What Data for This Category Looks Like
Computer equipment investment research data comes from hardware vendor official specification documents, third-party performance test reports, operation and maintenance archive logs, and industry compliance certification documents. Update cadence aligns with new product launch cycles. Compliance documents update in line with regulatory requirements. Most document formats include structured parameter tables, annotated PDF specification sheets, and JSON-formatted API response data. Fields include device model, release date, core hardware parameters, power consumption unit (watt), bandwidth unit (Gbps), certification number, and some documents include time-series operational status log data.
Constraints on Citation Sources and Provenance Workflows
High proportions of structured parameters require provenance to bind to specific fields, avoiding vague text to prevent parameter matching errors. Frequently updated product models and compliance documents require provenance tags to include version numbers and update times, preventing reference to outdated data. Multi-format data sources must retain original unit mappings during parsing, to ensure consistent parameter units when citing. Provenance for time-series operation and maintenance logs must link to collection timestamps, to match device operational status for the correct period and avoid cross-period parameter matching errors.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_top_k | Top 20-30 entries | Computer equipment has many parameter dimensions; this range covers sufficient matching items while avoiding redundant recall |
source_trace_field | ["device_model", "publish_date", "unit"] | Must bind device model, release time, and parameter unit to ensure precise provenance matching |
chunk_overlap | 50-100 characters | Most equipment parameter documents are long tables; overlapping fragments preserve cross-page parameter relationships |
max_context_tokens | 8000-12000 | Total token volume of equipment parameters and test reports is high; this range accommodates sufficient provenance context |
parse_keep_original_metadata | Enabled | Original document fields such as certification numbers and serial numbers for provenance must be retained, without filtering during parsing |
sync_interval | Every 7 days | Computer equipment iteration cycles are stable; incremental sync covers new product models and updated compliance documents |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific scenarios require individual analysis. Testing on local samples is recommended before finalizing settings.
Three Common Configuration Mistakes
- Symptom: The number of context entries displayed in the interface does not match the actual number of citations passed to the AI. For example, the interface shows 30 entries but 310 are actually passed. Cause: The association between
recall_top_kand front-end display count was not configured correctly. Recalled entries were truncated by the context window, but the front-end display was not updated synchronously. - Symptom: After setting
max_source_displayto 1500, chunks longer than 1500 characters in the knowledge base are still cited. Cause: Only front-end display count was limited,chunk_sizewas not bound to citation access rules, and recall of overly long chunks was not filtered. - Symptom: Knowledge base citation data passed in workflows cannot be correctly identified by the AI. Cause: Metadata fields specified by
source_trace_fieldwere not passed as required, only plain text content was sent, and necessary provenance information was missing.
How to Verify Correct Configuration
- The parsed document metadata panel may be reviewed to confirm that specified fields such as
device_modelandpublish_dateare fully retained and not filtered during parsing. - A knowledge base retrieval test may be run, with the number of recalled entries displayed on the front end compared to the actual number of entries recorded in backend logs, to ensure the two values match.
- A device specification document including parameter units may be uploaded, and final citation results may be checked for retained original unit information, with no unit loss or conversion errors.
- The value of
recall_top_kmay be adjusted, and changes in the number of retrieval results observed, to confirm that the configuration parameter takes effect.
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.