What the data for this category looks like
Data sources for automotive service financial reports include public annual and semi-annual financial reports of listed automotive service enterprises, monthly operation reports of regional chain stores, and joint operation data documents from industry alliances. Update frequency varies by entity level, and is divided into monthly, quarterly, and annual cycles. Document types are mixed, including native PDF official financial reports, structured Excel operation sheets, and scanned paper reports. Common document structures include revenue breakdown details, cost composition, customer service volume statistics, and inventory turnover data. Fields typically cover per-vehicle service revenue, spare parts purchase amounts, venue rental fees, and repair volumes, with units mainly being yuan, ten thousand yuan, and service volumes.
What constraints these characteristics impose on the "document parsing and chunking" link
The mixed-format nature of automotive service financial reports requires the parsing process to support native PDF, Excel spreadsheets, and scanned documents, to avoid issues where content from scanned files cannot be extracted. There are many detailed fields with close correlations—for example, revenue details correspond one-to-one with corresponding cost items. Chunking must retain the contextual association between fields, and it is not advisable to forcibly split content across business modules. The high-frequency, small-batch documents updated monthly require the parsing and chunking processing speed to adapt to frequent calls, while also accurately identifying the business attribution of different documents to avoid mixing operation data from different stores.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Automotive service financial reports often include multi-page PDFs and multiple Excel worksheets. 500 MB covers the document volume of most single-batch uploads |
DOC_PARSE_OCR_ENABLE | Enabled | Historical operation reports from some stores are saved as scanned documents. Enabling OCR allows extraction of text content from scanned documents |
CHUNK_SIZE | 800–1200 characters | There are many detailed fields and associated data in automotive service financial reports. This length retains complete context for a single business module while adapting to the granularity requirements of knowledge base retrieval |
CHUNK_OVERLAP_RATIO | 10% | There is relatively little content across business modules. A 10% overlap ensures contextual coherence for associated fields and avoids content breaks during retrieval |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing Excel documents with multiple worksheets and long PDF financial reports takes a long time. 120 seconds covers the parsing cycle of most documents |
DOC_PARSE_EXCEL_SHEET_MODE | Split by worksheet | Excel documents for automotive service financial reports are often stored as different worksheets categorized by month and store. Splitting by worksheet ensures consistent chunking of data with the same dimension |
The parameter values provided on this page are common recommendations for starting point 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 mistakes
- Phenomenon: After uploading a PDF financial report with a digital signature, the parsing result is empty or only extracts the cover content. Cause: Some digitally signed PDFs restrict text extraction permissions, and the default parsing configuration cannot bypass the encryption restrictions.
- Phenomenon: Calling the Doc2x tool in FastGPT V4.9.1 returns a file reading error, with an error message containing
Only support .txt, .m(truncated supported format prompt). Cause: The uploaded document format is not correctly identified, or the file extension does not match the actual content—for example, renaming an Excel file to a .pdf format. - Phenomenon: After uploading a complex operation table with multiple merged cells, the parsed text is chaotic and field correspondences are incorrect. Cause: The
DOC_PARSE_EXCEL_SHEET_MODEconfiguration is not adjusted, or the table structured parsing parameter is not enabled, resulting in incorrect splitting of merged cell content.
How to confirm the configuration is correct
- Upload 1 to 2 typical monthly operation Excel documents for automotive services, and check whether the parsed text content includes all core business fields, such as revenue details and cost items.
- Upload a PDF financial report with a digital signature, and verify whether the parsing result extracts the main content except the cover.
- Trigger a parsing test for a single document, and check the parsing log to confirm that the file format is correctly identified, with no unsupported format error prompts.
- View the parsed knowledge base entries, confirm that the chunked content is aggregated by business module, and that operation data from the same worksheet is not split across modules.
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.