Forms and Interactions for Kitchen and Bath Appliance

What the data for this category looks like

Marketing data for kitchen and bath appliances comes primarily from official product manuals, e-commerce platform detail page parameters, in-store sales guide brochures, and installation and after-sales documents. Update timing is triggered by new product launches, energy efficiency standard adjustments, or product line iterations, with no fixed cycle. A single document typically includes core product parameters, installation requirements, function descriptions, applicable scenarios, and after-sales terms. Fields combine physical and scenario attributes, such as smoke exhaust volume, rated power, and installation opening size. Supported units include cubic meters per hour, watts, and millimeters.

Constraints on Forms and Interactions

Kitchen and bath appliance data includes many precise physical parameters and scenario adaptation details. Forms must support multiple field types to avoid retrieval errors from ambiguous input. Data updates have no fixed cycle, so the interaction interface must support quick addition and modification of dedicated parameter entries in the knowledge base to adapt to product line changes. Different kitchen and bath appliance categories require distinct pre-collected information, so interaction logic must dynamically switch form fields. User consultations often include real installation environment photos or voice explanations. Forms must support multimodal input and speech-to-text functions, while ensuring accurate recognition of professional terms.

How to Set Configurations

Configuration Item	Recommended Setting	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Kitchen and bath appliance manuals and installation guides are mostly in PDF or high-definition image formats, and single-file size usually does not exceed 500 MB
`PARSE_FILE_TIMEOUT_SECONDS`	`300 seconds`	Complex installation scenario documentation includes numerous step-by-step diagrams and parameter descriptions, requiring longer parsing time
`form_field_required`	Configured by product category	Built-in kitchen and bath appliances require collection of installation opening size, while desktop models require collection of countertop adaptation width. Required fields vary by category
`rag_top_k`	`3–5 entries`	Accuracy of kitchen and bath appliance parameters is critical. Excessive redundant retrieved content will interfere with the model's judgment of core parameters
`multimodal_input_enabled`	Enabled	Users often upload real photos of installation sites or product appearance images for consultations. Image information must first be parsed via a multimodal model
`whisper_asr_enabled`	Enabled	Users may find it inconvenient to manually input information when asking about installation or usage issues. Speech-to-text improves interaction efficiency

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, 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

Symptom: An InvalidParameter error is returned when calling deepseek_reasoner. Cause: The form fails to pass dedicated kitchen and bath appliance parameters, such as smoke exhaust volume and installation size. The model cannot retrieve valid context to complete inference.
Symptom: Speech input recognition results contain professional unit errors. For example, "cubic meters per hour" is recognized as "kilowatts". Cause: The whisper_special_tokens parameter is not configured. No dedicated recognition weight is set for kitchen and bath appliance-related professional terms.
Symptom: Knowledge base retrieval does not trigger after form submission. Cause: The form_field_trigger_rag configuration is not enabled. User-entered product parameters are not automatically spliced into retrieval context.

How to Verify Configurations Are Correct

Upload a complete built-in range hood manual. Check if parsed fields include dedicated parameters such as smoke exhaust volume, rated power, and installation opening size.
Submit a consultation with voice input. Verify that the recognition result accurately identifies professional units like "cubic meters per hour" and "millimeters".
Submit a consultation with a real product photo. Confirm the system first calls a multimodal model to parse image content, then splices parameters to retrieve the knowledge base.

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.