What the Data for This Category Looks Like
Data sources for professional chain due diligence include brand headquarters ERP systems, sales data uploaded by store POS terminals, business filing information publicly disclosed by industrial and commercial authorities, and third-party business district passenger flow monitoring data. Update cycles are divided by module: store basic information is updated quarterly, individual store sales data is updated daily, and supply chain supply ledgers are updated weekly. The document structure is divided into four parts: store basic archives, individual store operation reports, supply chain collaboration ledgers, and member operation statistics. Fields include store number, business area (unit: square meters), daily revenue (unit: yuan), supply batch number, member repurchase frequency, and others. There is no unified fixed document format, and field mapping must be customized per brand.
Constraints Imposed on Workflow Orchestration
Store data is scattered across multiple systems. Workflow configurations must include multiple parallel data source pull nodes, with scheduled trigger rules set based on data update cycles. There is no unified standard for document fields across different chain brands. A preset field mapping variable pool must be supported to enable custom field matching. The length of individual documents for single-store operation data varies widely. Some brands’ monthly revenue ledgers may exceed conventional AI input limits, so an input length verification node must be configured. The batch field in supply chain ledgers must be bound to variables for associated calls to avoid poor adaptability caused by hardcoding.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Adapts to the total length of spliced multi-store operation data, avoiding AI input overflow |
input_max_length | 15000 characters | Covers the conventional length of a single brand’s monthly operation ledger, blocks over-length input requests |
variable_mapping | Map based on brand preset field pools | Adapts to differences in custom store and revenue fields across chain brands |
workflow_trigger_cron | Daily at 02:00, Weekly Monday at 01:00 | Matches the update cycles of POS data (daily update) and member data (weekly update) |
knowledge_retrieve_threshold | 0.75–0.85 | Filters business district and supply chain data matching the due diligence theme, reducing invalid recalls |
intercept_error_code | 413 | Matches the standard error code for input over-limit, triggers custom intercept prompts |
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. Testing on independent samples is advised before finalizing values.
Three Common Mistakes
- Phenomenon: The workflow returns a
413 Request Entity Too Largeerror during execution, and the custom intercept prompt is not triggered. Cause: Theinput_max_lengthverification node is not configured, and the original document is directly passed to the AI chat node. - Phenomenon: The knowledge base search returns no results or matches irrelevant documents. Cause:
variable_mappingis not configured correctly, and the due diligence requirement is not bound to the brand’s custom fields, leading to incorrect variable references. - Phenomenon: No submit button appears in the conversation, and subsequent workflow nodes cannot be triggered. Cause: The
message_button_confignode is not added to the workflow, or the trigger rule after button click is not bound.
How to Verify Successful Configuration
- Upload a professional chain operation document exceeding 12,000 characters, and check whether the preset input over-limit intercept prompt is triggered.
- Configure brand-specific store field variables, initiate a due diligence request, and check whether the knowledge base recall results match content related to the preset fields.
- Add a button node in the workflow test panel, initiate a conversation, check whether a submit button with preset text appears, and confirm whether subsequent nodes are triggered after clicking.
- Configure the scheduled trigger rule, wait for the corresponding time point, and check whether the workflow automatically pulls the latest POS or member data to perform 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.