What This Type of Data Looks Like
Large state-owned bank financial report data is sourced from the investor relations section of official websites. It is released on a fixed schedule: quarterly, semi-annually, and annually. Documents include structured reports and accompanying written explanations. Structured reports present core business indicators as multi-page tables. Accompanying written explanations include business analysis and risk warnings. A complete financial report document is lengthy, containing multiple coherent text passages and multiple sets of linked tables. Data fields include asset size, operating revenue, net profit, and others. All units are 100 million yuan.
What Constraints These Characteristics Impose on Vector Models and Indexing
Fixed release schedules require indexes to support incremental updates. This avoids repeated compute resource consumption from full reindexing. Long documents and multi-paragraph structures require chunking strategies that preserve contextual connections. This prevents breaks in cross-paragraph business logic. Mixed structured and unstructured content formats require indexes to support vectorization of both tabular data and text passages. Multi-dimensional business indicator field structures require indexes to allow retrieval weight configuration by field category. This improves retrieval accuracy.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the length of single text passages in large state-owned bank financial reports. Avoids excessive splitting that breaks business logic connections |
chunk_overlap | 100–150 characters | Preserves contextual connections between adjacent chunks. Prevents breaks in cross-paragraph indicator explanations in financial reports |
embedding_model | Prioritize compliant models that support long texts | Meets the long text embedding requirements of financial reports. Covers semantic expression of complete business information |
index_refresh_interval | Hourly incremental refresh | Matches the fixed release schedule of large state-owned bank financial reports. Balances real-time performance and resource consumption |
retrieval_top_k | Top 8–12 results | Covers the retrieval needs of multi-dimensional indicators in financial reports. Avoids missing core information due to insufficient recall |
similarity_threshold | 0.75–0.85 | Filters low-relevance retrieval results. Adapts to the semantic matching accuracy required for financial report terminology |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis. It is recommended to conduct tests on relevant samples before finalizing the configuration.
Three Common Configuration Mistakes
- Phenomenon: An error of the type "undefined model must match" is returned when calling the embedding interface. Cause: The platform's preset compliant vector model is not used, or the manually entered model name does not match the platform's supported naming rules. This prevents successful vectorization of financial report text.
- Phenomenon: Semantic retrieval returns high similarity scores, but the results have low relevance to core financial report indicators. Cause: Index weights are not configured separately for structured financial report data and text content, or chunk length is set incorrectly. This causes deviations in semantic matching.
- Phenomenon: A single financial report data entry cannot generate multiple corresponding vectors, or the interface only displays a single vector model configuration option. Cause: The multi-chunk vector storage function is not enabled, or the multi-vector indexing mode is not activated. This fails to meet the vectorization requirements of multi-field, multi-paragraph financial reports.
How to Confirm the Configuration Is Complete
- A single test financial report document is uploaded. Embedding task run logs are reviewed to confirm successful model calls and no format errors.
- A retrieval test is executed. Keywords for core financial report indicators are entered. Retrieved result chunks are verified to match original text logic.
- The index management page is viewed. The incremental refresh task is confirmed to trigger per the preset cycle, and newly uploaded financial report documents have completed index updates.
- The multi-vector configuration module is checked. Multi-chunk storage is confirmed to be enabled, and multiple vector entries corresponding to a single document can be viewed.
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.