Data Characteristics for This Category
Intelligent due diligence report data for engineering consulting is primarily sourced from project approval documents, construction drawing design files, site survey records, cost accounting ledgers, compliance review reports, and similar materials. The update rhythm adjusts based on project progression phases: high frequency during the initial approval phase, node-based updates during the construction phase, and archived and frozen upon project completion.
Document structures typically include modules such as project overviews, technical parameter tables, progress node details, cost accounting items, compliance clause lists, and risk reminders. Fields include building area, total cost, construction period, compliance item numbers, with corresponding units including square meters, ten thousand yuan, calendar days, and other engineering-specific units.
Constraints Imposed on Model Integration and Configuration
The professional fields and units of engineering due diligence reports require models to retain structured information, so dedicated prompt templates and field mapping rules must be configured. The large size and multi-section nature of documents requires adjusting upload file size, parsing timeout, and context window parameters to avoid parsing failures or context truncation. The non-fixed update cycle of data requires configuring incremental synchronization rules triggered by project nodes, rather than fixed-cycle synchronization. The need for precise matching of compliance clauses and technical parameters requires adjusting similarity thresholds and recall counts to ensure the relevance and comprehensiveness of retrieval results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single engineering due diligence report documents often contain multiple pages of technical parameters and compliance clauses. Complete loading of core content is required to support model inference |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single engineering documents such as construction drawing PDFs and surveying and mapping files often reach hundreds of MB in size. The upload limit must be relaxed |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Large engineering documents require parsing large numbers of nested tables and drawing metadata. Conventional parsing time far exceeds that of general documents |
similarityThreshold | 0.75–0.85 | Precise matching of engineering professional fields and compliance clauses is required to avoid recalling low-relevance general content |
topN | Top 8–10 entries | Engineering due diligence requires covering technical, cost, and compliance multi-dimensional data. Excessive recall will exceed the context window limit |
chunkSize | 1500–2000 characters | Engineering documents contain long sections of technical descriptions and detailed items. Appropriately extended segmentation is required to retain contextual logic |
The parameter values provided on this page are common 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 values.
Three Common Misconfigurations
- Phenomenon: Calling the model interface returns
400 Bad Requestwith the prompt "Model input format error". Cause: No dedicated prompt template configured for the professional fields and units of engineering due diligence reports, resulting in the model being unable to correctly parse structured data. - Phenomenon: A
504 Gateway Timeouterror is triggered when loading large engineering documents after deployment. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to complete parsing and vector generation for complex documents. - Phenomenon: Locally deployed large models configured via OpenAPI cannot be found in the system model selection list. Cause: Front-end visibility for the corresponding channel was not enabled in the model integration configuration, or the configured model identifier does not match the unique identifier registered in the system.
How to Verify Configuration Is Complete
- Upload a standard engineering due diligence report document. Check whether the segmented content generated after parsing retains professional fields and units. The segmentation length can be verified against the configured
chunkSizerange via parsing logs. - Initiate a model call request. Check whether the interface response duration falls within the range configured by
maxContextandPARSE_FILE_TIMEOUT_SECONDS, with no timeout errors. - View the configured model list on the system model selection interface. Confirm that the locally deployed large model accessed via OpenAPI is displayed in the list and can be normally selected to initiate a test call.
- After configuring the similarity threshold and recall count, initiate a knowledge base retrieval. Check whether the number and relevance of returned results meet business requirements. Parameters can be adjusted for re-verification.
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.