What the Data for This Category Looks Like
Data sources for white goods intelligent due diligence reports include official brand specifications, third-party testing institution reports, e-commerce product parameter pages, and after-sales operation and maintenance records. The data update rhythm changes with new product launches and adjustments to compliance energy efficiency standards, with no fixed weekly update cycle. Each individual data document mostly consists of structured tables paired with explanatory text. Core fields include device model, rated power, volume, appearance dimensions, energy efficiency rating, and warranty period. Units are mostly watts, liters, millimeters, and kilograms. Some documents include explanatory content for multi-country compliance certification marks.
What Constraints These Characteristics Impose on Workflow Orchestration
Dispersed data sources and mixed formats require configuring multiple data source access nodes to adapt to specifications, test reports, and e-commerce data in different formats. Fields include multiple units and compliance identifiers, so a standardized field mapping step must be added to avoid mismatched parameters and units. The unfixed update rhythm requires setting adjustable synchronization cycles to ensure the latest compliance parameters and new product data are included in due diligence reports. Additionally, some documents include long installation and usage instructions, so mixed-format parsing nodes must be adapted; pure text parsing rules alone are insufficient.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Knowledge base recall count | Top 8-12 entries | Core parameters of white goods parameter documents are concentrated in the first half of a single document. Excessive recall increases token consumption, while insufficient recall risks missing key compliance or performance parameters |
Chunk size | 800-1200 characters | White goods parameter descriptions often include long sections of installation and usage notes. Segments that are too long break parameter associations, while segments that are too short lead to unreasonable context splitting |
Data Source Sync Cycle | 7 days | The cycle for new product launches and energy efficiency standard updates is mostly monthly or quarterly. A 7-day synchronization cycle covers conventional update rhythms and avoids data lag |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single white goods testing reports have relatively large parsing content. The conventional 60-second threshold is insufficient for complete parsing |
Search Filter Citation limit | 1500-2000 token | Combined with the token density of white goods parameters, this matches the conventional output length of due diligence reports and avoids exceeding model context limits |
Text Processing Node Trigger Condition | Trigger Condition Contains Unstructured Description Field | Most white goods data consists of structured parameters. Processing is only required for unstructured usage instructions, and pure parameter content does not need processing |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After importing a workflow JSON shared by others, the text processing module does not display normally, and this module option is not available in the local workflow editing interface. Cause: The corresponding text processing plugin is not installed in the local environment, or the plugin version does not match the shared workflow.
- Phenomenon: After the workflow configuration is completed, it cannot be exported as a JSON format file, and there is no export button in the interface. Cause: The sharing permission setting of the workflow is not enabled, or the current account does not have export operation permissions.
- Phenomenon: After setting
Search Filter Citation limitto 2000, the generated due diligence report still exceeds the token limit. Cause: The token allocation is not adjusted based on the units and field length of white goods parameters, and only the fixed upper limit is used without matching the parameter density of the category.
How to Confirm Proper Configuration
- Manually trigger the workflow, parse a single official brand specification document, and check whether the parsed fields include core parameters. If any are missing, adjust the configuration values of
Chunk sizeorPARSE_FILE_TIMEOUT_SECONDS. - View the workflow's data source synchronization logs to confirm that new product data from the last 7 days has been synchronized. If not synchronized, adjust the value of
Data Source Sync Cycle. - Generate a test due diligence report, check whether the token consumption matches the set
Search Filter Citation limit. If it does not match, re-adjust the value range. - Test the session automatic trigger function, observe whether the workflow process starts automatically after the session window loads. If not, check the configuration of the session trigger rules.
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.