What this category of data looks like
This category of data is sourced from regulatory rule databases, higher-level law databases, departmental policy document libraries, and administrative regulatory document filing systems. Update frequency is irregular. Daily processed documents include drafts of regulatory documents, drafting explanations, legality review opinions, summaries of solicited opinions, and filing reports. Most document structures contain policy provisions, drafting background, review conclusions, and attached tables. Core fields include document numbers, issuing authorities, effective dates, rights and obligations setting clauses, and other content required for compliance review.
What constraints do these characteristics impose on the "document parsing and chunking" link
Documents in this category mostly contain structured content such as legal provisions and review opinions, and often include attached tables and image attachments. This creates high accuracy requirements for parsing. Because review requires comparison with higher-level laws and authority basis, chunking must retain the contextual association of provisions, avoid breaking clause logic, and ensure accurate matching of original legal provisions during review. Document sources are scattered and formats are inconsistent, so the system must adapt to multiple official document formats. Additionally, single processing document volume is large. It is necessary to properly control the timeout threshold for parsing and chunking to avoid process interruption due to overly long processing time.
How to Configure
The following configurations apply to FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Provisions in regulatory documents are usually several hundred characters long. This range retains the complete context of a single or associated legal provision, and fits the comparison needs of legality review |
chunkSplitter | Split by heading hierarchy and paragraphs | Documents in this category mostly have hierarchical legal provisions and review opinions. Splitting this way retains the logical association of clauses, and avoids damaging the integrity of provisions during splitting |
customPdfParse | Enabled | Documents in this category are mostly in official PDF format. Enabling this option optimizes parsing effects for tables and images, and resolves issues with poor attachment recognition |
UPLOAD_FILE_MAX_SIZE | 200–500 MB, adjust based on actual testing | Regulatory documents often have multiple attached files. This threshold covers the document volume of most batch review scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds, adjust based on actual testing | Parsing large compliance documents takes a long time. This time range avoids interrupting the parsing process due to timeout |
chunkSettingMode | Manual configuration | Documents in this category have fixed structures but large format differences. Manual configuration allows flexible adaptation to different types of review documents |
Three Common Mistakes
- After enabling
customPdfParseand importing a PDF document, table content is not correctly extracted. The cause is that the enhanced parsing switch for the corresponding format is not checked, or the document is encrypted, preventing the parsing engine from reading the table structure. - After configuring custom URL parsing, the task shows success but no parsed data. The cause is that the custom URL does not have public access permissions, or the document format pointed to by the link is not supported by the parsing engine.
- After the document parsing node is configured, the model cannot read the uploaded file. The cause is that
UPLOAD_FILE_MAX_SIZEis set too small, so files exceeding the threshold are automatically blocked, or the parsing timeout parameter is configured too short, causing the task to terminate early.
How to Confirm the Configuration is Correct
- Upload a single typical draft regulatory document, view the parsed text preview, and confirm that table and image content has been correctly extracted.
- Adjust the
chunkSizeparameter, batch import multiple review documents of different formats, and check if the chunked text retains clause logic. - Submit a document larger than the conventional volume, confirm that the parsing task does not have timeout errors, and the chunking results meet expectations.
- Test the custom URL parsing function, confirm that the link can be accessed normally and valid text blocks are generated after parsing.
The values listed here are common starting points. They should be evaluated 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 2026-09-28.