What data does this category cover?
This category supports compliance knowledge services for party building learning Q&A scenarios. Core data comes from enterprise contract management systems, compliance risk databases, legal and regulatory repositories, case management systems, and reporting platforms. Daily processed documents include compliance risk lists, contract legal review opinions, major issue legal opinions, compliance review forms, and violation report investigation results. Data is updated monthly. Document structures vary significantly: some are structured tables, such as compliance review forms and risk lists; others are long-form texts, such as legal opinions and investigation reports, which contain fields like risk descriptions and handling suggestions.
What constraints do these characteristics impose on the document parsing and chunking link?
This category’s documents are used for party building learning Q&A scenarios, so compliance content must be accurately linked to party building-related requirements. Parsing and chunking must retain the logical connections of the content. Documents originate from scattered sources and have diverse structures. Parsing tools must adapt to different formats of compliance documents. Monthly updated batch document demands require the parsing process to have stable batch processing capabilities, to avoid overall task backlogs caused by excessive time spent on a single document. Structured table documents require accurate extraction of compliance-related fields within cells, to avoid missing key information such as risk levels and violation items. Long-form text documents must retain the hierarchical connection between paragraphs and titles, to prevent damage to the logical integrity of legal clauses or handling suggestions after chunking. Parsing errors in compliance documents may lead to major legal risks, so parsing error rates must be strictly controlled to avoid loss or misjudgment of key content.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Fits the paragraph and clause length of compliance documents, and meets the requirement that single chunks can be independently retrieved for party building learning Q&A scenarios, avoiding splitting of key legal clauses or risk items |
chunkSplitter | Split by paragraph + title | Matches the hierarchical structure of compliance documents, retains the logical connections of risk lists and legal opinions, and ensures that compliance content can be linked to corresponding requirements during party building learning Q&A |
customPdfParse | Enabled | Supports parsing of non-pure text content such as embedded tables and annotations in compliance documents, and adapts to structured compliance review forms and scanned compliance files |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Compliance documents are usually lengthy, this avoids batch parsing task failures due to timeouts, and adapts to the batch data processing rhythm of monthly updates |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to batch uploads of compliance archive packages, and meets the needs of batch data processing for monthly updates |
chunkSettingMode | Manual configuration | Adjusts chunking rules for different types of compliance documents (such as long-form texts and table documents), to optimize knowledge retrieval effects for party building learning Q&A scenarios |
Three Common Errors
- Issue: Image-format compliance documents (such as scanned compliance review forms) cannot be parsed, and an error message "Unable to extract text" is returned. Cause:
customPdfParseis not configured and enhanced parsing tools are not connected, so text content in images cannot be recognized. - Issue: After deploying FastGPT locally and enabling the enhanced PDF parsing function, document parsing tasks become unresponsive or time out. Cause: The service address for
customPdfParseis not pointed to the locally deployed MinerU port, or the port checked via curl does not match the port configured in FastGPT. - Issue: After chunking compliance documents, vector retrieval results for table data are empty. Cause: Multi-vector support configuration for table data is not enabled, so compliance-related fields within tables are not properly chunked and vectorized.
How to Verify Successful Configuration
- Upload a typical long-form compliance document (such as a major issue legal opinion), check the parsing record in the knowledge base of FastGPT v4.17.0, and confirm that the title hierarchy and paragraph structure of the original text are retained.
- Go to the knowledge base settings page, check the status of the
customPdfParseswitch, and confirm that it matches the configuration of the locally deployed enhanced parsing service. - Upload a compliance review form with a structured table, verify that all field content within the table is fully extracted in the parsing results, with no missing or misaligned content.
- Upload a single compliance document, check the parsing task time record, and confirm that it does not exceed the configured
PARSE_FILE_TIMEOUT_SECONDSthreshold, and no timeout errors occur.
The values listed above are common starting points. They should be evaluated against the reader's own specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.