What the Data for This Category Looks Like
Home goods-related data primarily comes from brand product manuals, official detail pages, supply chain inventory ledgers, and marketing material libraries. Data update rhythm adjusts with new product launches. Regular SKU information remains stable long-term, and is only updated when specifications are adjusted, prices change, or inventory fluctuates. Most documents are structured tables and detail pages combining text and images. Core fields include SKU code, material, dimensions, applicable scenarios, inventory quantity, and recommended selling price. Units for dimension fields are mostly centimeters or millimeters, units for inventory fields are pieces or sets, and selling price fields retain two decimal places.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Home goods have numerous structured fields with clear units. In multi-turn dialogue, SKU codes and parameter units must be accurately matched to avoid mixing information from different SKUs. Data updates do not follow a fixed cycle; unsynchronized information after new product launches or inventory changes may cause outdated content to be returned in dialogues. Real-time data verification trigger logic must be configured. The document structure combining text and images requires multi-turn dialogue to distinguish between parameter text and the call path for display materials, to avoid mistakenly using product image descriptions as parameter responses. Additionally, marketing customer acquisition scenarios require recalling applicable information for multiple SKUs simultaneously, so context length must accommodate batch calls of multiple sets of parameters.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Home goods have rich multi-SKU parameters, and multi-turn dialogue needs to retain multiple sets of SKU codes and applicable information to avoid loss of critical parameters due to context overflow |
recallCount | Top 6–8 results | Marketing customer acquisition scenarios need to cover frequently consulted matching product parameters. Too many recalls will lead to redundant responses, while too few will fail to meet user needs |
UPLOAD_FILE_MAX_SIZE | 200 MB | Home goods product manuals mostly consist of high-definition image collections and multi-page PDFs, with single-file volume typically larger than that of general product categories |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large product manuals requires processing large amounts of images and text, which takes longer |
SIMILARITY_THRESHOLD | 0.75–0.85 | SKU codes and product keywords consulted by users need to be accurately matched to avoid recalling irrelevant parameters |
rerankTopN | Top 3–4 results | Retain the most relevant SKU parameters after reranking, improving the accuracy of parameter calls in multi-turn dialogue |
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 targeted analysis, and testing on local samples is recommended before finalizing settings.
Three Common Misconfigurations
- Front-end conversation records disappear after refreshing the conversation window, but background conversation lists can still be accessed. This occurs because front-end context storage configuration does not enable persistence, and conversation records are only cached in browser memory, which is released after refreshing.
- Attachments uploaded in containerized deployment environments cannot be recognized, while local development environments can parse them normally. This occurs because the corresponding file storage directory is not mounted during containerized deployment, or system libraries required for file parsing are not properly installed.
- Inconsistent product parameter units are returned in multi-turn dialogue. This occurs because the prompt does not unify unit conversion rules, and does not specify that all dimension parameters must be converted to a unified unit.
How to Verify Proper Configuration
- Test multi-turn dialogue, input inquiries about different SKUs, and check whether returned parameters match the latest information for the corresponding SKUs.
- Upload a home goods product manual PDF that meets the configured size limit, and verify that it can be properly parsed and generate knowledge base entries.
- Refresh the conversation window, and check whether front-end conversation records match the conversation content stored in the background.
- Adjust the similarity threshold, test inquiries about the same product keyword, and observe whether the number of recalled SKUs meets expectations.
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.