What this category of data looks like
Credit report data originates from official credit reporting agencies and compliant credit reporting service providers, with a monthly or quarterly update frequency. Documents use a fixed standard template, with a mixed layout of structured tables and semi-structured text. Core fields fall into four categories: subject basic information, credit transaction details, inquiry records, and public utility records. Credit amounts are measured in yuan, inquiry times use the YYYY-MM-DD format, and overdue status is marked with text instead of numeric codes. Most paragraphs in the document are arranged by timeline or business type, and the overall information density is high.
Constraints on document parsing and chunking from these characteristics
The fixed mixed-layout standard template requires parsing tools to support both table extraction and semi-structured text recognition, to prevent field misalignment caused by general plain text parsing. The high information density and arrangement by business type require chunking to preserve the integrity of individual credit transaction details and individual inquiry records, and avoid splitting cross-business paragraphs. Clear field units and format requirements mean that after parsing, the binding relationship between fields and their corresponding values must be retained; units cannot be stripped, and time formats cannot be altered. The monthly or quarterly update frequency requires the parsing process to have stable fault tolerance to adapt to minor format adjustments across different batches of documents.
How to configure parameters
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
pdf_parse_engine | doc2x | This engine has relatively high parsing accuracy for fixed-format PDF credit reports, and supports mixed layouts of structured tables and text |
parse_mode | structured+table | Extract both table content and semi-structured text, to avoid missing table-based fields such as credit transaction details and inquiry records |
chunk_size | 800–1200 characters | Can hold 3 to 4 complete credit transaction details, balancing context coherence and chunk granularity |
chunk_overlap | 100–150 characters | Retain business context across chunks, and avoid splitting individual credit records |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapt to the high information density and page count of credit reports, and reserve sufficient parsing time |
enable_table_parse | true | Accurately extract fields and their corresponding values in tables, and avoid treating table content as plain text for parsing |
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 configuration mistakes
- Symptom: When calling the API interface to create a file collection, specifying PDF parsing parameters returns a parsing failure. Cause: The parsing configuration fields are not correctly included in the request body, or the parameter value format does not meet interface requirements.
- Symptom: When using the
doc2xengine to parse a credit report PDF, a parsing failure error occurs unexpectedly, returning status code500. Cause: Recent minor adjustments to the PDF layout of credit reports exceed the adaptation scope of the currentdoc2xengine, or temporary service fluctuations occur in the engine. - Symptom: After uploading multiple credit reports, the parsing results cannot distinguish the corresponding source files. Cause: The file metadata retention configuration is not enabled, or the file identification field is not bound during chunking, resulting in the loss of the association between parsing results and original files.
How to verify correct configuration
- Upload a single test credit report PDF, review the parsed text content, and confirm that table fields match the original document.
- Check the parsing task's running logs, confirm that the
pdf_parse_engineparameter is correctly called, and there are no logs related to timeouts or parsing failures. - Review the chunk result list, confirm that each chunk contains complete credit transaction details or business paragraphs, with no cross-business type splitting.
- Call the file collection's query interface, confirm that the correspondence between parsing results and uploaded files is accurate.
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.