What data for this category looks like
Data sources for this category include formula systems, raw material batch ledgers, internal mixer operation logs, Mooney and rheometer test data, vulcanizer process records, and laboratory finished product performance reports. Data is generated for each raw material truck batch, each feeding batch, and each production mold cycle. Daily documentation includes formula sheets, weighing records, mixing curves, rubber compound quick test reports, vulcanization process cards, mold records, and finished product performance reports. Fields cover rubber type proportion, feeding weight, real-time temperature, holding time, tensile strength, and more. Most units are degrees Celsius, minutes, phr, and megapascals.
Constraints imposed by these characteristics on citation sources and traceability
The high-frequency update requirement for every truck batch, feeding batch, and mold cycle means traceability systems must quickly match the latest batch data. This prevents referencing expired historical formulas or processes. Multi-source heterogeneous data formats include curve, table, and text types. Traceability functions must support cross-type document association verification. This ensures mixing temperature data matches parameters on vulcanization process cards. Standardization of field units directly affects traceability accuracy. Units across different documents must be unified. Otherwise, parameter misalignment will occur. Frequently generated documents require traceability systems to support fast aggregation of citations by production batch. This adapts to batch review needs in production workflows.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | Matches the text length of a single mixing curve or vulcanization process card, avoids truncating critical traceability information |
responseData | Enabled | Ensures returned results carry metadata for referenced files, meets traceability requirements for cross-review |
detail | Enabled | Returns full citation paths, making it easy to locate specific document nodes |
| Maximum number of citation sources | Top 5 | Covers core documents involved in a single production batch, avoids redundant information interfering with review |
| Context window size | Calibrated via actual testing | Adapts to the aggregated length of multi-source documents, ensures all associated data is fully loaded |
| Retrieval matching threshold | 0.75–0.85 | Filters low-correlation historical documents, ensures referenced documents are directly linked to current review content |
Three common configuration errors
- Symptom: When calling the API, enabling the
detailparameter prevents retrieving both knowledge base call parameters and streaming returned citation data simultaneously. Cause: The return format of theresponseDataparameter was not configured correctly, leading to separation of parameters and results. - Symptom: Returned referenced files do not match the actual production documents being reviewed. Cause: The retrieval matching threshold was set incorrectly, introducing historical data from unrelated batches, or the retrieval scope was not aggregated by production batch.
- Symptom: Citation content is still returned even though the citation return switch is not enabled. Cause: The default configuration of FastGPT v4.17.0 was changed, and the corresponding setting item was not manually reset.
How to verify proper configuration
- Initiate a test API call, check if returned results include the names and batch information of referenced files. Confirm that the content returned by the
detailparameter meets expectations. - Check if the number of returned citations matches the preset maximum limit. Verify that the configurations for
quoteMaxTokenand maximum number of citation sources take effect. - Compare the field units of referenced files with the units of actual production documents. Confirm that no unit misalignment occurs in the retrieval and matching logic.
- Check if the
responseDatafield in the API return contains complete knowledge base call metadata. Confirm that parameter configurations are correct.
All provided configuration values are common starting points. Adjust them based on your own specific samples and use cases.