What the data for this category looks like
Intelligent due diligence data for small home appliances in the financial, insurance, and wealth management sectors primarily comes from brand official parameter pages, e-commerce platform product detail pages, national compulsory product certification (3C) reports, energy efficiency label documents, and after-sales maintenance manuals. Update schedules align with new product launches. Regular in-stock models’ parameters are updated quarterly.
Each due diligence document includes four structural sections: basic attributes, performance parameters, compliance certifications, and after-sales terms. Fields cover rated power (unit: watt), product dimensions (unit: millimeter), total weight (unit: kilogram), certification number, launch date, and more. Subcategories such as kitchen small home appliances also include specialized parameters like heating power and rotation speed.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
The segmented and multi-dimensional nature of small home appliance parameters requires multi-turn dialogue to guide users to focus on specific SKU models, avoiding parameter matching errors caused by generalized queries. The length and field density of a single document requires prompt engineering to clearly specify the priority of extracted fields, preventing information loss caused by context overflow.
The differences between different model parameters requires multi-turn interactions to bind the dedicated parameter library of the corresponding SKU, avoiding parameter confusion across models. Compliance fields such as 3C certification numbers are mandatory extraction items. Multi-turn dialogue must include a confirmation step to ensure no omissions.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | A single small home appliance due diligence document typically contains 2000-5000 characters of parameter content. Multi-turn interactions need to retain complete parameter fragments and conversation history |
CHAT_FILE_EXPIRE_TIME | 7 days (platform default maximum limit) | Small home appliance due diligence files are mostly for temporary analysis purposes. A 7-day expiration aligns with conventional usage cycles. Adjustments beyond this limit require a formal application |
PARSE_SEGMENT_LENGTH | 1000–1500 characters | Small home appliance parameters contain multi-dimensional associated information. Segments that are too long will destroy the logical connection between parameters, while segments that are too short will lead to incomplete field splitting |
RECALL_TOP_K | Top 6–8 entries | Small home appliance parameters have a large number of fields. Enough associated fragments need to be recalled to cover the three core content types: basic attributes, performance parameters, and compliance certifications |
SIMILARITY_THRESHOLD | 0.75–0.85 | Small home appliance model names have high similarity. Low-match irrelevant parameter documents need to be filtered out to avoid extracting incorrect model data |
LOG_USER_ID_ENABLE | Enabled | User identification must be bound to track logs for corresponding due diligence conversations, meeting subsequent troubleshooting and permission management requirements |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: Conversation files are automatically cleared within 7 days, making historical due diligence records unavailable. Cause: The
CHAT_FILE_EXPIRE_TIMEparameter was not adjusted, or the set value exceeded the platform’s maximum allowable limit. - Phenomenon: Parameter extraction misalignment occurs in batch-executed AI dialogue nodes, with parameters from different small home appliance models mixed together. Cause: Independent SKU parameter context was not bound to each dialogue node, leading to cross-contamination of multi-turn interaction contexts.
- Phenomenon: Conversation logs cannot be associated with the specific user who initiated the due diligence. Cause: The
LOG_USER_ID_ENABLEconfiguration item was not enabled, so the system did not record the user identification field.
How to confirm correct configuration
- Launch a multi-turn dialogue targeting a specified small home appliance model, and check that the conversation context retains complete parameter fragments with no truncation or confusion.
- After uploading a small home appliance due diligence document, review the parsed segmented content to confirm that the segment length meets the configured requirements.
- View the conversation logs to confirm that each record is associated with the corresponding user identification field.
- Test batch parallel dialogue nodes to confirm that the parameters returned by each node only correspond to the specified small home appliance SKU, with no cross-contamination 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.