Data for This Category
This category’s data comes from code repositories, dependency lists, license texts, and contribution records. Processed documents include LICENSE files, NOTICE files, dependency license lists, and copyright statements. Each version release or dependency change triggers an update to the data. Core fields in document structures include license type identifiers, copyright years, contributor information, and distribution terms. Document formats vary widely. Some use plain text, others use structured lists. No unified typesetting standard exists.
Constraints on Document Parsing and Chunking
The characteristics of this category’s data impose multiple constraints on the document parsing and chunking workflow. First, data sources are scattered and formats are inconsistent. Parsing processes must adapt to multiple document types including plain text and structured lists. This avoids loss of core compliance fields such as license type identifiers and copyright years. Second, data update frequency is high. Parsing workflows must support fast batch processing to align with version release and dependency change timelines. Third, the integrity of core fields directly impacts subsequent compliance checks. The chunking process must ensure critical information is not split across chunks. It must also avoid overly large chunks that reduce retrieval accuracy. Finally, information density varies across document types. Chunking logic must be adjusted separately for LICENSE files, NOTICE files, and dependency lists to match their respective information structures.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Must cover the full semantics of a single license clause or copyright statement, to avoid splitting core compliance information |
chunkSplitter | Match rules by document type | Adapt to different formats of LICENSE files, NOTICE files, and dependency lists, and preserve the integrity of key fields |
customPdfParse | Enabled | Preserve text hierarchy and field structure for exported dependency license list PDF files |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to upload requirements for large dependency license list files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Avoid timeout exceptions during parsing of large compliance documents |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different types of compliance documents to match their respective information densities |
Three Common Configuration Errors
- Phenomenon: After uploading multiple compliance documents, knowledge base search results cannot distinguish chunked content from different files. Cause: No file attribution marker for chunk metadata is configured, so chunked information lacks file identification fields.
- Phenomenon: Target compliance clauses cannot be retrieved during knowledge base searches. Cause: The
chunkSizesetting is too small, splitting a single complete license clause into multiple chunks, leading to semantic fragmentation that cannot match retrieval requests. - Phenomenon: Timeout errors occur when parsing large dependency license lists. Cause: The
PARSE_FILE_TIMEOUT_SECONDSvalue is lower than the actual time required for parsing, leading to forced termination of parsing tasks.
How to Verify Proper Configuration
- Upload a single LICENSE file, and check if the parsed chunked content includes complete license clauses and copyright statements.
- Upload multiple compliance documents of different types, and verify that the metadata for each chunk includes identification information for the corresponding file.
- Trigger a parsing task for a large dependency license list, and confirm that no timeout exception occurs for the task.
- Run a knowledge base search test, and verify that target compliance clauses can be accurately retrieved.
The values provided are common starting points, and should be evaluated against relevant use case 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.