What data for this category looks like
Multi-financial investment research data sources include third-party brokerage research reports, trust/asset management company financial reports, industry regulatory documents, market transaction statistics documents, and more. Update cycles vary significantly: regulatory documents are updated irregularly alongside policy releases, corporate financial reports follow fixed quarterly or annual update cycles, and industry research reports are updated in real time alongside market events. Document structure spans a wide range: from short regulatory notices spanning a few pages to hundreds of pages of financial report footnotes. Some documents contain structured tables such as balance sheets and industry scale statistics, where fields are tightly bound to units. For example, trust scale is measured in hundreds of millions of yuan, and product net value is measured in yuan per share. A large number of professional terms and nested chapter structures are also present.
What constraints these characteristics impose on the document parsing and chunking link
The mixed multi-source format of multi-financial documents requires the parsing engine to support text extraction, structured table recognition, and unstructured content restoration simultaneously, to avoid missing professional fields and unit information. The wide span of document lengths requires the chunking logic to flexibly adjust granularity, to avoid splitting paragraphs that contain complete business logic. The tight binding between fields and units requires retaining contextual associations during chunking, to prevent splitting cross-field rows or statements. The presence of nested chapters and cross-page tables requires restoring the original document hierarchy after parsing, to avoid contextual breaks after chunking that would affect subsequent retrieval and use of investment research information.
How to set configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the length of professional paragraphs in multi-financial documents, avoiding splitting complete business statements that include fields and units |
chunk_overlap | 100–150 characters | Retains contextual associations across segments, preventing loss of professional terms or cross-segment table information |
parse_table_mode | Structured extraction + retain formatting | Adapts to the large number of structured tables in multi-financial documents, fully extracting field and unit information |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to the parsing time required for hundred-page financial report footnotes, avoiding parsing timeouts for long documents |
enable_table_merge | Enabled | Resolves misalignment issues for cross-page tables, restoring complete table structures |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to upload requirements for large industry research report collections |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: After uploading a PDF or Word document, the parsed content is empty or a "parsing failed" error is returned. Cause: Failure to adapt to the large size or complex format of multi-financial documents, such as not adjusting the
UPLOAD_FILE_MAX_SIZEparameter, or not enabling the parsing plugin for the corresponding format. - Symptom: Parsed tables have column misalignment, row breaks, or separated fields and units. Cause: Not enabling the
enable_table_mergeconfiguration, or settingchunk_sizetoo small, splitting complete rows of cross-page tables. - Symptom: After connecting to the open-source version API, uploading a file during a conversation fails with a 413 status code returned. Cause: Not adjusting the file upload size limit in the API gateway configuration, exceeding the threshold of the
UPLOAD_FILE_MAX_SIZEparameter set by FastGPT by default.
How to confirm the configuration is correct
- Upload a single hundred-page financial report document, check if the parsed text fully covers all chapters with no obvious content truncation.
- Upload an industry research report containing cross-page tables, verify that the parsed tables are fully spliced with no column misalignment or missing rows.
- Call the API to upload a small regulatory document, check if the returned parsing result includes complete clause content with no field splitting errors.
- View the platform parsing logs to confirm there are no timeout errors matching the configured
PARSE_FILE_TIMEOUT_SECONDSparameter setting.
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.