What this category of data looks like
Data for this category originates from work safety supervision systems, enterprise hazard self-inspection systems, law enforcement inspection records, and accident statistics systems. The update frequency is daily. Daily documents include hazard inspection lists, hazard management ledgers, rectification notices, review records, and major hazard supervision and rectification orders. Fields cover hazard identifiers, rectification responsible entities, rectification completion deadlines, review and verification results, and more. Different source documents have inconsistent field order and naming, with no unified fixed format.
Constraints on tool calling and plugins
Scattered data sources and inconsistent formats require tool calling to adapt to API interfaces for multiple data sources. Independent authentication rules must be configured to secure data access across different systems. The daily update frequency requires tool triggering logic to align with daily scheduling, preventing data lag or duplicate summaries. Diverse document structures require plugins to support parsing ledgers and notices in varying formats. Dedicated parsing tools must be bound for each document type. This category centers on full-process hazard handling. Tool calling must cover the full workflow of inspection, rectification, and review, unlike other scenarios that only require post-hoc data summary. Hazard inspection data is linked to work safety responsibilities. A clear alarm and retry mechanism must be configured for tool calling failures, to avoid data summary interruptions that disrupt subsequent full-process handling.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | Specify the hazard inspection toolset | Call corresponding data source interfaces accurately, avoid interference from unrelated tools |
| Return format configuration | Enable Markdown format | Adapt to front-end multi-module parsing, optimize display effects of ledgers and reports |
functionCall | Bind dedicated document parsing functions | Meet parsing requirements for hazard documents in different formats |
| Retry mechanism configuration | Retry 2 times after failure, 60-second interval | Address temporary network fluctuations or short-term interface exceptions |
| Scheduled triggering configuration | Trigger at 2:00 AM daily | Match the daily data update rhythm, ensure timeliness of summary data |
| Data pull limit | Pull the top 5 latest data entries | Match daily inspection batch processing needs, avoid data overload |
Three Common Configuration Mistakes
- Phenomenon: Returned content is plain text with no formatting. Front-end parsing results in monotonous display. Cause: Markdown format output configuration is not enabled, or return format is not constrained via
functionCall. - Phenomenon: Stream data disconnects after forwarding to an intermediate service, and page data stays static. Cause: Continuous forwarding logic for stream data is not configured, or the intermediate service times out before fully transferring response content.
- Phenomenon: The packages/plugins/register directory cannot be located during Docker deployment, preventing system plugin configuration. Cause: FastGPT v4.17.0 adjusted the plugin registration directory structure. Configuration must be completed directly via the background plugin management interface, and manual creation of this directory is unnecessary.
How to Verify Successful Configuration
- Call the test interface to confirm the returned content includes Markdown-formatted titles, tables, and other elements.
- Review tool calling logs to verify the specified hazard data source tool was triggered, and returned data fields match core ledger requirements.
- Manually trigger the scheduled task to confirm a properly formatted ledger report is automatically generated at the set time.
- Disconnect and reconnect the intermediate service to confirm stream data can resume normal display or resume transmission.
The values provided 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.