What the data for this category looks like
This category's data comes from government portals, document management systems, government information disclosure directories, policy document repositories, and press conference materials, with a daily update frequency. Daily documents include policy documents, policy interpretation drafts, public disclosure directories, information release approval forms, press releases, and website column update records. Document fields include file number, publishing entity, public disclosure attribute, confidentiality level, publishing time limit, column affiliation, and more. The length of individual documents varies widely, from notifications of a few hundred words to dozens of pages of policy details.
What constraints these characteristics impose on the tool calling and plugins link
Daily updated data sources require tool calling configurations to include scheduled synchronization tasks, to avoid data lag that affects ledger timeliness. Multi-source, multi-format documents require plugins to adapt to proprietary formats of document management systems and long PDF file parsing, to prevent some documents from being unreadable. The diversity of document fields requires tool calling to support custom field extraction rules, ensuring that ledgers cover core information such as file number and public disclosure attribute. Processing long documents requires adjusting plugin calling parameters, to avoid errors triggered by overly large single files, while also adapting to format differences across document sources.
How to configure settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
toolChoice | auto | Automatically matches applicable tools, adapts to processing needs for multiple document types such as policy documents and press releases |
functionCall | enabled | Forces the model to return structured tool calling results, facilitating standardized summary of ledger fields |
| Large file parsing timeout | 1000–1500 seconds | Adapts to parsing hundreds-page PDF documents, avoids timeout errors triggered by long file processing |
| Plugin calling retry count | 2–4 times | Addresses temporary network fluctuations or plugin service abnormalities, improves calling success rate |
| Custom field extraction rules | Calibrated based on actual testing | Adapts to unique fields of documents in this category, such as file number, public disclosure attribute, and confidentiality level |
Three common configuration mistakes
- Phenomenon: When calling a long document parsing plugin, a hundreds-page PDF file triggers an error, while files of dozens of pages can be processed normally. Cause: The large file parsing timeout period was not adjusted, and the processing duration of a single file exceeded the plugin's default limit.
- Phenomenon: Tool calling actually executes successfully, but the platform does not generate corresponding calling logs. Cause: Tool calling log collection configuration was not enabled, or the log collection threshold was set too high.
- Phenomenon: Calling a locally deployed parsing plugin returns a "Cannot read properties of undefined" error. Cause: The plugin version is incompatible with the FastGPT version, or local plugin dependencies were not configured correctly.
How to confirm the configuration is complete
- Upload a hundred-page PDF policy document, trigger the tool calling process, check whether parsing can be completed normally and structured data is generated.
- View the tool calling log module, confirm that a complete record corresponding to this call has been generated.
- Check the generated ledger data, confirm that core fields of this category such as file number and public disclosure attribute are included.
- Simulate a daily scheduled synchronization task, confirm that the tool calling process can be automatically triggered after the data source is updated.
The values given 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.