What Data for This Category Looks Like
Data sources for packaging and printing intelligent due diligence include printing equipment operation logs, raw and auxiliary material inventory ledgers, finished product quality inspection reports, customer order archives, and environmental monitoring records. Data is generated synchronously after each production batch is completed, or aggregated daily per production shift. Document structures include structured work order tables, unstructured printing sample photos, and handwritten quality inspection annotations. Fields include print weight (unit: g/㎡), printing registration accuracy (unit: μm), order delivery cycle (unit: days), equipment operating duration (unit: hours), and total raw and auxiliary material usage (unit: kilograms).
What Constraints These Characteristics Impose on Workflow Orchestration
Multi-source heterogeneous data structures require the workflow to first connect an OCR parsing node to process sample photos, then align parsed results with structured work order fields. Batch-updated data requires the workflow to bind work order numbers as unique identifiers, to avoid mixing data across batches. Single-batch data volume is usually contained within a single work order, so do not set an overly large context recall threshold, as this will introduce historical data from unrelated batches. Additionally, some fields use precise units, so a unit validation node must be added to the workflow to ensure extracted values match preset units, and prevent unit conversion errors.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | High-definition printing sample OCR parsing and ledger file structured processing require longer processing time, to avoid mid-run interruptions |
maxContext | 8000–12000 characters | Single-batch work order data volume is concentrated, so an overly large context window is unnecessary, to avoid introducing historical data from unrelated batches |
RECALL_TOP_N | Top 3 entries | Only core data related to the current work order’s raw and auxiliary materials and quality inspection needs to be recalled; excessive recall will interfere with due diligence conclusions |
WORKFLOW_TRIGGER_MODE | Trigger by work order number | Packaging and printing production data is managed via independent work orders; triggering by work order prevents mixing data across batches |
SEGMENT_LENGTH | 1000 characters | Text paragraphs in printing quality inspection reports are moderately sized; segment length aligns with field extraction precision requirements |
FILE_UPLOAD_MAX_SIZE | 500 MB | Total size of single-batch high-definition samples, ledgers, and quality inspection files typically falls within this range, to align with storage and parsing limits |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: After connecting multiple AI chat modules in the workflow, the final output includes the chat results of all modules. Cause: No result filtering node is configured, or the output of the last AI module is not bound to the workflow’s final output node.
- Phenomenon: After restoring a backup project, knowledge base and intelligent agent configurations do not display synchronously. Cause: The backup file only contains workflow orchestration configurations, and does not include associated knowledge base vector library index files; corresponding resources must be manually rebound during restoration.
- Phenomenon: Unit mismatches appear in field extraction results, such as extracting mm as μm. Cause: No unit validation node is added to the workflow, and no preset unit rules are bound to extracted values.
How to Confirm Proper Configuration
- Verify workflow trigger configuration, confirm that the trigger rule is bound to the work order unique identifier field, to ensure only data from the corresponding batch is processed.
- Run single-batch test data, check that the output only includes fields associated with the current work order, with no redundant content from cross-batch data.
- Upload the maximum allowed single-batch file size, confirm that the parsing process does not trigger timeout errors, and that parameter configurations align with file size limits.
- View node execution logs, confirm that the execution order of each node matches the preset configuration, with no reversed execution order.
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.