What the data for this category looks like
Business process-related data for advanced chemical materials mainly comes from internal enterprise process specification documents, product implementation standards, safety and environmental assessment reports, and business approval process templates. The data update rhythm adjusts based on new product launches, process iterations, or compliance requirements, with no fixed cycle. Most documents are long text format, containing structured parameter tables, process node descriptions, compliance clauses, and other content. Fields include product grades, density, melting point, implementation standard numbers, approval nodes, and related items. Units include professional chemical measurement identifiers such as g/cm³, ℃, and MPa.
Constraints Imposed on Document Parsing and Chunking
The long text nature of chemical documents means chunks must not split key parameters and their context excessively. This prevents information breaks in business guidance. Embedded structured tables must retain their original format. Otherwise, compliance requirements and process parameters cannot be transmitted accurately. The non-fixed update frequency requires the parsing link to support incremental synchronization. This avoids repeated parsing of full documents. Professional measurement fields bind units and values. Chunking must ensure these are not separated, otherwise the accuracy of subsequent business guidance will be affected.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to long parameter sections and process nodes in chemical documents, avoiding splitting values and their bound units |
chunkSplitter | Split by paragraph + heading | Preserves contextual association between process descriptions and approval processes, ensuring logical consistency of business guidance |
customPdfParse | Enable embedded table recognition mode | Adapts to the large number of compliance tables and parameter comparison table structures present in chemical documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatible with large-volume documents such as comprehensive safety and environmental assessment reports and annual process manuals |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Reserves sufficient time for long document parsing, avoiding mid-task interruptions |
chunkSettingMode | Manual configuration | Allows flexible adjustment of chunking rules based on different types of business documents |
Three Common Mistakes
- Uploading a local file and calling the document parsing tool returns an error. The cause is that
UPLOAD_FILE_MAX_SIZEis not configured correctly, and the file is blocked because it exceeds the set threshold. - Some PDF-format product standard documents cannot be recognized. The cause is that the embedded table recognition mode of
customPdfParseis not enabled, resulting in failed parsing of documents with structured tables. - Individual numerical or unit fields appear in the chunking results. The cause is that
chunkSizeis set too small, cutting the binding between parameters and their corresponding units during splitting.
How to Verify Correct Configuration
- In the FastGPT v4.17.0 environment, upload a single chemical process manual with a volume not exceeding 1000 MB, and check whether the parsing task is completed within 600 seconds with no timeout errors.
- Upload a PDF standard document containing embedded parameter tables, and check that the row and column structure of the tables in the parsing result matches the original document.
- Review the chunked text fragments, and confirm that the process numerical values and their corresponding measurement units in each fragment are not separated.
- Switch
chunkSettingModeto automatic configuration, and verify whether the chunking rules are automatically adjusted based on the document type.
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.