What the Data for This Category Looks Like
Snack food investment research data primarily comes from brand SKU profiles, offline terminal sales performance reports, e-commerce platform sales and review data, and industry association category monitoring reports. Data update rhythms adjust with new product launches and promotion nodes. Bulk updates typically occur quarterly or monthly, with daily incremental updates for SKU price adjustments and inventory changes. Document structures include fields such as SKU code, product name, ingredient list, net content, shelf life, supply price, retail price, channel share, and consumer review keywords. Net content uses grams or kilograms as units. Shelf life uses months or days as units. Ingredient lists are usually long text paragraphs.
Constraints on Deployment and Upgrade
Multi-source data access requires support for multi-API connection configuration during deployment. This avoids repeated code modifications later. Long-text ingredient lists and sales performance reports require the parsing phase’s chunking logic to adapt to long paragraph processing. Upgrades must maintain compatibility with existing chunking rules. Multiple fields with different units require adding configurable switches for unified unit conversion during preprocessing. Bulk data incremental sync requirements mean upgrade phases cannot interrupt existing sync tasks. They must also support flexible adjustment of incremental sync frequency. For scenarios with large SKU counts, deployments must configure vector database sharded storage. This prevents retrieval performance degradation.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Snack food documents include long ingredient lists and quarterly sales reports, requiring sufficient time to complete full parsing |
maxChunkSize | 800–1200 characters | Balances complete long-text semantics and recall accuracy, avoiding excessive fragmentation of professional content such as ingredient lists |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports bulk upload of large files such as quarterly sales reports and industry monitoring reports |
recallTopK | Top 8 entries | Investment research analysis requires cross-SKU horizontal comparison data, so the number of recalled entries must meet multi-dimensional information retrieval needs |
chunkOverlap | 100–150 characters | Retains contextual association between chunks, preventing long ingredient lists from being split into unrelated segments |
AUTO_SYNC_INTERVAL | Every 7 days | Matches the regular cycle of new product launches and promotion adjustments for snack foods, with sync frequency adjustable as needed |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Errors
- Issue: After deploying a packaged Docker image, accessing via a secondary domain name returns a 404 status code. Cause: The secondary domain name routing rules for Nginx reverse proxy are not configured, and the container internal port is not mapped to the access path of the corresponding domain name.
- Issue: After upgrading to version 4.9.6, the container fails to start with the error
Container obcannot run normally. Cause: The persistent storage volume of the original vector database was not mounted during the upgrade, resulting in loss of the original knowledge base index files and inability to load retrieval data. - Issue: After knowledge base splitting in version 4.8.10, long ingredient lists are truncated into multiple independent segments, making it impossible to match complete ingredient information during retrieval. Cause: The
maxChunkSizeandchunkOverlapparameters were not adjusted, and the default chunking configuration caused professional text to be fragmented.
How to Confirm Proper Configuration
- Upload a snack food document containing a complete ingredient list and sales data, check that the parsed chunks retain complete text content with no obvious truncation or data loss.
- After configuring the secondary domain name, access the deployed FastGPT instance via the domain name to verify that the interface returns normally, with no connection timeouts or 404 errors.
- After executing the version upgrade script, check that the container logs have no error messages, the index data of the original knowledge base is not lost, and retrieval requests can be initiated normally.
- Trigger an automatic sync task to verify that incremental data is synced to the knowledge base on time, with no data omissions or format conversion errors.
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.