What this category’s data consists of
Data for this category typically originates from creator backends, enterprise credit information query APIs, account historical behavior records, and contract systems. Daily processed documents include onboarding application forms, identity qualification scan copies, audit review circulation records, and cooperation agreement texts. Data updates are triggered by application workflows. The update frequency for a single application data is daily or per application. Core fields include applicant account ID, qualification verification status, audit circulation nodes, and agreement signing status. There are no unified fixed units, as they adjust based on document type. The most time-consuming steps focus on qualification verification and account risk assessment. Business risks associated with the data include fraudulent verification, cooperation disputes, and mismatched account rights and interests.
What constraints these characteristics impose on tool calling and plugin workflows
Data sources are scattered and update with application triggers. Tool calling must support dynamic configuration for multi-source data retrieval to avoid audit delays caused by fixed data sources. The qualification verification step must call multiple third-party APIs, and handle differences in return formats across APIs. As such, tool calling must include built-in format conversion logic. The field structure of a single application data varies by document type. Plugins must support dynamic field mapping to adapt to parsing requirements for different documents such as onboarding applications and qualification materials. The account risk assessment step must call historical behavior data. Tool calling must retain call logs to enable audit workflow tracing, while limiting interface call frequencies to avoid triggering rate limits. Business risks associated with the data require that tool call results include traceability information, to ensure that audit links can trace call sources and parameters.
Configuration guidelines
This guide applies to the tool calling and plugin configuration for FastGPT v4.17.0.
| Config Item | Recommended Value | Rationale |
|---|---|---|
| Tool call timeout duration | 300–600 seconds | Aligns with average multi-source data retrieval time, to avoid interrupting the overall audit workflow due to single interface delays |
toolChoice | auto | Automatically selects called tools based on application document type, covering scenarios such as onboarding applications and qualification verification |
| Plugin call retry count | 2–3 times | Addresses temporary fluctuations in third-party APIs, reducing audit rejections caused by single call failures |
| Maximum parallel call count | First 3 entries | Meets multi-source data retrieval requirements for a single application, avoiding exceeding interface call limits |
| Result traceability switch | Enabled | Retains complete tool call logs to meet tracing requirements for audit links |
| Field mapping rules | Calibrated based on actual testing | Adapts to field differences across document types, ensuring parsed data matches business fields |
Three common configuration errors
- Phenomenon: The system does not record complete tool call logs, but plugin execution is actually triggered. Cause: Persistent storage configuration for tool call logs is not enabled, or the log storage directory permission configuration is incorrect.
- Phenomenon: Plugins return empty values and do not generate expected qualification verification results or business links. Cause: Plugin input parameter mapping is not configured correctly, preventing the plugin from reading valid business data.
- Phenomenon: Visual models cannot be called to complete image verification of qualification materials. Cause: Visual model call parameters are not added to plugin configurations, or model interface access permissions and call scopes are not configured.
How to verify correct configuration
- Submit a test onboarding application, verify that the tool calling module triggers the corresponding plugin as configured.
- Access the system log page, confirm that tool call request parameters and return results are fully recorded.
- Modify the plugin timeout configuration, submit a test application to verify whether the timeout interruption logic works properly.
- Adjust the field mapping rules, check whether the plugin can correctly parse custom fields in the test document.
The values provided are common starting points and should be measured against corresponding samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.