What the data for this category looks like
The data sources for integrated services investment research include exchange public announcements, brokerage research report libraries, financial data APIs, and internal investment research documents. Data update frequency varies by source: public announcements are synced in real time, brokerage research reports are updated according to their release frequency, and internal documents are updated on demand. A single document usually includes four fixed modules: abstract, industry analysis, target valuation, and investment advice. Fields include target code, issuing institution name, release date, core recommended targets, earnings forecast value (unit: RMB yuan), etc. There is no unified formatting template, and some documents include structured data charts.
What constraints these characteristics impose on the knowledge base retrieval and recall link
Mixed multi-source data contains structured fields and unstructured text. This requires the retrieval link to support both vector recall and precise field matching, to avoid missing accurate target code or institutional rating information. Frequently updated data sources require the recall logic to filter non-latest documents older than 30 days by default, to prevent outdated investment advice from interfering with decision-making. Documents contain a large number of professional terms and structured numerical values, so the semantic similarity judgment standard must be higher than that of general scenarios. Single documents are relatively long, so context association across paragraphs must be retained during segmentation, to avoid losing core investment logic after splitting.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_count | Top 10-15 entries | Investment research documents for integrated services have relatively long length. Too many recalled entries will exceed the application context window, while too few will fail to cover all relevant information |
similarity_threshold | 0.72-0.85 | Investment research documents contain a large number of professional terms, so the threshold must be higher than general scenarios to avoid low-relevance non-professional content being included in retrieval results |
rerank_count | Top 3-5 entries | Investment decisions rely on accurate information. Retaining a small number of high-quality results after reranking facilitates quick location of core content |
UPLOAD_FILE_MAX_SIZE | 200 MB | Single research report collections or historical document packages have large volume, so the upload limit needs to be relaxed to support batch import |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing requires processing a large amount of text and embedded charts, so the timeout setting must be sufficient to cover the full parsing process |
segment_length | 800-1200 characters | Investment research documents contain dense professional data. Too long segments will reduce vector recall accuracy, while too short segments will destroy semantic coherence |
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, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is no retrieval results after enabling the
rerank modelin the application, but normal results in the knowledge base test. The cause is that the application's rerank model call permission is not bound to the corresponding knowledge base, or the application's context window configuration does not accommodate the reranked returned content. - The symptom is that the knowledge base search response time exceeds 10 seconds. The cause is that the recall entry count is set too high, or field filtering is not enabled, resulting in an overly large retrieval scope, and no retrieval result caching mechanism is configured.
- The symptom is that after upgrading from version 4.8.7 to 4.8.16, the knowledge base cannot display content normally. The cause is that the vector database index configuration was not updated synchronously during the version upgrade, or the old document parsing format is incompatible with the new version.
How to confirm the configuration is correct
- Enter the knowledge base management interface, perform a batch test retrieval, and check that the number of returned results matches the set
recall_countvalue. - In the application debugging panel, enter an investment research-related query term, and check whether the retrieval log contains complete records of field filtering, similarity calculation, and rerank model calls.
- Upload a test research report document, wait for parsing to complete, and check whether the parsed segmented content retains the core valuation and investment advice modules.
- Compare the retrieval results from the knowledge base test and the in-application results to confirm that the returned content is consistent, with no permission or configuration differences.
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.