What data for this category looks like
Core data for this category comes from five sources: meteorological warning systems, hydrological monitoring systems, emergency command platforms, grassroots disaster reporting systems, and video surveillance. The default update frequency is daily. Real-time push support is available in emergency scenarios.
Daily office documents include duty records, warning notices, consultation minutes, rapid disaster reports, emergency response plans, and material allocation slips. Fields cover rainfall amount, flow rate, warning level, number of transferred people, material stock, and more. Corresponding units include millimeters, cubic meters per second, level, person, piece, and others.
What constraints these characteristics impose on tool calling and plugin workflows
Multi-source heterogeneous data sources require tool calling to adapt to different API interface protocols. This avoids data pull failures caused by system compatibility issues.
The mixed update rhythm of real-time and daily updates requires tools to support both on-demand polling and scheduled pull modes. This adapts to different needs for daily duty and emergency response.
Complex document structures and standardized fields require plugins to support structured data parsing. This ensures accurate and complete information in time-consuming tasks such as summarizing rainfall and water conditions and drafting consultation materials.
High fault tolerance requirements in emergency scenarios require configuring failure retry and circuit breaker mechanisms. This prevents single call failures from disrupting the overall response process.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Supports automatic selection of multiple tools to meet multi-source data call demands in emergency scenarios; supported by default in FastGPT v4.17.0 |
| Tool call timeout | 120–180 seconds | Covers complex transaction processing steps such as drafting consultation materials and counting material allocations, preventing task interruptions mid-process |
| MCP service timeout configuration | 180 seconds | Adapts to custom complex transaction processing, avoiding task failures caused by the system's default 90-second wait threshold |
functionCall | enabled | Supports structured data calls, adapting to standardized pulling and parsing of rainfall, water condition and disaster data |
| API address whitelist | Only allow internal emergency system domain names | Ensures security of emergency data calls, preventing unauthorized external access |
| Failure retry count | 3 times | Addresses temporary network fluctuations or short system failures, improving data pull success rates |
Three common misconfigurations
- Phenomenon: Calling internal knowledge base interfaces returns empty results or errors. Cause: The API address whitelist for internal emergency systems is not configured, resulting in request interception.
- Phenomenon: Custom MCP service execution exceeds 90 seconds and returns MC-related errors. Cause: The MCP service timeout configuration is not adjusted, and the system's default 90-second wait threshold is used.
- Phenomenon: Rainfall data fields returned by tool calls are missing. Cause: The structured output format for
functionCallis not specified, resulting in incomplete data parsing.
How to confirm configurations are correct
- Call the test interface
http://localhost:3000/api/core/chat/chatTest, pass in a prompt that includes rainfall data pulling, and check if structured call results are returned. - View tool call logs to confirm that the timeout configuration is active, with no forced interruption records within 120 seconds.
- Simulate a temporary network disconnection, check if the system triggers the failure retry mechanism and normally pulls data after recovery.
- Verify that internal system domain names are included in the whitelist, confirm that external requests cannot call emergency data interfaces.
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.