What Data for This Category Looks Like
This category of data primarily comes from advertising platform backends, the national enterprise credit information public disclosure system, customer-submitted account opening application materials, and industry access rules. Commonly processed documents include account opening application forms, scanned business licenses, industry qualification certificates, and account opening audit records. Most fields include subject name, unified social credit code, industry license number, application date, and similar items. Data updates occur daily or are triggered with each account opening application. Document formats are mostly PDF, some with digital signatures, and a small number contain complex table structures.
Constraints on Document Parsing and Chunking
The data characteristics of this category impose multiple constraints on the document parsing and chunking process. Dispersed data sources lead to inconsistent document formats, requiring adaptation to parsing differences between scanned PDFs and native PDFs. Some documents include digital signatures, which may trigger errors in standard parsing workflows, requiring additional compatibility with signature verification logic. A small number of documents contain complex qualification tables. Unreasonable chunking rules will split field associations and disrupt subsequent verification work. Data is updated in real time alongside account opening applications, so parsing process timeliness must be maintained to avoid timeouts that delay audit progress. Many structured fields are present, so contextual connections between fields must be preserved to prevent loss of associative verification capability after chunking.
Configuration Recommendations
For the security and compliance material review scenario of ad account opening audits, based on FastGPT v4.17.0, refer to the following configuration items:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field length of qualification documents, avoids splitting key qualification information, and ensures chunk granularity suitable for subsequent verification |
chunkSplitter | Split by header, footer and table boundaries | Matches the characteristic that documents in this category mostly contain structured tables and fixed-format qualification pages, and retains field associations |
customPdfParse | Enabled | Compatible with PDF documents with digital signatures, avoiding errors in standard parsing processes |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Adapts to the parsing duration of a single qualification document, preventing account opening audit process interruptions caused by timeouts |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Covers the upload requirements of multi-page qualification collections, meeting the needs of batch account opening audit scenarios |
chunkSettingMode | Manual configuration | For the special formats of documents in this category, chunking rules can be flexibly adjusted to adapt to different types of qualification materials |
Three Common Configuration Mistakes
- Symptom: After uploading a PDF with a digital signature, the parsing result is empty or a file read error is triggered. Cause: The
customPdfParseconfiguration is not enabled, and the standard parsing process cannot handle document formats with digital signatures. - Symptom: The pdf-marker function works normally in local deployment, but FastGPT knowledge base uploads PDFs with no parsing results. Cause: The local call link between FastGPT and pdf-marker is not configured, or the uploaded file size exceeds the
UPLOAD_FILE_MAX_SIZElimit. - Symptom: Complex qualification tables are split into multiple unrelated chunks, making subsequent verification unable to associate fields. Cause: The
chunkSplitteris not specified to split by table boundaries, and the default chunking rule disrupts field associations within the table.
How to Confirm the Configuration Is Correct
- Upload a qualification PDF with a digital signature, and verify that the parsing result includes complete text content.
- Upload an account opening application document containing a complex table, and verify that the chunking result retains field associations within the table.
- View file parsing logs in the FastGPT backend, and confirm that parsing duration does not exceed the set value of
PARSE_FILE_TIMEOUT_SECONDS. - Upload a qualification collection larger than the conventional single-page size, and verify that upload and parsing complete normally.
The values provided are common starting points and 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 2026-10-19.