Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The internal documents of the basic chemical industry mainly come from production process specifications, equipment operation and maintenance logs, safety compliance manuals, raw material quality inspection records, and employee training materials. Document sources cover the entire production process, with update cycles following compliance checks, equipment maintenance, or raw material batch adjustments. Documents include long-text chapters, structured parameter tables, PDFs with industrial flowcharts, and some archived scanned documents. Document fields mostly contain physical parameters such as equipment pressure, reaction temperature, and material flow rate, with units mostly MPa, ℃, and cubic meters per hour.
What constraints do these characteristics impose on the document parsing and chunking link
Long-text process specifications are prone to cross-chapter information binding. When chunking, retain adjacent chapter context to avoid separating process parameters from operation steps. For documents with structured parameter tables, preserve the table row and column structure during parsing, otherwise parameters cannot be associated with corresponding equipment and working conditions after chunking. Archived old scanned documents have issues such as blurry fonts and messed up layouts, so adjust parsing parameters to adapt to low-quality PDFs. For large volumes of uniformly formatted raw material quality inspection records across multiple batches, distinguish chunking results by batch or document ID to avoid mixing data from different batches.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Basic chemical industry documents mostly contain long-text paragraphs and parameter tables. This range balances context integrity and retrieval accuracy |
chunkSplitter | Split by paragraph + title | Chemical documents often have hierarchical titles and independent operation step paragraphs, which can retain the logical structure of the document |
customPdfParse | Enabled | Basic chemical industry documents often contain industrial flowcharts, embedded formulas, and scanned documents. Custom parsing can adapt to special layout elements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large process specification PDFs have many pages, requiring sufficient time to complete full parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Some equipment operation and maintenance logs are archived as bundled multiple documents, requiring support for large file uploads |
chunkSettingMode | Manual configuration | The structure of chemical documents varies greatly. Manual adjustment can adapt to different types of internal documents |
Three common mistakes
- Phenomenon: PDF parsing returns error messages or empty content. Cause:
customPdfParseis not enabled to adapt to industrial flowcharts and scanned documents, orPARSE_FILE_TIMEOUT_SECONDSis set too short, causing large document parsing to interrupt. - Phenomenon: Parsing results cannot be attributed to individual documents after multiple file uploads. Cause: Chunking results are not associated by document ID or upload batch, and original file metadata is not retained during chunking.
- Phenomenon: Target parameter content cannot be found during knowledge base search. Cause:
chunkSizeis set too large, causing parameters to be split into different chunks, or the binding relationship between tables and parameters is lost during parsing.
How to confirm the configuration is correct
- Upload a single large process specification PDF, check that the parsing progress and results are complete, and confirm that
PARSE_FILE_TIMEOUT_SECONDSmeets the document parsing time requirements. - Upload multiple internal documents of different types, verify the attribution markers of the parsing results, and confirm that original file metadata is retained during chunking.
- Extract chunk content related to a single parameter, check that the parameter is fully bound to its corresponding operation steps and equipment information, and confirm that the chunking logic adapts to the document structure.
- Trigger a knowledge base search test, verify that target parameters or operation steps can be retrieved normally, and confirm that the chunking parameters meet business retrieval needs.
The values given 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.