What this category of data looks like
This category of data comes from online composition analysis equipment, DCS control systems, laboratory testing systems, kiln and grinding production equipment, raw material and fuel ledgers, and energy metering devices. Data update frequencies fall into three categories: real-time (such as kiln temperature, material flow), shift-based (such as inspection records, batching adjustment sheets), and daily (such as quality reports, energy consumption statistics). Daily documents include raw material batching plans, kiln operation records, test reports, quality control notices, equipment inspection sheets, and energy reports. Fields cover material ratios, mineral compositions, fineness indicators, temperature parameters, and more. Units include percentage, kilogram, square meters per kilogram, degrees Celsius, and others.
What constraints these characteristics impose on HTTP interfaces and external systems
The multi-source and multi-update-frequency characteristics of this category of data create multiple constraints for HTTP interfaces. Multi-source data requires interfaces to support dynamic switching of data source types, to match different pull modes including real-time and batch. Data fields include professional process parameters, so interfaces must allow specifying return field ranges to avoid redundant content transmission. Consequences of incorrect process adjustments are severe, so interfaces must be configured with reasonable timeout thresholds and retry mechanisms to ensure data transmission stability and prevent process parameter abnormalities caused by transmission delays. Interfaces must also adapt to the authentication rules of the enterprise’s existing systems to ensure the legality of interface calls.
How to configure settings
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
Authorization | Use Bearer Token format, with the value set to the authentication key of the enterprise’s existing system | Adapt to the authentication rules of the enterprise’s existing external systems to ensure the legality of interface calls |
variables | Real-time data pull interval: 30–60 seconds; batch data pull interval: 8–12 hours | Match the real-time, shift-based, and daily update frequencies of this category of data to reduce invalid requests |
responseData | Specify return fields including raw meal modulus, clinker f-CaO content, and grinding specific surface area | Only transmit core data required for process specifications and technical standards to lower transmission load |
| Timeout threshold | 30 seconds | Match the real-time response requirements of kiln and grinding systems to avoid blocking production processes |
| Retry times | 2 | Respond to temporary network fluctuations while avoiding process data abnormalities caused by repeated submissions |
This page is adapted for FastGPT v4.17.0.
Three common configuration mistakes
- Phenomenon: The interface returns a 401 unauthorized error, or returns an empty authentication verification result. Cause: The
Authorizationparameter is not configured correctly, or does not match the authentication format of the enterprise’s external system. - Phenomenon: Incomplete data fields or non-compliant data formats are returned after calling the interface. Cause: Required process fields are not specified via
responseData, or the configuration does not match the return structure of the data source. - Phenomenon: The interface return result cannot be parsed normally when called via code, or DB node query results cannot be directly used for process Q&A. Cause: The professional field format of this category of data is not adapted, the difference between JSON arrays and single data records is not handled correctly, and field mapping logic is not configured.
How to confirm the configuration is correct
- Call the interface to retrieve a single real-time data entry, and verify that the returned fields include preset core process parameters such as raw meal modulus, clinker f-CaO content, and grinding specific surface area.
- Simulate a batch pull of daily data, and verify that the returned content covers document types including quality control notices and energy reports.
- Trigger an interface timeout test to confirm that the system returns a timeout prompt within the preset threshold and executes the retry logic.
- Check the pull interval configured in
variablesto confirm that it matches the update frequency of the corresponding data, with no duplicate or missing requests.
The values provided are common starting points and should be measured against the reader's own samples.