What This Category’s Data Looks Like
Semiconductor research reports primarily come from sell-side research institute industry teams, public reports from semiconductor industry associations, financial reports and capacity announcements from wafer fabrication manufacturers, and supply chain analysis documents from downstream electronic device manufacturers.
Update cycles include weekly industry trend briefings, monthly industrial chain data tracking, quarterly full-industry in-depth reports, and real-time analysis documents following sudden technical events.
Typical document structures include core summaries, industry macro data, enterprise updates in segmented tracks, professional technical parameter analysis, upstream and downstream industrial chain association analysis, and risk warning modules. Fields cover professional metrics such as production capacity, process nodes, and revenue scale, with corresponding units of wafers per month, nm, and 100 million yuan respectively.
Constraints Imposed on Knowledge Base Retrieval and RAG
Data sources are scattered and have diverse formats, including PDF, Word, web pages and other formats, requiring adaptation to multi-source parsing logic. Update frequencies are uneven: Research reports for sudden events need immediate synchronization, while quarterly in-depth reports can be updated on a scheduled basis, creating differentiated requirements for incremental update strategies. Individual documents are lengthy; some in-depth research reports span dozens of pages, containing long paragraphs of technical analysis. Context integrity of professional terms must be preserved during segmented retrieval. Professional terms are dense with many segmented dimensions, so retrieval must accurately match the professional semantics of the semiconductor industry to avoid retrieving generic industry content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Semiconductor research report PDFs may contain large numbers of charts and long text; the default 100 MB threshold cannot meet upload requirements |
Segment Length | 1200–1500 characters | Semiconductor research reports include long paragraphs of technical analysis. Excessively long segments will break semantic associations of professional terms, while excessively short segments will split complete technical logic |
Number of Retrieved Results | Top 8–12 | Semiconductor research reports cover many segmented tracks, requiring sufficient retrieved results to cover content across different dimensions such as industry trends, enterprise data, and technical analysis |
Similarity Threshold | 0.72–0.80 | Semiconductor professional terms have high semantic differentiation. A threshold that is too low will introduce irrelevant generic industry reports, while a threshold that is too high may miss valid content |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing large-volume semiconductor research reports takes a long time; the default timeout may cause parsing failures |
Incremental Update Trigger Rule | Based on file modification time + daily incremental scan | Adapts to the uneven update frequency of semiconductor research reports, balancing sudden updates and scheduled synchronization needs |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test against local samples before finalizing settings.
Three Common Misconfigurations
- Issue: When a single semiconductor research report larger than 100 MB is uploaded, the interface prompts that the file size exceeds the limit. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration was not adjusted, and the default threshold was retained, which cannot meet the upload requirements for large-volume research reports. - Issue: When the large language model is called, an
insufficient_quotaerror is returned, or a prompt indicating upstream service saturation is displayed. Cause: Too many documents were retrieved, and the total context token count sent to the large language model was not limited, triggering quota or load restrictions from upstream services. - Issue: The answer returned by the large language model is unrelated to the knowledge base content and is generated solely based on general knowledge. Cause: The similarity threshold was set incorrectly, or the retrieved documents did not properly match the semantic associations of professional terms, resulting in valid content not being retrieved.
How to Verify Proper Configuration
- A single semiconductor research report larger than 100 MB is uploaded. Successful upload and error-free parsing are confirmed, and the
UPLOAD_FILE_MAX_SIZEconfiguration is verified to match the file size. - A query containing semiconductor professional terms such as FinFET, wafer capacity is submitted. All retrieved result documents are confirmed to be semiconductor industry research reports, and the
Similarity Thresholdis adjusted until the results meet expectations. - Token consumption and response time of the question and answer are checked. The
Number of Retrieved Resultsand context truncation configuration are adjusted to keep resource consumption within a reasonable range. - A test research report with a marked modification time is uploaded. The incremental update task is confirmed to be triggered automatically, and the
Incremental Update Trigger Ruleconfiguration is verified to be effective.
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.