Workflow Orchestration for Coke Marketing Content

Coke-related data mainly comes from public statistics of the Dalian Commodity Exchange, domestic coal industry association, major ports and steel

What the data for this category looks like

Coke-related data mainly comes from public statistics of the Dalian Commodity Exchange, domestic coal industry association, major ports and steel mills. Data updates follow two rhythms: futures market data is updated in real time per trading day, spot transaction data is updated once daily. Most data is formatted as structured tables or CSV files, with a small number of industry analysis documents being unstructured text. Standard fields include daily benchmark price, spot transaction price, total port inventory, total warehouse receipts, and average daily steel mill procurement volume. The units are yuan/ton, yuan/ton, 10,000 tons, 10,000 tons, 10,000 tons respectively.

What constraints do these characteristics impose on workflow orchestration

The real-time or daily update rhythm of coke data requires workflow trigger frequencies to match business needs, to avoid resource waste or delayed content. The high proportion of structured data requires configuring structured data parsing nodes in the workflow to adapt to multi-field extraction rules. The presence of unstructured industry documents requires adding text segmentation and keyword extraction steps to the workflow. Differences in field naming across different data sources require configuring field mapping nodes in the workflow to unify data standards. The requirement for marketing content to match the latest market trends requires embedding a data validation step in the workflow to ensure the latest updated dataset is called.

How to set the configurations

Configuration ItemRecommended ValueBasis for This Value
PARSE_FILE_TIMEOUT_SECONDS300 secondsCoke industry documents are mostly structured tables or CSV files. 300 seconds is sufficient to process batch files and avoid parsing timeouts
maxContext0–2Coke marketing content is mostly generated based on real-time market trends, so excessive historical context is not needed to avoid interference from redundant information
Scheduled Trigger IntervalDaily 09:00 or Hourly (trading days)Matches the update rhythm of spot data (updated once daily) and futures data (updated in real time per trading day)
Recall countTop 3–5 entriesAccurately covers core coke market indicators. Excessive recall will dilute the information density of core marketing content
Chunk size800–1200 charactersSingle segments of coke industry documents have high information density. This segment length can retain complete indicator logic
WORKFLOW_TIMEOUT600 secondsCovers the entire process of data parsing, RAG recall and content generation, to avoid mid-run timeout interruptions

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. It is recommended to test on samples matching the actual deployment before finalizing values.

Three common mistakes

  • Phenomenon: The workflow runs and returns a 504 Gateway Timeout error or shows a timeout failure status. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter is not adjusted according to the parsing requirements of coke industry documents. The default timeout period is too short to complete parsing of batch structured files.
  • Phenomenon: After configuring an external page call link in the workflow, no corresponding coke market data is returned during operation. Cause: The interface authentication rules of the corresponding data source are not adapted, or the request parameters do not include the correct coke variety code.
  • Phenomenon: After setting maxContext to 0, multi-turn conversations cannot be implemented, and subsequent generated marketing content is not associated with previous market discussions. Cause: The maxContext parameter controls the number of historical conversation entries passed to the API. Setting it to 0 clears the historical context. This issue does not have obvious error log prompts in FastGPT v4.8.10.

How to confirm the configuration is correct

  • Trigger a test run, check the data parsing time in the workflow log, confirm that the time does not exceed the configured PARSE_FILE_TIMEOUT_SECONDS value.
  • Verify the coke data fields in the generated marketing content, confirm that they match the fields returned by the configured data source.
  • Test multi-turn conversation scenarios, adjust the maxContext parameter to a value that meets business requirements, confirm that subsequent generated content can associate historical discussions.
  • Check the scheduled trigger configuration, confirm that the trigger time matches the update rhythm of coke data.

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.