What the data for this category looks like
The data for building construction intelligent due diligence reports comes from project construction logs, supervision on-site inspection records, cost accounting documents, planning surveying and mapping drawings, and completion acceptance archives. Data updates trigger based on project progress nodes, and sync after key milestones including main structure topping out, facade construction, and final account completion are completed. Single report document length varies widely, from dozens of pages to hundreds of pages. Core fields include individual building floor area (unit: ㎡), sub-project cost (unit: ten thousand yuan), construction period (unit: days), hidden work acceptance number, and some fields require association with data from external government approval systems.
Constraints imposed by these characteristics on deployment and upgrade workflows
The long document length, multi-source format, and phased update characteristics of building construction due diligence reports impose clear constraints on deployment and upgrade workflows. Long documents require longer parsing timeout and context window configurations to avoid parsing interruptions or content truncation. Mixed-format input requires pre-configuring linkage between multiple file parsing engines during deployment, to prevent inconsistent parsing of different formats such as cost Excel files and construction log PDFs. Phased update mode requires upgrade workflows to support incremental synchronization configurations, to reduce resource consumption from full re-runs. Fields associated with external government approval system data require interface retry and circuit breaker mechanisms configured during deployment, to ensure stable data pulling.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | The longest intelligent due diligence report for building construction projects can reach hundreds of pages. Sufficient time is required for complete parsing, and 600 seconds covers the parsing needs of most long documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Complete completion archives include multi-page drawings and cost details. 1000 MB covers the upload limit for most project reports |
chunkSize | 1000–1200 characters | Fields in building construction reports are dense. Setting the segment length to this range balances information integrity and context call efficiency |
RECALL_TOP_N | Top 8 entries | Core information in due diligence reports is scattered across different chapters. Retrieving 8 entries covers key compliance, cost, and progress fields |
MODEL_API_TIMEOUT | 120 seconds | Generating structured reports after long document vector retrieval requires sufficient time. 120 seconds avoids model call timeout interruptions |
AUTO_PARSE_ENABLE | Enabled | Building construction reports include multiple formats such as PDF, Excel, and CAD exported files. Automatic parsing adapts to parsing rules for multiple file types |
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 targeted analysis. It is recommended to test on local deployment samples before finalizing settings.
Three common errors
- Phenomenon: After uploading a building construction project due diligence report, parsing failure is displayed, and the log contains the
File parse timeoutfield. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted to a value suitable for long documents. The default timeout duration cannot complete complete parsing of hundreds of pages of reports. - Phenomenon: A
gpt-4o-mini API call failedlog is generated during workflow operation, but no actual model call request is triggered. Cause: The timeout configuration of the workflow node is shorter than the time required for model generation, or the environment variables of the model interface are not correctly bound, causing subsequent logic to be triggered before the pre-step is completed. - Phenomenon: After configuring the local inference service, model calls cannot be completed, and the console returns a
connection refusederror. Cause: The model access address was not configured as the actual listening IP and port of the service, or the network access permission for the corresponding port was not enabled.
How to confirm correct configuration
- Upload a typical-length building construction project due diligence report, check whether the parsing status shows completed, and verify whether the parsed text fragments include core fields.
- Trigger a workflow test, check whether there are no timeout or interface call failure error messages in the log, and confirm that the model call link is normal.
- Check the configuration file or interface settings, confirm that the values of core parameters such as
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSmeet the actual needs of the project documents. - After connecting to the local inference service, call the test interface to verify whether the model response is normal, and confirm that the network access and port configurations are correct.
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.