What data for this category looks like
Data sources for this category include tracking systems, data warehouses, CRM systems, and ticket systems. Update cycles are typically daily or weekly. Daily processed documents include usage analysis reports, tracking plans, indicator specification tables, and dashboard requirement sheets. Most document structures contain fields such as indicator names, statistical specifications, value ranges, and associated customer IDs. Some documents contain embedded images or tables. Units include times, person-times, yuan, and others. Field naming rules vary across different documents.
What constraints do these characteristics impose on document parsing and chunking
Multi-source data and diverse document formats for this category require parsing logic to adapt to multiple file types including excel, pdf, and word. It also requires handling embedded images and tables. Daily or weekly update cycles create batch processing needs. Parallelizable parsing logic must be configured. Structured content such as indicator specification tables and tracking plans in documents requires chunking to preserve logical units. It must avoid splitting the association between indicators and their corresponding specifications. Some documents have inconsistent field naming. Context must be preserved during chunking to ensure field consistency for subsequent analysis. Unlike other customer management categories, this category requires processing batch documents across multiple customers. Unified parsing rules must be configured to adapt to multi-customer data.
How to configure settings
The following configurations are based on the parameter logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents in this category mostly contain continuous indicator specifications or analysis logic. This value range balances context completeness and chunk granularity |
chunkSplitter | Split by title + paragraph | Daily documents include structured content such as usage analysis reports and tracking plans. Splitting by title and paragraph preserves logical units |
customPdfParse | Enabled | Documents in this category often contain embedded analysis charts and indicator tables. Enabling this preserves the association between table structures and embedded images |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Weekly analysis reports for batch processing may be large in size, so this adapts to batch upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large tracking plan documents require longer parsing times to avoid timeout interruptions |
chunkSettingMode | Manual configuration | Chunking requirements vary significantly across different document types, such as indicator specification tables and dashboard requirement sheets. Manual configuration allows flexible adjustments |
Three common configuration errors
- Symptom: When parsing excel-format tracking plans, embedded configuration images are not extracted, and only plain text content is returned. Cause: The table and embedded resource parsing switch corresponding to
customPdfParseis not enabled. The default parsing logic only extracts plain text content. - Symptom: When uploading weekly analysis reports in batch, some documents fail to parse and return timeout prompts. Cause: The value of
PARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing time of this type of document, and insufficient processing time is reserved. - Symptom: In split indicator specification table fragments, indicator names and statistical specifications belong to different chunks and cannot be associated. Cause: The value of
chunkSizeis too small, andchunkSplitteris not configured to split by title + paragraph, which destroys the logical structure of the document.
How to verify the configuration is correctly applied
- Upload an excel-format tracking plan document that contains embedded images. Check whether the parsing result retains image association information to confirm that the custom parsing configuration takes effect.
- Upload a weekly usage analysis report of approximately 100 MB. Check that no timeout prompt appears during the parsing process to confirm that the timeout configuration meets current document processing requirements.
- Randomly select an indicator specification table document. Check whether the chunking result retains the association between indicator names and their corresponding specifications in the same chunk to confirm that the chunking configuration adapts to structured documents.
- Batch upload 3 daily documents of different types. Check the completion status of parsing tasks to confirm that the uploaded file size configuration adapts to batch processing requirements.
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.