What data this category includes
Data sources for this category include state-owned assets supervision and administration commission investment supervision systems, enterprise ERP and project management systems, industry market data, audit and financial statements. The data update frequency is quarterly. Commonly used documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset appraisal reports, and post-investment evaluation reports. Data fields include project ID, project initiation approval document number, planned investment amount, actual investment amount, commissioning date, and post-evaluation score. Corresponding units are count, ten thousand yuan, and day.
What constraints these characteristics impose on the tool calling and plugin workflow
Multiple data sources require plugins to support API integration with heterogeneous systems. Unified field mapping rules must be configured to integrate data formats from different systems. Quarterly update frequency requires scheduled sync tasks via tool calling to match the quarterly rhythm, to avoid frequent pulls that exceed system load. Diverse document types require plugins to support parsing various formats of project initiation and post-evaluation related documents. Corresponding document parsing adapters must be configured. Severe error consequences require configuring failure retry and data validation logic in the tool calling step, to ensure the accuracy of ledger data.
How to configure this
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to multi-type tool calling needs, automatically selects appropriate plugins to execute ledger summary and report generation tasks |
functionCall | Enabled | Supports structured output of required field information for reports, facilitating subsequent data organization and analysis |
| Scheduled sync cycle | 90 days | Matches the quarterly update data frequency of this category, balancing data timeliness and system load |
| Data source pull limit | Top 1000 entries | Adapts to a reasonable scale for single ledger data pulls, avoiding exceeding interface call limits |
| Interface timeout threshold | 600 seconds | Adapts to interface response times for large project ledger data, avoiding call interruptions due to excessive data volume |
| Failure retry count | 3 times | Addresses occasional exceptions in single interface calls, ensuring stability of data synchronization |
Three common configuration mistakes
- After configuring a model plugin, response latency is significantly higher than direct curl calls. The cause is that the built-in context preprocessing step of FastGPT is not disabled, which adds extra data processing time.
- Calling the API does not output the R1 thought chain process. The cause is that the thought chain output switch corresponding to
functionCallis not enabled, resulting in no retention of the reasoning process during structured calls. - Ledger data retrieval takes too long. The cause is that pagination pull parameters for the data source are not configured. Pulling full data in a single request exceeds the interface response threshold.
How to confirm correct configuration
- Check plugin logs to confirm that fields returned by the data source match the preset mapping rules, with no missing or format errors.
- Test the scheduled sync task to confirm that the task runs automatically every 90 days, and the sync result matches the quarterly update data scope.
- Call the API interface to confirm that the returned result includes structured fields marked with
functionCall, and thetoolChoiceconfiguration takes effect. - Simulate an interface call failure scenario to confirm that the system triggers the preset failure retry mechanism, and the task completes normally after retries.
The values provided 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.