What data belongs to this category
This category’s data comes primarily from pressure testing platforms, APM monitoring tools, database slow logs, and production traffic baselines. Daily deliverables include pressure testing plans, capacity evaluation reports, pressure testing data records, and optimization suggestion sheets. Document fields include throughput (unit: requests/second), latency (unit: milliseconds), resource usage (unit: %), capacity thresholds (unit: cores/GB), and additional metrics. Data updates occur monthly or during major software version releases. Individual pressure testing data records hold full-link metric snapshots from a single test. No real-time high-frequency temporary data is included.
What constraints apply to tool calling and plugin workflows
Data sources for this category are scattered, with many field dimensions. Teams must configure adaptation parameters for multi-source plugins when calling tools, to avoid format conflicts across data sources. Data updates occur at low frequency. Reasonable cache expiration times must be set for tool calls, to prevent returning outdated pressure testing metrics. Individual documents contain many metric items. Explicit specification of fields to extract is required during tool calling, to avoid returning redundant content. Performance test results directly relate to production resource configurations. Tool calling failures may lead to incorrect capacity conclusions. Failure fallback and alert logic must be configured for this scenario.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | {"type": "function", "function": {"name": "get_pressure_test_data"}} | Mandatorily call the specified tool to obtain real pressure testing data, avoid large model generated estimates |
functionCall | Allow calling up to 3 associated tools | Adapt to the multi-data-source plugin calling needs of this category, avoid overload from single calls |
| Cache expiration time | 7 days | Match the monthly or major version update frequency of this category’s data, balance data timeliness and calling efficiency |
| Single tool call timeout | 600 seconds | Cover the typical time required for pulling pressure testing data and calculating metrics, avoid mid-process interruptions |
| Maximum tool response length | 800–1200 characters | Adapt to the typical summary length of capacity evaluation reports, avoid exceeding context window limits |
| Parameter collection trigger threshold | 2 required parameters | Automatically trigger workflow questions when more than 2 parameters are needed for the tool, supplement missing pressure testing scenario information |
Three Common Misconfigurations
- Failing to supplement necessary parameters when calling pressure testing-related tools results in empty pressure testing metric lists. Required fields such as pressure testing scenario and pressure testing time window are not collected via workflow question prompts, so the tool cannot locate corresponding data.
- Failing to trigger retries when tool calls time out leads to delayed model responses. No timeout retry policy is configured, and the process terminates directly after a single call exceeds 600 seconds.
- Failing to enable tool reranking configuration results in unranked pressure testing data from knowledge base retrieval. Reranking settings are not enabled, and the tool returns redundant data in default order, failing to focus on key bottleneck metrics.
How to Verify Proper Configuration
- Review workflow configurations, confirm
toolChoicespecifies a performance testing-related tool name, with no vague calling settings. - Check the cache expiration time setting, confirm it matches the 7-day cycle. Trigger a tool call to verify the update time of returned data.
- Test the multi-parameter calling workflow, confirm the workflow automatically displays parameter collection prompts to supplement required fields such as pressure testing scenario and pressure testing time window.
- Confirm the current running environment is FastGPT v4.17.0, to avoid configuration ineffectiveness due to version differences.
The values provided here are common starting points, and should be validated against samples from local deployments.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.