This page is compatible with FastGPT v4.17.0.
What Data Looks Like for This Category
This category of data comes from registered and archived formulas, raw material safety materials, weighing and emulsifying equipment, ERP/MES systems, laboratory records, and packaging material version documents from skincare, haircare, makeup, and special cosmetics manufacturing enterprises. Daily documents include formula process sheets, weighing and feeding records, emulsification and filling records, cleaning and sanitation records, semi-finished and finished product inspection reports, and label review documents. Fields include raw material names, proportions, operating temperatures, batch numbers, inspection indicators, and others. Units involve grams, milliliters, degrees Celsius, and batch numbers. Updates are triggered per production batch or each line change.
What Constraints These Characteristics Impose on the Document Parsing and Chunking Link
Frequently updated production documents need parsing processes that support batch fast processing, to avoid slowing down the response speed of process Q&A. Significant structural differences across multiple document types demand precise matching of hierarchy and field extraction logic for each document type, to ensure core information is not lost. The accuracy of fields such as raw material proportions, operating temperatures, and batch numbers links directly to compliance and production safety, requiring chunking to retain the association between fields and context. Mixed multi-source data formats require compatibility with encoding and typesetting differences across documents from different sources. Label review documents contain compliance text, requiring retention of the corresponding chunking logic with archived information to facilitate subsequent Q&A matching.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the text length of single process steps and raw material proportions in documents of this category, to avoid splitting that disrupts operational logic |
chunkSplitter | Separate by paragraphs + headings | Adapts to the hierarchical structure of formula process sheets and inspection reports, retaining contextual association between operating steps and fields |
customPdfParse | Enabled | Adapts to non-standard typesetting of multi-source documents, accurately extracting field information from label review and cleaning records |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports the need to upload multiple documents packaged for a single production batch, to avoid interception due to oversized files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time consumption for complex formula documents, preventing parsing process interruption due to timeout |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types, adapting to differentiated content such as raw material proportions and operation records |
Three Common Configuration Mistakes
- A "the argument ‘windows-1252’ is invalid encoding" error occurs when parsing documents. This happens because a custom file parsing address is not configured, or compatible document encoding rules are not specified, resulting in failure to properly parse production records in non-UTF-8 formats.
- The document parsing tool returns empty results after being called in a workflow. This occurs because the
UPLOAD_FILE_MAX_SIZEparameter is not set correctly, or the uploaded file exceeds the configured limit, resulting in interception of the parsing task. - A single process step is split into multiple independent chunks after chunking. This happens because the
chunkSizesetting is too small, disrupting the contextual integrity of the operational process.
How to Verify Correct Configuration
- Upload a typical formula process sheet, check if the parsed text retains complete contextual information for core fields such as raw material proportions and operating temperatures.
- Adjust the
chunkSizeparameter, compare chunking results across different values, and confirm that chunk length matches the content structure of the current document. - Upload a single document of the maximum expected volume, verify that the parsing process completes normally without timeout or error prompts.
- After enabling
customPdfParse, check that compliance text in label review documents is fully extracted with no missing fields.
The values provided here are common starting points, and should be evaluated against the reader's own samples.