What the data for this category looks like
Data for commercial property intelligent due diligence reports comes from three sources: official real estate registration authorities, property operator backend systems, and public data released by business district management committees. Update rhythms vary across data types:
- Ownership data is updated quarterly
- Operational data is updated monthly
- Business district supporting data is updated biweekly
Each standard report includes four modules: ownership certification, operational data, business district analysis, and on-site inspection. The data contains both structured fields such as building area and rental unit price, and unstructured on-site description text. Field units include square meters, yuan/square meter/day, person-times, and similar units.
What constraints these characteristics impose on workflow orchestration
Multiple heterogeneous data sources require workflows to support multiple invocation methods. These include pulling structured data via API, and uploading local documents to parse unstructured content. Long documents and multi-module report structures require workflows to include segmented parsing and context control nodes. This prevents overflow or truncation during processing. Differentiated update rhythms require workflows to trigger corresponding data source nodes on different time cycles. No full-process reconfiguration is needed for this. Mixed structured and unstructured content formats require workflows to include both structured data extraction and unstructured text summarization nodes. This adapts to different information processing needs.
How to set configurations
| Config Item | Suggested Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Commercial property due diligence reports often include multi-page floor plans and operational spreadsheets, with longer parsing times than general documents |
split_chunk_size | 800–1200 characters | Adapts to the content structure of commercial property reports, which contain both structured tables and large blocks of explanatory text |
max_context_window | 16384 tokens | Prevents context overflow during long document parsing, and adapts to the overall processing needs of multi-module reports |
api_request_timeout | 30 seconds | Meets the response duration requirements of most real estate registration API interfaces |
global_var_scope | Workflow-level | Ensures core parameters such as property ID and business district code can be shared across different data source nodes |
file_upload_allowed_types | pdf, xlsx, txt | Covers common upload formats for commercial property due diligence reports |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Phenomenon: Parameter errors are returned when calling the real estate registration API, with logs showing empty core business fields. Cause: Core parameters such as property ID and business district code are not configured as workflow global variables, or are not correctly bound to the API request node.
- Phenomenon: After uploading a TXT report for on-site inspection, the parsing result is empty or the backend returns an abnormal format. Cause: The
multipart/form-datarequest header is not configured in the HTTP request node, and the uploaded file is not correctly bound as a request parameter. - Phenomenon: After importing someone else’s due diligence report workflow, the local text processing module cannot be found, or the text processing node reports an error during runtime. Cause: Plugins related to text processing are not enabled in the plugin marketplace, or dependent plugin packages are not installed synchronously when importing the workflow.
How to confirm the configuration is complete
- Trigger a test run, and check whether global variables in the logs are correctly passed to all API nodes.
- Upload a standard commercial property due diligence report, and check whether the parsed segment length matches the configured
split_chunk_size. - Call the connected real estate registration API, and check whether the returned data can be correctly extracted by the workflow and associated with subsequent nodes.
- Test the HTTP file upload node, confirm that the uploaded TXT file can be correctly passed to the backend and return results in the expected format.
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.