What data looks like for this category
This category's data sources include animal quarantine information, supplier batch records, production traceability ledgers, temperature collection data, metal detection results, and laboratory microbial test reports. Daily documents include quarantine certificates, slaughter and cutting records, ingredient marinating records, thermal processing records, cold chain temperature records, and microbial test documents. Data is updated synchronously per production batch and per shift. Cold chain temperature data must be collected and updated continuously. Data fields include batch number, quarantine identifier, temperature value (℃), detection time, microbial test item results, and other related items.
What constraints these characteristics impose on the tool calling and plugins link
The biological risk attributes of this category require that tool calls be strictly linked to batch and quarantine information to avoid cross-batch data confusion. The high-frequency updates of continuous temperature control data require plugin calls to adapt to short-interval data pulling to avoid timeouts. The workflow of raw and cooked product separation and zone-based processing requires tools to support data filtering by production area, and plugin authentication must distinguish permissions for different production links. Batch-level traceability requirements require that tool calls carry batch numbers as required parameters to ensure that Q&A results are bound to corresponding production links. The timeliness of microbial testing requires that plugin calls prioritize returning the latest test data and avoid using expired results.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Set to auto and specify equipment maintenance-related tools | Adapt to the tool calling requirements of equipment inspection Q&A, automatically match corresponding maintenance tools, based on the tool calling logic of FastGPT v4.17.0 |
| Workflow/API function-call configuration | Enable batch calling mode | Support pulling temperature and test data from multiple batches at the same time, matching the batch-level data requirements of this category |
| Plugin call timeout | 300–600 seconds | Adapt to high-frequency pulling of continuous temperature control data, avoid call timeouts caused by large data volume |
| Batch parameter mandatory verification | Enable | Ensure that tool calls carry batch numbers, avoid cross-batch data confusion, and meet traceability requirements |
| Data filtering dimension | Filter by production area and batch number, return the top 10 records | Adapt to the business requirements of raw and cooked product zoning and batch traceability, narrow the data query scope |
Three common mistakes
- GPT-4o-mini related error logs appear during workflow calls. The cause is that the
toolChoiceparameter is not configured correctly, causing the model to attempt to call unauthorized tools, or the parameter value exceeds the allowed range. - Knowledge base Q&A pair extraction tasks get stuck during training, with no related records in the call logs. The cause is that batch parameter mandatory verification is not enabled, and the batch number field is missing during tool calls, causing the task to fail to match corresponding data to start training.
- Authentication failure occurs when the plugin calls a third-party interface. The cause is that authentication keys are not managed uniformly, and different tools use expired or mismatched keys, causing interface verification to fail.
How to confirm the configuration is complete
- Trigger a Q&A containing equipment inspection or maintenance keywords, check whether the call logs include the configured tool call records to confirm that the
toolChoiceparameter takes effect. - Submit a test question with a clear batch number, verify whether the tool can correctly pull temperature and test data for the corresponding batch, and confirm that the batch parameter verification takes effect.
- View the plugin authentication configuration page, confirm that the keys of all third-party interfaces have been stored according to unified rules, with no risk of plaintext exposure.
- Simulate high-frequency temperature control data pulling requests, verify that no timeouts occur during plugin calls, and confirm that the timeout configuration is reasonable.
The values provided here are common starting points and should be evaluated against the reader's own samples.