What this category of data looks like
The data for this category mainly comes from warranty work orders submitted by customers, system operation logs, project contract warranty clauses, and software version update records. Commonly processed documents include standardized warranty work orders, defect confirmation sheets, repair execution records, and customer confirmation sheets. Most documents include fields such as work order number, defect type, repair node, and customer feedback flag. Updates are primarily triggered via daily batch synchronization or individual work orders. The size of a single document typically ranges from a few KB to tens of MB.
What constraints do these characteristics impose on the document parsing and chunking link
Heterogeneous data from multiple sources requires the parsing process to adapt to structured work orders, semi-structured confirmation sheets, and unstructured log formats. This avoids loss of associated fields related to responsibility boundaries. High-frequency updated single work order data requires the parsing flow to support low-latency processing. This prevents work order closure from being delayed due to timeouts. The wide range of single document sizes requires adaptation to parsing limits for different file sizes. Chunking must retain contextual associations between defect descriptions and repair records. This prevents responsibility determination from failing after splitting. The configuration on this page is based on FastGPT v4.17.0.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapt to the field association length of warranty work orders and defect confirmation sheets. Avoid splitting complete paragraphs related to responsibility determination |
chunkSplitter | Split by paragraph + semantic grouping | Retain contextual associations between repair records and customer feedback. Align with the logical structure of documents in this category |
customPdfParse | Enabled | Adapt to PDF format parsing for contract warranty clauses. Retain field alignment information from original typesetting |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Cover the size of most single warranty-related documents. Avoid large file upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapt to parsing time for batch work orders. Avoid timeout interruptions in high-frequency update scenarios |
chunkSettingMode | Manual configuration | Flexibly adjust chunking rules to adapt to different document structures for heterogeneous document types in this category |
Three common misconfigurations
- When uploading warranty-related PDF files larger than 100 MB, a prompt "Offset out of range" appears after the progress reaches 90%. The cause is that the
UPLOAD_FILE_MAX_SIZEconfiguration has not been adjusted. Parsing exceptions are triggered after exceeding the system's default file size limit. - A large amount of duplicate content appears in the chunking results. The cause is that a reasonable
chunkSizeparameter has not been set. This leads to an overly large overlapping range of adjacent chunks or chunk lengths that do not match document logic. - After parsing a PDF of contract warranty clauses, key clause fields are empty. The cause is that the
customPdfParseconfiguration has not been enabled. Structured typesetting information from the PDF cannot be extracted correctly.
How to confirm the configuration is set correctly
- Upload a single 100 MB warranty work order PDF. Verify that the upload progress completes without errors. Check whether the
UPLOAD_FILE_MAX_SIZEconfiguration covers the document size. - Parse a complete defect confirmation sheet. Check whether the chunking results retain the complete context of defect descriptions and repair records. Verify whether the
chunkSizeandchunkSplitterconfigurations meet expectations. - Submit batch work order data. Verify that parsing time does not exceed the duration set by
PARSE_FILE_TIMEOUT_SECONDS. No timeout interruption prompts should appear. - Adjust the
chunkSizeparameter and compare the two chunking results. Confirm that the proportion of duplicate content meets business requirements. Verify the adaptability of the chunking rules.
The values provided here are common starting points and should be evaluated against samples tailored to the specific use case.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.