What data for this category looks like
Data for engineering consulting intelligent due diligence reports comes primarily from project pre-feasibility survey records, feasibility study reports, cost lists, contract compliance documents, and site survey materials. Data updates trigger based on project progress milestones, with no fixed cycle. Up to 3 updates may occur within a single project cycle.
Document structures include project overview, detailed technical parameters, cost accounting sheets, compliance clause explanations, and progress milestone records. Fields contain unit-bearing numeric content: building area (unit: ㎡), investment amount (unit: ten thousand yuan), construction period (unit: days), and survey point longitude and latitude coordinates. Large sections of unstructured compliance explanation text are also interspersed throughout.
What constraints do these characteristics impose on vector models and indexing?
Engineering consulting due diligence reports have three types of data characteristics: structured numeric fields, long-text compliance clauses, and multi-type files. These create multiple constraints for the vector model and indexing workflow.
Structured fields with units require retaining metadata during vector encoding to avoid losing field attribute information during recall. Single document length varies widely, from dozens of pages of feasibility reports to hundreds of lines of cost lists. This requires a flexible chunking strategy.
Data updates trigger based on project milestones with no fixed cycle, so the index must support incremental updates to reduce resource consumption from full reconstruction. Multiple mixed file formats are uploaded, so the parsing and vectorization workflow must be compatible with common engineering consulting file types.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to mixed content of long-text compliance clauses and structured details in engineering consulting due diligence reports, balancing context completeness and vector recall density |
chunk_overlap | 100–150 characters | Prevents critical information breaks after long text chunking, ensuring context coherence across chunks |
index_incremental_update | Enabled | Matches the on-demand update rhythm of engineering consulting data based on project milestones, reducing resource consumption from full index reconstruction |
similarity_threshold | Calibrated via actual testing | Document similarity varies widely across different projects, so recall matching accuracy must be adjusted based on business scenarios |
recall_top_k | Top 8–12 results | Covers multi-dimensional technical, cost, and compliance information in engineering consulting due diligence reports, avoiding missing key items in recall results |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapts to upload requirements for single large feasibility reports or batch survey files, preventing file truncation |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Phenomenon: Index construction gets stuck during processing of the final set of files, with progress displayed as stagnant on the interface. Cause: Incremental update configuration is not enabled. When performing full index reconstruction, the large variation in file size of engineering consulting reports causes subsequent large file processing to time out without triggering progress updates.
- Phenomenon: Knowledge base search tests return a model call failure error with status code 500. Cause: The newly added embedding model is not configured with field metadata encoding adaptation, and cannot process structured numeric fields in engineering consulting reports.
- Phenomenon: Some survey-related files cannot be vectorized, and no corresponding content appears in the knowledge base. Cause: The parsing switch for the corresponding file format is not enabled. Common engineering consulting files such as construction drawing files and cost templates are not included in the supported range.
How to confirm configuration is correct
- Upload a single compliance clause fragment, check if the vector generation log includes field metadata, and confirm that the embedding model is compatible with structured content.
- Trigger an incremental index update, compare the number of index entries before and after the update, and confirm that the incremental update configuration is effective.
- Enter a query containing cost amount or coordinate information, and verify whether the recall results include relevant documents with the corresponding fields.
- Upload a single large feasibility report, check whether the upload and indexing process completes normally, and confirm that the file size configuration meets requirements.
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.