What the data for this category looks like
Kitchen and bathroom appliance research report data primarily comes from public reports released by the China Household Electrical Appliances Association, official brand disclosure channels, and third-party market research institutions. The standard update cycle is quarterly, with temporary updates during new product launches or industry exhibitions. Document structure typically includes three core sections: product parameter summary tables, market competition analysis, and channel sales data. Fields include product name, rated power, energy efficiency level, installation dimensions, recommended retail price, and more. Power is measured in watts, dimensions in millimeters, and energy efficiency levels are graded using Arabic numerals.
What constraints do these characteristics impose on tool calling and plugins
The structured fields for kitchen and bathroom appliance research reports have clear definitions and fixed units. This requires precise matching of field names and units during tool calls to avoid unit confusion or missing fields. Update cycles are irregular and include temporary updates. This requires plugins to support manual cache refresh and adapt to fast retrieval logic for temporary updates. Documents include multi-dimensional comparison data. This requires tool calls to support filtering retrieval results by dimensions such as brand and energy efficiency level. Product parameters require high precision. This requires format validation of extracted fields during tool calls to ensure compliance with industry general standards.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
max_tool_calls | 3-5 | Kitchen and bathroom appliance research report retrieval typically requires 3 rounds of tool calls: obtaining parameter data, market data, and competitor comparison. Excessive calls will cause context overflow |
tool_call_timeout | 15-30 seconds | Response times for third-party research report data sources vary. This interval covers most normal response scenarios and avoids prolonged wait times slowing the overall workflow |
structured_extract_schema | ["product_name", "rated_power", "energy_level", "install_size", "price_range"] | Matches the core structured fields of kitchen and bathroom appliance research reports, ensuring tools can accurately extract target data |
rag_recall_count | Top 8-12 | Single research report content is lengthy. Too many recalled entries will exceed the context window limit, while too few may miss critical parameter information |
cache_expire_seconds | 86400-604800 seconds | Adapts to the standard quarterly update cycle for kitchen and bathroom appliance research reports. Temporary updates can overwrite old data via manual cache refresh |
plugin_auth_type | api_key | Most public research report data sources use API key authentication. This configuration enables quick access verification for third-party interfaces |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: Calling a custom research report plugin returns a
401 Unauthorizederror. Cause: A valid data source API key was not entered in the tool configuration, orplugin_auth_typewas not correctly set toapi_key. - Symptom: Structured fields returned by tool calls are empty, for example the
energy_levelfield has no valid content. Cause: The field was not configured instructured_extract_schema, so the tool cannot identify and extract the corresponding data. - Symptom: After uploading a kitchen and bathroom appliance research report PDF file, the tool does not automatically trigger the parsing process. Cause: The file trigger mode was not set to automatic, so the model cannot independently determine whether to read the file content.
How to confirm the configuration is complete
- Call the configured tool plugin, pass the specified kitchen and bathroom appliance research report retrieval keyword, and confirm that structured data including core fields such as product name and rated power is returned, matching expected field extraction.
- Upload a kitchen and bathroom appliance research report PDF file, trigger the tool call process, and confirm that the tool automatically initiates the file parsing and content extraction steps.
- View the tool call logs, confirm that the number of calls does not exceed the set limit of
max_tool_calls, and that response times meet business requirements. - Manually trigger the cache refresh operation, verify that newly uploaded or updated research report data can be successfully recalled.
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.