What Data for This Category Looks Like
This category processes data from regulatory and rule databases, higher-level law databases, departmental policy document databases, and administrative normative document filing systems. Update frequency is irregular. Commonly processed documents include normative document drafts, drafting explanatory notes, legality review opinions, solicited comment summaries, and filing reports. Most documents are clause-based policy texts, with fields including document subject, drafting basis, rights and obligations settings, and solicited comment feedback. There are no unified fixed quantitative unit fields, and most content consists of abstract policy rule text.
What Constraints These Characteristics Impose on the "Tool Calling and Plugins" Workflow
Scattered data sources require tool calling to support chained calls of multiple data source plugins, to cover verification basis from different sources such as regulatory rules and higher-level laws. Most documents are clause-based policy texts with long length, so plugins must adapt to long text parsing and segmented verification requirements. Irregular update frequency requires tool calling configurations to pull the latest data on demand, and avoid enabling fixed caching logic. Content to be verified involves formulation authority, procedures, and text legality, so tool calling parameters must match the comparison logic of policy rules, and adapt to the special verification needs of legality review.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to automatic multi-tool selection needs, covers multi-step verification scenarios for legality review |
functionCall | enabled | Forces tool calling, avoids cross-data source verification that cannot be completed with pure text generation |
| Tool calling timeout | 120–180 seconds | This category's verification involves multiple data source pulls and long text comparison, requires sufficient execution time |
| Long text segmentation threshold | 800–1200 characters | Clause content of daily documents is mostly 800-1200 characters per segment, adapts to segmented verification needs |
| Data source plugin call order | Pull higher-level laws first, then pull departmental policies | Legality review must first match higher-level law basis, then verify departmental formulation authority |
| Verification rule matching threshold | Calibrated based on actual testing | Must adapt to verification strictness of policies at different levels, avoid false positives or missed judgments |
Three Common Misconfigurations
- The symptom is that tool calling works normally in debug mode, but throws errors in runtime mode. The cause is that permissions for multiple data source plugins are not configured in runtime mode, or caching logic conflicts with on-demand pull configuration.
- The symptom is a connection failure when calling marker-pdf, with logs showing connection timeout. The cause is that the deployed plugin service has not opened the corresponding port, or the FastGPT container and plugin container are not in the same network environment.
- The symptom is the question-and-answer pair extraction task stuck in training, with no records in the call log. The cause is that the tool calling trigger condition is not bound to the review task trigger event, or the configured
toolChoiceparameter is not enabled correctly, causing the task to not start.
How to Confirm Configuration Is Complete
- Enter the workflow debug mode of FastGPT v4.17.0, trigger a simulated review task, and check whether the tool call log shows multiple data source pull and verification steps.
- Check the
toolChoiceandfunctionCallparameters in the workflow configuration, confirm that the parameter values match the preset configuration. - Execute a network test command inside the FastGPT container to verify connectivity with the deployed plugin service.
- Submit a test normative document draft, check whether the generated legality review opinion includes cross-data source verification content.
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.