What data in this category looks like
Backend service development technical documentation and API Q&A data primarily originates from code repositories, API gateway logs, databases, and configuration centers. Commonly used documents include interface design documents, database change orders, code review records, and release notes, with an update frequency of daily or per version. Interface design documents typically include structured content such as interface paths, request parameters, response formats, and error code definitions. Fields include parameter names, data types, required flags, and business descriptions, with units including milliseconds, bytes, and similar units.
Constraints imposed on document parsing and chunking
Data sources cover text and configuration fragments across multiple formats, requiring parsing rules to adapt to non-standard code-based text structures. Frequently updated documents require chunking logic to support fast incremental processing, avoiding additional overhead from full re-parsing. Structured document fields are closely linked. Chunking must retain contextual associations between interfaces, parameters, and exception handling. Failure to retain these associations will negatively impact the accuracy of subsequent Q&A. Large configuration files and batch-uploaded API documents also impose adaptation requirements for parsing timeouts and file size limits.
How to configure settings
For FastGPT v4.17.0, document parsing and chunking logic can be adjusted via the following configuration items:
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field density of backend interface documents, avoiding including too much associated logic in a single chunk |
chunkSplitter | Split by code semantics | Matches the structured format of backend documents, retaining contextual associations between interfaces and parameters |
PARSE_FILE_TIMEOUT_SECONDS | 60–120 seconds | Adapts to the processing duration of batch-uploaded interface documents, avoiding interrupting the parsing process due to timeouts |
UPLOAD_FILE_MAX_SIZE | 100–500 MB | Matches scenarios where backend teams batch upload configuration center files |
customPdfParse | Disabled | Most backend documents are in text format, so no additional PDF parsing logic is needed |
chunkSettingMode | Manual configuration | Allows backend teams to adjust chunking rules based on different document types |
Three common misconfigurations
- No parsing result is generated after uploading a Java interface file with a modified file extension. This occurs because custom parsing rules are not enabled. The default parsing logic only adapts to standard text formats, and cannot recognize the syntax structure of Java interfaces.
- The indexing status remains stuck after uploading using the chunk mode pushdata API. This occurs because
PARSE_FILE_TIMEOUT_SECONDSis configured too short. Large interface documents enter the indexing stage before parsing is completed. - Images in uploaded documents are ignored. This occurs because
customPdfParseis not enabled, and the document uses a non-standard text format with embedded images. The default parsing logic only extracts text content.
How to confirm configurations are properly set
- A typical single interface design document may be uploaded, and the parsed chunk list can be reviewed to confirm chunk granularity aligns with business expectations.
- A large configuration center file may be uploaded, and no timeout-related errors will appear during the parsing process.
- A code-style document with a modified file extension may be tested for upload, and the parsing result will include core content such as interface definitions and parameter descriptions.
- Parsing logs may be checked to confirm that chunking rules match the structured characteristics of the currently uploaded document.
The values listed above are common starting points, and should be evaluated against samples from the target deployment environment.
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.