This configuration is based on FastGPT v4.17.0.
What the data for this category looks like
Data for special event operations mainly comes from content libraries, event backends, traffic data platforms, and user feedback. Daily documents include four types: event plans, resource slot schedules, event page copy, and post-event review reports. Fields include event cycle (unit: days), number of resource slots (unit: units), character count of copy, traffic statistics values, and more. The data update rhythm is weekly, with temporary adjustments around holidays based on event schedules. Some temporary event documents are archived after the event ends.
What constraints do these characteristics impose on the "tool calling and plugins" workflow
Special event operation data is scattered across multiple platforms and has flexible update rhythms. This requires tool calling to support cross-data-source synchronous reading and adapt to temporarily updated content. Event documents have clear structured fields such as cycle and resource slots, so tool calling must accurately match field dimensions to avoid mixing data across events. Event copy has character length limits, so tool processing must adapt to text inputs of varying lengths. Historical data from post-event review reports must support batch comparative calls to ensure the comprehensiveness of review content.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
toolChoice | auto or two-option mode | Adapt to scenarios where special event operations require flexible tool selection, supporting automatic matching or forced calling of specified tools |
functionCall | enabled | Support custom tool thought output, adapting to multi-application call requirements |
| Tool call timeout period | 300-600 seconds | Event data is scattered across multiple platforms, so sufficient time must be reserved for cross-data-source retrieval |
| Context window length | 8000-12000 token | Event plans and post-event review reports have long text lengths, requiring support for long text processing needs |
| Number of returned results | Top 3-5 entries | Event-related data must be accurately matched to avoid redundant information interfering with review judgments |
| Custom tool trigger condition | Triggered by event cycle | Event data updates with the cycle, so tool calls must be triggered to match the event schedule |
Three common mistakes
- Phenomenon: When a custom tool is called by another application, only the tool execution result is returned, with no AI thought process. Cause: The
functionCallconfiguration is not enabled, only tool execution parameters are configured. - Phenomenon: Concurrent calls occur during the tool selection phase, and resource slot data for the same event is retrieved multiple times. Cause:
toolChoicedoes not have the two-option restriction set, and multi-tool parallel calling is enabled by default. - Phenomenon: When calling the API to read event documents, the returned content is empty or cannot match event fields. Cause: The mapping rule between the data source and event fields is not configured, or the timeout period is set too short, resulting in retrieval failure.
How to confirm the configuration is correct
- Initiate a tool call request for event copy, check whether the returned result includes the AI thought process and tool execution result.
- Simulate two tool call requests for the same event, confirm that only one tool execution is triggered, with no concurrency.
- Call the API to retrieve event document data, check whether the returned content includes expected fields such as event cycle and resource slots.
- Change the large model configuration, confirm that there are no abnormal errors in the tool call link.
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 2026-10-19.