What the data for this category looks like
Investment research data for large state-owned banks comes primarily from monthly and weekly reports produced by internal investment research teams, regulatory documents released by the central bank and national banking regulatory authority, public indicators from macroeconomic databases, and statistical reports from industry associations. Update rhythms vary widely. Regulatory files update in real time as released. Macro indicators update daily or weekly. Internal reports update alongside investment research progress. Documents include long research reports, structured indicator tables, and semi-structured analysis paragraphs. Fields include issuing institution, release time, document type, and core business indicators. Indicator units include basis points, percentage, hundreds of millions of yuan, and others.
What constraints do these characteristics impose on vector models and indexing
Long research reports account for a large share of the data. Chunking strategies must balance semantic completeness of paragraphs and reasonable chunk granularity. Direct encoding of single long texts causes semantic fragmentation. A large number of structured indicator tables require support for table structure recognition and vectorization. Without this support, association information between indicators will be lost. Coexisting data with multiple update rhythms requires indexes to support flexible switching between incremental updates and full reconstruction. This reduces update time. Core indicators have clear units. Vector models must adapt to standardized encoding of numeric fields. This ensures indicators with different units can be correctly compared.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Segment Max Length | 800–1200 characters | Research reports from large state-owned banks are mostly professional long paragraphs. This range covers complete semantic units and avoids chunk breakage |
Paragraph Recognition Depth | 3–5 levels | The structure of bank research reports mostly uses nested chapters. A 3-level depth accurately identifies semantic boundaries of sub-paragraphs |
Vector Dimension | 1024–1536 dimensions | Adapts to the output dimensions of mainstream multimodal Embedding models, and covers detailed information in investment research texts |
Recall count | Top 10–15 results | Investment research scenarios require a balance between information breadth and relevance. Too many results increase context load, while too few miss key content |
Similarity threshold | 0.72–0.85 | Investment research texts are highly professional. A higher threshold filters low-relevance non-professional content |
Incremental Index Update Interval | Once per hour | Macro indicators and policy files update at high frequencies. This interval ensures index timeliness |
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. Each scenario requires specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: After configuring the Embedding model and index, the page still displays "No available index model detected". Cause: The vector model was not bound to the index configuration item of the corresponding knowledge base, or the model deployment status was not synchronized to the front-end cache.
- Phenomenon: When calling the API to create a chunking task, the returned parameters do not meet expectations. Cause: The enabled status of the
paragraph_recognizeparameter was not specified correctly, and the value ranges ofmax_chunk_sizeandmax_paragraph_depthwere incorrect. - Phenomenon: After upgrading to a new version, old vector database data cannot be properly recalled by the new index. Cause: The vector dimension or chunking strategy of the old and new versions is inconsistent, and data format conversion was not performed before direct migration.
How to Confirm Successful Configuration
- Navigate to the index configuration page of the knowledge base, verify that the bound vector model matches the currently used model, and confirm the model status shows as ready.
- Upload a typical large state-owned bank research report document, view the chunking preview result, and confirm that the chunking granularity and paragraph recognition meet configuration expectations.
- Initiate a small-scale recall test, enter investment research-related query terms, and verify that the relevance and number of recall results meet configuration requirements.
- Trigger an incremental index task, view the task log, and confirm that the index update process has no errors and data synchronization is normal.
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.