What this type of data looks like
Data for urban gas utility application materials and case review comes from internal installation application systems of gas operating enterprises, safety inspection management platforms, and government-shared gas qualification databases. Installation application materials are updated in real time as users submit them. Review cases are archived after approval is completed. A single application document includes fields such as applicant identity information, gas usage address, designed gas usage scale (unit: cubic meters per day), gas facility drawing descriptions, and business qualification certificates. Cases include structured content such as review nodes, rectification opinions, approval results, and archive numbers.
What constraints these characteristics impose on the tool calling and plugin workflow
The characteristics of urban gas application materials and case review impose multiple constraints on the tool calling and plugin workflow. Real-time submitted installation materials require tool calling response delays to match the user submission pace, to avoid excessive waiting. Structured data with multiple fields requires that function parameters for tool calls strictly correspond to exclusive fields such as gas usage scale and qualification number, to avoid unit or format errors. Archived cases with multi-node review records require plugins to support filtering data by review node, and to handle cross-system data source synchronization delays. The content length of single documents varies widely, so adaptation to different lengths of context input is required.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Adapts to the multi-type tool calling needs of urban gas application materials, no need to manually specify a fixed function |
functionCall | enabled | Supports explicitly calling preset gas data query functions, to meet the structured data extraction needs of case review |
| Maximum context | 8000–12000 token | The total content length of a single gas application material and case usually covers thousands of tokens, reserving sufficient space to avoid context overflow |
| Single tool call limit | Top 3 entries | Gas review usually only requires the latest 3 relevant cases or installation records, excessive data will increase context burden |
| Tool call timeout | 60 seconds | Internal gas system data queries usually complete within 10-30 seconds, reserving buffer time for peak load |
Three common mistakes
- Phenomenon: Tool call parsing fails, returning Tool call Parser n error. Cause: The thinking content returned by the inference model is wrapped in think tags and placed in the content field, which does not meet the FastGPT tool call parsing format requirements.
- Phenomenon: The number of results returned by the tool call does not match expectations, only returning 1 entry or exceeding the preset limit. Cause: The single tool call limit configuration item is not set correctly, or the case time range for the query is not limited.
- Phenomenon: Tool call triggers context overflow, causing request interruption or returning empty results. Cause: The maximum context configuration does not cover the total content length of a single application material and case.
How to confirm the configuration is correct
- Use FastGPT v4.17.0 or a later version. Initiate a simulated gas installation material review request. Check whether the tool call automatically matches the corresponding data query function, to confirm that the
toolChoiceconfiguration takes effect. - View the results returned by the tool call. Confirm that the extracted fields such as gas usage scale and qualification number match the format of the internal system, to verify the rationality of the
functionCallconfiguration. - Observe the response duration of the tool call. Adjust the timeout configuration to ensure that data queries can be completed under peak load.
- Test input of ultra-long case content, confirm that the context is not truncated, to verify the adaptability of the maximum context configuration.
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.