What the data for this category looks like
The data sources for party building learning in expressway operations include internal party building management systems, official documents issued by superior party committees, study ledgers and party lesson courseware from toll station branches. Update cycles follow monthly additions of special study materials and quarterly updates of annual party building compilation documents. Single file sizes vary widely, ranging from a few pages of study notices to hundreds of pages of compilation manuals. Supported document formats are PDF, Word, and image posters. Most documents include hierarchical headings such as party committee deployment, branch implementation, and study reflections, embedded tables, and annotated images. Fields include file name, issuing unit, and release date, with units of "copies", "articles", and "pages" as standard metrics.
What constraints do these characteristics impose on the document parsing and chunking process
The above data characteristics impose multiple constraints on the document parsing and chunking process. First, hierarchical headings mixed with tables and images require parsing tools to support structured extraction, preventing semantic fragmentation after chunking. Second, large-volume compilation documents need longer parsing timeouts to avoid mid-task interruptions. Third, mixed-format document libraries must support batch parsing configurations to accommodate frequent imports of updated party building materials. Fourth, study ledgers from different stations have minor format differences, so custom parsing adjustment space must be retained to ensure unified chunking logic across all document types.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Party building study documents are mostly theoretical texts. This length range preserves complete semantic units and meets the accuracy requirements of RAG retrieval |
chunkSplitter | Split by heading hierarchy | Party building documents have clear hierarchical structures for party committees, branches, and study topics. Splitting by headings preserves contextual relevance |
customPdfParse | Enabled | Party building PDFs often contain embedded tables and image annotations. Custom parsing can fully extract text and format information |
UPLOAD_FILE_MAX_SIZE | 200 MB | Accommodates the size of party building compilation files imported in bulk for expressway operations, to avoid single-file upload failures |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large-volume party building compilation documents take longer to parse. This duration covers the parsing process for most complex documents |
chunkSettingMode | Manual configuration | Adjustment of chunking parameters based on the structural characteristics of party building documents is required to meet the personalized needs of the business scenario |
Three common mistakes
- Phenomenon: After an external system actively pushes files, the knowledge base does not generate corresponding parsing tasks. Cause: Automatic parsing trigger rules after file pushes are not configured, and only manual parsing triggering is supported.
- Phenomenon: After uploading party building promotional images, the parsing result only returns a small amount of metadata, with no text content from the images. Cause: OCR parsing configuration is not enabled. The default parsing logic only processes plain text format files.
- Phenomenon: When calling the workflow API to upload images, the interface returns a parameter format error. Cause: The image file is not converted to binary stream format, or the content type in the request header is not configured correctly.
How to confirm the configurations are set correctly
- Upload a party building PDF document that includes tables and heading hierarchies. Check if the parsed chunked results retain the heading hierarchies and table content, and verify that the chunk length falls within the configured
chunkSizerange. - Call the batch upload interface to push a batch of party building documents. Check if the status of each task in the parsing task list changes from "pending parsing" to "completed", with no timeout or failure errors.
- Configure a workflow API to call the image parsing node. Pass a test image, then check if the returned results include text content from the image, to confirm that OCR parsing is active.
- Adjust the
chunkSizeparameter and re-parse the same party building document. Compare the chunked results from both parsing runs to confirm that the configuration parameters have taken effect.
The values listed here are common starting points. They should be evaluated against your own sample datasets.
Reference only; verify against the target FastGPT release and deployment documentation.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.