What the data for this category looks like
Daily documents for this category include four types: onboarding applications, identity qualification materials, certification audit records, and cooperation agreements. Data sources are creator backend, enterprise credit information system, account history database, and contract management system. Onboarding applications include basic account information and application reasons. Identity qualification materials include business licenses, ID card scans, and qualification lists in Excel format. Certification audit records include audit status and opinions. Cooperation agreements include both parties' information and rights and obligation clauses. Data update frequency is daily or triggered by individual applications. Core fields include account ID, qualification number, audit time, agreement number, and others.
What constraints these characteristics impose on the document parsing and chunking link
Document types are diverse, including structured tables, semi-structured text, and unstructured images. Parsing logic must support multiple formats to avoid missing table row and column association information. Data sources are scattered, so association identifiers for documents from each source must be retained to avoid confusing materials from different applicants during audits. Update frequency is daily or application-triggered, so the parsing process must support on-demand processing without occupying excessive system resources. Error consequences involve false certifications and cooperation disputes, so the integrity of core fields must be retained during parsing, and key semantic blocks must not be split. In addition, daily submitted files include Excel qualification lists, so complete extraction of table content must be supported to avoid extracting only scattered text.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the text density of onboarding applications and audit records, balances semantic integrity of qualification materials, and avoids overly fragmented or overly long chunks |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Matches the parsing time required for multi-page PDF qualification materials and complex Excel tables, and avoids request failures due to insufficient processing time |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports uploading cooperation agreements with attachments, and covers the maximum file specifications for daily submissions |
chunkSplitter | Split by paragraph + title | Retains the chapter structure of audit records and cooperation agreements, and avoids splitting core semantic blocks such as rights and obligation clauses and audit opinions |
chunkSettingMode | Custom mode | Adjusts chunking rules for different document types, adapting to scenarios such as short text for onboarding applications and long text for qualification materials |
Three common mistakes
- Phenomenon: After uploading an Excel format qualification list, the parsing result only extracts scattered text without table row and column association information. Cause: No dedicated parsing rule is configured for table files, and the default chunking logic does not recognize cell association relationships.
- Phenomenon: After uploading a cooperation agreement attachment larger than 1000 MB, the system directly returns an upload failure. Cause: The
UPLOAD_FILE_MAX_SIZEparameter is not adjusted, exceeding the default file size limit of FastGPT v4.17.0. - Phenomenon: After uploading multi-page PDF qualification materials, the system displays a request failure, and the elapsed time is close to 2 minutes. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set to 100 seconds, which cannot complete the complete parsing process for multi-page files.
How to confirm the configuration is complete
- Upload a test Excel qualification list file, and check whether the parsing result retains the row and column titles and corresponding content of the table.
- Upload a test PDF file of around 1000 MB, confirm that the parsing time is within 180 seconds, and there is no timeout error prompt.
- View the background configuration page of FastGPT v4.17.0, confirm that
chunkSettingModeis set to custom mode, andchunkSplitteris set to split by paragraph + title. - Upload a certification audit record document containing long paragraphs, and check that the chunked content does not have semantic splits, and core audit opinions are completely retained in a single chunk.
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.