What Data for This Category Looks Like
Professional chain financing daily report data is mostly sourced from the headquarters financial systems of chain brands, daily store remittance ledgers, and credit approval receipts from partner financial institutions. Updates occur daily, with each document covering full business data from the previous day. Most documents are structured tables, while some are PDF scans or editable Word/Excel files. Core fields include store ID, store name, daily financing received amount, repayment deadline, and fund usage direction. The amount unit is ten thousand yuan, and time fields use the YYYY-MM-DD format.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking?
Structured table-based formats require preserving the binding relationship between row and column fields during parsing, to avoid splitting associated fields of the same financing record. Fixed-format documents updated daily require chunking rules adapted to fixed field combinations, rather than indiscriminate character-based splitting. Scanned document formats require triggering OCR recognition, and need to verify the integrity of recognized fields to prevent misalignment between store IDs and corresponding amounts. Excel files with multiple worksheets need automatic identification of the target business worksheet to avoid mixing irrelevant data. Fixed amount units require automatically associating numerical values with units during parsing, to prevent loss of context after chunking.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Professional chain financing daily reports use structured tables as their core carrier. Preserving table structure ensures the associative integrity of fields such as store ID and financing amount |
PARSE_OCR_ENABLE | Automatically enable for scanned documents | Some documents are in PDF scan format. OCR is required to extract text content, ensuring parsing availability for non-editable documents |
MAX_CHUNK_LENGTH | 800–1200 characters | A single store's financing record contains 3-5 core fields. This length can cover a complete single record while avoiding redundant content within the chunk |
PARSE_EXCEL_SHEET_FILTER | Match worksheet names to "financing daily report" | Excel files for professional chain financing daily reports usually name worksheets with fixed names, allowing accurate extraction of target business data |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single daily report documents have moderate data volume. 120 seconds covers the full process of conventional parsing, OCR recognition, and content chunking |
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. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: After uploading an Excel-format financing daily report, search results only return scattered values, with no complete store financing records. Cause: The
PARSE_TABLE_ENABLEconfiguration is not enabled, causing the table structure to be split into unassociated scattered text. - Symptom: After importing a PDF scan-format financing daily report, the knowledge base search returns no results and displays a parsing failure prompt. Cause: The
PARSE_OCR_ENABLEconfiguration is not enabled, making it impossible to extract valid text content from the scan. - Symptom: Cannot find a dedicated parsing function entry in the configuration interface. Cause: The original miner-u parsing function has been integrated into the general file parsing configuration in the current version. Enable it via custom rule matching for document formats.
How to Confirm the Configuration Is Correct
- Upload a single test document to the knowledge base, view the parsed text preview, and confirm that the table structure is complete and fields are not misaligned.
- Enter the knowledge base search test interface, enter the store ID keyword, and confirm that complete content blocks containing the corresponding store's financing information can be retrieved.
- Adjust the
MAX_CHUNK_LENGTHparameter, re-upload the test document, and compare the chunking result with the matching degree of single store financing records until a single chunk covers a complete business unit. - For scan-format documents, view the parsing log to confirm that the OCR recognition step has been executed and there are no recognition failure prompts.
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.