What the Data for This Category Looks Like
Data for residential development intelligent due diligence reports comes primarily from land transfer announcements issued by territorial and spatial planning departments, construction permit notices from housing and urban-rural development departments, project financing ledgers from partner banks, and actual household measurement data from third-party surveying institutions. This data serves as core reference for financial institutions conducting due diligence for residential development project financing.
Update cycles vary across sources:
- Land transfer announcements are updated monthly.
- Construction permits are updated in real time alongside project milestones.
- Financing ledgers are exported in bulk quarterly.
- Household data is updated after a project tops out.
Document formats include official PDF notice files, structured Excel ledgers, and standardized data returned via RESTful API interfaces. A single due diligence report can range from 50 to 100 pages in length.
Exclusive field characteristics include:
- Parcel number (string format)
- Land transfer fee (uses units of ten thousand yuan or yuan)
- Floor area ratio (no unit)
- Total construction area (unit: square meters)
- Construction start date (YYYY-MM-DD format)
Constraints Imposed by These Characteristics on Workflow Orchestration
The multi-source, heterogeneous nature of residential development due diligence data requires the workflow to support three data access methods: API interface connection, local file upload, and database pulling.
The update cycles of different data sources vary widely. Some data must be pulled on a scheduled bulk basis, while other data requires manual triggering for ad-hoc pulls. This means the workflow must be configured with a mixed trigger mechanism.
Field units and formats for due diligence data are not uniform. For example, land transfer fee uses both ten thousand yuan and yuan as units. A standardization cleaning node must be added to the workflow.
Long documents require chunk processing adapted to per-page content length to avoid losing critical information during extraction. Associated fields such as parcel number must be accurately extracted for cross-data-source project association and matching, ensuring due diligence data from different sources can be correctly linked to the same project.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
HTTP_REQUEST_TIMEOUT | 300 seconds | Official APIs for residential development projects may return multi-page data. A too-short timeout will cause pull operations to interrupt |
JSON_PATH_EXTRACT_RULE | $.data.list[*].landParcelNumber | Parcel information for residential development projects is typically nested in the data.list array returned by the API. This path accurately extracts parcel numbers for all projects |
DOC_SPLIT_CHUNK_SIZE | 1200 characters | Per-page content of residential development due diligence reports typically falls between 800 and 1500 characters. This chunk length balances extraction accuracy and processing efficiency |
DB_CONNECTION_TIMEOUT | 60 seconds | Internal network deployment of residential development project ledger databases carries latency risks. This timeout duration covers most connection wait scenarios |
WORKFLOW_TRIGGER_TYPE | Scheduled trigger + manual trigger | Monthly updates to land transfer announcements require scheduled pulls, while ad-hoc project due diligence requires manual workflow triggering. Mixed triggers accommodate both use cases |
ERROR_RETRY_TIMES | 3 times | Network fluctuations or API rate limits may cause single request failures. Retries reduce the probability of workflow interruptions |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: The HTTP request node returns a response, but the extracted variable fields are empty. Cause: The actual nested path of the residential development API return data was not matched. For example, mistakenly using
$.宗地编号instead of$.data.list[*].landParcelNumber, which prevents locating the target field. - Symptom: The database connection node throws the error
Failed to connect to jyfkk:1433 - 38BBDDC3AF7F0000. Cause: The correct internal network database instance address or port permissions were not configured. Internal network access to residential development project financing ledgers requires specifying the exact internal domain name and access permissions. - Symptom: The problem classification node cannot correctly identify the land transfer fee field in the due diligence report. Cause: The background knowledge does not include the unit conversion rules for land transfer fees in residential development projects, and the conversion logic between ten thousand yuan and yuan was not clearly specified, leading to field identification deviations.
How to Verify Proper Configuration
- Trigger a single workflow run, view the execution logs of each node, and confirm that the JSON data returned by the HTTP request includes expected fields such as parcel number and total construction area.
- Run the data cleaning node, check that the converted land transfer fee fields are uniformly using ten thousand yuan as the unit, with no format confusion.
- Export the workflow configuration file, verify that the
JSON_PATH_EXTRACT_RULEpath matches the actual data structure returned by the API. - Test the scheduled trigger node, confirm that updated data from the corresponding data source is automatically pulled at the set cycle, and the workflow execution status is normal.
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.