What the data for this category looks like
Urban water utility ledger data comes from four sources: PLC collected data from municipal pipeline network monitoring nodes, water plant central control system logs, drainage pump station inspection records, and user payment records. Update rhythms differ: real-time monitoring data such as pipeline pressure and instantaneous flow updates per minute, inspection records and monthly summary ledgers update daily, and payment data updates in real time. A single ledger document includes fields such as device ID, monitoring time, instantaneous flow (unit: m³/h), pipeline pressure (unit: kPa), inspection personnel, maintenance status, and monthly cumulative water supply. Some cross-node summary ledgers require associating historical data from multiple devices.
What constraints these characteristics impose on the tool calling and plugins workflow
Multi-source heterogeneous data sources require tool calling to support parallel calls to multiple dedicated plugins, to pull different types of ledger data separately. Differences in update rhythms require configuring differentiated trigger cycles for different data sources. This avoids interface overload from high-frequency pulling of real-time data, and prevents missing daily-updated ledger files from low-frequency triggers. Fields with clear built-in units require plugins to automatically validate field formats and units, to prevent unit inconsistency errors during summarization. Cross-node summarization requirements require tool calling to support batch data splicing logic that uses device ID and monitoring time as association keys.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Automatically adapts to multi-source data pulling and splicing logic, no manual specification of individual tool functions is required |
functionCall | Call grouped by data source | Separate real-time monitoring data and inspection data into two call groups to adapt to different update rhythms |
| Trigger cycle | 10–60 seconds (real-time data), 1 day (inspection and summary data) | Match the update frequencies of different types of data for urban water utilities, balance interface load and data timeliness |
| Single pull data volume | 10000 entries | Avoid excessive single call data volume causing interface timeout or response delay |
| Field mapping rules | Use device ID and monitoring time as association keys | Ensure accurate splicing and summarization of cross-source ledger data |
| Result verification threshold | Calibrate based on actual measurements | Adapt to data fluctuation ranges of different water utility nodes, filter abnormal monitoring values |
Three Common Mistakes
- Symptom: Unable to locate file processing plugins, unable to import Excel files for inspection ledgers. Cause: The public utility plugin repository was not enabled in FastGPT v4.17.0.
- Symptom: Java API calls remain in a waiting response state with no return results. Cause: The batch pulling logic for multi-source data from urban water utilities was not adapted, and the default timeout threshold is insufficient to cover the time required for cross-node data summarization.
- Symptom: Attempting to extract elements from ledger JSON using JS code execution plugins fails to retrieve target values. Cause: The field path prefix for water utility ledger JSON was not configured, causing the plugin to fail to locate the corresponding data node.
How to Confirm Proper Configuration
- Trigger tool calling, check if pull records for the corresponding water utility data source exist in the system logs, confirm that the trigger cycle matches the data update rhythm.
- Call the test function with
toolChoiceset toauto, check if the returned result automatically splices core fields of multi-source ledgers, such as instantaneous flow, pipeline pressure, etc. - Import a simulated Excel file for water utility inspection ledgers, confirm that the plugin can correctly recognize preset fields such as device ID and monitoring time.
- After completing tool calling, check if the summary result is displayed immediately on the chat interface, with no delays or cached omissions.
The values given are common starting points and should be measured 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.