What the Data for This Category Looks Like
Data for black home appliances primarily comes from official brand parameter databases, product detail pages on mainstream e-commerce platforms, and product manuals from offline authorized stores. Update cycles align with new product launches, firmware updates, and marketing campaign adjustments, with no fixed schedule. The structure of individual data documents includes fields such as model number, appearance dimensions, core functional parameters, official marketing copy, and frequently asked user questions. Dimension units are millimeters, power units are watts, marketing tags are text type, and user questions are a structured set of question-and-answer pairs.
Constraints Imposed on Multi-turn Dialogue and Prompting
Individual black home appliance data includes multi-dimensional parameters, marketing copy, and user questions. Multi-turn dialogue must retain context to connect different dimensions of user questions and avoid repeated inquiries about model information. Parameters have fixed units, so prompts must explicitly require outputs to strictly follow the specified units to prevent unit errors. Marketing copy and user questions are dynamically adjusted with campaigns, so a regular knowledge base refresh mechanism must be configured to ensure dialogue content matches the latest information. Parameter differences across models are significant, so multi-turn dialogue must automatically identify the currently discussed model to avoid mixing parameters across different models.
Recommended Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 10-15 turns of dialogue context | Black home appliance parameters and marketing content are closely linked. Retaining 10-15 turns avoids context loss while controlling token consumption |
knowledgeBaseRefreshCycle | Every 7 days | Marketing campaigns and new product information updates have no fixed schedule. Refreshing every 7 days balances timeliness and resource usage |
systemPrompt | Must strictly use the units specified in the documentation, prioritize matching the parameters of the currently discussed model, and include the corresponding marketing tags in outputs | Matches the characteristics of fixed units for black home appliance parameters and model differentiation, ensuring compliant outputs |
recallTopK | Top 6 results | Individual black home appliance data has multiple dimensions. Recalling 6 results covers parameters, marketing content, and user questions |
similarityThreshold | 0.75 | Black home appliance model numbers are highly distinguishable. A threshold of 0.75 enables accurate matching of knowledge base content for the target model |
streamResponse | Enabled | Marketing content and parameter descriptions are lengthy. Streaming output improves user dialogue experience |
The parameter values provided on this page are common 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 settings.
Three Common Configuration Mistakes
- Issue: No return data when calling the online dialogue interface, with a 400 status code returned. Cause: The
knowledgeBaseRefreshCyclewas not configured, causing the knowledge base to fail to load, orsystemPromptcontained unescaped special characters that triggered interface verification failures. - Issue: After upgrading to v4.8.10, the AI returns the full result at once for short text queries before switching to streaming output. Cause: The trigger conditions for
streamResponsewere not set correctly, or the system default configuration does not match the short text scenario. - Issue: Unable to obtain the output content of the code execution node in the workflow. Cause: The output field of the code execution node was not mapped to a global variable, or the dialogue node did not correctly reference the corresponding field name of the global variable.
How to Verify Successful Configuration
- Navigate to the knowledge base management page, check if the
knowledgeBaseRefreshCycleconfiguration value matches the preset value, trigger a manual refresh, and verify that a knowledge base update log is generated. - Initiate a test dialogue, enter a short text query that includes a model number and parameter question, observe if the output is returned in streaming format and uses the units specified in the documentation.
- Navigate to the workflow debugging page, run a test case that includes a code node and a dialogue node, and check if the output field from the code execution exists in the global variable list.
- Call the online dialogue interface, check if the response header includes the
Content-Type: text/event-streamidentifier to confirm that the streaming output configuration is active.
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.