What This Category of Data Looks Like
Data sources for this category include medical insurance intelligent monitoring systems, fund supervision rule bases, medical insurance settlement data, drug and consumable traceability codes, and complaint clues. The update frequency is monthly. Commonly processed documents include audit notices, inspection work papers, suspicious item lists, interview records, handling decision documents, and rectification reports. Data fields cover audit targets, types of violations, involved settlement batches, handling suggestions, and more. Common units include batches, person-times, and similar units.
Constraints Imposed on Tool Calling and Plugins Workflow
Monthly updated data sources require tool calling to support scheduled triggering and batch processing, to align with the monthly audit work rhythm. Multiple document structures require plugins to adapt to text reading across different formats, and accurately extract core fields from content such as suspicious item lists and handling decision documents. Multi-source data requires calling multiple tools to retrieve settlement data, rule base information, and complaint clues separately, to avoid incomplete coverage from a single tool. Audit result errors can lead to fund losses, so tool calling must be configured with failure retry and operation log recording mechanisms to ensure data accuracy.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto or specified audit tool group | Covers multiple types of data retrieval required for medical insurance audit |
functionCall | Enabled | Supports calling external plugins to obtain medical insurance settlement data and rule base information |
| File reading chunk length | 800–1200 characters | Adapts to the standard text length of audit notices and inspection work papers |
| Single tool call limit | top 6 entries | Matches the standard quantity range of suspicious item lists for monthly audits |
| Timeout setting | 600 seconds | Covers the reasonable time required for cross-system retrieval of medical insurance settlement data |
| Plugin request size limit | 1000 MB | Adapts to the batch data transmission requirements of drug and consumable traceability codes |
Common Mistakes
- Symptom: An error indicating the model does not support the feature is returned when calling
toolChoice. Cause: The current model’s support for thetoolChoicefunction was not confirmed, and a model that does not support tool calling was incorrectly selected. - Symptom: An empty result is returned via API call after the application is published. Cause: Permission parameters for external system calls were not configured, preventing normal retrieval of medical insurance settlement data and rule base information.
- Symptom: Data queries cannot be triggered after importing an HTTP plugin. Cause: The plugin’s request address was not matched with the official interface of the medical insurance intelligent monitoring system, resulting in invalid requests.
- Symptom: Application call results are displayed directly in the terminal. Cause: The switch to only use results as context for the large model was not configured, causing results to be output directly.
How to Confirm Configurations Are Correctly Set
- Test calling
toolChoiceto confirm that the specified audit data retrieval tool is triggered, and a suspicious item list in the corresponding format is returned. - Call the published API interface to confirm that the returned ledger data fields match the preset audit document structure.
- Initiate a test request after importing the HTTP plugin to confirm that medical insurance settlement data and rule base information can be retrieved normally.
- Configure the application to not output call results directly, confirm that the large model can correctly use the results to generate audit reports, and no directly output raw data is present.
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.