What the Data for This Category Looks Like
General equipment investment research data sources include monthly operation monitoring data released by the China General Machinery Industry Association, official technical manuals of domestic and foreign general equipment manufacturers, periodic reports of listed companies, and third-party compliance test reports. Document structures include structured parameter tables (with fields such as flow rate, pressure, power, and units mostly m³/h, MPa, kW), unstructured technical descriptions, operation log snippets, and industry analysis content. The update rhythm is as follows: industry monitoring data is updated monthly, listed company reports are released quarterly or annually, manufacturer technical manuals are updated statically, and real-time operation data has a high synchronization frequency.
Constraints These Characteristics Impose on the Citation Source and Traceability Link
The multi-source nature of general equipment data requires complete labeling of the publishing organization and publishing time in traceability information to avoid parameter confusion. Standardized expression of structured parameters requires retrieved documents to be bound to specific parameter sources to ensure traceability accuracy. Differences in the length of unstructured documents require retaining original chapter associations during segment processing to avoid losing context after splitting. High-frequency updates of real-time monitoring data require configuring incremental synchronization mechanisms to prevent the use of expired data. Differences in units across different data sources require retaining original unit labels during traceability to avoid unit misuse during investment research.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
recall count | top 8–12 | General equipment investment research data includes both structured parameters and long-text descriptions. Excessive recall will lead to redundant context, while insufficient recall will fail to cover core parameters and industry analysis content |
similarity threshold | 0.72–0.85 | Technical parameter expressions for general equipment are highly standardized. A threshold that is too low will introduce irrelevant documents, while a threshold that is too high will miss compliant parameters from different manufacturers in the same category |
segment length | 800–1200 characters | General equipment technical manuals are mostly paragraph-based descriptions. Segments that are too long will lose context associations, while segments that are too short will destroy the binding relationship between parameters and descriptions |
reordered return count | top 4–6 | Investment research scenarios require prioritizing matching core parameters and authoritative industry reports. Retaining a small number of supplementary documents after reordering can meet analysis needs |
citation source display toggle | enabled | Investment research scenarios require clear labeling of parameter sources, which complies with information disclosure requirements for financial compliance |
traceability information field configuration | includes publishing organization, publishing time, document type | Data sources for general equipment are scattered. Complete recording of traceability information can effectively verify the authority and timeliness of parameters |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: The AI response shows that a knowledge base document was cited, but the content does not include the core parameters from the document. Cause: The
segment lengthis set too long, leading to the loss of the binding association between parameters and descriptions during document splitting, or the recalled documents do not correctly match the core keywords of the query. - Phenomenon: Only text datasets are recalled, and image and table datasets do not appear in the citation list. Cause: The
multimodal data recallconfiguration is not enabled, or structured table data is not processed through OCR and text conversion. - Phenomenon: After configuring dynamic knowledge base variables, the AI response does not associate documents from the specified knowledge base. Cause: The data source scope of the
knowledgeSearchvariable is not correctly bound during dynamic value transfer, or thesimilarity thresholdis set too high, filtering valid recall results.
How to Confirm the Configuration Is Complete
- Upload a general equipment manufacturer's technical manual, submit a query that includes specific parameters, and check whether the interface displays the corresponding document source link and release information. View the recall log in the knowledge base backend to confirm that the matched document types include structured tables, technical descriptions, etc., and include other types in addition to text data.
- Dynamically pass the specified knowledge base ID to submit a query, and verify whether the AI response only associates document content from the specified knowledge base.
- Temporarily disable the
citation source display toggle, submit a query, confirm that the interface no longer displays citation information, and restore the toggle to re-display complete traceability 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.