What data for this category looks like
The data for engineering consulting intelligent due diligence reports comes primarily from project approval archives, government planning approval documents, on-site survey and mapping records, cost accounting ledgers, and industry technical standard documents. Update frequency adjusts based on project progress. On-site data is updated weekly during the project implementation phase. After project completion, data is archived as static documents. Industry standards are updated every 1 to 2 years. Most documents use a multi-chapter structured format, including modules such as project overview, technical parameter details, compliance review items, and risk assessment reports. Fields include project ID, survey date, cost unit (ten thousand yuan/square meter), compliance clause number, and more. Units and field definitions strictly follow general construction decoration industry specifications.
What constraints do these characteristics impose on knowledge base retrieval and recall
Dispersed data sources require simultaneous retrieval of internal project archives and external industry standards, increasing cross-source recall configuration complexity. Single reports have significant length. Segmented processing must retain contextual links of technical logic to avoid breaking critical parameters after splitting. Precise matching of structured fields has higher priority than general text. Relying solely on full-text fuzzy matching will cause confusion between compliance clauses and irrelevant content. Non-fixed update rhythms require the retrieval system to support incremental updates, reducing resource consumption while ensuring data timeliness.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | top 8-12 results | Engineering consulting due diligence reports have long content; too many recalled results will exceed the context window, while too few will fail to cover critical technical parameters and compliance clauses |
similarity threshold | 0.75-0.85 | Due diligence reports involve compliance and technical details; a high matching threshold is needed to avoid mixing irrelevant content and ensure the accuracy of retrieval results |
segment length | 1000-1500 characters | Each segment must retain complete technical logic, while avoiding excessive segment length that causes embedding vector deviation, adapting to the representation needs of professional terminology |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large-scale engineering due diligence reports contain a large number of drawings and table parsing content; the default timeout cannot cover the complete parsing process |
embedding model selection | text-embedding-3 | Engineering consulting text contains a large number of professional technical terms; text-embedding-3’s vector representation capability is better suited for semantic matching of professional domain text |
structured field recall toggle | enabled | Due diligence reports include structured fields such as project ID and cost unit; enabling this toggle enables precise matching and improves the accuracy of compliance queries |
The parameter values provided on this page are conventional recommendations used as a starting point 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 mistakes
- Phenomenon: Retrieval results contain a large number of general industry articles unrelated to engineering technology. Cause: The structured field recall toggle is not enabled, and only full-text fuzzy matching is used, leading to confusion between compliance review items and general popular science content.
- Phenomenon: Calling the knowledge base upload interface returns a
413 Request Entity Too Largeerror. Cause: TheUPLOAD_FILE_MAX_SIZEparameter is not adjusted; the default value cannot accommodate single large-scale engineering due diligence report PDF files exceeding 100 MB. - Phenomenon: The accuracy of answers to the same question decreases after multi-turn conversations. Cause: Redundant historical information in the context window is not cleaned; technical parameters of engineering due diligence reports rely on precise context, and redundant content will interfere with the matching logic of vector recall.
How to confirm that configurations are set correctly
- Upload a small test engineering due diligence report, check the segmented content after parsing, and confirm that the segment length matches the preset configuration.
- Initiate a query containing specific technical parameters or compliance clause numbers, and verify that the similarity scores of the retrieval results fall within the preset range.
- Call the knowledge base upload interface to upload the test file, confirm that the interface returns normally without timeout or file size errors.
- Initiate two related queries, observe whether the retrieval results always focus on the current conversation topic, and are not interfered with by redundant historical content.
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.