What Data for This Category Looks Like
The primary entities in this category are enterprises manufacturing coatings, resins, additives, agrochemical intermediates, and specialty chemicals. Daily generated documents include batch production instructions, feeding verification sheets, reaction process records, cleaning records, inspection reports, deviation and change orders. Data sources include formula and process libraries, raw material batch records, reactor DCS data, weighing systems, LIMS systems, and warehouse management systems. Update frequency is once per batch production or each key process step. Most document structures combine structured forms and unstructured process records, with dedicated fields including feeding amount (unit: kilogram, liter), reaction temperature (unit: degrees Celsius), batch number, and other specific parameters.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
The multi-batch switching and mixed document type characteristics of this category require document parsing and chunking to isolate content by production batch, to avoid cross-batch data confusion. The coexistence of structured forms and unstructured process records in document structures requires adapting different chunking logic, to ensure key information such as feeding parameters and reaction data is not split or broken. Frequently updated business data requires the parsing link to have reasonable timeout settings, to avoid delays to real-time inspection processes caused by parsing delays. At the same time, confidentiality requirements for formulas and processes require filtering sensitive batch identifiers during chunking, only retaining device parameter content that can be publicly used for maintenance Q&A.
How to Set Configurations
| Configuration Item | Recommended Value Range / Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | This category's documents contain structured parameters and unstructured processes. This range preserves complete information for a single feeding step or single reaction segment |
chunkSplitter | By paragraph + semantic boundary | Mixed document types require avoiding splitting key parameters and explanatory text |
customPdfParse | Enabled | Most documents for this category are compliance-focused PDF forms. Enabling this allows accurate extraction of structured fields |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Single-batch production documents include multiple sub-items, requiring sufficient parsing time |
chunkSettingMode | Manual configuration | Chunking rules must be adjusted for this category's batch isolation requirements, to adapt to specific scenarios |
Three Common Misconfigurations
- Phenomenon: Unrendered Markdown tags or pure code fragments appear in knowledge base context references. Cause: The
customPdfParseconfiguration is not enabled, resulting in format tags in structured PDF forms not being properly stripped. - Phenomenon: After submitting an external document link, complete content cannot be extracted, only empty results or timeout prompts are returned. Cause: The
PARSE_FILE_TIMEOUT_SECONDSvalue is not configured correctly, or the value is too low, resulting in failure to complete parsing of large production documents. - Phenomenon: Chunk IDs after chunking cannot be copied on the page. Cause: The public ID display switch for
chunkSettingModeis not enabled, and this configuration item is not adjusted for debugging needs.
How to Verify Correct Configuration
- The FastGPT v4.17.0 platform is used to upload a single batch production instruction PDF, and parsed text is checked for stripped format tags and no remaining Markdown tags.
- An external compliant document link is submitted, and after parsing completes, content is checked for full extraction, with no empty results or timeout errors.
- The chunked chunk list is viewed, and each chunk's ID is confirmed to be copyable via click or right-click menu.
chunkSizeis adjusted to different ranges, a document containing feeding parameters is uploaded, and complete feeding amount and unit information is confirmed to be preserved.
The values provided are common starting points, and should be evaluated against samples from the actual deployment.