Knowledge Base Retrieval and Recall for Diversified Financial Financial Report Analysis

Diversified financial financial report data comes from official institutional disclosure documents. These include periodic reports and temporary

What the data for this category looks like

Diversified financial financial report data comes from official institutional disclosure documents. These include periodic reports and temporary announcements published on designated disclosure platforms of domestic and overseas exchanges, plus reference data released by industry self-regulatory organizations.

Update cycles follow two patterns: fixed schedules and temporary triggers. Periodic reports are released quarterly and annually. Temporary announcements are updated in real time alongside major operational events.

Document structures include structured financial data tables, unstructured business descriptions, risk management reports, and some files include chart attachments. Fields cover total asset size, trust asset balance, operating revenue, net capital, and more. Most units are hundreds of millions of yuan or ten thousands of yuan.

What constraints these characteristics impose on knowledge base retrieval and recall

Structured financial data tables account for a large share of content. This requires retrieval systems to support precise field matching, to avoid recall results with ambiguous semantics.

Document length varies widely, from a few pages of temporary announcements to dozens of pages of annual reports. This demands adaptive chunking and context concatenation strategies for variable lengths.

Updates follow both fixed schedules and temporary triggers. The knowledge base must support incremental updates to reduce costs from full reconstruction.

Attachments contain large numbers of charts. This requires enabling non-text content parsing capabilities to support chart-related retrieval needs.

Data-related entities are clearly defined. Retrieval results must include metadata such as report issuing institutions and release times, to avoid confusion between financial report data from different institutions.

How to set configurations

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS1200 secondsSingle files for diversified financial annual financial reports have large sizes and long parsing times. Sufficient time must be reserved to avoid parsing interruptions
Chunk Length800–1200 charactersFinancial reports contain long paragraphs of business descriptions. Excessively long chunks will lose context connections, while excessively short chunks will damage semantic integrity
Recall CountTop 8–12 resultsFinancial report data needs to cover multiple dimensions. Too many results will increase context pressure, while too few results will fail to meet complete analysis requirements
Similarity Threshold0.72–0.85Financial report fields have high precision requirements. Low-match irrelevant documents must be filtered, while variant expressions of the same field must be retained
UPLOAD_FILE_MAX_SIZE500 MBSome annual financial reports include multi-page chart attachments. Large file upload and parsing support is required
VECTOR_MODEL_NAMECalibrated based on actual testingDifferent vector models have varying matching effects on structured financial report fields. Adjustments must be made based on actual scenarios

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

  • Phenomenon: Chart images attached to financial reports fail to load normally in knowledge base retrieval results. Cause: The unstructured document image parsing switch is not enabled, or original embedded image information is not retained during parsing.
  • Phenomenon: Table data in PDF files is not correctly extracted when calling the API to create a file collection. Cause: The pdf_parse_mode parameter is not configured in the API request body. The default parsing mode is not adapted to the table structure of financial report PDFs.
  • Phenomenon: A 413 Request Entity Too Large error code is returned during knowledge base retrieval. Cause: The uploaded financial report file size exceeds the threshold set by the UPLOAD_FILE_MAX_SIZE configuration, resulting in request interception.

How to Confirm Configurations Are Correct

  1. Upload a typical diversified financial financial report PDF. Check whether tables, text, and images in the parsing results are complete, and confirm that the unstructured parsing switch is enabled.
  2. Call the API to create a file collection. Include the pdf_parse_mode parameter in the request body, and verify that the interface can correctly identify and apply this configuration.
  3. Retrieve financial report data for a specified field. Check whether the matching degree of returned results meets expectations, and adjust the similarity threshold to a range that fits business requirements.
  4. Upload a financial report file larger than 100 MB. Verify that the upload and parsing processes complete normally, and confirm that the UPLOAD_FILE_MAX_SIZE configuration is reasonable.

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.