What the data for this category looks like
Data sources for residential development research reports include public announcement documents from local housing and construction authorities, periodic disclosure reports of listed real estate enterprises, special research documents from third-party real estate industry consulting institutions, and industry research reports released by securities firms and financial institutions. Update frequency varies by data source type: monthly, quarterly, or special project node updates. Most document structures include modules such as project location parameters, land transaction details, construction cost breakdowns, sales rate statistics, and excerpts of supporting policies. Fields include clear quantitative and identification fields such as land transaction price, development cycle, pre-sale permit quantity, and plot ratio. Quantitative fields use standard units like yuan/square meter, units, and months.
Constraints imposed on workflow orchestration by these characteristics
Decentralized data sources and inconsistent update rhythms require distinguishing trigger cycles for different data sources when configuring multi-source pull nodes in the workflow. This avoids repeated pulls or missed updated data. The large number of document structure modules and significant field differences require specifying extraction rules for core fields in the workflow’s structured parsing node. This adapts to differences in module order across different research reports. Quantitative fields with clear units require configuring unit verification rules during the value extraction link. This prevents analysis deviations caused by cross-unit data confusion. Research reports updated at special project nodes have no fixed cycle. This requires configuring a manual trigger branch in the workflow to adapt to temporary data pull requirements. Unified formatting is required when merging multi-source data. This requires configuring a field mapping node in the workflow to align similar fields from different data sources to a unified naming convention.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Scheduled Task Trigger Interval | Configured by data source type: housing and construction data uses 30 days, financial report data uses 90 days | Matches the inherent update rhythm of each data source for residential development research reports |
Structured Extraction Field Whitelist | ["土地成交价", "开发周期", "预售许可套数", "容积率"] | Focuses on core analysis fields for residential development research reports to reduce interference from irrelevant content |
Similarity threshold | 0.75 | Filters research report fragments unrelated to residential development themes and retains highly relevant content |
maxContext | 8000 characters | Adapts to the conventional length of a single residential development research report and avoids context truncation |
Error Retry Count | 2 times | Addresses temporary network fluctuations or interface rate limits during multi-source data pulling |
Unit Validation Switch | Enabled | Ensures extracted quantitative fields match preset units and prevents cross-unit data confusion |
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. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: The numeric counter node in the workflow does not automatically increment by 1 after execution, and the output field remains at the initial value. Cause: The trigger condition of the variable update node is not set to after AI answer completion, or the counter variable is not bound to the correct output node.
- Phenomenon: Execution logs and intermediate results of the code running node are not displayed in the workflow debugging panel. Cause: The detailed log switch for workflow debugging is not enabled, or the code running node is not configured as a debug-visible node.
- Phenomenon: After importing an external workflow configuration, the intermediate results of the sub-workflow do not match expected outcomes. Cause: The global variable configuration dependent on the sub-workflow is not updated synchronously, or the field mapping rules do not match the input format of the main workflow.
How to confirm the configuration is complete
- Manually trigger the workflow once, and check whether the intermediate results of each node include the preset core fields.
- View the scheduled task logs of the workflow to confirm that the pull time of the corresponding data source matches the configured trigger interval.
- Submit a test residential development research report document, and check whether the extracted quantitative fields carry the correct units.
- Enable the workflow error alert to confirm that corresponding notifications are sent when temporary exceptions occur.
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.