This page configuration is based on FastGPT v4.17.0.
What the data for this category looks like
The daily documents for this category fall into four types: event plans, resource slot scheduling tables, event page copy, and event post-event review reports. Data sources include internal content libraries, event backend management systems, traffic statistics tools, and user feedback forms. Documents are updated on a weekly basis, with temporary additional updates around holidays. Individual documents contain structured fields such as event cycle, resource slot ID, delivery channel, and conversion data. Some post-event review reports include unstructured user comment snippets.
What constraints these characteristics impose on document parsing and chunking
The cycle field and resource slot ID in event plans must retain contextual association. Do not split them during chunking. The multi-row table structure of resource slot scheduling tables can easily be broken by standard chunking logic. Adapt table parsing rules for these documents. User comment snippets attached to post-event review reports use non-standard phrasing. Adjust chunk granularity to avoid semantic breaks. Temporary updates to event documents increase timeliness requirements during batch parsing. This raises the risk of timeouts. Some documents include cross-page event process descriptions. Preserve logical connections between paragraphs during chunking to avoid incomplete semantics after splitting.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the paragraph length of event plans and post-event review reports. Retains contextual association between resource slot IDs and event cycles |
chunkSplitter | Split by paragraph + title | Matches the title hierarchy and paragraph structure of event documents. Avoids breaking the logic of table-based scheduling documents |
customPdfParse | Enable table recognition mode | Adapts to the multi-row table structure of resource slot scheduling tables. Retains field association within cells |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Compatible with large batch-uploaded event post-event review reports and multi-page event plan documents |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses batch document parsing triggered by temporary updates around holidays. Prevents timeouts caused by large file sizes or complex content |
chunkSettingMode | Manual configuration mode | Adjust chunking rules and parsing parameters flexibly for the non-standard formats of event documents |
Three Common Errors
- Uploading a PPT document for parsing returns the error "the argument ‘windows-1252’ is invalid encoding". The cause is failure to configure a custom encoding to match the non-standard character set used in event documents.
- Multi-row XLSX resource slot scheduling tables are split into scattered text blocks. The cause is failure to enable table recognition mode. The default chunking logic cannot retain field association between cells.
- Knowledge base recall results do not include document source traceability information. The cause is failure to enable metadata collection configuration in the document parsing and chunking link. Source document identifiers are not recorded during chunking.
How to Verify Correct Configuration
- Upload a test event plan document. Check if parsed chunks retain contextual association between event cycles and resource slot IDs.
- Upload an XLSX-format resource slot scheduling table. Verify that the parsed result retains the table’s cell structure and field correspondence.
- Trigger a batch document parsing task. Check that the task completes within the set timeout period with no abnormal errors.
- View metadata for chunks in the knowledge base. Confirm that each text block includes source document identifier information.
The values provided are common starting points. They 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.