What the Data for This Category Looks Like
This category covers production facilities for carbonated drinks, fruit juices, tea drinks, functional beverages, and packaged drinking water. Teams create daily documents including formula sheets, water treatment records, blending records, sterilization or aseptic filling records, packaging material inspection reports, and finished product inspection reports. They source data from water source and raw material testing, formula systems, online sugar and acidity monitoring equipment, filling equipment, visual inspection systems, and LIMS systems. Updates occur per batch, per shift, or via continuous collection. Document fields include raw material feeding amounts, water treatment parameters, filling liquid levels, sealing pressures, label batch numbers, microbial test results, and other parameters, some with industry-specific units.
What Constraints These Characteristics Impose on the "Tool Calling and Plugins" Workflow
High-frequency, continuously updated data for this category requires tool calling to support real-time pulling of the latest business data for a single batch or shift, to avoid referencing expired water treatment and filling parameters. Documents of multiple types with specialized fields require tool calling configurations to match corresponding business fields. For example, configure toolChoice to selectively call tool functions that match the business scenario. For scenarios involving formula compliance and aseptic control, tool calling parameters must strictly correspond to specialized fields such as feeding amount and sterilization temperature, and cannot use generalized matching. For exception report drafting, plugins must automatically associate abnormal records from visual inspection and filling equipment to generate corresponding rectification suggestions, and avoid missing key abnormal information.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Auto-match | Adapt to multi-type tool calling needs, covering scenarios such as formula verification, water treatment monitoring, and exception report generation |
| Workflow/API function-call configuration | Group by business scenario | Distinguish between two types of tool functions: feeding compliance check and abnormal record organization, to avoid calling confusion |
| Problem Optimization | Enabled, parameter range calibrated via actual testing | Adapt to high-frequency updated data from continuous collection, optimize retrieval and matching accuracy of exception reports |
| Single Tool Call Upper Limit | Top 6 entries | Match the number of core documents corresponding to a single batch of production, to avoid redundant data interfering with generation results |
| Maximum Context Length | 8000–12000 characters | Accommodate full-process records of formula, water treatment, and filling for a single batch, meeting complete context requirements |
| Timeout Threshold | 300 seconds | Adapt to the conventional response time of LIMS system data pulling, to avoid interrupted calls due to timeout |
Three Common Mistakes
- Phenomenon: An
messages is emptyerror is returned when calling the openAPI. Cause: The document data source corresponding to this category is not bound in the tool calling configuration, causing the system to fail to obtain valid context to fill the message body. - Phenomenon: The generated exception report misses filling liquid level abnormal records. Cause: The data source of the visual inspection equipment is not configured as an associated knowledge base for tool calling, causing the tool to fail to pull corresponding abnormal data.
- Phenomenon: The number of results returned by tool calling does not match the actual number of documents. Cause: The single tool call upper limit is set unreasonably, and does not match the actual number of documents for a single batch of this category.
How to Verify the Configuration Is Correct
- Enter the application debugging interface of FastGPT v4.17.0, initiate a request to draft process documents for a single batch of beverage production, and check whether the tool calling log has pulled the corresponding formula and water treatment records.
- Simulate the scenario of filling liquid level abnormality, initiate an exception report drafting request, and confirm whether the tool automatically associates abnormal data from the visual inspection system.
- Check the request body of the openAPI call, confirm that the
messagesfield is filled with valid context data, and there are no null values. - View the tool calling return results, confirm that the number of returned documents matches the actual number of documents generated for a single batch.
The values provided here are common starting points and should be evaluated against the reader's own samples.