What the Data for This Category Looks Like
The data for this category mainly comes from ticket systems, customer interview records, CRM systems, and product roadmaps. The update frequency is usually weekly or per version release cycle. Daily processed documents include requirement pool lists, requirement evaluation forms, customer feedback records, and version planning descriptions. Common document fields include unique requirement identifiers, associated customer information, priority tags, feedback content, corresponding version nodes, and more. The overall structure primarily uses itemized requirement records. Some documents include hierarchical requirement association relationships.
Constraints on Document Parsing and Chunking
Requirement pool documents have many items and complex association relationships. Fixed-length forced splitting cannot be used, as it will split apart complete requirement context. High update frequency means the parsing process must support incremental updates, to avoid repeated parsing of full data. Documents from different sources have large format differences. For example, CSV files exported from CRM may have multiple fields per line. Text exported from ticket systems may contain nested replies. Parsing rules must be flexibly adapted. Requirement fields include key information such as priority and associated customers. Chunking must retain this metadata to ensure retrieval accuracy. Irrelevant fields must not be mixed into chunked content.
Configuration Recommendations for FastGPT v4.17.0
The document parsing and chunking process for the customer requirement pool management scenario can be optimized using the following configuration items:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Requirement pool documents are mostly itemized content. This length preserves complete context for a single requirement or associated requirement group, avoiding overly fine splitting that causes scattered retrieval or overly coarse splitting that causes redundancy |
chunkSplitter | Split by requirement item | Requirement pool documents take independent requirements as core processing units. Splitting by items ensures each chunk corresponds to complete information for a single requirement, adapting to subsequent requirement merging and sorting scenarios |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to some large version planning descriptions or batch-exported customer feedback records, avoiding upload failure due to oversized files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large batch requirement documents take a long time to parse. This duration covers parsing needs for most scenarios, avoiding mid-parsing timeout interruptions |
customPdfParse | Enabled | PDF documents for requirement pools are mostly exported system reports. Enabling custom parsing preserves field association relationships within tables, avoiding chaotic content after parsing |
Three Common Misconfigurations
- Phenomenon: When uploading Word format requirement documents larger than 10 MB, parsing progress stalls for a long time or returns a timeout error directly. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default duration is insufficient for parsing large batch requirement documents. - Phenomenon: After importing an Excel format requirement pool list, multiple lines of content are merged into a single chunk, and cannot be split by individual requirement. Cause: The
chunkSplitteror custom delimiter was not configured correctly. Splitting was not done using the line breaks or field delimiters corresponding to requirement items. - Phenomenon: A specific knowledge base cannot retrieve questions that exactly match chunked content, but a newly created knowledge base with the same configuration can retrieve normally. Cause: The
chunkSettingModeconfiguration of the knowledge base is incorrect. This causes loss of some key metadata during chunking or abnormal splitting rules, failing to match the characteristics of the original chunks.
How to Verify Proper Configuration
- Upload a small test document containing a single requirement. Confirm the number of parsed chunks matches the number of requirement items in the original document.
- Upload a batch requirement document of around 10 MB. Confirm parsing time falls within the preset
PARSE_FILE_TIMEOUT_SECONDSrange, with no timeout errors. - After configuring a custom delimiter, import an Excel format requirement list. Verify chunked results correspond one line per independent requirement.
- Import a requirement document with hierarchical associations. Verify parsed chunks retain complete information of associated fields, with no missing content or formatting confusion.
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.