What the data for this use case looks like
Core data for the department budget preparation scenario originates from the budget management integrated system, department staff establishment system, prior year final accounts, project library, and Ministry of Finance budget preparation notices. The update frequency is annual centralized updates.
Daily processed documents include department budget drafts, project application forms, performance target forms, staff expense calculation forms, budget approval documents, and similar materials. These documents contain fields such as project codes, expense calculation details, staff establishment base, and performance target entries, with units including amount, number of people, and performance weight. A single complete document can have hundreds of pages.
Constraints for document parsing and chunking from these characteristics
Annual centralized updates create bulk large-volume document parsing demands during budget preparation season. Single documents have many pages and uneven structural complexity, ranging from plain text policy explanations to nested table detail data.
Document formats vary across sources. Some PDFs exported from systems have fixed headers and footers, while some documents have table layout offset issues. Core fields have strong correlations; parsing must retain the binding relationship between project codes and corresponding expenses, performance targets, otherwise the accuracy of subsequent service consultation and response will be affected.
In bulk parsing scenarios, adaptation to large file upload and parsing time limits is also required.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000–2000 MB | Adapt to full sets of department budget PDF files for batch parsing in a single batch, avoid file truncation during upload |
PARSE_FILE_TIMEOUT_SECONDS | 600–900 seconds | Cover the full parsing time for hundreds of pages of budget documents, avoid timeout errors during large file parsing |
chunkSplitter | Split by header/footer + table separators | Match the structured layout of budget documents, retain the association between project codes and corresponding details |
chunkSize | 800–1200 characters | Balance single-block information density and retrieval recall accuracy, adapt to long text paragraphs and table details in budget documents |
customPdfParse | Enable structured parsing mode | Extract table data and coding fields from budget documents, avoid loss of core business information during plain text parsing |
chunkSettingMode | Manual configuration mode | Adjust chunking parameters for different types of budget documents such as drafts and application forms to adapt to detailed business scenarios |
Three Common Misconfigurations
- Parsing errors occur when uploading hundreds of pages of department budget PDFs, while dozens of pages of documents parse normally. The cause is failure to adjust the values of
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDS, failing to adapt to the parsing requirements of large-volume budget documents. Cannot read properties of undefinederrors occur when deploying a third-party PDF parsing tool locally. The cause is not using FastGPT's built-incustomPdfParsefunction, instead using an older parsing tool with insufficient compatibility.- A large number of duplicate budget project entries appear in chunking results, and the number of recalled results does not meet expectations. The cause is failure to adjust
chunkSizeand chunk boundary settings based on the field density of budget documents, leading to chaotic chunk boundaries and excessive duplicate content.
How to Verify Proper Configuration
- Upload a single department budget PDF with more than 100 pages, check that the parsing task completes within the time limit set by
PARSE_FILE_TIMEOUT_SECONDS, with no timeout or out-of-memory errors. - View the parsed chunk content, confirm that core business fields such as project codes and expense amounts are fully retained, with no field loss or layout confusion.
- Batch upload multiple budget documents of different types, check that the
UPLOAD_FILE_MAX_SIZElimit adapts to the total file size, with no upload truncation issues. - Launch retrieval tests related to budget preparation, confirm that the recalled chunk content matches the business question, with no redundant or missing core information.
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 2026-09-28.