What this type of data looks like
Data for building construction engineering research reports comes primarily from public industry analysis reports, local construction engineering statistical bulletins, custom research reports from professional architectural consulting organizations, and engineering sector announcements from publicly traded real estate enterprises.
Update frequencies vary. Policy-related data updates quarterly. Industry trend research reports update monthly. Bidding-related research reports update in real time alongside project progress.
Typical documents include project overviews, cost breakdowns, policy compliance requirements, construction difficulty analyses, and industry benchmark cases. Fields include building area (unit: ㎡), project cost (unit: 10,000 yuan), building material usage (unit: tons/cubic meter), construction period (unit: days), and policy document numbers.
Constraints on knowledge base retrieval and recall
Building construction engineering research reports contain both structured parameters and unstructured analysis content. Retrieval systems must support both precise field matching and semantic recall to avoid missing matches for professional parameters.
Update frequencies differ widely across data sources. Targeted synchronization scheduling logic must be configured to distinguish trigger times for full updates and incremental syncs.
Documents contain a large number of professional units and terms. Recall processes must retain associated unit semantics to prevent matching deviations caused by missing units.
Users often include clear parameter limits during retrieval. Systems must support parameterized combined retrieval to improve recall precision in specific use cases.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Number of recall results | Top 10-15 items | Building construction engineering research reports have lengthy individual content. Too many recall results will exceed the large model context window. Too few will fail to cover associated information for specific use cases |
Similarity threshold | 0.75-0.85 | A large number of professional terms appear in building construction engineering. A threshold that is too low will introduce irrelevant general industry content. A threshold that is too high may miss targeted research reports with precise matches |
Number of reranked returned results | Top 5-8 items | Research report content has complex structures. Retaining a small number of highly relevant entries after reranking can compress context length to adapt to large model input limits |
UPLOAD_FILE_MAX_SIZE | 500 MB | Individual building construction engineering research reports may include large numbers of drawing attachments and high-definition charts. Larger file uploads must be allowed |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing research reports that include multi-page drawings requires longer processing time to complete OCR and text extraction |
Knowledge base sync frequency | Differentiated by data source type: policy data every 7 days, bidding data every 1 hour | Update rhythms differ widely across data sources. This avoids invalid syncs that occupy system resources |
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 targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- After importing a JSON-formatted knowledge base configuration file, the target knowledge base cannot be automatically selected during invocation, and the dropdown menu appears empty. Cause: The
kb_idfield for the specified knowledge base is not bound in the workflow, or the field format in the JSON file does not meet system requirements. - In the knowledge base orchestration workflow for version 4.8.22, a red cross appears in the interface after enabling "Result Reranking", and the function fails to work. Cause: The API key for the reranking model is not configured, or the current model version does not support linked calls with the reranking model.
- When searching for building construction engineering cost parameters, a large amount of non-building construction general construction content is mixed in the recall results, and matching precision is insufficient. Cause: The number of recall results is set too high, and professional field filtering configuration is not enabled, leading to overly broad semantic recall coverage.
How to Verify Proper Configuration
- Upload a single building construction engineering research report that includes drawings and parameters, review the parsed text content, and confirm that professional fields and units are correctly extracted.
- Initiate a search with specific parameters, and verify that the recall results include matching targeted research report content.
- After enabling the result reranking function, check whether the order of retrieval results aligns with professional relevance logic.
- After migrating mirror data, check whether the system interface and knowledge base configuration language meet preset 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.