What Data for This Category Looks Like
Reimbursement rule Q&A data draws from internal enterprise financial management systems and special reimbursement rule documents. Update cadence follows financial policy adjustments, typically annual updates or immediate updates after policy changes. Documents use a chaptered structure, divided into modules by expense type such as travel expenses and office expenses. They include fields like amount limits, document compliance requirements, and approval levels. Common units include yuan, sheets, and workdays. Individual document lengths range from thousands to tens of thousands of words. Some documents include attachment format instructions.
Constraints on Tool Calling and Plugins
Reimbursement rule Q&A data is structured by expense type. Tool calling must accurately match fields for the corresponding category, and cannot use generalized calls for universal rules. Documents have long lengths and include attachment format requirements. Tool calling must limit the scope of recalled documents to avoid interference from irrelevant content. Data update frequency is not fixed. Plugins must support regular synchronization of the latest financial policy documents to ensure the timeliness of Q&A content. Fields related to reimbursement documents require compliant formats for images or scanned copies. Tool calling must adapt to the format requirements for passing multiple images.
Configuration Settings
This configuration uses the interface and parameter logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Automatically match the most suitable reimbursement rule tool, covering calls for multiple expense types |
| Multi-image passing format | Base64 encoding, pass single or multiple images in sequence | Adapt to the image verification requirements for reimbursement documents |
| Plugin synchronization cycle | Every 7 days | Align with financial policy update cadence, balancing timeliness and resource consumption |
| Call timeout | 600 seconds | Adapt to time requirements for long document recall and multi-image processing |
functionCall output format | Strictly match reimbursement field names and units | Ensure call results correspond to correct expense categories and rules |
| Recalled result limit | Top 3 entries | Filter redundant content and focus on core reimbursement rules |
Three Common Configuration Mistakes
- Phenomenon: After passing multiple reimbursement document images during tool calling, the returned result is empty or prompts "parameter format error". Reason: Multiple images were not converted to base64 encoding and passed in sequence; only a single image was passed, or the encoding conversion was not completed correctly.
- Phenomenon: Calling the reimbursement rule Q&A plugin returns "parameter verification failed". Reason: Data was not passed in the field format required by
functionCall, and required fields such as amount and expense type were omitted. - Phenomenon: Rule content returned by plugin calls does not match the latest financial policies. Reason: The associated knowledge base documents were not updated regularly according to the configured synchronization cycle, resulting in outdated data.
How to Confirm Proper Configuration
- Upload a single reimbursement document image, perform tool calling, and verify that the passed parameter format matches the configured multi-image passing requirements.
- Manually trigger the knowledge base synchronization operation for the plugin, and check whether the update status of the associated documents aligns with the configured synchronization cycle.
- Initiate a query that includes a specific expense type, and verify that
toolChoiceautomatically selects the appropriate tool, and that the returned rule content matches the query scenario. - Simulate a query that includes multiple document images, and confirm that the tool calling process can properly handle multi-image passing.
The provided values are common starting points, and should be evaluated 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.