What the data for this category looks like
Core business data for jewelry comes from brand SKU management systems, supply chain new product ledgers, and product detail page assets. Update rhythm follows quarterly new launches and monthly restocks. Daily marketing copy is adjusted as needed. Each data document includes fields such as product ID, category (necklace, ring, etc.), material, gram weight (unit: gram), dimensions (unit: millimeter), pricing (unit: yuan), inventory quantity, launch time, long detail page text, and applicable scenario tags. Marketing-related fields also include user preference tags and activity adaptation keywords.
What constraints these characteristics impose on deployment and upgrade
Jewelry has a large number of SKUs and frequent updates. Sufficient storage and database connection pool configuration is required during deployment. Marketing copy lengths vary widely, so timeout parameters must be adjusted in the parsing stage. Data is scattered across relational and non-relational databases. Full backup is required before upgrade to avoid data loss. In power outage scenarios, if persistent storage volumes are not configured, database files may be corrupted, causing startup failure. Additionally, jewelry marketing content needs to adapt to multi-channel distribution, with higher concurrent request volume than general categories, so concurrency limit parameters must be adjusted.
Recommended Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Jewelry detail pages include high-definition main images and multi-dimensional parameter tables, so single file size is larger than general categories |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Jewelry marketing copy and parameter documents are relatively long, so parsing time exceeds average levels |
MAX_CONCURRENT_REQUESTS | First 15 | Jewelry marketing content needs to serve multiple channels such as in-store terminals and community groups, so concurrency demand is higher |
DB_CONNECTION_POOL_SIZE | 20–30 | Jewelry SKU data volume is large, so database connection count must adapt to concurrent synchronization tasks |
RECALL_TOP_N | First 8 | Jewelry marketing requires precise matching of user needs, too many recalled results will increase inference load |
AUTO_SYNC_INTERVAL | 2:00 AM daily | Jewelry new product launches mostly occur during early morning hours, so scheduled synchronization avoids resource occupation during business peaks |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After Docker deployment and power outage restart, the FastGPT container fails to start. Logs show PostgreSQL connection refused and MongoDB connection failure. Cause: The data directory of the database container is not mounted to persistent storage. Power outage causes database files in the local volume to be corrupted.
- Phenomenon: When the number of concurrent users exceeds the threshold, remaining requests remain in a loading state without response. Cause: The
MAX_CONCURRENT_REQUESTSparameter is not adjusted. The default value is too low to meet the multi-channel distribution needs of jewelry marketing content. - Phenomenon: After running the initialization script for upgrading from version 4.8 to 4.9, an HTML page is returned instead of a success prompt. Cause: The access path of the upgrade script is not configured with correct authentication permissions, or an unofficial upgrade script version is used, resulting in a system error page being returned.
How to Confirm Correct Configuration
- Upload a jewelry detail page file containing high-definition main images and detailed parameters, confirm that the upload and parsing process has no errors.
- Initiate multiple concurrent requests to call the marketing content generation interface, observe that all requests return results normally with no prolonged loading states.
- Manually back up the database storage directory, then perform an upgrade operation, confirm that the backup directory content is complete and no abnormal data loss occurs after the upgrade.
- Restart the deployment container, check that the database service logs have no connection exceptions, and the FastGPT management backend can log in normally.
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.