This document is written based on FastGPT v4.17.0.
What the Data for This Category Looks Like
The data for this category primarily comes from ERP, MES, VIN and configuration systems, tightening tools, EOL inspection lines, and quality traceability systems. Daily documents include production orders, VIN lists, assembly work instructions, tightening data, offline inspection reports, rework records, and more. In some scenarios, thousand-page annual quality analysis PDFs and ten-thousand-row Excel configuration lists are also involved. Data update frequencies cover per vehicle, real-time, and per shift. Core fields include unique VIN codes, torque values, inspection results, and part batch numbers. Some documents come with standard units such as newton-meters and percentage.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
The data characteristics of this category impose clear constraints on document parsing and chunking: First, associated data identified by a unique VIN requires retaining cross-field contextual associations during parsing, to avoid splitting configuration and inspection data for the same vehicle into different chunks. Second, the scale of thousand-page PDF reports and ten-thousand-row Excel lists requires chunking rules that balance content completeness and retrieval efficiency. Third, parsing differences exist between internally deployed Confluence data sources and public network documents, so adaptation to internal network access restrictions is required. Fourth, table structures in tightening data and inspection reports must be fully preserved, otherwise subsequent matching and traceability of quality defects cannot be supported.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of work steps in final assembly documents, retains complete context for single-station operations |
chunkSplitter | Mixed paragraph + fixed character splitting | Balances natural paragraphs in assembly work instructions and table structures in tightening data, avoids splitting key associated content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing time of thousand-page PDFs and ten-thousand-row Excel files, prevents interruptions during large file parsing |
customPdfParse | Enabled | Preserves tables and multi-column layouts in PDFs, ensures complete content of offline inspection reports |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports uploading annual quality analysis PDFs with over 1000 pages and large Excel configuration lists |
Three Common Misconfigurations
- Internal network Confluence pages fail to return content: Phenomenon: After uploading an internal network Confluence link, the parsing result is empty or only returns the title. Cause: The default parsing rule only adapts to public network domain names, and access permissions and parsing whitelists for internal network data sources have not been configured.
- Large Excel files have overly coarse chunking after splitting: Phenomenon: 10000-row Excel data is split into a small number of large chunks, making it impossible to accurately match quality records for single stations. Cause: The
chunkSizeparameter was not adjusted, and the default chunk length for general documents was used, without adapting to the field association requirements of table data. - Incomplete content is returned when parsing thousand-page PDFs: Phenomenon: Tightening data tables on some pages are missing or truncated. Cause: The
customPdfParseconfiguration was not enabled, and the default PDF parser did not preserve table structures, resulting in failure to fully extract key quality data.
How to Verify Proper Configuration
- Upload one internal network Confluence link for an assembly work instruction, and check that the parsing result contains complete content including VIN codes, station numbers, and operation steps.
- Upload one Excel test file containing 10000 rows of data, and verify that each chunk after splitting contains complete headers and 3-5 consecutive rows of quality records.
- Upload one offline inspection report PDF with over 500 pages, confirm that parsing time does not exceed 600 seconds, and that all table content is fully extracted.
- Search the chunked knowledge base, and verify that tightening data and rework records corresponding to the same VIN code are located in the same or adjacent chunks.
The values listed above are common starting points, and should be adjusted based on the reader's own samples.