Data characteristics of this category
Black home appliance investment research data comes primarily from official brand specification documents, industry association monitoring reports, e-commerce platform transaction data, third-party testing institution reports, and supply chain price data. Update frequency adjusts flexibly based on new product launches, industry energy efficiency standard revisions, and supply chain price fluctuations. Most documents combine structured tables and long-form text, including physical parameter fields with clear units, rating identifiers, and price ranges. Some documents include high-resolution photos and equipment disassembly data.
Constraints on deployment and upgrade from these characteristics
Configure precise field extraction rules during deployment to avoid unit confusion or parameter matching errors during recall. Structured parameter fields are numerous and include clear units. Adapt multi-format parsing plugins during deployment to support multiple document types. Synchronously update parsing rules during upgrades to support new document formats. Reserve video memory resources for multimodal models during deployment to support multimodal indexing needs for images and disassembly data, and avoid resource shortages during parsing or recall. Configure flexible incremental update trigger mechanisms during upgrades for non-fixed update frequency data sources, to avoid excessive server resource usage from full reindexing. Configure permission isolation parameters during deployment to restrict unauthorized access to documents that contain sensitive supply chain data.
Configuration settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Black home appliance documents often include multi-page PDFs and long parameter tables. A standard 60-second timeout frequently causes parsing tasks to fail |
Chunk size | 800–1200 characters | Black home appliance parameter documents are mostly structured paragraphs. This length preserves the connection between parameters and context, avoiding split breaks |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some official brand documents include high-resolution disassembly photos, leading to large single-file sizes |
Recall count | top 8–10 entries | Investment research scenarios require covering multi-dimensional parameter comparisons. Too many recalled entries add context redundancy, while too few miss critical information |
Similarity threshold | 0.75–0.85 | Black home appliance parameter fields are mostly standardized content. A threshold that is too high misses similar parameter comparison information, while a threshold that is too low introduces irrelevant data |
ENABLE_MULTIMODAL_RETRIEVAL | enabled | Some documents include disassembly photos and real-shot images. Multimodal retrieval must be enabled to cover visual information |
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 configuration mistakes
- The symptom is a
CUDA out of memoryerror during local deployment, with the interface showing a knowledge base parsing task failure. The cause is failing to allocate sufficient video memory for the multimodal document indexing needs of black home appliances, and failing to enable quantization deployment which leads to excessive video memory usage. - The symptom is a
500status code returned when calling the MCP MySQL query service with a locally privately deployed large model. Logs show field format mismatches. The cause is failing to configure output format constraints for the large model based on the field types of black home appliance structured parameters, leading to query parameters returned by the large model not matching database fields. - The symptom is that image parameters in the knowledge base do not refresh synchronously with updates to the brand's official website, with the interface showing that the image indexing status has not updated. The cause is failing to configure an incremental update trigger rule based on file hash or update time, only performing full indexing which leaves old images unreplaced.
How to verify correct configuration
- Upload a single black home appliance document that includes high-resolution photos and a long parameter table. Check the parsing task status and field extraction results, confirm that parameter units match the original document.
- Trigger an incremental update task, compare the number of knowledge base index entries before and after the update, confirm that only newly added or modified documents are reindexed.
- Call a test interface, input a query statement targeting black home appliance parameters, check that the number of returned recalled entries and similarity matching meet the preset configuration.
- Start a multi-node deployment test, simulate multiple concurrent requests, confirm that the service has no errors and response delays meet preset standards.
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.