What the data for this category looks like
Securities research report data primarily comes from brokerage research institutes, public and private equity research departments. It is updated in batches on trading days, with no new releases on non-trading days. Individual documents mostly use long-text structures, containing fields such as title, publishing institution, release date, core logical reasoning, industry ratings, profit forecast tables, and more. The rating field uses a fixed enumeration value. The profit forecast field includes quantitative units and a large amount of structured table content. Core logic is presented as coherent long text with a high density of professional terminology.
What constraints do these characteristics impose on the vector models and indexing link
The long-text structure of research reports requires vector models to adapt to long contexts, preventing semantic segmentation from breaking professional logic. The presence of structured fields and table content requires indexing systems to support retrieval that combines structured and plain text features. The batch update per trading day requirement means indexes must support incremental updates to match the fast release rhythm. The high density of professional terminology requires vector models to be adapted to financial professional corpora, otherwise semantic matching deviations may occur. The large volume of content in individual documents requires the recall phase to control the number of vectors processed per request, avoiding excessive resource usage.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
embedding_model | shaw/dmeta-embedding-zh or other open-source Chinese embedding models adapted to the financial domain | Securities research reports contain a large number of financial professional terms, requiring adaptation to Chinese long-text semantic understanding capabilities |
chunk_size | 800–1200 characters | The length of core logical paragraphs in research reports is concentrated. This range ensures complete semantics after segmentation while controlling the overhead of single vector calculation |
chunk_overlap | 100–150 characters | Retains contextual connection between segments, avoiding key reasoning logic being truncated at segment boundaries |
index_refresh_interval | 5 minutes | Adapts to the batch update rhythm of research reports per trading day, ensuring newly released reports can be retrieved quickly |
retrieve_top_k | Top 10–15 results | Individual research reports have large content volume. This setting controls the redundancy of recall results while covering core relevant reports |
structured_field_embedding | Enable separate vectorization for the industry rating and profit forecast fields | Research reports include structured quantitative and enumeration fields. Combining structured features can improve retrieval accuracy |
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 settings.
Three common configuration mistakes
- Phenomenon: Knowledge base search responses time out, and the number of returned results does not reach the preset threshold. Cause: The
chunk_sizeandretrieve_top_kparameters are not adjusted for research report long texts, resulting in single-request vector calculation and recall volume exceeding hardware load limits. - Phenomenon: Structured table or rating field content is not correctly recalled. Cause: The
structured_field_embeddingconfiguration is not enabled, and vectors are only generated for plain text content, ignoring the retrieval value of structured fields. - Phenomenon: Newly released research reports cannot be retrieved. Cause: The
index_refresh_intervalis set too long, failing to adapt to the trading day update rhythm of research reports, resulting in delayed index updates.
How to confirm the configuration is correct
- Upload a single standard securities research report, check the vector generation log to confirm that the segmentation length matches the set
chunk_sizeparameter. - Initiate a retrieval request containing financial professional terms or structured fields, verify whether the recall results include the core content of the corresponding research report.
- Check the index management interface to confirm that the incremental index update frequency matches the set
index_refresh_intervalparameter. - Test retrieval with rating or profit forecast conditions, confirm that the recall results include matching structured field content.
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.