What the Data for This Category Looks Like
Data sources for black home appliance research reports primarily consist of publicly available industry research reports, offline retail monitoring data, and financial reports and sales data disclosed by official brand channels. The update rhythm follows monthly retail data updates and quarterly in-depth industry report updates as its main schedule. Document structures typically include modules such as shipment volume by segmented category, average retail price, share by specification, upstream raw material price fluctuations, and impact of industry policies. Fields and units follow clear specifications: shipment volume is measured in 10,000 units, average retail price in yuan per unit, upstream panel procurement cost in US dollars per square meter. Some reports also include sales share data for segmented sizes.
Constraints Imposed on Workflow Orchestration by These Characteristics
First, pulling data from multiple sources requires configuring multiple data source nodes, each connecting to public reports, retail monitoring platforms, and financial report interfaces respectively. This increases the complexity of node orchestration. Second, the monthly and quarterly update rhythm requires configuring scheduled trigger rules for the workflow. This prevents frequent pulling of invalid data or missing the latest data sources. Third, field naming differs across report sources from different platforms. A field mapping node must be added to unify formats, otherwise field mismatches will occur during retrieval. Fourth, black home appliance research reports involve associated data such as upstream raw material prices. Cross-data source association nodes must be configured to ensure retrieval results include complete industry analysis content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recallTopK | Top 8-12 entries | Single black home appliance research report has lengthy content. Too many recalled entries will exceed context limits, while too few will fail to cover segmented category data |
similarityThreshold | 0.72-0.80 | Black home appliance research reports contain many industry terms. A threshold that is too low will introduce irrelevant home appliance category reports, while a threshold that is too high will fail to recall precise segmented data |
chunkSize | 1000-1500 characters | Black home appliance research reports include numerous tables and technical terms. Segments that are too long will damage semantic integrity, while segments that are too short will increase context splicing costs |
workflow_cron | 0 2 1 * * | Retail monitoring data is updated monthly. Scheduled triggers ensure the data source for research report retrieval is the latest version |
enable_field_mapping | Enabled | Field naming varies across different report sources. Enabling this option unifies field formats and avoids field mismatch issues during retrieval |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single in-depth black home appliance research report has lengthy content, resulting in longer parsing duration. Default timeout may cause parsing failures |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values will be 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 Configuration Mistakes
- Phenomenon: When calling the API, the content of the last AI reply will overlay the variable results from the previous node. Cause: The
enable_historyparameter of the AI node in the workflow is not set tofalse, or context variables are not cleared before each call, resulting in context being retained across two consecutive conversations. - Phenomenon: An error "File format not supported" is prompted when exporting the workflow. Cause: The JSON export format supported by FastGPT is not selected, or associated data source configuration items are not checked during export.
- Phenomenon: The research report data returned by the API call exceeds the black home appliance category. Cause: Correct category filtering parameters are not passed in the API request, or the global variable is not bound to the corresponding category filtering condition.
How to Verify Proper Configuration
- Manually trigger the workflow, check if the output variables only include the processing results of the current node, with no historical variable overlay.
- Call the API with preset black home appliance category filtering parameters, verify that the returned research report data only includes content related to black home appliances, with no data from other home appliance categories.
- Export the workflow file, confirm that the file can be properly imported into a new workflow instance, and all configuration items are correctly retained.
- Check the workflow running logs, confirm that the scheduled trigger node starts normally at the set time, with no timeout or failure records.
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.