What the Data for This Category Looks Like
Market and yield rate data for paint and ink comes primarily from public statistical datasets released by domestic paint industry associations, and public quote APIs from bulk commodity spot trading platforms. Spot quote data updates the previous day's market trading information daily. Industry production capacity and inventory statistics update weekly operating data every Wednesday. Data is stored in CSV format, with each row corresponding to a single product SKU. Fields include product_name, origin, factory_price, stock_volume, and others. Factory price units are typically yuan per kilogram, while inventory units are tons. Some data sources include latest manufacturer quote notes, with no unified format template.
Constraints on Workflow Orchestration
Differing update cadences across multi-source data require two scheduled trigger node types in workflow configuration. This avoids duplicate data pulls or missed data. Inconsistent field units across data sources require standardization conversion steps in the workflow. This ensures consistent calculation of price and inventory data. A large volume of individual product SKUs requires controlling concurrency and timeout values during batch processing. This prevents triggering interface call restrictions. Aligning multi-source data requires clear matching primary keys. Without these, data confusion or missing fields may occur, harming the accuracy of final broadcast content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
CRON Expression | 0 1 * * * (spot data pull), 0 2 * * 3 (industry data pull) | Matches the update cadence of the two data types, avoids duplicate or missed pulls |
Multi-source Data Matching Primary Key | product_name + origin | Aligns product SKU information across data sources, prevents data confusion |
Data Unit Conversion Rule | Uniformly convert factory prices to yuan per kilogram | Unifies price measurement units across different channels, ensures data consistency |
Batch Processing Node Timeout | 1200 seconds | Covers the time required for batch pull and cleaning of multiple product SKUs |
function call Enable Status | Enabled | Supports workflow orchestration for multi-step data processing, adapts to multi-data source call requirements |
Context Window Size | 8000 characters | Retains complete market data and processing logs, facilitates subsequent troubleshooting and broadcast generation |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: After calling an external data interface in the workflow, the returned result is empty or does not include expected market and yield rate data. Cause: The selected model does not support function call capabilities, or the workflow's function call configuration item is not enabled. This prevents automatic triggering of data pull and merging steps, leading to workflow interruption.
- Phenomenon: When the workflow canvas has more than 20 nodes, drag operations become noticeably delayed, and the interface displays a loading state for over 5 seconds. Cause: The current FastGPT version is 4.6.5. This version's canvas rendering logic does not optimize multi-node layouts, causing performance bottlenecks with large node counts.
- Phenomenon: The workflow outputs sorted content normally in the run preview page, but returns no results when called in the chat window. Cause: The workflow trigger permission for the chat window is not configured, or the workflow's output format does not adapt to the chat scenario's message parsing rules.
How to Verify Proper Configuration
- Check the scheduled task execution log to confirm whether the pull time matches the configured
CRON Expression - Manually trigger the workflow once, and verify that the output fields include unified measurement units and aligned product SKU identifiers
- Call the workflow in different chat sessions to confirm that returned content conforms to the expected broadcast format
- View the workflow run log to confirm that no timeout errors occurred during batch processing steps
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.