What data looks like for this use case
Typical users of this use case are implementation consultants, test managers, and customer business representatives. Daily processed documents include UAT test cases, acceptance issue tickets, acceptance reports, and signed confirmation forms. Data sources cover requirement specification documents, test environment configurations, customer business samples, and defect management systems. Updates occur once per phase or version. Documents contain structured fields. For example, UAT test cases have test steps and expected results. Acceptance issue tickets have issue numbers and severity levels. Signed confirmation forms include confirmer and date fields. Units vary flexibly based on document scenario.
What constraints do these characteristics impose on document parsing and chunking
Multi-source heterogeneous data sources require the parsing step to support multiple formats and structured content. It must avoid breaking field associations between documents. The phase-based update requirement means the chunking logic must adapt to document version changes. It must ensure chunking consistency across the same scenario. Document structures vary widely. UAT test cases are divided by test scenario paragraphs. Acceptance issue tickets have large amounts of tabular content. Field associations must be preserved. Otherwise, subsequent issue reproduction and acceptance confirmation may be affected. This can lead to acceptance delays or scope disputes.
How to set configurations
Based on FastGPT v4.17.0, the following configuration items and recommendations apply:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the paragraph length of UAT test cases and acceptance reports, avoids splitting individual test steps or related issue content |
chunkSplitter | Split by paragraph | Matches the test scenario paragraph structure of UAT test cases, preserves business context integrity |
customPdfParse | Enabled | Adapts to PDF format documents such as signed confirmation forms, preserves text association information in signature areas |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers parsing time for large acceptance reports, avoids parsing failures due to timeouts |
chunkSettingMode | Manual configuration | Adapts to different types of UAT documents, allows flexible adjustment of chunking parameters to match document structures |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports upload of large batch acceptance documents, aligns with phase delivery document volumes |
Three common configuration mistakes
- Symptom: Text is missing from parsed signed confirmation form PDFs, and the interface shows parsing failure. Cause: The
customPdfParseconfiguration is not enabled, so basic parsing cannot extract signature area and associated text from PDFs. - Symptom: Tabular data in UAT test cases cannot be indexed by multiple vectors, and no matching results appear during searches. Cause: Table multi-vector support is not enabled, so structured tabular content is not properly split and associated.
- Symptom: Fields returned are empty when pulling multi-dimensional table data from a Chinese enterprise collaboration platform via API. Cause:
chunkSettingModeis not configured to adapt to field associations in structured multi-dimensional tables, so data is not properly parsed.
How to confirm configurations are correctly set
- Upload a single UAT test case PDF. Check that the parsed text fully retains test steps and expected result fields.
- Navigate to the knowledge base settings page. Verify that parameters such as
customPdfParseandchunkSizeare configured per the recommended values. - Initiate an API pull test. Confirm that field data from multi-dimensional tables is correctly returned and indexed.
- Upload an acceptance report larger than the default size. Confirm that the upload succeeds and parsing completes without timeout errors.
The values listed 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.