What this category of data looks like
Data for engineering machinery declaration materials and file review comes primarily from complete machine factory archives, component inspection reports, project declaration approval forms, on-site maintenance records, and compliance files. Data updates trigger with project initiation, acceptance, and maintenance cycles. Single batch upload volumes are large. Most documents include complete machine numbers, project batch numbers, inspection parameters, qualified judgment results, and approval signature fields. They also include attached drawings and inspection report documents. Units used include units, operating hours, MPa, N·m, and other engineering-specific units.
Constraints on knowledge base retrieval and recall
The large batch size of engineering machinery declaration data and its inclusion of professional engineering parameters leads to excessive redundant content in basic retrieval and recall. Recall scope and matching accuracy must be limited. Documents contain specialized units and non-standard fields. General retrieval models cannot accurately match professional terms. Retrieval matching logic must be optimized. Scenarios with attached drawings and report attachments require support for text extraction and associated retrieval of multi-format files. This prevents missing key attachment information. Single retrieval must cover approval processes and maintenance history. Retrieval scope must align with all process nodes of declaration files. This prevents incomplete recall.
Configuration Settings
These configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Adapts matching accuracy for engineering machinery professional terms, filters irrelevant general engineering content |
limit | Top 8 entries | Controls the number of materials recalled per single retrieval, adapts to the processing rhythm of batch review |
searchMode | Exact match | Targets structured fields such as complete machine numbers and project batch numbers, improves accurate recall rate |
usingReRank | Enabled | Rearranges recall results by professional parameter relevance, prioritizes displaying core inspection items |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands the query scope for engineering units and terms, covers specialized expressions such as "operating hours" and "MPa" |
collectionIds | Exclusive collection ID corresponding to engineering machinery declaration files | Isolates data from other categories, avoids cross-collection recall interference |
Three Common Mistakes
- Retrieval results return a large number of irrelevant general engineering documents. This occurs when the
similaritythreshold is not set, or is set too low, failing to filter non-exclusive content. - Retrieval results omit key component inspection reports. This occurs when
datasetSearchUsingExtensionQueryis not enabled, preventing matching of synonymous expressions for specialized parameters. - Retrieval results have excessive redundancy, obscuring core review information. This occurs when uploaded document formats and fields are not standardized, and files are not organized according to the fixed structure of declaration materials, leading to retrieval of irrelevant content.
How to Verify Correct Configuration
- Upload one standard engineering machinery declaration file, run a retrieval test, and confirm the returned result set only contains content from the target dataset.
- Enter a query term containing professional engineering parameters, confirm the relevance of retrieval results meets expectations, and adjust the
similaritythreshold to a reasonable range. - Check the number of retrieval results, confirm it matches the
limitparameter setting, and verify the retrieval upper limit meets review requirements. - Check the sorting order of retrieval results, confirm core review items appear first after
usingReRankis enabled.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.