What data for this category looks like
Data for this category typically comes from Figma or Axure source files, internal team design systems, user feedback and usability test records, and design review meeting minutes. Daily produced documents include interactive prototypes, page flowcharts, component specification descriptions, and review revision records. Data updates follow weekly iterations or releases before each version. Document structures center on page hierarchy, operation paths, component attributes, and review comments as core fields. No unified standardized fixed format exists. Some files embed interactive logic and state transition descriptions.
What constraints these characteristics impose on document parsing and chunking
Inconsistent document formats mean some files embed interactive logic and state transitions. Parsing processes must retain contextual associations of operation paths. File structures vary widely across different sources, so general template parsing cannot be used. Adaptation to export formats of Figma and Axure is required. Data update frequency is high, so chunking logic must support incremental processing to avoid repeated parsing of full content. Documents contain extensive associated information between page hierarchies and operation steps. Chunk length must cover complete operation nodes to avoid losing interactive logic context after splitting.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of single-page operation paths for interactive prototypes and flowcharts, avoiding loss of complete interactive logic after splitting |
chunkSplitter | Parse by semantic segments | Retains associations between page hierarchies and operation steps, avoiding damage to interactive context from fixed-character splitting |
customPdfParse | Enabled | Adapts to PDF formats exported by Axure and Figma, extracts embedded interactive logic, page comments, and operation path information |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time for large design system files, avoids interrupting the parsing process due to timeout |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch uploads of large design system files and collections of review records |
chunkSettingMode | Manual configuration | Adjusts chunking parameters for different types of design documents, adapts to diverse document structures |
Three common errors
- After uploading PDF files exported from Axure or Figma, search test results are empty. The cause is that the
customPdfParseconfiguration is not enabled. General PDF parsing cannot extract embedded interactive logic and page hierarchy information. - Knowledge base vectorization takes too long. The cause is that
chunkSizeis not adjusted to the range suitable for design documents, orchunkSplitterwith semantic segment parsing is not enabled, leading to redundant chunks and excessive parsing steps. - Data processing returns empty after local deployment. The cause is that a reasonable
PARSE_FILE_TIMEOUT_SECONDSvalue is not set. Parsing of large design files times out without triggering retries, resulting in incomplete data generation.
How to confirm the configuration is correct
- Based on FastGPT v4.17.0, upload a single-page PDF file exported from Axure. Check if page hierarchy and interactive action fields are extracted in the parsing log to confirm that the
customPdfParseconfiguration is active. - Upload a design system file under 100 MB. Verify that parsing time falls within the preset
PARSE_FILE_TIMEOUT_SECONDSrange, with no timeout errors. - Initiate a test query. Verify that search results contain complete operation paths and component descriptions to confirm that the
chunkSizeandchunkSplitterconfigurations do not break document context. - Upload batch design files. Check that the total size of uploaded files does not exceed the
UPLOAD_FILE_MAX_SIZElimit, with no upload failure prompts.
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.