What this category of data looks like
Data for this category is produced daily by customer service, technical support, and customer success teams. Core documents include customer tickets, issue categorization tables, processing records, and service reports. Data sources cover ticket systems, customer service chat logs, product operation logs, and customer contract SLA documents. Update frequency is daily or real-time. Ticket documents include fields such as ticket ID, customer identifier, problem description, and submission time. Issue categorization tables include fields such as priority, impact scope, and responsible team. Data is stored using individual tickets or single tables as basic units.
What constraints do these characteristics impose on the document parsing and chunking link
Mixed parsing of multi-source data requires the parsing engine to support multiple formats including PDF, Excel, and plain text, to avoid losing field structures across different document types. Real-time or daily updated data requires the parsing process to be efficient, to avoid data synchronization delays caused by overly long parsing times. Strong field association between tickets and categorization tables requires chunking operations to retain key identifiers, and must not split the problem description and processing record of the same ticket. Otherwise, the accuracy of subsequent issue categorization and assignment will be affected. Additionally, the size difference between bulk ticket packages and SLA contracts requires parsing configurations to adapt to file upload and parsing of different sizes.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Ticket content includes continuous problem descriptions and processing records. This length preserves contextual association and avoids splitting critical information. The default value of FastGPT v4.17.0 is 1000 characters, which can be adjusted slightly based on actual ticket length |
chunkSplitter | Split by paragraph + title | Tickets and categorization tables have clear title and paragraph structures. Splitting this way preserves field association and avoids chunking across tickets or fields |
customPdfParse | Enabled | Tickets are often submitted in PDF format. Enabling this option fully extracts text layout and table fields, avoiding content missing or format confusion |
PARSE_FILE_TIMEOUT_SECONDS | 60–90 seconds | Ticket PDFs containing multi-page chat records or attachments take longer to parse. This value covers parsing needs for most scenarios and avoids triggering timeout errors |
UPLOAD_FILE_MAX_SIZE | 50–100 MB | Bulk ticket packages and customer contract SLA files have large size differences. This value adapts to most upload scenarios, and can be calibrated based on actual business requirements |
Three common mistakes
- Uploading a PDF ticket results in parsing failure, with request timeout returned in logs. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default value is insufficient for parsing ticket PDFs containing multi-page chat records. - Imported issue categorization table content appears empty in search results. Cause:
customPdfParsewas not enabled. The default parsing engine cannot fully extract priority and impact scope fields from tables. - Chunked content splits the problem description and subsequent processing records of the same ticket. Cause:
chunkSplitterwas set to split by fixed characters, instead of by paragraph and title. This causes content spanning fields to be split into different chunks.
How to confirm the configuration is correct
- Upload a single-page PDF customer ticket, and check that the parsed text includes complete ticket ID, problem description, and submission time fields.
- Upload an issue categorization table containing tables, and confirm that the parsed result retains the priority and impact scope column content from the table.
- Upload a 10 MB bulk ticket package, and check that the parsing process does not trigger a timeout error prompt.
- Adjust
chunkSizeto 700 characters, and confirm that the chunked content does not split continuous processing record paragraphs.
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.