Workflow Orchestration for Condiment Smart Due Diligence Reports

Data sources for condiment-related data include:

What Data for This Category Looks Like

Data sources for condiment-related data include:

  • Category monitoring reports released by industry associations
  • POS inventory and sales data from offline supermarkets and online e-commerce platforms
  • Supply ledgers provided by suppliers
  • Public inspection and sampling documents issued by market supervision departments

Update frequencies vary:

  • Inventory and sales data is updated daily
  • Industry monitoring reports are updated weekly
  • Sampling notices are released irregularly

Document structure includes two types of content: Structured fields include product name, specification model, batch number, production date, raw material proportion, and test indicator values. Unstructured content includes detailed ingredient lists and sampling conclusion explanations.

Field units include professional units such as kilogram, box, yuan/500g, and total bacterial count CFU/g.

What Constraints Do These Characteristics Impose on Workflow Orchestration?

Multi-source data has inconsistent update frequencies. Workflows must support a combination of scheduled and manual triggering modes, and filter invalid data outside valid time ranges by time period. Documents contain both structured and unstructured content. Workflow configurations must include separate nodes for structured field extraction and unstructured text parsing, to avoid loss of critical information. Diverse field units and conversion requirements exist across different categories. Workflows must include a built-in unit unified conversion node, to ensure data from different sources can be aligned for calculation. Condiments are managed by batch. Workflows must use batch as the core aggregation key, to prevent cross-batch data mixing that causes errors in due diligence results.

How to Set Configurations

Configuration ItemRecommended ValuesRationale
segment_length800–1200 charactersCondiment ingredient lists are often long continuous text; splitting this way preserves complete association between ingredients and test items
similarity_threshold0.75–0.85Condiment SKUs are numerous and have highly similar product names; this filters redundant search results
PARSE_FILE_TIMEOUT_SECONDS300 secondsParsing a single sampling report or supply ledger takes significant time; this prevents mid-run interruptions
maxContext4000–6000 charactersAccommodates context from multiple inventory datasets and test reports, preventing information truncation
recall_countTop 8 entriesCondiment competitor information is abundant; limiting recall volume avoids redundant interference
HTTP_REQUEST_TIMEOUT600 secondsSome supplier supply ledger APIs return large datasets; this reserves sufficient response time

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. Each scenario requires individual analysis. It is recommended to test on samples relevant to the specific deployment before finalizing settings.

Three Common Mistakes

  • Phenomenon: After configuring custom environment variables in a workflow deployed via Docker, nodes return empty values. Cause: Environment variable reference permissions were not enabled in the workflow node configuration, or the variable name spelling does not match the deployment configuration.
  • Phenomenon: After an HTTP node calls an interface that returns an image file stream, subsequent workflow nodes cannot read or parse the content. Cause: The HTTP node's receiving format was not set to binary stream, and no file parsing node was added to complete format conversion.
  • Phenomenon: The workflow cannot execute branch logic to skip or perform knowledge base retrieval based on user-selected input options. Cause: No conditional branch node was configured to bind the user selection variable, and no corresponding jump rules were set for the branch node.

How to Verify Correct Configuration

  • Upload a real condiment inventory ledger, and verify whether the workflow completes multi-source data aggregation using the preset merged fields.
  • Trigger the workflow, and check the number of knowledge base recall results to confirm they match the configured recall rules.
  • Test the custom environment variable call, and verify that the returned value matches the deployment configuration content.
  • Upload a condiment document containing an ingredient list, and check that the parsed fields match the preset mapping rules.

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.