What the Data for This Category Looks Like
Data sources for this category cover raw datasets, ETL logs, annotation platforms, and sampling results, updated daily or per batch. Daily associated documents include cleaning rules, quality inspection sampling tables, abnormal data lists, and delivery reports. These support core processes such as duplicate data identification, outlier handling, and sampling quality inspection. Data quality issues directly lead to delivery failures.
What Constraints These Characteristics Impose on the "Tool Calling and Plugins" Workflow
This category has scattered data sources, clear update schedules, and long core processing times. Tool calling must support connections to multiple data sources, and scheduled batch task triggers that run daily or per batch. Core processing steps rely on preset documents such as cleaning rules and abnormal data lists. Plugins must be able to load these documents as calling parameters. Because data quality issues directly impact delivery, tool calling must include built-in result verification logic, and a failure retry mechanism must be configured to prevent overall task interruptions caused by single call errors.
How to Set Configurations
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
toolChoice | auto | Adapts to tool calling needs across different cleaning and quality inspection scenarios, automatically selects matching plugins to perform tasks |
functionCall | Force specify outlier handling function | Must strictly follow preset outlier identification logic, prevents the model from generating unexpected processing rules |
| Retry Count | 3 times | Batch data processing is vulnerable to network fluctuations; 3 retries balances task success rate and total processing time |
| Single Call Timeout | 600 seconds | Batch cleaning and quality inspection tasks process multiple batches of data; this prevents task interruptions caused by excessively long single batch processing times |
| Batch Task Batch Size | 500–1000 items per run | Excessively large single batch sizes trigger plugin rate limits, while excessively small sizes increase scheduling and resource overhead |
| Result Verification Switch | Enabled | Data quality issues directly lead to delivery failures; verify whether the proportion of abnormal data meets preset standards |
Three Common Mistakes
- Symptom: Error occurs when the MySQL database connection plugin runs multi-line queries. Cause: The plugin is not configured to support batch statement execution, or the delimiter rule for multi-line queries is not specified in the calling parameters, so the plugin can only process single SQL statements.
- Symptom: Tool calling tasks frequently time out and interrupt. Cause: The single call timeout setting is too short, or the batch task batch size is too large, exceeding the processing capacity of the plugin or data source.
- Symptom: Tool calling results are unstable, and some abnormal data is not correctly identified. Cause: Preset cleaning rules or abnormal data lists are not correctly loaded as calling parameters, so the processing logic generated by the model does not match business requirements.
How to Confirm Correct Configuration
- Run a single batch test task, check whether the results returned by the plugin match the expected outcomes of the preset cleaning rules.
- Review tool calling logs, confirm that the retry mechanism triggers normally and resumes the task in simulated network anomaly scenarios.
- Check batch task scheduling records, confirm that tasks automatically trigger at the preset daily or per-batch frequency.
- Verify the multi-line query function of the MySQL plugin, confirm that multiple SQL statements execute sequentially according to the configured delimiter rules.
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.