What This Type of Data Looks Like
Power industry research report data primarily originates from National Energy Administration public announcements, regular reports of listed power companies, brokerage industry research reports, and local grid operation monthly reports. Update frequencies cover daily (real-time grid operation data), monthly (regional electricity price and installed capacity statistics), and quarterly/annual (full industry perspective analysis). Document structures typically include fields such as title, publishing entity, publication date, core quantitative indicators (such as power generation, installed capacity), policy interpretations, and risk reminders. Quantitative indicator units are mostly ten thousand kilowatt-hours, ten thousand kilowatts, and yuan per kilowatt-hour.
Constraints Imposed on Vector Models and Indexes
The multi-frequency update feature of power industry research reports requires indexes to support incremental vector updates, eliminating performance loss from full reindexing. The coexistence of long full-perspective research reports and short, concise policy summaries requires vector models to balance long-context encoding capabilities and short-text semantic matching accuracy. The presence of multiple quantitative fields and fixed units requires indexes to retain field metadata during vectorization, preventing confusion of vector spaces between different indicators. Format differences across multiple data sources require the vectorization link to adapt to text formats extracted from structured tables, ensuring consistent semantic encoding.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Balances semantic integrity of long policy interpretations and short quantitative data in power industry research reports, ensuring vector retrieval accuracy |
chunk_overlap | 100–150 characters | Prevents semantic breaks after long text segmentation, maintaining cross-segment context coherence |
embedding_model | Prioritize text-embedding-3-large or text-embedding-v3, based on actual testing | Adapts to the large volume of long-text analysis content in power industry research reports, while matching the accuracy of short policy summaries |
top_k | 20–30 entries | Covers the diverse retrieval needs of power industry niche segments, recalling sufficient relevant results |
similarity_threshold | 0.72–0.80 | Filters low-relevance general industry reports, retaining results that strongly match power industry niche segments |
index_refresh_interval | 1 hour | Adapts to the update rhythms of daily grid data and monthly brokerage research reports, balancing index freshness and system performance |
The parameter values provided on this page are all conventional recommendations, used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Phenomenon: An
undefined model must match "^(text-embedding-.*)$"error occurs when selecting a vector model other thantext-embedding-ada-002. Cause: The verification logic of some vector model interfaces only allows model names matching a fixed prefix, and does not adapt to custom naming rules of other vendors. - Phenomenon: Semantic retrieval scores are high, but returned results are not associated with power industry niche segments. Cause: The vectorization link does not retain metadata of industry-specific quantitative fields, causing general semantic vectors to fail to distinguish similar expressions across industries.
- Phenomenon: Multiple duplicate vectors are generated for a single piece of power data. Cause: A reasonable
chunk_overlapparameter is not configured, or the redundant segmentation switch is not turned off in version v4.8.7.
How to Confirm Correct Configuration
- Upload a single typical power industry research report, check the parsed segmented content, confirm that the segmentation parameter configuration meets expectations.
- Initiate a retrieval request targeting core power industry indicators, check the relevance of returned results, adjust the similarity threshold to a range suitable for business needs.
- Submit a new piece of power industry data, trigger incremental index update, confirm that the updated data can be retrieved normally.
- View the vector model call logs, confirm that the request format of the selected model meets interface requirements, with no errors returned.
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.