What the data for this category looks like
Jewelry research report data for financial and wealth management scenarios mainly comes from public reports of domestic fashion jewelry industry associations, brand new product launch documents, and sales monitoring data from cross-border and domestic e-commerce platforms. The update rhythm is flexibly adjusted according to the industry new product cycle. Regular quarterly updates are conducted, and monthly supplementary documents are added during peak new product seasons such as Valentine's Day and Christmas. The document structure includes fields such as material parameters, process details, price ranges, supply chain cost proportion, and popular trend analysis. Units include gram weight, unit price (yuan/item), shipment volume (ten thousand items), material content values, etc. Some documents are attached with product photos and process flow charts.
What constraints these characteristics impose on deployment and upgrade
Multi-source data for jewelry research reports has significant format differences. There are standardized PDF reports released by associations, structured Excel documents from brand merchants, and CSV-format sales data exported from e-commerce platforms. During the deployment phase, parsing rules adapted to different formats must be configured to avoid missing fields or format chaos after parsing. The update rhythm is flexibly adjusted according to the new product cycle. The post-deployment upgrade link must support dynamic modification of the cycle parameters of scheduled synchronization tasks without requiring a full redeployment of the system. Fields include non-universal professional parameters such as material content and process details. When upgrading the vector recall model, the tokenization and vectorization logic must be adjusted to ensure the semantic matching accuracy of professional fields. Some data comes from e-commerce monitoring, so dedicated deduplication rules must be configured to avoid duplicate entries of sales data for the same product style and improve retrieval accuracy.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 150–250 MB | Jewelry research reports are mostly documents combining text and images. The size of a single document usually falls within this range to avoid upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Some long documents contain multiple pages of process details and tables, which take a long time to parse. 600 seconds covers most scenarios |
RECALL_TOP_N | Top 8–12 entries | Jewelry research reports have many professional fields. A sufficient number of entries must be recalled to cover relevant parameters and avoid missing key information |
SIMILARITY_THRESHOLD | 0.72–0.78 | Semantic matching for professional terms requires a relatively high threshold to avoid recalling irrelevant general fashion content while retaining sufficient matching results |
SCHEDULE_SYNC_INTERVAL | 7–30 days | Regular research reports are updated quarterly. The interval can be shortened to 7 days during peak new product seasons, supporting dynamic adjustment of the synchronization cycle |
MARKER_IMAGE_TAG | v0.1.0 | Meets mirror version compatibility requirements to ensure normal operation of image-based research report parsing functions |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by data format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing values.
Three common mistakes
- Phenomenon: A
504 Gateway Timeouterror occurs after deploying the quick experience version. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted, and the long document parsing timeout was not covered. - Phenomenon: The system cannot respond normally to conversations and returns empty results. Cause: The large model key was not configured correctly, or the key is not bound to the corresponding service permissions.
- Phenomenon: The mirror fails to start after executing the
docker run --gpus all -itd -p 7231:7231command. Cause:MARKER_IMAGE_TAGwas not specified as a compatible version, or the host machine's GPU driver does not match the mirror version, and does not meet the dependency requirements of FastGPT 4.9.0.
How to confirm the configuration is complete
- Upload a jewelry research report document that includes process tables and material parameters, check if the parsed fields fully match the preset professional fields to confirm that the parsing rules are effective.
- Manually trigger a scheduled synchronization task, check the data deduplication results in the synchronization log to confirm that the deduplication rules are configured correctly.
- Submit a query containing jewelry professional terms, verify the relevance of the recall results to confirm that the similarity threshold and recall count configuration meet business requirements.
- Check the system version information to confirm that the currently running FastGPT version is compatible with the
MARKER_IMAGE_TAGversion and meets deployment requirements.
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.