What the Data for This Category Looks Like
Data for construction machinery intelligent due diligence reports covers all stages of the equipment full lifecycle, including factory ledgers, operation and maintenance logs, rental records, property registration documents, and on-site inspection reports. The data update rhythm changes with business nodes. Operation and maintenance data syncs daily. Ownership change data updates in real time.
Document structures include structured fields and unstructured attachments. Structured fields include 设备序列号, 累计作业时长, 出厂日期, 租赁甲方, and other items. Unstructured attachments are mostly PDF inspection reports and transcribed text from scanned paper maintenance records. Field units are standardized to hours, yuan, standard date format, and general name-based units.
What Constraints These Data Characteristics Impose on Vector Models and Indexes
Mixed-structured data requires configuring both attribute indexes and vector embedding indexes. Precise matching indexes are needed for unique identifier fields such as 设备序列号, while vector embedding for unstructured text supports semantic retrieval.
Differentiated update frequencies require a refresh strategy combining incremental and full updates, to avoid excessive resource usage from full index rebuilding. Document lengths vary widely: maintenance records as short as hundreds of characters, inspection reports up to tens of thousands of words. Flexible segmentation rules are needed to ensure embedding accuracy.
Multi-source data may have inconsistent field formats. Field validation and unit unification must be completed before indexing, to avoid impacting vector calculation accuracy.
How to Set the Configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
vector_segment_size | 800–1200 characters | Matches the average paragraph length of unstructured content in construction machinery due diligence reports, avoids semantic fragmentation from overly short segments or reduced embedding accuracy from overly long segments |
vector_db_duplicate_check | Deduplicate based on the 设备序列号 field | The unique identifier for engineering machinery equipment is the serial number, which prevents duplicate index entries for the same device |
index_refresh_interval | Daily full refresh + real-time incremental sync | Adapts to the business rhythm of real-time operation data sync and immediate ownership change updates, ensuring data consistency |
filterable_fields | ["设备序列号", "累计作业时长", "出厂日期"] | Covers high-frequency filtering dimensions in due diligence scenarios, supports quick recall of results by device unique identifier, operating hour range, and manufacturing year |
vector_model_name | Calibrated via scene-specific testing | Construction machinery text contains a large number of technical terms, requiring domain-specific embedding models to ensure semantic matching effectiveness |
recall_top_k | Top 10 results | Balances retrieval efficiency and information completeness, avoids excessive recall increasing context length pressure |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: A
403 Forbiddenerror is returned when calling the vector model, but embedding results can be obtained normally when testing with curl alone. Cause: Request authentication parameters for the vector model are not configured correctly, or the proxy forwarding rules do not open access permissions for the local service. - Phenomenon: Duplicate device entries exist after index merging, and content with the same
设备序列号appears multiple times in retrieval results. Cause: The deduplication logic based on unique identifier fields is not enabled, or the deduplication configuration is not bound to the设备序列号field. - Phenomenon: A permission denied error is returned when operating the vector database via an external management system, and add/delete operations cannot be performed. Cause: Only the default super user permissions are configured for the vector database, no fine-grained access roles are assigned to external systems, and no API access whitelist is configured.
How to Confirm the Configuration Is Correct
- A single construction machinery maintenance document is uploaded, and the index generation log is checked to confirm content splitting is completed according to the configured segmentation parameters, with segmentation results matching the document's content characteristics.
- Associated records for the same
设备序列号are retrieved, confirming only one unique entry is retained in the retrieval results, verifying the deduplication configuration is effective. - The vector database API is called via an external management system to perform add/delete operations, confirming the operations execute normally and the permission configuration meets business requirements.
- A domestic vector model is switched to initiate retrieval, confirming no "model not supported" errors occur, and retrieval results cover the expected device information dimensions.
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.