What the data for this category looks like
Carbon steel-related data primarily comes from commodity exchange spot monitoring systems, steel plant factory outbound ledgers, and industry association public reports. Update cadences vary across data sources: spot transaction prices update daily, steel plant production scheduling plans update weekly, and monthly production statistics update monthly. Standard document structures include fields such as product name, specification parameters (thickness, width, yield strength), origin, daily average price, weekly fluctuation range, and cumulative production. Most field units are yuan/ton, ten thousand tons, and megapascals.
What constraints these characteristics impose on workflow orchestration
Differing update cadences across multiple data sources require layered scheduled trigger nodes in the workflow, matching daily, weekly, and monthly data pull windows to avoid pulling invalid, unupdated data. Numerous and inconsistently unitized specification parameter fields for carbon steel require adding standardized validation nodes in the workflow to unify units and formats for fields such as yield strength and thickness. Large monthly production data volumes require configuring segmented pull and merge nodes to reduce timeout risks for single requests. Differing return formats across data sources require configuring format conversion nodes to align data and ensure consistent fields for subsequent analysis.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Segment Length | 800–1200 characters | Carbon steel data documents often contain long specification parameters. Excessively long segments cause context overflow, while excessively short segments disrupt data logic |
Number of Retrieved Entries | Top 8–12 entries | Carbon steel due diligence requires covering multi-dimensional data including spot prices, scheduling, and production. An appropriate number of retrieved entries ensures comprehensive information |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Monthly production statistics documents have large file sizes. Extending parsing timeout prevents interruptions |
TOOL_CALL_TIMEOUT | 30 seconds | Adapts to response times of multiple data source APIs, preventing tool call failures due to timeout |
VARIABLE_PASS_MODE | JSON format | Ensures variables passed via APIs are correctly parsed, preventing prompt variables from failing to take effect |
Similarity Threshold | 0.75–0.85 | Filters low-relevance carbon steel data entries, ensuring information accuracy of due diligence reports |
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 targeted analysis. Testing on local samples is recommended before finalizing settings.
Three Common Mistakes
- Phenomenon: After prompt variables are passed via API, returned content does not replace variable values and matches preset content. Cause:
VARIABLE_PASS_MODEis not configured correctly, so variables are not parsed correctly by the system. - Phenomenon: Workflow debugging shows tool call failed with timeout status code. Cause:
TOOL_CALL_TIMEOUTis not set to a sufficiently long value, causing multi-data source API response times to exceed the preset threshold. - Phenomenon: Target knowledge base cannot be dynamically selected via variables, and the plugin always reads the default knowledge base. Cause: Variable binding is not enabled in plugin configuration, and knowledge base identification parameters are not passed correctly.
How to Confirm Proper Configuration
- Manually trigger the workflow, verify that prompt variables are correctly filled with no empty or unreplaced values.
- Check workflow run logs to confirm tool call response times do not exceed the
TOOL_CALL_TIMEOUTsetting. - Sample parsed carbon steel data entries, verify that specification parameter units are unified with no format confusion.
- Adjust scheduled trigger configurations to verify that the workflow automatically executes pull tasks at preset times.
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.