Workflow Orchestration for Coke Intelligence Due Diligence

What the data for this category looks like

Coke-related due diligence data comes from Dalian Commodity Exchange futures listing data, coastal port inventory ledgers, and monthly operation reports from steel industry associations. Each source has a unique update frequency:

Futures data updates daily after market close
Port inventory data updates weekly
Industry operation reports release monthly

Two document structure types exist:

Futures data uses structured tables, with fields including delivery grade, transaction price, and open interest
Industry reports use plain text, with content including production capacity, operating rate, and procurement volume

Most field units are yuan/ton, ten thousand tons, and ten thousand tons/year. Some cross-source data sets use inconsistent units.

Constraints on workflow orchestration

These data characteristics impose constraints on workflow design:

Mismatched update frequencies across sources require configuring multiple scheduled trigger nodes. Each node aligns to the update cycle of one data type: futures, port inventory, or industry reports.
Differences in document structures require adapting different parsing rules. Use table parsing nodes for structured tables, and general text extraction nodes for plain text reports.
Inconsistent field units require adding unit conversion nodes to standardize cross-source data.
Long industry report content requires adjusting text extraction node segmentation parameters to avoid exceeding the model's context limit per single input.

How to set the configurations

Configuration Item	Recommended Setting	Rationale
`Scheduled Task Interval`	`Twice daily, at 16:30 and 10:00 respectively`	Aligns with the closing time of Dalian Commodity Exchange coke futures and the release time of port inventory weekly reports
`Text Segmentation Length`	`800–1200 characters`	Adapts to the effective information density per segment of coke industry reports, avoiding exceeding the model's context limit
`API Call Timeout`	`600 seconds`	Covers the standard response duration of external industry report interfaces, reducing task failures caused by temporary timeouts
`Field Mapping Rule`	`Map according to the standard of "delivery grade - price - inventory"`	Unifies field names and units across multiple data sources, eliminating format differences between cross-source data
`Extraction Confidence Threshold`	`≥0.7`	Ensures the accuracy of coke data extraction, filtering invalid content with low confidence
`Interface Retry Count`	`3 times`	Addresses temporary fluctuations in external data sources, reducing the probability of single call failure

The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and testing on own samples is recommended before finalizing settings.

Three common mistakes

Symptom: When creating a Question Classification Node with the system-initialized AI model, a 500 Internal Server Error occurs when clicking run or saving and publishing. The error resolves after switching to another AI model. Cause: The workflow call permission for the initialized model is not enabled, or the model's token quota is insufficient to support the context requirements of the classification task.
Symptom: After configuring a Text Content Extraction Node, the output JSON result is an empty array. Cause: The Extraction Field Matching Rule is not set, or the segmentation length is set too long, preventing the model from identifying valid extraction content.
Symptom: When AI Reply Annotation Trigger Timing is set to after the stream reply completes, the annotation content does not generate synchronously with the complete conversation context. Cause: The segmented return mechanism of the stream flow is not clearly defined, so the context bound to the annotation only includes the last segment of reply content.

How to confirm the configuration is complete

Manually trigger the workflow, and confirm that the output content of each node matches the standard field format of coke data.
Review the workflow run logs, and confirm there are no records of node execution timeouts, field parsing failures, or interface call errors.
Adjust the unit format of the test data source, and verify that the Field Mapping Rule completes unit unification and field alignment.
Simulate a temporary timeout of the external interface, and confirm that the Interface Retry Count configuration takes effect, with the task not failing directly.

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.