Category Looks Like
The core data of this category comes from slab or billet batches, heating furnaces, mill automation control systems, online thickness and width measurement equipment, surface inspection devices, and MES systems. Daily operation and maintenance documents include rolling plans, heating schedules, rolling regulations, plate shape and thickness records, surface quality reports, and quality certificates.
Data updates per coil or billet. Some key parameters such as heating temperature and rolling speed are synced in real time. Data fields include batch number, heating furnace temperature, rolling speed, plate shape deviation value, thickness tolerance, and surface defect type. Their units are batch identifier, degrees Celsius, meters per second, millimeters, millimeters, and defect category, respectively.
Constraints on HTTP Interfaces and External Systems
Data for this category updates per coil or billet, with some key parameters synced in real time. This requires HTTP interfaces to support precise querying by batch number, to avoid returning irrelevant multi-batch data.
Daily operation and maintenance documents include multi-dimensional rolling-related parameters. Interface request parameters must support passing filter conditions such as rolling type and detection time, to narrow the return scope and improve query efficiency.
Real-time data synchronization requirements demand interfaces with low-latency response capabilities, to meet the instant query needs of on-site equipment inspection.
The coil-level traceability business rule requires that returned data must include traceable batch identifiers, to ensure that Q&A results match the actual data of the corresponding steel coil.
How to Set Configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Use Bearer token format, set token validity period to 24 hours | Complies with the authentication specifications of steel rolling enterprise MES systems, to ensure interface access security |
variables | Store batch number, mill model, detection standards, limit lifecycle to a single request | Adapts to independent data query requirements per coil or billet, avoids cross-request data contamination |
responseData | Only return plate shape deviation, thickness value, surface defect type fields, limit pagination to 20 items per page | Reduces network transmission load, adapts to the display capabilities of on-site inspection terminals |
| Request timeout setting | Set to 300 seconds | Adapts to real-time collection delays of heating furnace and mill data, avoids invalid retries triggered by network fluctuations |
| Conversation context configuration | Limit to the previous 2 rounds of conversation history | Reduces redundant data in interface requests, improves response speed of inspection Q&A |
Three Common Misconfigurations
- Issue: Invoking the FastGPT OpenAPI chat interface returns a 401 Unauthorized status code, or prompts authentication failure. Cause: The
Authorizationparameter is not configured correctly, or an expired Bearer token is used. - Issue: The AI-generated equipment inspection Q&A results do not include valid data returned by the HTTP interface, or return empty fields. Cause: The
responseDatafields returned by the interface are not correctly bound invariables, and the mapping between data and Q&A logic is not completed. - Issue: Interface calls frequently trigger timeout errors, or return more results than expected. Cause: A reasonable request timeout period is not set, or the number of returned response data items and pagination rules are not limited.
How to Confirm Configuration is Complete
- The configured HTTP interface is invoked, and the returned data is checked for the presence of preset plate shape deviation, thickness value, and surface defect type fields.
- A query request containing a specific steel coil batch number is sent, and the returned data is confirmed to match the plate shape and thickness records of the corresponding steel coil.
- High-frequency interface calls are simulated, and authentication failure errors are checked for, confirming that the token validity period and authentication rules take effect.
- FastGPT running logs are reviewed, and it is confirmed that the
variablesparameter of interface requests correctly passes the query dimensions of on-site inspections.
The values provided are common starting points and should be evaluated against the reader's own samples.