What data for this category looks like
Typically, data processed in this category comes from customer system interfaces, API documentation, test data, and integration debugging logs. Update frequency is daily or per project phase. Commonly used documents include interface lists, integration debugging records, field mapping tables, and issue tracking sheets. Most data structures are structured tables or time-series logs, containing content such as interface addresses, request methods, status codes, response durations, field names and corresponding data types. There is no unified fixed unit system; it varies based on specific interface definitions.
What constraints do these characteristics impose on document parsing and chunking
Since data comes from real-time or periodic inter-system interaction content, and most documents are structured tables and time-series logs, document parsing and chunking must retain associative relationships between data. Do not split cross-field mapping entries or interrupt call chains. Data update frequency is also high. Parsing configurations must adapt to the volume of batch-imported documents. Unreasonable chunking rules can increase time spent on subsequent steps, including confirming consistent field definitions and troubleshooting call chains. It may even trigger data synchronization issues.
The following configurations apply to FastGPT v4.17.0.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field length and association density of interface lists and field mapping tables, avoiding splitting cross-field mapping relationships |
chunkSplitter | Split by semantic segments | Adapts to the time-series logic of debugging logs and issue tracking sheets, retaining continuous call chain context |
customPdfParse | Enabled | Supports parsing PDF versions of interface documents, extracting structured interface parameters and sample content, and adapts to the underlying parsing logic of minerU |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the maximum volume of batch-imported debugging logs and API document packages |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Prevents large interface list or log files from triggering timeouts during parsing |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types (such as interface tables, time-series logs) to meet field alignment requirements |
Three common mistakes
- Symptom: After parsing PDF-format interface documents, interface parameters and sample content are missing. The interface shows parsing successful but content is empty. Cause: The
customPdfParseconfiguration is not enabled. The default parsing logic cannot extract structured content from PDF documents. - Symptom: After parsing Feishu multi-dimensional table data pulled via API, field mapping relationships are mixed up and cannot match interface definitions. Cause: The
chunkSplitterconfiguration is not adjusted for structured tables. The default chunking logic disrupts row-column associations in multi-dimensional tables. - Symptom: Multi-vector support for table data does not take effect. The parsing result only generates a single vector. Cause: The
chunkSettingModeis not adjusted for table structures, and corresponding chunking rules are not enabled.
How to confirm configurations are correctly set
- Upload a single interface list PDF, and check if the parsed result contains complete interface addresses, request methods, and response fields.
- Import a small-volume debugging log file, confirm that the parsed chunks retain continuous call chain records without time-series breaks.
- Adjust the
chunkSizeparameter to different ranges, compare parsed chunk results, and ensure field mapping entries are not split. - Upload a file close to the
UPLOAD_FILE_MAX_SIZElimit, verify that the parsing process does not trigger timeout errors.
The values provided are common starting points and should be validated against relevant 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.