What the data for this category looks like
Engineering consulting data sources include project feasibility study reports, cost estimates, bidding documents, construction decoration industry specifications, project ledgers, and more. Updates are triggered on demand during the full project cycle, only at milestones such as feasibility study preparation and settlement review, or when industry specifications are revised. Most documents are long text, mixed with standardized structured tables. They contain professional fields like building area, unit cost, and construction days. Common units are square meters, ten thousand yuan, days, and similar units.
What constraints these characteristics impose on deployment and upgrade
Engineering consulting documents are mostly long text and include large numbers of structured tables. This places higher requirements on file parsing timeout settings and segment length limits. There are many professional fields with fixed dimensions, so structured recall must be enabled to accurately match retrieval needs. Data updates are not real-time, and only trigger at project milestones. Incremental update trigger strategies must adapt to project cycles to avoid unnecessary full parsing. Large attachments account for a high proportion, so higher upload file size limits are required. During upgrades, existing project ledger associations must be retained to avoid damaging pre-configured retrieval rules.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Most engineering consulting documents are long text, with long average parsing times. This setting avoids interrupting the parsing process due to timeout |
maxChunkSize | 1500–2000 characters | Balances retrieval accuracy and retrieval overhead for long text segments, and adapts to professional paragraphs and table structures in engineering consulting documents |
VECTOR_RECALL_TOP_K | Top 10–15 results | Covers key information from multiple related documents, and meets multi-dimensional data retrieval needs for investment research scenarios |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Adapts to large CAD attachments, high-resolution scanned drawing files, and similar files included in engineering consulting projects |
ENABLE_STRUCTURED_RECALL | Enabled | Accurately matches structured content such as bill of quantities and cost tables, and improves professional matching accuracy of retrieval |
INCREMENTAL_UPDATE_TRIGGER | Manually triggered by project milestone | Engineering consulting data only updates at project stages, so fixed-cycle automatic incremental updates are not needed |
The parameter values provided on this page are general recommendations that serve as a starting point for configuration. Actual values are affected by material form, 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 errors
- Phenomenon: Hybrid retrieval takes more than 10 seconds, and single vector retrieval takes approximately 8 seconds. Cause: Non-essential reranking model calls are not disabled, or the recall threshold is not optimized for long engineering consulting text, leading to additional computational overhead.
- Phenomenon: No channel interface appears when accessing OneAPI after Docker deployment. Restarting the service does not resolve the issue. Cause: The configuration directory is not mounted correctly, or container port mapping conflicts with existing ports on the host machine, causing the service to fail to load channel configurations properly.
- Phenomenon: After upgrading to version 4.8.10, some browsers cannot open the platform interface, while version 4.7.1 works normally. Cause: Browser cache is not cleared, or the new version’s front-end dependency libraries have compatibility differences with older browsers, leading to interface loading failures.
How to confirm configurations are properly set
- Upload a typical engineering consulting document, such as a feasibility study report. Check that the number of parsed segments matches the document length, and there are no system logs indicating parsing interruptions.
- Run a retrieval test for professional fields. Verify that structured fields can be accurately recalled, and retrieval latency falls within the acceptable range for the business.
- Perform an incremental update operation. Confirm that only newly added or modified documents are reindexed, and no full document parsing is triggered.
- Check container runtime logs. Ensure there are no error messages related to file parsing timeouts, port conflicts, or missing dependencies.
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.