What this category’s data looks like
Data sources for cement due diligence reports include monthly statistical bulletins from building materials industry associations, cement plant factory ledgers, supply waybills, and test reports from third-party quality inspection institutions. Data updates follow two schedules: factory batch data updates daily, industry statistical data updates monthly. Typical document structures include fields such as batch number, strength grade, 3-day compressive strength, 28-day flexural strength, supplier name, and production date. Units use megapascals (MPa) and standard date formats consistently. Some reports also include image files from quality inspection steps.
What constraints these characteristics impose on workflow orchestration
The high-precision requirements for multiple fields in cement data require workflows to split into independent nodes such as text extraction, field validation, and multimodal adaptation. This avoids reduced accuracy caused by a single node handling too much content. Daily updated factory batch data requires workflows to support scheduled trigger pulls, and cannot rely on static local data sources. Association logic between fields (such as matching production dates to batch numbers) requires workflows to include built-in association validation steps. This prevents invalid data from entering the report generation phase. Mixed input of multiple data types (text ledgers and quality inspection images) requires workflows to support assigning different processing models based on data type.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Cement due diligence reports often include multiple pages of quality inspection data and ledgers, leading to long parsing times |
TEXT_EXTRACT_MIN_CONFIDENCE | 0.85 | High precision is required for cement fields, so low-confidence extraction results must be filtered |
WORKFLOW_TRIGGER_CRON | 0 0 2 * * ? | Cement factory data updates daily, so scheduled pulls for the latest batch data are required |
MULTIMODAL_MODEL_SWITCH | Auto-switch based on input data type | Cement data includes text ledgers and quality inspection images, so different model capabilities must be supported |
TOOL_CALL_RETRY_TIMES | 3 times | Supply chain traceability data pulls may fail due to interface fluctuations, so a retry mechanism must be configured |
UPLOAD_FILE_MAX_SIZE | 50 MB | Single complete cement due diligence report files are usually large in size |
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
- Issue: A
504 Gateway Timeouterror is returned when calling supply chain data interfaces in a workflow. Cause: TheTOOL_CALL_RETRY_TIMESparameter is not configured, or the retry count is too low. This causes direct failure during interface fluctuations. - Issue: Empty fields are returned by the text extraction node, and preset prompt responses are not triggered. Cause: The
TEXT_EXTRACT_MIN_CONFIDENCEthreshold is not configured, or the threshold is set too high. This filters out normal extraction results. - Issue: Plain text is not assigned to the tool call node when both quality inspection images and text ledgers are input into a workflow. Cause: The auto-switch rule for
MULTIMODAL_MODEL_SWITCHis not enabled. This assigns all data to a single model uniformly.
How to Verify Proper Configuration
- Upload a standard cement quality inspection PDF file, check the output fields of the text extraction node, and confirm that all required fields are correctly extracted.
- Configure a scheduled trigger task, wait for the preset time, then check the workflow execution logs to confirm that the task starts automatically and pulls the latest data.
- Input plain text ledgers and quality inspection images separately, check the node assignment results of the workflow, and confirm that data types match the assigned models.
- Simulate an interface fluctuation scenario, call the tool node, and confirm that the retry mechanism is triggered and the execution eventually succeeds.
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.