What data looks like for this use case
Service subjects include IT asset managers, financial asset staff, and desktop support personnel. Daily processed documents include asset ledgers, inventory sheets, loan and return forms, scrap applications, and similar materials. Data sources are asset management systems, procurement systems, financial fixed asset modules, and terminal management platforms. Update frequency is monthly, quarterly, or annually. Most documents are a mix of structured tables and small amounts of free text. Fields include asset number, name, specification model, user, storage location, purchase date, and similar items. Units are mostly physical measurement units such as unit, set, piece, and similar items.
Constraints imposed on document parsing and chunking
The mixed structure of structured tables and free text requires parsing tools to support both structured table extraction and text segmentation logic. Differences in data formats from multiple sources require adaptation to document layout styles exported by different systems. Batch update requirements of monthly, quarterly, or annual cycles require the chunking step to adapt to batch document processing efficiency. Fields containing sensitive information such as asset ownership and location require parsing and chunking to ensure data is not leaked. Unique identifier fields such as asset numbers require accurate extraction to avoid splitting critical associated information during chunking.
How to set configurations
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field length and batch processing needs of documents such as asset ledgers, avoiding including excessive unrelated information in a single chunk |
chunkSplitter | Split by paragraph and table | Adapts to asset-related documents that mix structured and free text, preserving table integrity and paragraph logic |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing duration of batch monthly inventory sheets, avoiding timeout for large document parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports uploading full quarterly batch asset documents in a single operation, meeting batch processing requirements |
customPdfParse | Enable structured table parsing | Accurately extracts table fields from asset ledgers, avoiding text garbling and field misalignment |
chunkSettingMode | Manually configure chunking rules | Customize chunking rules for the structured characteristics of asset-related documents, without relying on default rules |
Three common configuration mistakes
- Parsing results are empty after uploading an asset ledger document. The cause is that the
customPdfParseconfiguration is not enabled, preventing structured tables from being recognized and extracted. - Parsing timeout occurs when batch uploading monthly inventory sheets. The cause is that
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a duration suitable for batch documents. - Chunking across asset numbers occurs after configuration. The cause is that
chunkSplitteris not set to split by asset number, causing the chunking logic to not match the core fields of the document.
How to confirm configurations are correct
- Upload a single asset ledger document. Confirm whether the parsing result fully extracts table fields and corresponding text.
- Upload batch monthly inventory sheets. Check the completion status of parsing tasks to confirm no timeout errors occur.
- Adjust
chunkSizeto different ranges. Compare the field integrity of chunking results to confirm the chunking logic matches the document structure. - Upload a scrap application containing sensitive information. Confirm that chunked content does not split critical asset identifier fields.
All listed configuration values are common starting points. Adjustments should be made based on the target document samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.