What the data for this category looks like
Data sources for hotel and catering intelligent due diligence reports cover store business licenses, ingredient purchase ledgers, passenger flow statistics systems, third-party review platforms, and kitchen monitoring records. Update frequencies vary:
- Business licenses are updated annually
- Ingredient purchase ledgers are updated daily
- Passenger flow data is synced in real time
- Third-party review comments are added in real time
Document structures include structured table files such as purchase ledgers and passenger flow reports, unstructured text such as review content, and audio/video clips such as monitoring footage. Fields and units are clearly defined:
- Ingredient purchase fields include purchase date, supplier name, ingredient category, unit price (yuan/kg), purchase quantity (kg)
- Basic store fields include business area (square meters), daily average passenger flow (person-times), hygiene rating
What constraints these characteristics impose on workflow orchestration
Differences in data source update frequencies require staged data pull tasks in the workflow. This avoids uneven interface loads from simultaneous requests to high-frequency and low-frequency data sources.
Differences in multi-source data formats require format conversion nodes in the workflow. These nodes unify units and naming rules for structured fields.
Unstructured monitoring footage and review content need separate parsing nodes. Monitoring footage must first be transcoded into parsable text. Review content must first undergo sentiment analysis preprocessing.
The unique store identifier field requires the workflow to use store ID as the association key during data aggregation. This prevents mixing of data from different stores.
How to set configurations
Use the following reference for configuration settings:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
API Request Timeout | 300–600 seconds | Purchase ledgers and passenger flow data interfaces for hotels and catering may return large volumes of paginated data. Overly short timeouts will truncate valid content |
Variable Scope | Session-level | Due diligence data for different stores must be isolated to avoid cross-session data contamination |
Condition Judge Matching Rules | Combination of contains, starts with, ends with | Fields in catering due diligence reports such as hygiene rating may have prefixes or suffixes. Pure equality rules will miss valid results |
File Parsing Segment Length | 800–1200 characters | Single-segment parsing accuracy for review text and monitoring logs meets conventional requirements. Context breaks that impair AI understanding are avoided |
Multi-source Data Merging Strategy | Associate by store ID | All data sources for hotels and catering use store ID as the unique identifier. Association generates complete due diligence reports |
API Request Retry Count | 2–3 times | Some third-party passenger flow interfaces may experience temporary fluctuations. Retries reduce task failure rates |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- When calling an API in a workflow, output fields are empty or unrecognizable by subsequent nodes. The cause is failure to map JSON fields returned by the API to input parameters of workflow nodes, using raw return values without parsing.
- Cross-session data contamination occurs during parallel due diligence for multiple stores. The cause is writing store-specific data to global scope variables instead of using session-level variables.
- When using "equals" or "starts with" matching rules, qualifying results are assigned to the ELSE branch. The cause is failure to account for spaces, capitalization, or unit suffixes in fields. Matching rules do not cover actual data formats.
How to confirm proper configuration
- Trigger a single-store due diligence workflow. Check that all API return fields in node logs are complete and free of missing values.
- Trigger 2-3 parallel due diligence tasks for different stores. Check that exclusive data for each task in the session variable panel does not interfere with others.
- Configure different judgment rules. Input test data with prefixes and suffixes, verify that judgment branches trigger correctly.
- Upload a historical purchase ledger file. Check that parsed segmented content matches the set segment length and has no context breaks.
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.