What This Category of Data Looks Like
Data for this category primarily originates from customers’ historical business systems, CSV or Excel import templates, database export files, and product import logs. Documents processed daily include data mapping templates, migration execution plans, field correspondence tables, and migration verification reports. Update cycles vary per individual project, and are typically irregular. The data includes business fields, unit identifiers, mapping relationships, and similar content. Its structure varies significantly based on the customer’s original system format. Some documents are multi-column tables or instruction documents with embedded images.
Constraints on Document Parsing and Chunking
Documents for customer data import migration often include structured field mappings and tabular business data. Some documents also have embedded images. Diverse data sources create inconsistent document formats. The parsing workflow must support CSV, Excel, PDF and other common formats. Irregular update cycles require the parsing process to adapt flexibly. This avoids parsing failures when document structures change. The accuracy of field mapping directly affects the compliance of subsequent data imports. Document chunking must retain field association information to prevent loss of mapping relationships after splitting. Additionally, avoid chunk sizes that are too large and cause subsequent retrieval failure, or too small and increase redundant processing costs. This ensures parsing efficiency and the accuracy of compliance review.
Configuration Settings
The following configuration settings are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of structured text documents such as field mapping tables and migration plans. It avoids losing field associations after splitting, and ensures the accuracy and compliance of subsequent data mapping. |
chunkSplitter | Split by paragraph + table header | Adapts to the structure of multi-column tables and field mapping tables. It retains the correspondence between table columns and content, and prevents compliance risks caused by field misalignment. |
customPdfParse | Enable embedded image parsing | Adapts to migration documents with screenshot instructions. It extracts images and their corresponding text content in the document, avoids missing sensitive image information, and meets compliance review requirements. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatible with large-volume log files exported from databases and multi-page PDF migration plans. It also limits the upper file size to reduce the risk of data leakage during transmission. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Prevents tasks from failing due to parsing timeout for large-volume import logs. It adapts to the processing duration of batch data, and ensures the stability and compliance of the parsing process. |
Three Common Misconfigurations
- Issue: Fields are misaligned after parsing a multi-column table, and the number of result entries does not match the number of columns in the original table. Cause: No chunking rules adapted to multi-column structures are configured. The default chunking logic splits by row, causing loss of column associations and leading to field mapping errors.
- Issue: Images are not extracted after uploading a PDF, and the parsing result only contains plain text. Cause: The
customPdfParseembedded image parsing configuration is not enabled. Only the text content in the document is extracted, resulting in missing compliance review materials related to images. - Issue: Import log parsing task times out, and a timeout error is displayed on the interface. Cause:
PARSE_FILE_TIMEOUT_SECONDSis not adjusted to a value adapted to large-volume logs. The default duration is insufficient to complete batch data parsing, leading to task interruption.
How to Verify Proper Configuration
- Upload a field mapping table containing multi-column tables, and check whether the parsed text retains the correspondence between table columns and content.
- Upload a migration plan document with embedded images, and confirm that the parsing result includes the associated text and image identifiers of the images.
- Upload a single import log file of conventional volume, and verify that the parsing task can be completed normally without timeout errors.
- Adjust
chunkSizeto different value ranges, and check whether the split text fragments do not lose core field mapping information.
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 2026-10-19.