What this category of data includes
This category of data originates from central enterprise strategic investment departments, project companies, state-owned assets supervision departments, and external consulting and evaluation institutions. Common documents include annual investment plans, project proposals, feasibility study reports, due diligence reports, asset appraisal reports, and post-investment evaluation reports. Data comes from state-owned assets investment supervision systems, enterprise ERP and project management systems, industry market data, audit reports, and financial statements. Updates occur on a quarterly basis. Most documents combine structured fields and unstructured text. Fields cover project numbers, investment amounts, implementation periods, review opinions, and similar items. Units include ten thousand yuan, days, percentage, and other standard units.
What constraints do these characteristics impose on document parsing and chunking?
Quarterly updated batch documents require parsing efficiency that supports parallel processing of multiple files. This avoids parsing delays caused by backlogged batch tasks. Heterogeneous documents from multiple sources — such as structured tables exported from systems, and PDF-format feasibility study reports — need compatible parsing rules. This ensures consistent parsing across different document formats. Documents contain precise fields like project numbers and investment amounts. Chunking must retain contextual associations to prevent field fragmentation, and ensure complete information during ledger summary. The rigor of state-owned asset-related documents requires parsing results to have no omissions or errors. Failures here could lead to losses of state-owned assets. Large differences in chapter structures across documents require flexible chunking logic. This maintains chapter coherence during report generation.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the chapter granularity of long texts such as feasibility study reports and post-evaluation reports, and avoids splitting key argument paragraphs |
chunkSplitter | Split by title + paragraph | Aligns with the structure of chapter titles and main text in documents, retains contextual associations, and facilitates aggregation by project dimension during ledger summary |
customPdfParse | Enable structured extraction | Adapts to PDF-format due diligence reports and asset appraisal reports, extracts the corresponding relationship between tables and paragraphs, and reduces information chaos after chunking |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Covers the upload requirements of single large feasibility study reports or batch quarterly documents, and prevents parsing failures caused by oversized files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing time of complex multi-page PDF documents, and prevents parsing interruptions caused by timeouts |
chunkSettingMode | Manual configuration | Adjusts chunking parameters for different types of investment documents (such as approval-type and post-evaluation-type) to meet personalized parsing needs |
Three common configuration errors
- A 404 error appears on the parsing node after a file is uploaded via the front end. The cause is an incorrect file storage path configuration in the server environment, which prevents the parsing node from accessing the locally uploaded file address. This differs from normal parsing in local environments.
- Specified response fields cannot be extracted from PDF document parsing results. The cause is that the
customPdfParseconfiguration is not enabled, or the used model version is incompatible with the structured parsing logic, leading to failed field extraction. - Knowledge base retrieval results only return main content, and do not include chapter title information. The cause is that title context is not retained during chunking, or the
chunkSplitterconfiguration does not associate titles with main text, preventing retrieval from linking auxiliary information at the chapter dimension.
How to verify correct configuration
- Upload a single 100MB PDF feasibility study report, check if parsing completes within a reasonable time frame in the FastGPT v4.17.0 environment, and confirm the
PARSE_FILE_TIMEOUT_SECONDSconfiguration matches current parsing time. - Extract parsed chunked content, verify that key fields such as project numbers and chapter titles are included, and confirm the
customPdfParseconfiguration is active. - Upload multiple quarterly updated investment documents, check the success rate of batch parsing, and confirm the
UPLOAD_FILE_MAX_SIZEconfiguration covers current file size limits. - Simulate a ledger summary scenario, retrieve chunked content, confirm that the association between chapter titles and main text is retained, and validate the reasonableness of the
chunkSplitterconfiguration.
The values provided are common starting points, and should be evaluated against the user'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.