Document and Material Drafting for Proactive Public Disclosure and Policy Release: Tool Calling and Plugins

Document and Material Drafting for Proactive Public Disclosure and Policy Release: Tool Calling and Plugins

Reference only; verify against the target FastGPT release and deployment documentation.

What this category of data looks like

Data sources for this category include government portals, internal document management systems, government information disclosure directories, official policy document repositories, and press conference materials. Documents processed daily include policy documents, policy interpretation drafts, proactive public disclosure directories, information release approval forms, press releases, and website column update records. The data update frequency is daily, requiring synchronization of the latest policy updates and published content. Documents must include fields such as public attribute identifiers, confidentiality review markers, release time limits, and corresponding column information. Some documents need to be linked to original policy documents and interpretation materials.

Constraints imposed by these characteristics on tool calling and plugin workflows

Data sources are scattered and updated daily, so multiple data source interfaces must be called to sync the latest policies and published content. Documents contain sensitive attribute fields, so tool calling must include built-in confidentiality review verification logic to prevent classified information from being leaked. Proactive public disclosure must strictly follow release time limit requirements, so tools must support scheduled triggering of release workflows. The need for multi-document association requires plugins to support cross-system data pulling, ensuring consistency between public disclosure directories and actual published content. Additionally, adaptation to different formats of policy documents and interpretation drafts is required, so tool calling must be compatible with multiple document parsing rules.

How to set configurations

Configuration ItemRecommended SettingRationale
toolChoiceSet to autoAutomatically match the current document type to call the corresponding tool
Timeout thresholdSet to 120–180 secondsAdapt to the duration requirements of complex transaction processing, avoid premature interruption
functionCallEnable forced calling modeEnsure that format conversion and public verification plugins are called when generating policy interpretation drafts
Trigger ruleTrigger based on document public attribute tagsMatch the hierarchical processing workflow for government documents
Context windowSet to 8000–12000 tokenAccommodate complete original policy documents and linked public directory data
Retry countSet to 2 timesHandle scenarios where the large model returns an empty response or tool calling fails

Three common mistakes

  • Phenomenon: Tool calling times out, returning an error message containing "MC | Whether to stop output". Cause: The default timeout setting is 90 seconds, which cannot meet the duration requirements of complex transaction processing exceeding 120 seconds.
  • Phenomenon: The large model returns an empty response, and the log shows chat:LLM_model_response_empty. Cause: No retry mechanism is configured, or the context window is too small to accommodate complete policy materials, preventing the model from generating valid content.
  • Phenomenon: Tool calling is not triggered, and the public directory is inconsistent with actual published content. Cause: The trigger rule is not bound to the document public attribute tag, and verification tools are not called in accordance with the hierarchical requirements for government documents.

How to confirm the configuration is complete

  • Upload a policy document with public attribute tags, trigger the document drafting workflow, and check whether the corresponding tool is automatically called.
  • Simulate complex transaction processing, confirm that no timeout interruption is triggered when the tool calling duration exceeds 90 seconds.
  • Trigger the large model to generate a policy interpretation draft, check that valid content is returned, and there are no errors of the type chat:LLM_model_response_empty.
  • View the system configuration log, confirm that the toolChoice and functionCall parameters have been loaded with the set values.

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.