Data characteristics for this use case
Typical data sources include concentrate and auxiliary material analysis reports, DCS systems, cell voltage and current monitoring data, laboratory test results, and energy and environmental monitoring equipment. Daily documents include batching lists, smelting records, electrolyzer operation records, laboratory reports, anode and cathode quality records, and environmental protection ledgers. Data updates in real time for each batch of raw materials, individual furnace run, or single electrolyzer. Fields include raw material composition parameters, equipment operation parameters, test indicator values, and operation status flags. Units include composition content values, current and voltage readings, timestamps, mass units, and more.
Constraints for HTTP interfaces and external systems
The high-frequency real-time data, multi-source heterogeneous documents, and granular business dimensions of this use case create multiple constraints for HTTP interfaces. Unlike steel production processes, which use management logic centered on the iron-carbon system and continuous casting rhythm, this use case requires fine-grained management of electrolyzer groups, metal recovery, and mineral impurities. Interfaces must support pulling data per individual tank or batch. Real-time production data requires interfaces to support short-cycle polling or callback pushes, to avoid data lag behind actual production progress. Multiple data sources require interfaces to support parameter transfers in different formats, to meet data pulling needs from systems such as laboratories and DCS. Complex field structures require interfaces to support custom return fields, to reduce transmission load and improve data processing efficiency.
Configuration guidelines
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {custom authentication key} | Complies with HTTP interface authentication standards, ensuring legality and security of external system calls |
variables | {"batchId": "batch ID to query", "tankNo": "electrolyzer number to query"} | Adapts to the business requirement of pulling ledger data per batch or electrolyzer number, and passes precise business dimension parameters |
responseData | Return only batching composition, cell voltage, test indicator, and environmental protection data fields | Filters redundant data, reduces transmission load, and matches the need to extract core ledger data for this use case |
| Number of records per request | 100–200 records | Matches the volume of ledger data for a single batch or electrolyzer, preventing request timeouts |
| Request timeout | 30–60 seconds | Matches the time required for complex data calculation and transmission for this use case, preventing interrupted calls |
| Authentication method | Fixed key authentication | Adapts to the complexity of external system integration for small and medium-sized smelting enterprises, eliminating the need for complex third-party authentication processes |
Three common configuration mistakes
- Garbled content returned after calling the interface. Cause: The request header
Content-Typeis not set toapplication/json; charset=utf-8, causing a mismatch in encoding formats. - Interface call returns status code 401. Cause: The
Authorizationparameter does not carry a correct authentication key, or the key format does not meet requirements. - Significant discrepancies between in-platform chat and API call results for the same knowledge base. Cause: The API call does not pass the
variablesparameter to supplement business context, or the system prompt does not match the production scenario.
How to confirm proper configuration
- Call the test interface, check if the returned
responseDatafield includes preset business parameters and has no redundant fields. - Simulate calls with parameters for different batches and electrolyzer numbers, confirm the interface can return ledger data for the corresponding dimensions.
- Check interface call logs, confirm the
Authorizationparameter verification passes, and there are no failed call records. - Compare results from in-platform chat and API calls, confirm output logic remains consistent when the same
variablesparameter is passed.
The values provided are common starting points and should be measured against the reader's own samples.