What data looks like for this category
Financial institutions issue intelligent due diligence reports for hotel and catering stores. Data sources include daily operation ledgers provided by store operators, third-party fire and hygiene inspection reports, franchise cooperation documents, passenger flow statistics reports, and similar materials. Document types include PDF-format inspection reports, Word-format operation status explanations, Excel-format food purchase ledgers and passenger flow detail reports, and structured franchise contract texts. Update rhythms vary significantly: food purchase ledgers are updated daily, passenger flow statistics reports are updated monthly, fire and hygiene inspection reports are updated quarterly or semi-annually, and franchise contracts are one-time archived files. Documents include specialized business fields such as average daily table turnover rate per store, food procurement cost ratio, business area, and average daily in-store passenger count. Units include passenger count, yuan, square meters, kilograms, and similar units.
What constraints do these characteristics impose on the document parsing and chunking step
Mixed multi-format document structures require parsing components to support PDF, Word, Excel and other formats, and handle attached documents nested within reports. Specialized business fields and units require retaining field associations after parsing, to avoid field confusion or unit loss caused by general parsing. Differences in update frequencies across different documents require grouping by document type during chunking, to avoid mixed arrangement of cross-cycle data that affects subsequent recall accuracy. Large-volume Excel files with multiple worksheets require parsing components to support reading multiple worksheets, to avoid data loss. Some due diligence reports contain long-text business review content, requiring chunking strategies to balance context integrity and recall accuracy.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_EXCEL_SUPPORT_MULTI_SHEET | Enabled | Hotel and catering due diligence Excel ledgers often contain multiple worksheets with purchase, revenue, and passenger flow data. Enabling this allows complete extraction of content from all worksheets |
PARSE_EXCEL_MAX_COLUMNS | 50 | Hotel and catering purchase ledgers typically include dozens of columns for fields such as food name, unit price, quantity, and total price. This value covers most business scenarios |
MAX_PARSE_CHUNK_SIZE | 800-1200 characters | Hotel and catering due diligence documents contain both short fields (such as food unit price) and long paragraphs (such as business review explanations). This range balances recall accuracy and context integrity |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Due diligence documents for some chain hotel and catering businesses include multiple batches of purchase Excel files and multi-year passenger flow PDF files, resulting in large single-file sizes |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing large-volume multi-format documents requires longer processing time to avoid interrupting the parsing process due to timeout |
RECALL_SIMILARITY_THRESHOLD | 0.75-0.85 | Hotel and catering due diligence fields mostly use specialized business terminology. This threshold filters irrelevant recall results and retains accurately matched business data |
ENABLE_NESTED_FILE_PARSE | Enabled | Hotel and catering due diligence reports often contain nested attached documents. Enabling this allows complete parsing of nested PDF, Excel and other attached content |
The parameter values provided on this page are conventional recommendations used as a starting point 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 against relevant samples before finalizing settings.
Three common mistakes
- Issue: Only the first two columns of data are extracted after uploading an Excel file, with remaining columns not retrieved. Cause: The
PARSE_EXCEL_MAX_COLUMNSconfiguration was not adjusted, and the default value limits the number of parsed columns. - Issue: A connection failure is returned when calling the document parsing service, with a 502 status code shown in logs. Cause: The parsing container deployed via Docker did not correctly map ports, or the container network policy restricts external access.
- Issue: Knowledge base recall results contain a large amount of irrelevant content, or core business fields are not recalled. Cause: The
RECALL_SIMILARITY_THRESHOLDvalue is unreasonable, and does not match the semantic weight of hotel and catering specialized business terminology.
How to confirm the configuration is correct
- Upload a food purchase Excel file containing 3 worksheets, check if the parsing result includes fields and data from all worksheets, to verify that the
PARSE_EXCEL_SUPPORT_MULTI_SHEETconfiguration is effective. - Upload a due diligence report PDF containing nested attachments, check if the parsing result includes text and table data from the attachments, to verify that the
ENABLE_NESTED_FILE_PARSEconfiguration is effective. - Enter a specialized business query such as "2024 first half food procurement cost ratio", check if the recall results only include relevant due diligence document content, to verify that the
RECALL_SIMILARITY_THRESHOLDvalue is reasonable. - Upload a multi-format mixed due diligence document with a size of 1.2 GB, check if parsing completes within 120 seconds without timeout errors, to verify that the
PARSE_FILE_TIMEOUT_SECONDSandUPLOAD_FILE_MAX_SIZEconfigurations are 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.