What the data for this category looks like
Data sources for construction machinery mainly include equipment operation reports released by industry associations, public technical manuals and product specifications from original equipment manufacturers (OEMs), supply chain component price lists, and monthly working condition monitoring data. Update rhythms fall into three categories: OEM product manuals are updated quarterly, industry operation reports are released monthly, and supply chain price data is updated weekly. Document structures include three categories: structured parameter tables, unstructured working condition analysis documents, and bidding compliance documents. Core fields include equipment model, manufacturer, rated lifting capacity, working radius, and compliance standards. Most parameter units use general engineering units such as tons, meters, and hours.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Scattered data sources with inconsistent update rhythms require differentiated incremental update strategies for different document types. This prevents mixing of old and new data. Documents contain large amounts of structured parameters and long-text technical descriptions. When splitting retrieval units, retain the association between parameters to avoid damaging the integrity of the parameter table. Core parameters follow a fixed unit system. Complete unit normalization during retrieval to avoid matching failures caused by unit conversion errors. Long individual document length increases parsing and indexing time. Adjust the index sharding strategy to optimize retrieval efficiency.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | Top 8-12 results | Construction machinery single technical documents are dense with parameters. Too many recalled results cause context redundancy and reduce answer accuracy |
similarity threshold | 0.72-0.85 | Need to distinguish subtle parameter differences between similar models. A threshold that is too low includes matching results from unrelated models |
segment length | 1000-1500 characters | Balances parameter integrity and context window utilization. Avoids splitting that breaks the association between parameter tables |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing large OEM technical manuals takes a long time. The default timeout period is insufficient to complete full parsing |
structured field mapping | Map according to equipment model, rated lifting capacity, working radius | Extract structured fields from the parameter table to support precise parameter retrieval |
UPLOAD_FILE_MAX_SIZE | 500 MB | Adapts to the single-file upload limit for large OEM technical manuals. Prevents large file upload failures |
The parameter values given on this page are common recommended starting points for determining configuration baselines. Actual values are affected by material format, 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 configuration mistakes
- A
403 Forbiddenerror returns when calling the knowledge base query interface. The cause is unconfigured API call permission for the knowledge base, misuse of the application key when initiating the request, and failure to use the API key. - Embedded device schematic diagrams in retrieval results fail to load normally. The cause is unconfigured external link whitelist for knowledge base image resources, or failure to retain relative image paths during parsing.
- Knowledge base retrieval time exceeds expectations, with obvious delays in returned results. The cause is disabled incremental indexing, where full indexing scans a large number of historical construction machinery documents and increases retrieval overhead.
How to confirm the configuration is correct
- Initiate a precise parameter search, enter a specified combination of equipment parameters, and verify that returned results only match documents of the corresponding model.
- Upload a single-page technical manual, and check if parsed structured fields correctly extract core parameters.
- Call the knowledge base query API, and check if returned results include correct document source identifiers.
- Adjust the similarity threshold value, and verify if the matching accuracy of retrieval results meets expectations.
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.