What the data for this category looks like
Data sources for engineering consulting intelligent due diligence reports include project approval documents entrusted by financial institutions, geotechnical survey reports, engineering cost budgets, construction contract ledgers, construction progress logs, and other materials. Update rhythm follows project milestones: progress data is synced weekly after project initiation, and static data is archived after completion. Document structure mixes structured tables (including fields such as cost details and duration milestones) and unstructured attachments (PDF survey reports, CAD construction drawings). Fields include "construction and installation cost" (unit: ten thousand yuan), "number of survey points" (unit: count), "planned duration" (unit: calendar days), and others. Format adjusts flexibly based on project type.
What constraints these characteristics impose on deployment and upgrade
Mixed structured and unstructured data formats require support for multi-format parsing and field standardization mapping during deployment, to avoid post-parsing field confusion. Non-real-time update rhythm following project milestones requires adapting incremental sync interval configurations during upgrades, to reduce resource usage from full sync operations. Long documents and CAD attachments have long parsing times, requiring adjustments to parsing timeout parameters to prevent task interruptions. Multiple fields with multiple units require configuring field weight differentiation during vector recall, to improve matching accuracy.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Engineering consulting due diligence reports include CAD drawings and long-text survey reports, with parsing time significantly longer than general documents |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Support uploading large budget documents and multi-page CAD attachments, avoid upload failures |
chunk_size | 800–1200 characters | Adapt to long survey description paragraphs in due diligence reports, balance context completeness and recall accuracy |
recall_top_k | Top 10–15 entries | Due diligence reports have many fields and high information density, requiring sufficient context to support accurate matching |
SIMILARITY_THRESHOLD | 0.75–0.85 | Due diligence data fields are precise, requiring a high threshold to filter low-matching irrelevant content |
INCREMENTAL_SYNC_INTERVAL | Every 12 hours | Match the update rhythm of project milestones, avoid real-time sync to reduce server load |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: The platform only supports selecting a single vector model, and cannot configure vector models separately for structured table data and unstructured text. Cause: When using version v4.8.7, the multi-vector library association configuration is not enabled, or the API key for the corresponding vector model is not bound.
- Phenomenon: Interface rendering exceptions and interface request errors (status code 400) occur when accessing the platform with a low-version browser. Cause: Front-end compatible polyfill parameters are not configured during deployment, or the used image version does not adapt to old browser rendering rules.
- Phenomenon: After modifying the root password in docker-compose.yml and restarting the container, the login still prompts an incorrect password. Cause: The password parameter in the database initialization script is not updated synchronously, or the configuration volume mounted by the container is not reloaded.
How to confirm the configuration is properly set
- Upload a PDF of an engineering consulting due diligence report and a structured budget table, check if the parsed fields fully match the preset field mapping rules, and verify that the parsing time does not exceed the configured timeout threshold.
- Initiate an incremental sync task, check that only updated project data is correctly loaded, and no historical data is repeatedly imported.
- Initiate a vector recall test, verify that the number of recalled entries conforms to the configured
recall_top_krange, and the matching results match the input query keywords as expected. - Access the platform front-end page with a low-version browser, test whether core functions such as document upload and vector recall load normally, with no interface errors.
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.