Technical Documentation and API Q&A for Indigenous IT Ecosystem Replacement Adaptation: Document Parsing and Chunking

The data for this category primarily comes from existing enterprise system inventories, domestic hardware and software catalogs, documents generated

Data Profile for This Category

The data for this category primarily comes from existing enterprise system inventories, domestic hardware and software catalogs, documents generated in test environments, and publicly available manufacturer materials. Daily produced documents include adaptation inventories, compatibility test reports, migration plans, and issue logs. Data updates follow per-project or quarterly cycles, with documents within a single project adjusted dynamically alongside adaptation progress. Document structures include structured tables (such as columns for hardware/software model and compatibility level in adaptation inventories), long text paragraphs (such as migration step instructions), enumerated fields (such as compatibility status). There is no unified fixed unit format, and some fields are purely string types.

Constraints on Document Parsing and Chunking

Document types for indigenous IT ecosystem replacement adaptation are diverse and have inconsistent structures. This requires that the parsing and chunking process must not damage the integrity of original structured fields, and avoid splitting key information such as hardware/software models and version numbers in adaptation inventories. Decentralized data sources lead to differences in import formats, so support for multiple document formats including PDF, Word, and Excel is required. Single-project data volumes are large, so the parsing process must support large file processing to avoid parsing interruptions caused by oversized files. In addition, domestic hardware and software have specific naming rules, and these naming conventions must be preserved during chunking to prevent splitting that would cause compatibility verification failures.

Configuration Recommendations

The following configuration items are defined based on the rules of FastGPT v4.17.0.

Configuration ItemRecommended SettingRationale
chunkSize800–1200 charactersPreserve the integrity of long text fields in indigenous IT adaptation documents, avoid splitting key steps in migration plans
chunkSplitterBy paragraph + title anchorAdapt to the structured formats of adaptation inventories and compatibility test reports, prevent splitting table rows or title content
customPdfParseEnabledAdapt to the special layout of domestic hardware and software PDF documents, resolve native parsing error issues
UPLOAD_FILE_MAX_SIZE1000 MBSupport large-scale compatibility test reports for single-project bulk imports
PARSE_FILE_TIMEOUT_SECONDS600 secondsAdapt to the parsing time required for large documents, avoid task interruptions due to timeout
chunkSettingModeManual configurationAdjust chunking rules for different indigenous IT adaptation projects to adapt to document formats in specific scenarios

Three Common Misconfigurations

  • Issue: PDF parsing fails when calling the create file collection API without specifying the customPdfParse parameter. Cause: Custom PDF parsing for indigenous document special layouts was not enabled for the adaptation scenario.
  • Issue: HTTP call fails when storing variables output by FastGPT nodes in a Feishu multidimensional table, with a 400 status code returned. Cause: The request header and parameter format for the Feishu API were not correctly concatenated, and the variable field naming rules for the adaptation scenario were not matched.
  • Issue: After uploading multiple indigenous IT adaptation documents, parsed results cannot distinguish between source files. Cause: The configuration to retain document metadata during chunking was not enabled, resulting in loss of file identification fields after parsing.

How to Verify Proper Configuration

  • Upload a single indigenous IT adaptation PDF document, check whether the parsed chunks retain the integrity of key fields such as hardware/software models and version numbers.
  • Call the create file collection API with the customPdfParse parameter, verify that the returned status code is 200 and there are no parsing error logs.
  • Upload multiple indigenous IT adaptation documents in different formats, check whether the parsed results include corresponding file metadata fields for distinguishing sources.
  • Wait for the parsing task to complete, confirm that the elapsed time does not exceed the duration set by PARSE_FILE_TIMEOUT_SECONDS, and there are no timeout interruption prompts.

The values provided here are common starting points and should be evaluated against the reader's own sample documents.

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.