What the data for this category looks like
Data sources include brand-issued material quality inspection reports, supply chain raw material traceability archives, industry association-released category compliance standard documents, and physical test retention records. Updates are triggered by new product launches, compliance standard revisions, or raw material batch changes, with no fixed cycle. Document structures are mostly multi-chapter formats, including basic attribute fields, test parameter fields, and traceability association fields. Test parameters often include quantified content with units such as purity, weight, and coating thickness. Field units are mostly %, g, μm, and similar units.
What constraints do these characteristics impose on knowledge base retrieval and recall?
The multi-field quantified attributes, non-fixed update rhythm, and multi-chapter document structure of the jewelry category bring multiple constraints to retrieval and recall. Quantified test parameters come with dedicated units. Unit-related information must be strictly matched during recall to avoid mixing data from different batches or specifications of jewelry. After multi-chapter documents are split, quality inspection parameters and traceability information may easily separate. Associated fragments of documents from the same category must be recalled uniformly. The non-fixed update cycle requires the knowledge base synchronization mechanism to pull the latest compliance documents in a timely manner, preventing recall of outdated data from affecting the accuracy of due diligence conclusions.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Jewelry documents often contain long sections of test data and traceability information. This segment length preserves the complete logic of a single archive, avoiding broken associated information after splitting |
similarityThreshold | 0.72–0.85 | Jewelry due diligence requires precise matching of quantified parameters with units such as material and weight. A threshold that is too low will retrieve irrelevant batch data, while a threshold that is too high will not cover valid category-specific differences |
topK | Top 6–8 results | Jewelry intelligent due diligence needs to cover three core pieces of information: material testing, traceability records, and compliance standards. Retrieving more results can cover multi-dimensional associated documents |
parseTimeout | 120 seconds | Parsing large multi-chapter jewelry quality inspection documents requires longer processing time to avoid interruptions that cause file parsing failures |
fileMaxSize | 200 MB | Jewelry quality inspection reports often include high-definition physical images and test charts. This size can accommodate a single complete archive |
trainingType | qa_pair, raw_text | Jewelry due diligence needs to support both structured parameter retrieval and unstructured document recall. This combination of types covers both types of data requirements |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: After uploading a group of jewelry documents that include chapter titles, links, and introductions, the retrieved information from the same group is returned split. Cause: No document association grouping configuration was set. Documents are split by fixed length by default, and the binding relationship of information within the group is not preserved.
- Phenomenon: When calling the knowledge base "create training order" API, a
400 Bad Requesterror is returned. Cause: The value of the incomingtrainingTypeparameter is not on the officially supported list, or the format does not meet the API requirements. - Phenomenon: When retrieving jewelry due diligence reports, the units of quantified parameters in the recall results are missing or do not match the actual situation. Cause: No unit verification rule for similarity matching was configured, or the segment length was set improperly causing unit information to be split into adjacent segments and unable to be recalled uniformly.
How to confirm the configuration is correct
- Upload a multi-chapter jewelry quality inspection document, check the parsed segment structure, and adjust the segment configuration to preserve the complete information of a single chapter.
- Initiate a simulated retrieval request, enter a query containing quantified parameters, and check whether the recall results cover the three core types of information: material, traceability, and compliance. Adjust the number of retrieved results and similarity threshold to meet requirements.
- Call the knowledge base API with test training type parameters, confirm that the API returns no parameter errors, and verify the validity of the training type configuration.
- Upload a single jewelry document with attachments, confirm that the parsing task completes normally, and adjust the parsing timeout configuration to adapt to the document processing duration.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.