What this category of data looks like
Data related to construction engineering quality and safety supervision mainly comes from the project quality and safety supervision system, on-site construction site real-name management platform, supervision logs, and third-party test reports. Daily documents include supervision plans, supervision inspection records, hidden danger rectification notices, quality problem handling forms, and completion acceptance supervision reports. Data is updated weekly. Each document contains fields such as project number, participating unit information, inspection item details, and rectification closed-loop status. Some documents required for review must be retrieved across databases from multiple systems, with no unified fixed format.
What these characteristics impose on tool calling and plugins
Since data is retrieved across databases from multiple systems, tool calling must support linkage of multiple data source interfaces. This avoids obtaining only a single type of information in a single call. Documents have no unified format and diverse fields, so tools must adapt to unstructured document parsing. Tools must extract key fields for review and verification. Data is updated weekly, so plugin trigger cycles must match the business rhythm and should not be too frequent. Each document has a large content volume, so the context scope must be limited during tool calling to prevent exceeding processing limits. Cross-system retrieval increases latency, so a reasonable timeout mechanism must be configured to ensure the integrity of the review process.
Configuration settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to multi-tool linked review scenarios, automatically matches corresponding tools to handle different types of review tasks |
functionCall | enabled | Forces tool calling to ensure that key verification links call specified tools to complete data verification |
| Number of items returned per single tool call | Top 3–5 items | The amount of data associated with a single review document is limited; excessive returned content increases context processing pressure |
| Tool call timeout period | 600 seconds | Cross-system retrieval of multi-source data requires sufficient time to avoid interrupting the review process due to timeout |
| Maximum context length | 8000–10000 characters | Adapts to the volume of construction engineering quality and safety supervision documents, avoiding review gaps caused by content truncation |
Three common misconfigurations
- Phenomenon: The original document content returned by tool calling is directly used for review judgment without field extraction. Cause: No result parsing rule for tool calling is configured, and key review fields are not extracted from unstructured documents.
- Phenomenon: The tool calling result is directly output to the end user, and intermediate processing content is not hidden as required. Cause: No output filtering logic for
functionCallis set, resulting in exposure of intermediate verification data. - Phenomenon: The plugin trigger frequency is too high, causing abnormal system resource occupation. Cause: The trigger cycle is not set to match the weekly business update frequency, and repeated requests are caused by calling at a fixed short cycle.
How to verify a successful configuration
- A standard construction engineering supervision declaration material is submitted to trigger tool calling, and verification is performed to confirm that the corresponding tool is automatically matched to complete data retrieval.
- The tool calling log is checked to confirm that the number of returned results aligns with the preset single return limit.
- A cross-system data retrieval scenario is simulated to verify that the tool calling timeout period meets business time requirements.
- The post-call result processing logic is reviewed to ensure that sensitive fields have been filtered or trimmed.
The values provided 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.