What the data for this category looks like
Typical entities include game customer service teams, community operations teams, and distribution operations teams. Daily processed documents include player tickets, compensation applications, public opinion daily reports, and response scripts. Data sources cover customer service system tickets, community forum comments, app store reviews, and in-game logs. Update frequency is mostly daily or real-time. Document structures are mostly semi-structured or short text, with fields such as account ID, problem description, submission time, feedback category, and compensation type. No unified fixed format exists. Some compensation applications and public opinion daily reports are stored in Excel or PDF format.
What constraints do these characteristics impose on the document parsing and chunking link
The multi-source, non-uniform format documents of this category require the parsing link to support multiple formats including Excel, PDF, and short text. The real-time or daily update frequency requires the parsing process to have sufficient response speed to avoid delays that affect subsequent processing. Documents contain key sensitive fields such as account numbers and compensation application IDs. Chunking must avoid splitting content that spans related fields, otherwise subsequent verification and judgment will produce errors. Some documents use Excel files with multiple sheets. Parsing must support reading content from different tabs, otherwise some compensation application data will be omitted.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the single-block content length of player tickets and public opinion comments, avoids splitting key fields such as account IDs and compensation types |
chunkSplitter | Split by paragraph + title | Matches the structured layout of public opinion daily reports and response scripts, preserves contextual associations |
PARSE_FILE_TIMEOUT_SECONDS | 60–120 seconds | Adapts to the real-time or daily document processing rhythm, avoids timeout during parsing of large Excel files |
UPLOAD_FILE_MAX_SIZE | 100 MB | Supports batch imported public opinion daily report compression packages and multi-sheet compensation application Excel files |
customPdfParse | Enabled | Optimizes parsing of PDF-format public opinion daily reports, preserves table and title hierarchy |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different document types (tickets, public opinion reports, response scripts) to adapt to the category-specific document structure |
Three common mistakes
- Uploading an Excel file only loads the default sheet, and cannot read content from other tabs. The cause is that parsing rules adapted to multi-sheet documents are not configured, and the full-sheet reading function for the corresponding format is not enabled.
- Checking the PDF enhancement option when importing PPT or DOC documents results in no parsing effect. The cause is that the PDF enhancement function only applies to PDF-format documents, and the parsing mode for the corresponding document type is not switched.
- Unable to obtain both knowledge base call parameters and complete streaming return results during external calls. The cause is that general parsing logic bound to return fields is not configured, and segmented splicing of streaming data is not handled correctly.
How to confirm the configuration is complete
- Upload a compensation application Excel file with multiple sheets, check if the parsing result includes content and corresponding names from all sheets.
- Upload public opinion daily reports in PPT, DOC, and PDF formats separately, confirm that PDF format can be parsed normally and retains table structure.
- Call the FastGPT v4.17.0 external interface to test the parsing process, confirm that the returned results include knowledge base call parameters and complete streaming return content.
- Adjust the
chunkSizeparameter, then upload a short-text player ticket, check that the chunking result does not split key fields such as account IDs.
The values listed above are common starting points. Adjust them based on your own specific samples and use cases.
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.