What the Data for This Category Looks Like
Computer equipment investment research data comes from hardware manufacturer official specification documents, industry test institution reports, compliance certification files, operation and maintenance logs, and supply chain ledgers. Update rhythms adjust based on hardware iterations, firmware upgrades, or compliance requirements. There is no fixed cycle. Most individual documents include structured parameter tables, function module descriptions, and test verification chapters. Fields include standardized technical parameters such as clock speed (GHz), memory capacity (GB), power consumption (W), interface type, and warranty period (years). Some documents include measured performance curves and compatibility notes.
Constraints for Knowledge Base Retrieval and Recall
The high proportion of structured parameters requires the retrieval link to support both precise keyword matching and semantic relevance matching. This avoids missing precise parameter queries. The non-fixed update schedule requires regular data source synchronization tasks. This ensures recalled content aligns with currently available market models and latest compliance requirements. Long-text test reports and performance curves require retaining contextual links between parameters and their corresponding test conclusions during segmentation. This avoids losing complete parameter matching logic after splitting. Some documents include multi-language parameter descriptions. Unified field unit expressions must be used during recall to avoid confusion between parameter values of different standards.
How to Configure
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
similarity threshold | 0.75–0.85 | Computer equipment parameters mostly require precise matching. A threshold that is too low introduces irrelevant parameter descriptions. A threshold that is too high fails to cover semantically similar model comparison scenarios. Calibrate based on actual testing. |
recall count | Top 8–12 results | Investment research scenarios require covering multi-model comparisons. Too many results increase context redundancy. Too few fail to provide sufficient comparison samples. This range adapts to the parameter density of technical documents. |
segment length | 800–1200 characters | Computer equipment documents often include continuous parameter tables and test descriptions. This length retains the contextual association between parameters and corresponding scenarios, avoiding split breaks. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large-volume test reports or multi-page specification documents takes a long time. The default timeout duration is insufficient. Extend the value to avoid upload interruptions. |
rerank return count | Top 3–5 results | Prioritize returning core parameter content that most closely matches the query. This adapts to the precision needs of investment research decisions and avoids interference from irrelevant information. |
text retrieval matching fields | "parameter name, parameter value, model identifier" | Most computer equipment investment research focuses on precise parameter queries. Specifying these core fields improves the hit efficiency of keyword retrieval. |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issuing a general unrelated query still results in the use of knowledge base content. The cause is that the
similarity thresholdis set too low. This broadens the semantic matching scope and judges unrelated questions as knowledge base matching content. - Semantic retrieval results contain a large number of low-relevance device parameter descriptions. The cause is that no minimum relevance filtering rule is configured for semantic retrieval. Text fragments unrelated to the query are recalled.
- When deploying v4.8.10 locally and uploading large-volume device documents, the interface shows a timeout and does not display the uploaded file. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a duration suitable for large documents. Background parsing is still running but the front end does not synchronize the status update.
How to Verify Proper Configuration
- Issue a precise parameter query. Check whether the returned results include the target device's corresponding fields and parameter values. Confirm the hit logic of keyword retrieval and semantic retrieval.
- Upload a single large-volume device test report. Check whether the interface normally displays the upload progress and parsing completion status. Confirm that the timeout configuration is effective.
- Issue a general query unrelated to the knowledge base. Confirm that the reply does not use knowledge base content. Verify the configuration correctness of the similarity threshold and trigger rules.
- View the knowledge base parsing logs. Confirm that the segmented text fragments retain the contextual association between parameters and corresponding test scenarios. Verify the rationality of the segment length configuration.
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.