What the data for this category looks like
Coal chemical due diligence data comes from internal enterprise production ledgers, industry association monitoring data, and government regulatory filing documents. Three update cadences apply:
- Production operation data is updated monthly
- Compliance testing data is updated quarterly
- Project dynamic information is updated with approval nodes
A single due diligence document typically contains dozens of pages, split into two parts: structured fields and unstructured attachments. Structured fields include project code, designed production capacity, raw material procurement cycle, and ex-factory product prices. Unstructured attachments include process flow diagrams and scanned test reports.
Units follow industrial general standards: production capacity is measured in tons per year, procurement cycle in days, and product prices in yuan per ton.
Constraints imposed on workflow orchestration by these characteristics
The multiple data sources and differing update cadences for coal chemical due diligence data require layered trigger nodes in the workflow. Configure separate scheduling rules for monthly production data, quarterly compliance data, and real-time project dynamics.
The mixed format of unstructured attachments and structured fields requires splitting the workflow processing pipeline: multimodal attachments are connected to dedicated multimodal parsing nodes, while structured fields are directly connected to text processing nodes.
The large page count per single document requires configuring segmentation parameters to avoid exceeding the model context limit with a single input.
The diversity of field units and types requires adding a field verification step to ensure input data conforms to preset formats.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_CHUNK_SIZE | 800–1200 characters | Coal chemical due diligence documents have longer single-segment content, this value balances parsing accuracy and context usage |
RECALL_LIMIT | Top 6–8 entries | Coal chemical due diligence has many data fields; excessive recall will cause context overflow |
MULTIMODAL_MODEL | Specialized multimodal model | Required to process unstructured attachments such as process flow diagrams and scanned test reports |
TEXT_MODEL | Qwen2 series models | Required for text verification and logical deduction of structured fields |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Parsing coal chemical due diligence documents and processing across multiple nodes takes a long time; this duration covers the full workflow |
TRIGGER_SCHEDULE | Run daily | Covers scheduling needs for multiple data types updated monthly and quarterly |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Each scenario requires individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Multimodal attachments in the workflow do not trigger the multimodal model, and instead use a plain text model for processing, leading to parsing failure. Cause: No branch judgment node for multimodal data is set in the workflow, and input data types are not distinguished.
- Phenomenon: The content returned by the knowledge base search node in the workflow is too short to meet the long-text requirements of coal chemical due diligence. Cause: The parameters of the knowledge base node in the workflow are not adjusted, and the default low-limit configuration is used.
- Phenomenon: When inputting plain text due diligence fields, the system triggers the document parsing process, increasing processing time. Cause: No direct processing branch for plain text input is set in the workflow, and all inputs default to triggering the document parsing step.
How to confirm the configuration is complete
- Review the workflow node configuration to confirm that the multimodal attachment branch is bound to the multimodal model, and the plain text branch is bound to the specified text model.
- Upload a single coal chemical due diligence document and trigger the workflow, then check the parsing logs to confirm no file parsing timeout occurs.
- Review the return results of the knowledge base search node to confirm the number of entries conforms to the preset recall rules.
- Check the configuration of the field verification step to confirm that format matching rules have been set for the structured fields of coal chemical due diligence.
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.