What the data for this category looks like
General equipment research report data mainly comes from industry association public statistical materials, periodic reports of listed general equipment manufacturers, industry analysis reports for professional niche fields, and product manuals and technical parameter documents from equipment manufacturers. In terms of update frequency, listed company reports are updated quarterly, industry analysis reports are released monthly or via special research initiatives, and product parameters are updated irregularly as technology iterates. Each single document usually includes core equipment parameters, specific proportion values of downstream application scenarios, market supply and demand data, policy impact analysis, and corporate operating data. Core fields include equipment model, rated power, maximum load capacity, machining accuracy, revenue scale, and production capacity scale, with corresponding units being unit, kilowatt, kilogram, micrometer, ten thousand yuan, and units/year.
Constraints for Knowledge Base Retrieval and Recall
Dispersed data sources and inconsistent update frequencies require batch synchronization of documents from different sources to avoid recalling outdated product parameters or old operating data. Documents contain a large number of technical parameters and numeric fields. Traditional text retrieval tends to overlook the precision of parameter matching, so structured data retrieval capabilities are needed. Numeric content related to downstream applications requires support for filtering recall results by numeric ranges. Product parameter documents are usually short but highly professional, so the segmentation strategy needs to be adjusted to retain complete technical logic and avoid retrieval deviations caused by semantic breaks. Batch updates of listed company reports will create pressure for incremental synchronization of the knowledge base, so an incremental update mechanism needs to be configured to reduce resource occupation from repeated processing.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment length | 800–1200 characters | General equipment research reports contain continuous technical parameters and analytical logic. This length preserves complete semantic units within a single segment, avoiding breaks in parameter associations after splitting |
number of recalled entries | Top 10 entries | General equipment research reports have high effective information density. Too many recalled entries will exceed the context window limit, while too few will fail to cover multi-dimensional analysis requirements |
similarity threshold | 0.72–0.85 | Technical parameter queries have high requirements for matching accuracy. This interval filters irrelevant results while retaining parameter comparison information for devices of the same category |
incremental sync interval | 6 hours | Listed company reports are updated quarterly, and industry reports are released monthly. A 6-hour interval balances real-time performance and synchronization resource usage |
maxContext | 12000 characters | Single analytical content in general equipment research reports is relatively long. This window can accommodate the complete context of multiple recalled segments, supporting complex associated queries |
reranked returned entries | Top 3 entries | Prioritize returning the most matching core research report content to avoid user interference from redundant information |
The parameter values provided on this page are all common recommended starting points 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.
Three Common Misconfigurations
- Phenomenon: Irrelevant research reports unrelated to general equipment parameters are returned during semantic search. Cause: The similarity threshold is set too low, causing low-matching irrelevant documents to be recalled.
- Phenomenon: After importing corporate operating data into MySQL, no corresponding results are returned during retrieval. Cause: No association rules between structured data and text retrieval are configured, causing numeric fields to not be included in the retrieval index.
- Phenomenon: Application information errors occur during knowledge base synchronization, with
DB_CONN_FAILEDdisplayed in logs. Cause: MySQL connection port and permission parameters are not configured correctly, causing the system to fail to read imported business data.
How to Verify Correct Configuration
- Submit a query that includes specific equipment parameters, check whether matching technical parameter fields are included in the recalled results, and confirm that the segmentation and context configurations are effective.
- Trigger an incremental synchronization task, check whether only newly added research report documents are updated in the synchronization log, and confirm that the incremental sync interval configuration is effective.
- Adjust the test value of the similarity threshold, compare the number of recalled results under different thresholds, and confirm that the threshold interval meets the category requirements.
- Import a structured equipment data table, perform a numeric range query, and confirm that the structured retrieval function is properly configured.
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.