What this category of data looks like
The data for this category typically originates from community complaint systems, content detail pages, users’ historical complaint records, and official review rules. Commonly processed documents include complaint tickets, violation content handling records, user appeal forms, and standardized notification templates. Fields include unique complaint identifiers, involved content links, violation type tags, processing progress, and results. Data update cycles are mostly real-time or daily synchronization. The size of individual complaint data varies based on the complexity of involved content, and often includes multi-format attachments and structured fields.
Constraints imposed on document parsing and chunking
Complaint tickets and appeal forms often include multi-format attachments, such as long PDF complaint evidence, screenshots, and structured tables. Parsing time and success rate for large files directly impact processing efficiency. Real-time updated complaint data requires the parsing module to support low-latency triggering to avoid backlogs of pending tickets. Differences in fields across documents require chunking logic to adapt to mixed scenarios of structured content and unstructured text, preventing merging of unrelated fields across tickets which would reduce subsequent retrieval accuracy. Additionally, precise extraction of violation evidence requires chunking to retain contextual associations, avoiding splitting critical violation evidence fragments which could lead to deviations in review judgments.
How to configure settings
In FastGPT v4.17.0, the document parsing and chunking logic can be adjusted using the following configuration items:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed text length of complaint tickets and appeal forms, avoiding splitting critical violation evidence fragments |
chunkSplitter | Paragraph + semantic splitting | Adapts to the mixed structure of structured tickets and unstructured evidence text, retaining contextual associations |
customPdfParse | Enabled | For multi-hundred-page complaint evidence PDFs, uses custom parsing logic to improve success rate for large file parsing |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time of large-volume complaint PDFs, avoiding interruption of long document processing due to timeout |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Covers the maximum upload requirements for multi-attachment complaint tickets, avoiding compliance-related errors |
chunkSettingMode | Manual configuration | Adapts to the mixed field structure of complaint data, allowing flexible adjustment of chunking rules |
Three common configuration mistakes
- Parsing errors occur when calling the parsing tool for multi-hundred-page complaint evidence PDFs. The root cause is failure to adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter; the default timeout duration is insufficient to complete full parsing of large-volume PDFs. Cannot read properties of undefinederrors appear in locally deployed custom parsing components. The root cause is failure to match the corresponding version of parsing dependency packages, resulting in incompatibility with the large-file parsing scenario for community complaint handling.- Duplicate text appears after chunking, or the number of files in retrieval results does not meet expected standards. The root cause is failure to adjust
chunkSettingModeand retrieval rules based on the mixed document structure of complaint tickets, and failure to filter duplicate notification template text or limit retrieval scope.
How to confirm correct configuration
- Upload a single complaint evidence PDF with more than 500 pages, check the parsing status in the task logs of FastGPT v4.17.0, and confirm no timeout errors occur.
- Import a single complaint ticket containing multi-format attachments, review the chunked text fragments, and confirm that contextual associations of critical violation evidence fragments are not split.
- Adjust the
chunkSizeparameter, compare the length of chunked fragments, and confirm they fall within the preset character range. - Test batch import of 10 real-time complaint data entries, confirm that the completion duration of parsing tasks meets the rhythm requirements of business processing.
The values provided are common starting points and should be measured against applicable sample datasets.
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.