What the data for this category looks like
Data for tourist attraction financing daily reports comes from three sources: daily revenue ledgers from attraction ticketing systems, scenic area operation supervision reports from cultural and tourism authorities, and credit approval and receipt records from partner banks. Data updates once per day. It generates a summary report for the previous day during the early morning of the next day. Document structure primarily uses structured tables, with a remark field for individual financing records. Core fields include: unique attraction identifier, attraction name, daily associated financing application amount, bank approved amount, receipt date, credit type, and bill number. Amount fields use ten thousand yuan as the unit. Date fields use the YYYY-MM-DD format.
What constraints do these characteristics impose on workflow orchestration?
Multi-source data access requires workflow configuration to include cross-system data pulling and merging rules. It must ensure unique identifier matching across all data channels. The daily fixed update feature requires workflow configuration to include a scheduled trigger mechanism. This avoids delay risks from manual execution. Standardized structured field requirements require configuration of a field validation node. This filters data with empty values or abnormal formats. Differences in field naming across channels — for example, "approved amount" in bank records and "approval quota" in attraction ledgers — require unified mapping. This increases configuration complexity for data conversion.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Timed Trigger Frequency | Daily at 02:00 | Financing daily reports summarize previous day's data. Executing in the early morning ensures complete pulling and processing of that day's data |
Multi-data Source Mapping Rules | Associate by scenic spot ID | Attraction ID is the unique identifier across all data sources. This ensures accurate merging of data from different channels |
Field Required Validation Switch | Enabled | Empty core financing fields will cause subsequent AI analysis steps to fail. Validation intercepts abnormal data early |
Code Node Timeout Duration | 300 seconds | Typical time for multi-source data pulling and format conversion is under 200 seconds. This sets a reasonable buffer |
Knowledge Base Recall Similarity Threshold | 0.75 | Scenic area financing-related policies and cooperation documents must reach this matching level to provide effective reference for analysis |
AI Context Maximum Character Count | 8000 characters | Total length of structured financing daily report data and associated documents fits this threshold. This avoids input overflow |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are influenced 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 configuration mistakes
- A
chat:ai_input_is_eerror code is returned when running the workflow. Cause: The execution result of the code node was not correctly spliced into the input parameters of the AI model. This causes the input format to not meet requirements. - The "Select Knowledge Base" option bound to a global variable has no matching scenic area classification knowledge base. Cause: Dynamic assignment logic for the variable was not configured. The attraction ID was not associated with the label of the corresponding knowledge base.
- The text extraction node returns an empty financing amount field. Cause: The target column name of the data source was not specified, or the regular expression for field matching was not configured. This prevents accurate extraction of target content from multi-source data.
How to confirm the configuration is complete
- View the running logs of the scheduled trigger task. Confirm that pulling results from all data sources match expectations. Check the integrity of core fields.
- Manually trigger the workflow once. Check if the output result of the code node meets the field requirements of the financing daily report. Verify that the spliced AI input format is normal.
- Check the dynamic assignment configuration of global variables. Confirm that the "Select Knowledge Base" option automatically matches the scenic area classification.
- Test the output of the text extraction node. Confirm that extraction results for target fields have no empty values or abnormal formats.
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.