Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
Typical entities include food sampling departments of market supervision bureaus, grassroots supervision offices, testing institutions, etc. Daily documents include sampling plans, sampling forms, test reports, non-compliant food verification and disposal reports, and risk control notices. Data sources are the food safety sampling monitoring system, the national market supervision administration sampling result query system, testing institution LIMS, and enterprise ledgers. Update frequency is monthly. Document structures include two categories: standardized forms and free text. Fields include sampling number, test items, non-compliance determination results, disposal measures, etc. Units include batches, concentration units, etc.
What constraints these characteristics impose on the "document parsing and chunking" link
Monthly updated batch documents require efficient parsing processes. They must avoid delays in time-consuming business links such as formulating sampling plans and reviewing test reports caused by overly long parsing time for individual documents. Mixed multi-type document scenarios require flexible chunking rules. These rules must adapt to the different structures of form-based sampling forms and long-text test reports. The integrity of core business fields such as non-compliance determination results directly affects subsequent non-compliant food verification and disposal processes. Chunking operations must not destroy the relational connections across fields. At the same time, document sources involve export formats from multiple systems. The parsing module must support files with different encodings and layouts, to avoid field loss caused by format incompatibility.
How to set the configurations
| Config Item | Recommended Value | Rationale for This Value |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field density of sampling documents, avoids splitting the associated pair of test items and results in test reports |
chunkSplitter | By paragraph + semantic boundary | Matches the chapter structure of sampling documents, retains complete business logic of sampling forms and disposal reports |
customPdfParse | Enabled | Adapts to multi-format sampling documents, retains structured information of tables and forms, avoids field misalignment |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers full parsing time for large batch test reports and monthly sampling plan documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to upload requirements for batch sampling documents, meets storage requirements for monthly summary documents |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types, matches the field association requirements of sampling business |
Three common mistakes
- API parsing succeeds but no returned results: The phenomenon is that the API returns a successful call status, but there is no parsed text content in the returned results. The cause is that the
customPdfParseparameter is not enabled correctly, or thePARSE_FILE_TIMEOUT_SECONDSsetting is too short, which causes large test report parsing to interrupt and fail to complete the return. - Marker error prompts split exception: The phenomenon is that split-related error prompts appear in the parsing log. The cause is that
chunkSplitteris configured for fixed character splitting, which causes the table content in the sampling form to be incorrectly split, destroying the association between sampling information and test results. - Document parsing module receives no files: The phenomenon is that the parsing module does not read file content after uploading files. The cause is that
UPLOAD_FILE_MAX_SIZEis set too small, batch sampling plan documents exceed the upload limit, and no clear over-limit prompt is triggered.
How to confirm the configuration is correct
- Upload a single test report, check whether the parsed chunks retain the integrity of core fields such as test items and non-compliance determination results.
- Call the parsing API, verify that the returned results include parsed text blocks, and there are no empty fields or truncated content.
- Upload batch sampling plan documents, confirm that the upload progress is normal, and the parsing time matches the
PARSE_FILE_TIMEOUT_SECONDSsetting. - Adjust the
chunkSizeparameter, test the chunking effect under different values, ensure that sampling information and test results in the sampling form are not split into different chunks.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.