What This Category’s Data Looks Like
Research report data for professional services scenarios comes primarily from compliance-released industry research reports and individual stock analysis documents. Its update schedule aligns with the official release cycle of research reports. Each document follows a fixed structure, including fields such as title, issuing institution, release date, core logic, industry indicators, and target analysis. Numeric content mostly uses standard financial units, such as 100 million yuan, percentage, yuan per share, and similar units. Document lengths vary widely, with some in-depth research reports spanning tens of thousands of words.
What Constraints Do These Characteristics Impose on Knowledge Base Retrieval and Recall?
The fixed field structure of research reports requires retrieval and recall to support targeted field matching, such as filtering results by issuing institution or release date. The wide range of document lengths means long research reports must be split while retaining core logic units, to avoid breaking the argument chain. The presence of multiple numeric fields requires balancing recall rules for both semantic similarity and numerical matching. The update schedule aligned with research report release cycles necessitates an incremental synchronization mechanism to ensure data freshness, while avoiding performance overhead from full scans.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 1500–2000 characters | Matches the length of core argument units in research reports, retains complete logical chains after splitting |
maxContext | 10000–15000 tokens | Adapts to the context length following research report retrieval, avoids token overflow that disrupts model calls |
recall_top_k | Top 8–12 results | Balances result comprehensiveness and information conciseness, prevents redundancy from interfering with professional judgment |
similarity_threshold | 0.75–0.85 | Ensures matching accuracy between retrieval results and query requirements, filters out low-relevance content |
filter_by_metadata | Enabled | Supports quick filtering of results using research report metadata such as issuing institution and release date, aligns with professional retrieval needs |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Reserves sufficient time to parse long in-depth research reports, prevents parsing interruptions |
The parameter values provided on this page are common recommended starting points for configuration work. Actual values are affected by material format, data volume, and business rules. Individual scenarios require tailored analysis, and it is recommended to test on available self-hosted samples before finalizing settings.
Three Common Misconfigurations
- After uploading research reports in Excel format, table industry data cannot be extracted from retrieval results. Cause: No parsing rules for table documents are configured. The default parsing only extracts plain text content and does not retain structured table information.
- Images in markdown-formatted research reports stored in the knowledge base cannot be retrieved and recalled. Cause: Image OCR parsing configuration is not enabled. Only markdown text content is extracted, and text within images is not converted into retrievable text.
- A
413 Request Entity Too Largeerror occurs after a retrieval request is triggered. Cause: The recall token upper limit is not restricted. A large volume of retrieval context tokens is directly passed to the large model, exceeding the interface's bearing threshold.
How to Verify Proper Configuration
- Upload a standard in-depth research report, review the parsed segmented results. Confirm that the segments do not disrupt core argument logic, and verify the actual effect of the segmentation configuration.
- Initiate a retrieval request containing keywords for issuing institution and date. Confirm that the system can filter corresponding results using metadata, and verify that the metadata filtering configuration is active.
- Simulate a multi-concurrent retrieval scenario, observe interface response times. Adjust the values of recall count and context tokens, and keep response times within the range that meets business requirements.
- Upload a research report containing tables and images. Confirm that table values and text within images can be extracted after parsing, and verify the completeness of the parsing configuration.
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.