What the data for this category looks like
Research report data for investment platforms originates from securities firm research institutes, industry associations, periodic listed company announcements, and public disclosure documents. Update frequency fluctuates with market cycles. Update volume rises sharply during earnings season, with stable updates on weekdays outside of these periods. Most documents are long-form text, including structured fields such as abstracts, industry data, financial indicators, and investment ratings. Units include standard financial measurement units such as 100 million yuan, percentage, and multiple. Some files contain embedded tables and charts.
What constraints these characteristics impose on document parsing and chunking
The long-text nature of research reports means chunks cannot be too short. Too-small chunks will break the connection between industry logic and investment advice. The presence of structured fields requires the parsing process to handle both plain text and structured data. This prevents loss of key measurement information. The high-frequency update requirement means the parsing workflow must have high efficiency. Delays in parsing will harm platform retrieval timeliness. Embedded tables and charts require parsing tools to support rich text structures. Without this support, content extraction will be incomplete.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Ensures semantic coherence for research report long text, prevents individual chunks from being too fragmented |
chunk_overlap | 100–150 characters | Preserves cross-chunk context information, prevents key logic from being split apart |
parse_mode | structured+markdown | Adapts to the format of research reports containing tables, structured data, and rich text |
max_chunk_count_per_file | Calibrated based on material scale, no more than 3000 chunks per file | Avoids reduced indexing efficiency from too many chunks, matches platform default thresholds |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Meets the time requirements for research report file parsing, prevents timeout for large file parsing |
structured_extract_enable | Enabled | Extracts structured fields such as revenue and ratings from research reports, improves retrieval accuracy |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Each situation requires separate analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Scenario: After parsing a large file, the returned chunk count exceeds 3000, triggering a platform error. Cause: The
max_chunk_count_per_fileconfiguration was not adjusted, exceeding the platform default threshold. - Scenario: CSV file parsing fails after a version upgrade, with logs returning
400 Bad Request. Cause: The new version has stricter format validation for CSV files, and special characters or blank lines in the file were not cleaned beforehand. - Scenario: A third-party parsing interface call returns
500 Internal Server Error. Cause: Authentication parameters and file transfer format for the parsing interface were not configured correctly.
How to confirm the configuration is set correctly
- Upload a single typical research report file, view the parsed chunk list, and confirm chunk lengths fall within the preset
chunk_sizerange. - Check the parsing log to confirm no timeout errors or chunk limit exceeded prompts appear. Verify the
PARSE_FILE_TIMEOUT_SECONDSconfiguration matches file parsing time requirements. - Review structured extraction results to confirm core fields such as revenue and ratings have been correctly extracted, matching the
structured_extract_enableconfiguration status. - Test the retrieval function by entering key sentences from the research report. Confirm returned chunks contain complete context information, verifying the
chunk_overlapconfiguration effect.
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.