What the data for this category looks like
Power industry investment research data sources include public industry research reports, monthly operation reports of grid enterprises, annual social responsibility reports, technical documents of power equipment, policy documents issued by energy authorities, regional grid load monitoring data, and more. Update rhythms vary: policy documents are released irregularly, monthly reports are updated on a monthly basis, annual reports are updated annually, equipment technical documents are updated irregularly alongside product iterations, and load data is updated minute-by-minute. Document structures include structured tables, long research reports, short parameter descriptions, and more. Structured tables typically contain fields such as unit number, power generation, coal consumption for power supply, with corresponding professional units attached.
Constraints on Vector Models and Indexing from These Characteristics
First, there are many structured fields with fixed units. Indexing must support field-level vector extraction and unit association to avoid semantic confusion. Second, data update rhythms vary widely, ranging from minute-by-minute to annual updates. Configurable, customizable index refresh trigger rules are needed to differentiate update frequencies for different data sources. Third, document lengths span a wide range, from tens of characters of parameter descriptions to tens of thousands of characters of research reports. Flexible adjustment of chunking parameters is required to adapt to texts of different lengths. Fourth, professional terminology is dense. Vector models adapted to the energy and power sector must be selected to ensure accurate encoding of professional semantics.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Power industry investment research documents mostly contain professional indicator analysis with complete logic; chunking must cover core information units to avoid splitting critical content |
similarity_threshold | 0.72–0.85 | Power professional terminology has clear semantic boundaries; the threshold must be higher than general scenarios to filter low-relevance non-professional search results |
recall_top_k | Top 10–15 results | Power investment research requires covering multi-dimensional indicators; too many recalled results increase context processing pressure, while too few may miss critical data |
index_refresh_interval | 15 minutes (real-time load data), 1 day (monthly reports) | Match the update rhythms of different data sources to avoid ineffective full index refreshes |
structured_field_embedding | Enabled | Most power data contains structured indicators; separately embedding fields can improve retrieval accuracy for professional indicators |
embedding_model | Specialized embedding model for the energy and power sector | General embedding models have deviations in understanding power professional terminology; specialized models can improve retrieval relevance |
The parameter values provided on this page are conventional recommendations used as a starting point 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 values.
Three Common Misconfigurations
- Phenomenon: After updating to version 4.9-4.10, the original knowledge base cannot trigger vector retrieval, and the search returns no results. Cause: The new version adjusts the underlying storage format of the vector index, and does not automatically migrate the vector data of the original index, resulting in the original index being unrecognizable.
- Phenomenon: After batch uploading a large number of power equipment documents, the service crashes. After restarting, the knowledge base status shows not ready, and the index cannot be completed automatically. Cause: The shard threshold for batch uploads is not configured, and the single batch upload data volume exceeds the server load limit, causing the indexing process to interrupt and no breakpoint resume configuration is retained.
- Phenomenon: Unit-confused indicators appear in retrieval results, such as mixing and returning MWh and kWh data of power generation. Cause: The structured field embedding configuration is not enabled, and fields with units are not separately vector-encoded, resulting in deviations in semantic matching.
How to Confirm Proper Configuration
- Upload a single power professional document, trigger indexing, then check the
embedding_progressfield in the system console to confirm that the progress updates normally until completion. - Search for query terms containing known power professional indicators, and verify that the similarity scores of the returned results fall within the preset threshold interval.
- Configure an incremental update task, upload a new monthly operation report, and confirm that the index is automatically triggered and the vector database is updated.
- Enter the knowledge base management interface, check the
index_statusfield, and confirm that it shows the ready status.
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.