What this category of data looks like
Data for this category originates from enterprise internal control systems, ERP systems, financial sharing systems, audit management systems, and procurement contract project systems. Commonly processed documents include internal control self-assessment reports, audit notices, audit working papers, issue lists, rectification ledgers, and rectification closing certificates. Data update frequency is annual. Documents include both structured fields and unstructured text. Fields cover issue number, rectification responsible person, completion deadline, supporting material number, and other items. There is no unified fixed unit, with adjustments made based on specific business scenarios.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
Data sources are scattered across multiple internal systems, so plugin calling must adapt to the API formats and permission rules of different systems. The annual low-frequency update feature requires tools to support batch pulling of historical archived data, avoiding resource waste from single calls. Document types are diverse and fields vary, so tools must support both structured field extraction and unstructured full-text parsing. Business document field naming differs across enterprises, so plugin configuration must support custom mapping rules to adapt to personalized business needs. Tool calling requires selecting an appropriate calling method via the toolChoice configuration. functionCall can bind processing logic for different document types.
How to Set the Configuration
The following configuration items apply to FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto or specify function | Adapts to multi-tool combined calling requirements in audit scenarios, supports automatic tool selection or fixed calling of a specified plugin |
functionCall | Trigger based on document type | Calls corresponding tools for different document types such as internal control self-assessment reports and rectification ledgers, improving processing accuracy |
| Single search limit | Top 10 entries | Audit sample extraction needs to cover key evidence, returning an appropriate number of results balances efficiency and completeness |
| Timeout setting | 600 seconds | Internal system interface responses may experience delays, reserving sufficient time for data pulling and parsing |
| Document chunk length | 800-1200 characters | Adapts to the conventional text length of audit documents, balancing parsing accuracy and context window usage |
| Custom field mapping | Calibrated based on actual testing | Fields in rectification ledgers and issue lists vary across enterprises, requiring adaptation to the field naming of the relevant enterprise's system |
Three Common Misconfigurations
- An input error occurs when manually triggering plugin calls. Cause: The plugin's API request headers or parameter formats are not correctly configured, and do not match the verification rules of the internal system.
- Only simple search results return after using the search plugin, and complete content of target links cannot be read. Cause: The plugin's web content crawling configuration is not enabled, and only the basic search interface is called without obtaining full-text data.
- A 502 status code error returns when calling internal APIs. Cause: The plugin's request timeout setting is too short, or the authentication parameter in the request header is not correctly passed, and differs from the APIFOX configuration.
How to Confirm the Configuration is Properly Set Up
- Manually upload a single business document to trigger plugin calls, and verify whether the returned results include expected fields and content.
- Call the test API interface of the internal system to confirm that the plugin's request parameters and response format meet the system's requirements.
- View workflow run logs to confirm there are no timeout, 502 status code, or empty field errors.
- Test different types of business documents to verify that the plugin can adapt to the corresponding custom field mapping rules.
The values provided here are common starting points, and should be evaluated against the samples used in actual deployment.
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.