This guide covers the document parsing and chunking step within technical documentation and API Q&A workflows for content review rule operation scenarios, and is written based on FastGPT v4.17.0.
What this category of data looks like
Data for content review rule operations comes from content review backends, user reports, regulations and policies, and sample libraries. Commonly processed documents include review rules, disposal guidelines, appeal records, and quality inspection reports. Most documents have structures that include hierarchical headings, clause numbers, sample annotations, and disposal threshold fields. Data update frequency follows daily sync or triggers updates when regulatory policies change. Most single documents mix structured rule entries and unstructured sample descriptions.
What constraints do these characteristics impose on the "document parsing and chunking" step
The hierarchical structure of review rule documents requires chunking to retain the binding relationship between headings and corresponding clauses, to avoid breaking rule logic. The high-frequency update feature requires the parsing link to support incremental synchronization, to reduce resource consumption from full repeated parsing. Batch-uploaded review sample library documents are often large in size, which imposes requirements on parsing timeout limits and maximum file size. Errors in this category of data can directly lead to the spread of non-compliant content or regulatory rectification, so chunking must accurately cover core rule clauses, and must not miss key thresholds and disposal processes.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Review rule documents mostly use clause-style structures; a single chunk can fully contain one core rule or a set of associated disposal processes |
chunkSplitter | Split by heading + paragraph | Retain the binding relationship between hierarchical headings of review rules and corresponding content, to avoid chaotic logical splitting |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapt to the parsing time of batch review documents, to avoid mid-parsing interruption of long documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatibility with large-sized review sample library and quality inspection report documents |
customPdfParse | Enabled | Retain official formatting and metadata in review rule PDFs, to improve parsing accuracy |
chunkSettingMode | Manual mode | Allows precise control of chunking boundaries for review rules, adapting to different types of operation documents |
Three common configuration errors
- Phenomenon: Parsing interrupts when batch uploading review rule documents, and parsing cannot continue after restarting the service. Cause:
PARSE_FILE_TIMEOUT_SECONDSis not configured to adapt to long document parsing durations, orUPLOAD_FILE_MAX_SIZEis set smaller than the actual uploaded document package size. - Phenomenon: No parsing response is shown when uploading files via the dialog box, and no error logs appear in the backend. Cause:
customPdfParseis not enabled, causing review guidelines or appeal records with special formats to fail to be correctly identified and parsed. - Phenomenon: Service memory usage is too high after enabling PDF parsing. Cause:
chunkSizeis set too small, causing too many chunks to be generated for a single document, triggering a large number of embedding requests that exceed resource thresholds.
How to confirm the configuration is correct
- Upload a single typical review rule document, check the parsed chunk content, confirm that each core rule and corresponding disposal process is not split and broken.
- Batch upload 10 compliant-sized operation documents, confirm that the parsing progress is not interrupted, and the final number of knowledge base entries matches the number of source documents.
- Check backend running logs, confirm that no timeout errors related to
PARSE_FILE_TIMEOUT_SECONDSappear. - When calling the knowledge base content addition API, confirm that the request parameters match the field format of the review rule documents, to ensure that the newly added chunk content is complete.
- Upload a large-sized quality inspection report document, confirm that the parsing task completes normally and exits without exceptions.
The configuration values provided above are common starting points, and should be evaluated 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.