What Data for This Category Looks Like
Data for this category comes from customer drawings and special characteristic lists, ERP/MES systems, measuring tools, equipment process parameters, and supplier quality certificates. Update frequency is per batch and per shift, with continuous collection. Daily documents include control plans, process flowcharts, work instructions, first article and patrol inspection records, SPC reports, PPAP materials, and 8D reports. Documents often contain fields such as precision tolerance parameters, batch identifiers, and process requirements. Units include millimeters, newton meters, batch numbers, and similar units.
What Constraints These Characteristics Impose on the "Document Parsing and Chunking" Step
Documents in this category include key fields such as precision tolerances and batch identifiers. Context associations between fields must be preserved during chunking to avoid splitting critical parameter groups. Multi-source, high-frequency update data requires parsing workflows to adapt to exported documents of different formats. Chunking logic must also align with business logic for processes and batches. Due to strict constraints from vehicle customers, parsing results must meet field completeness and accuracy requirements. Missing critical information is not acceptable, as it may lead to batch quality defects. Continuously collected real-time data also requires fast parsing and chunking to ensure timeliness for subsequent workflows.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents in this category contain precision parameters and business context. This range preserves complete associated information for processes and batches |
chunkSplitter | Chunk by paragraph + semantics | Daily documents include structured and semi-structured content such as work instructions and 8D reports. Semantic chunking preserves business logic integrity |
customPdfParse | Enabled | Documents in this category often contain embedded tables and precision parameters. Custom PDF parsing improves extraction accuracy for table content |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Documents for high-volume manufacturing often include multi-page reports and equipment parameter records. This duration covers complete parsing for complex documents |
UPLOAD_FILE_MAX_SIZE | 500 MB | PPAP materials and SPC reports for this category are often multi-page batch files. This upper limit covers the scale of regularly submitted documents |
chunkSettingMode | Manual configuration | Chunking logic must be adjusted for different document types. Manual configuration adapts to business differences |
This configuration applies to FastGPT v4.17.0.
Three Common Configuration Errors
- Phenomenon: The document parsing tool returns a file read failure error, or returns results with empty fields. Cause: The associated service port for
customPdfParseis not configured correctly, or the locally deployed parsing service cannot connect to the FastGPT container network. - Phenomenon: After uploading multi-page SPC reports or PPAP materials, chunking results omit key fields such as tolerances and batch numbers. Cause:
chunkSizeis set too small, splitting the association between parameters and context. - Phenomenon: When uploading batch documents, the parsing task terminates early and returns a timeout status code. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set lower than the time required for document parsing, not adapting to the parsing time of multi-page reports.
How to Confirm the Configuration Is Correct
- Upload a single-page work instruction PDF, and check if the parsing result preserves the complete association between process steps and tolerance parameters.
- Submit a multi-page SPC report, and verify that the parsing task duration falls within the preset
PARSE_FILE_TIMEOUT_SECONDSrange. - Test the parsing tool's HTTP request, and confirm that the number of chunks in the returned result matches the document's page count and content structure.
- Upload the largest regularly sized document, and check if a file size limit prompt is triggered.
The values provided are common starting points and should be measured against the user's own samples.