Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The core data of this category includes basic government service item catalogs, implementation lists, service guides, standard material catalogs, flowcharts, and frequently asked questions. Data sources include the national basic government service item catalog, administrative licensing item list, power and responsibility list, and local government service item databases. Data is updated once per month. Data fields include core content such as item codes, implementing entities, acceptance conditions, and application material lists. Corresponding relationships between superior catalogs and local implementation lists must be strictly matched.
What constraints these characteristics impose on tool calling and plugins
The monthly updated data, multiple types of structured documents, and strict field verification requirements of this category impose multiple constraints on tool calling and plugin configuration. Monthly updated data requires that the tool calling cache strategy be adapted to the update cycle to avoid using expired historical data. Multiple types of documents require distinguishing reading rules for different data sources to ensure accurate positioning of corresponding files during calls. Strict field verification requirements require tools to support automated field-level comparison to replace manual one-by-one field checks. Cross-level catalog comparison tasks require tools to have batch data processing capabilities to adapt to daily high-frequency maintenance operations.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | Specify as "none" or a custom function | This category needs to call preset catalog comparison and field verification tools, to avoid the model automatically selecting unrelated tools |
| Function call timeout | 600 seconds | Batch catalog comparison and material verification tasks for this category usually take a long time, adapting to the batch processing needs of monthly updated data |
| Tool call return field filtering | Only retain item code, acceptance condition, and application material fields | The core maintenance fields for this category are fixed; filtering redundant data can improve processing efficiency |
functionCall | Force enable | This category needs to strictly call code functions according to preset rules to complete verification, to avoid the model generating unexpected content |
| Tool call retry count | 2–3 times | Data comparison may fail due to network fluctuations or temporary data synchronization issues; retries can reduce task interruption rates |
Three common errors
- Calling a custom Python function returns "API Key verification failed". This occurs because the global universal API key and the application-specific API key are mixed, and the authorization key for the corresponding workflow is not used.
- Tool call results include irrelevant knowledge base search content. This occurs because the knowledge base retrieval switch in the workflow is not turned off, or the
functionCallparameter is not correctly configured to restrict only calling specified tools. - Workflow execution times out. This occurs because the timeout time adapted to the batch comparison tasks of this category is not set, and the default timeout duration is insufficient.
How to confirm the configuration is complete
- Manually trigger a catalog comparison task, check whether the workflow calls the preset Python verification function and returns expected field verification results.
- View workflow logs to confirm that the tool call timeout and field filtering rules match the configured items.
- Simulate a data update scenario to verify that tool calls only return core maintenance fields with no redundant content.
- Call the workflow API to confirm that the returned results only include core answers for service guide maintenance, with no reference content from knowledge base retrieval.
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.