What the Data for This Category Looks Like
Production data for steel smelting comes from on-site PLC control systems, manufacturing execution systems (MES), energy management systems, and equipment maintenance systems. Data update rhythms fall into three categories:
- Real-time operating data (such as furnace temperature, rolling force) updates every second.
- Equipment operating status updates every minute.
- Production plans and energy consumption reports update in daily batches.
The data uses structured time-series format, with fields including unique equipment identifiers, timestamps, detection values, and operating tags. No unified fixed field names exist, so adaptation and mapping are required for each production line.
Constraints Imposed on HTTP Interfaces and External Systems
The varied data update rhythms for steel smelting require HTTP interfaces to match call frequencies to data types.
- Real-time operating data needs a call interval under 5 seconds to prevent data backlog and loss.
- Structured fields have no unified naming rules. Configure strict field mapping when setting
responseDatato align cross-system data. - Daily data volume per production line is high. Limit single interface return data to under 1000 entries, and use pagination.
Equipment permission binding requires the Authorization parameter to carry the production line attribution identifier. This prevents cross-regional unauthorized data calls and protects production data security.
Configuration Guidelines
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Carry production line attribution identifier plus Bearer prefix | Match the permission isolation requirements of multi-production lines in steel smelting, ensuring only authorized production lines can call the interface |
variables | Configure production line ID and data type as fixed variables | Adapt to the differentiated data pulling requirements of different production lines, reducing repeated interface configuration |
responseData | Map to fields such as furnace temperature, rolling force, and energy consumption value | Align with the standard data structure of steel smelting production systems, ensuring external systems can parse directly |
| Call interval | Real-time data: once every 5 seconds, batch data: once per day | Match the update rhythms of different data types, avoiding interface overload or data lag |
| Single return entry count | Top 100 entries | Control single interface load, adapting to the daily data scale of a single steel smelting production line |
Three Common Misconfigurations
- Phenomenon: Certificate errors appear when accessing the frontend after Docker deployment, with status code 400 or connection timeout. Cause: HTTPS certificate mounting is not configured properly, and SSL encryption is not enabled for the HTTP interface.
- Phenomenon: SQL generated by text2sql does not match steel smelting equipment fields, returning empty results. Cause: Steel smelting-specific table names and field mapping rules are not configured in
variables, so the generated SQL does not match the actual production system structure. - Phenomenon: Calling the published API interface returns Playwright MCP service parsing failure, while Gaode MCP functions normally. Cause: The local address of the Playwright service is not specified in the interface configuration, leading to cross-network access failure.
How to Confirm Proper Configuration
- Call the test interface to verify that returned data includes preset steel smelting-specific fields such as furnace temperature and rolling force.
- Check the production line identifier in the
Authorizationparameter. Attempt to call the interface for an unauthorized production line to confirm a permission error is returned. - Adjust the call interval, then check interface logs for overload alarms to confirm load matches configuration requirements.
- Verify that text2sql-generated SQL correctly matches the production system table structure and returns valid data.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.