What the data for this category looks like
Typical entities in this category include carbonated beverage, juice, tea, functional beverage, and packaged drinking water factories. Daily documents include formula sheets, water treatment records, blending records, sterilization or aseptic filling records, packaging material inspection records, and finished product inspection records. Data sources cover water source and raw material testing, formula systems, online sugar and acidity monitoring equipment, filling equipment, visual inspection equipment, and LIMS systems. Data is updated per production batch, per shift summary, and via continuous collection. Core fields include raw material batch number, sugar and acidity values, filling liquid level, seal tightness, label batch number, and shelf life.
What constraints these characteristics impose on the tool calling and plugins workflow
Data sources for this category are scattered and update frequently. Tool calling must connect to multiple real-time and batch data sources simultaneously to avoid delayed data impacting audit results. High-speed liquid filling and frequent product switching mean plugin calling parameters must be flexibly adjusted to fit audit rules for different product categories. Errors in core links carry serious consequences, so tool calling must include built-in verification logic to block abnormal data related to formula over-limits and microbial contamination. Structured requirements for multiple types of inspection records mean plugin output must use the functionCall mode to unify formats and support subsequent audit processes.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | auto | Adapt to document calling needs across multiple audit scenarios, automatically match different types of data such as formulas and inspection records |
| Workflow/API function-call configuration | Mandatory structured output | Ensure audit results conform to the entry format of LIMS systems and reduce manual sorting costs |
| Concurrent call limit | 1.5–2.5 times/second | Match the production rhythm of this category and avoid call failures caused by system overload |
| Plugin timeout | 600 seconds | Cover processing durations of long-cycle links such as water treatment and sterilization |
| Parameter verification switch | Enabled | Block core abnormalities such as formula feeding over-limits and label batch number errors |
| Multi-file parameter passing configuration | Bound per batch | Adapt to batch audit requirements for multiple packaging and filling quality inspection images |
Three common mistakes
- Phenomenon: Tool calls return null values when concurrent call volume exceeds 2 times per second. Cause: The concurrent upper limit configuration is not adjusted, and the system’s built-in current limiting mechanism is triggered.
- Phenomenon: Multiple packaging or filling quality inspection images cannot be properly passed into the tool calling workflow. Cause: Adaptation rules for multi-file parameter passing are not configured, and only single-file passing is supported.
- Phenomenon: Frequent parameter failures occur in plugin system calls, and internally deployed MinIO storage cannot be accessed normally. Cause: The FastGPT v4.17.0 plugin system requires storage services to be publicly accessible by default, and no document field mapping for this category is bound, resulting in parameters that do not match actual business data.
How to confirm the configuration is correct
- Initiate concurrent calls at 1-3 times per second, check if returned results include expected audit fields.
- Upload multiple packaging and filling quality inspection images, confirm that the tool calling workflow can normally receive and process files.
- Simulate a scenario where formula feeding exceeds limits, check if the plugin triggers verification interception.
- View system logs, confirm that plugin calling parameters match business document fields.
The values provided here are common starting points and should be validated against samples from the actual operational context.