What the data for this category looks like
The core data for this category comes from ticketing systems, chat logs, product logs, and customer contract SLAs, with an update frequency of daily or real-time. Commonly processed documents include customer tickets, issue tiering tables, processing records, and service reports. Tickets contain fields such as customer identifiers, problem descriptions, and response time limits. The tiering table is a structured issue type mapping table. Processing records are mostly short text interaction snippets. Service reports contain aggregated ticket data for a given cycle.
What constraints these characteristics impose on the document parsing and chunking link
Real-time data updates require the parsing link to support incremental synchronization and low-latency processing, to avoid blocking ticket workflows. Structured issue tiering tables coexist with unstructured ticket descriptions and processing records. This requires chunking rules to adapt to both structured field extraction and natural text semantic retention. Compliance documents such as customer contract SLAs may use encrypted formats. The parsing link must support non-standard PDF formats, and must not allow compliance materials to fail to be archived due to parsing failures.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the typical text length of ticket problem descriptions and processing records, avoiding chunking that splits problem context and processing logic |
chunkSplitter | By paragraph + semantics | Matches the natural paragraphing habits of ticket documents, retaining the association between problems and corresponding processing steps |
customPdfParse | Enabled | Used to parse PDF documents such as customer-uploaded contract SLAs and encrypted ticket attachments, restoring structured fields and complex formatted content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the real-time response time limit requirements of ticketing systems, avoiding blocking of ticket workflows due to parsing timeouts |
UPLOAD_FILE_MAX_SIZE | 100 MB | Adapts to the typical size range of ticket attachments used by customer service teams, avoiding parsing failures for large files |
chunkSettingMode | Manual configuration | For structured documents such as issue tiering tables, chunking rules can be individually adjusted to retain field relevance |
Three common mistakes
- Symptom: Complex formulas cannot be parsed normally in a local deployment environment, and a parsing failure prompt is returned on the interface. Cause: The
customPdfParseconfiguration is not enabled, or the used parsing engine version is incompatible with FastGPT v4.17.0. - Symptom: An error prompt that the file content cannot be read is displayed when clicking chunk preview for PDF documents in the knowledge base. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration value is smaller than the size of the uploaded PDF file, or the file is in encrypted format and corresponding parsing permissions are not enabled. - Symptom: Feishu knowledge base cannot synchronize PPT and PDF documents. Cause:
customPdfParseis not configured and parsing support for corresponding document types is not enabled, or synchronization tasks time out without automatic retries.
How to confirm the configuration is correct
- Upload test encrypted PDF and PPT documents, check whether the platform’s parsing logs show normal parsing status.
- Submit a ticket attachment containing complex mathematical formulas, confirm that the chunking result fully retains the formula structure and typesetting.
- Upload a test file within 100 MB, confirm that the parsing task completes within 600 seconds with no timeout errors.
- Check the synchronization logs of the Feishu knowledge base, confirm that the synchronization status of PPT and PDF documents is completed.
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.