What Data for This Category Looks Like
Data for thermal intelligent due diligence reports comes from four primary sources: pipe network operation monitoring systems of thermal supply enterprises, user payment ledgers, energy consumption statistical reports, and local public utility filing platforms. Data update cycles fall into three categories: real-time monitoring (such as pipe network pressure, water supply return temperature), daily summary (such as regional heating supply, user energy consumption), and monthly archive (such as annual total thermal supply). The document structure includes four fixed sections: basic information page, pipe network operation details, user service data, and energy consumption analysis module. Core fields include pipe network pressure (unit MPa), water supply return temperature (unit ℃), heating supply (unit GJ), and number of service households (unit households). Each field has a clear unit identifier.
What Constraints These Characteristics Impose on Tool Calling and Plugins
Real-time monitoring data requires plugins to use fixed short-interval polling during calls. Otherwise, real-time analysis requirements for due diligence reports cannot be met. Fixed field structures require plugin-returned structured data to strictly match preset field names and units. Otherwise, data cannot be automatically imported into the due diligence report template. Daily and monthly data batch processing requires plugins to support paginated pulling and breakpoint continuation. This avoids single-call timeouts or data truncation. Minor differences exist in ledger formats across different thermal enterprises. Plugins must support custom field mapping rules to adapt to multi-source data access.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
plugin_request_timeout | 300 seconds | Thermal bulk data pulling involves large single request data volumes. 300 seconds covers most paginated pulling scenarios |
plugin_batch_size | 500 items per request | Single thermal operation data entries have small volume. 500 items balances request efficiency and single-time data transmission volume |
field_mapping_enabled | Enabled | Differences exist in field naming across thermal enterprise ledgers. Enabling this allows mapping to standard due diligence report fields |
plugin_retry_times | 3 times | Public utility data interfaces may experience temporary failures due to network fluctuations. 3 retries reduces call failure rates |
plugin_response_format | Strict JSON format | Due diligence reports require automatic data parsing. Strict JSON format directly adapts to template filling logic |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: Points are consumed after calling the plugin, but the returned result is empty or contains an error. Cause: The return status code of the thermal data interface is not verified. When the interface returns
404 Not Foundor403 Forbidden, no exception capture and retry logic is triggered. - Phenomenon: A custom-implemented plugin cannot be called at all. Cause: The
Enableswitch is not turned on in the FastGPT plugin configuration page, or the plugin is not added to the application's tool call list. - Phenomenon: Thermal data fields returned by the plugin do not match the due diligence report template. Cause: The
field_mapping_enabledparameter is not enabled. Original interface field names are used directly to fill the template, causing the template to fail to recognize the fields.
How to Confirm the Configuration Is Complete
- Enter the FastGPT plugin debugging interface, enter the test address of the thermal data interface, initiate a call, and check whether the field names and units of the returned content match the preset standards.
- On the application's tool call configuration page, add the thermal plugin and initiate a test conversation. Check whether the request and return data of the plugin are fully recorded in the conversation log.
- Generate a thermal intelligent due diligence report. Confirm that modules such as pipe network operation and user service data from the plugin have been automatically integrated into the report.
- Simulate a scenario where the interface is temporarily unavailable, trigger a plugin call, and check whether the configured retry mechanism is triggered and data pulling is completed after the interface recovers.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.