Ledger Summary and Report Generation for Land Pre-examination and Planning Permits: Document Parsing and Chunking

Ledger Summary and Report Generation for Land Pre-examination and Planning Permits: Document Parsing and Chunking

What This Category of Data Looks Like

Data sources for this category include the national land and spatial planning one-map system, project approval and supervision platform, land use status database, and ecological protection redline data. Update frequency is irregular. Commonly processed documents include land pre-examination and site selection opinions, construction land planning permits, construction engineering planning permits, redline diagrams, and planning conditions. Most documents contain fields such as project name, land location, land scale, planning control indicators, and redline coordinates. Units include hectares, square meters, and others. Some redline diagrams are in vector format, and planning condition documents include pre-approval requirements coordinated across multiple departments.

Decentralized data sources lead to inconsistent document formats. Vector redline diagrams and text-based approval documents are mixed, so parsing workflows must support rules for multiple document types. The irregular update frequency requires parsing workflows to support incremental synchronization, avoiding repeated processing of full historical datasets. Fields include spatial coordinates and text indicators. Chunking must preserve field relationships, avoiding splitting that breaks the integrity of core business information such as project site selection and land scale. Cross-departmental collaborative content in pre-approval requirements must be accurately extracted. Chunk boundaries must avoid cross-departmental logical nodes, preventing parsed results from splitting business connections. Some documents have digital signatures. Parsing workflows must skip signature verification interference to ensure complete content extraction.

Configuration Settings

Reference only; verify against the target FastGPT release and deployment documentation.

Configuration ItemRecommended ValueRationale
chunkSize800–1200 charactersAdapts to the mixed structure of spatial coordinates and text indicators in this category of documents, avoiding splitting that breaks the relationships of core business fields
chunkSplitterSplit by semantic paragraphsMatches the chapter logic of planning documents, preserving the integrity of modules such as pre-approval and land indicators
customPdfParseEnable digital signature compatibility modeAdapts to approval documents with digital signatures, resolving issues where content recognition fails due to signatures
UPLOAD_FILE_MAX_SIZE100 MBAdapts to the upload requirements of vector files such as redline diagrams, preventing upload failures for large files
PARSE_FILE_TIMEOUT_SECONDS600 secondsAddresses parsing time for large redline diagrams or multi-page planning condition documents, preventing timeout interruptions
chunkSettingModeManual configurationSupports adjusting chunking rules for different document types (text/vector), adapting to the diverse document formats within this category

Three Common Mistakes

  • Symptom: When calling the Doc2x tool to parse a file, a read failure error is returned, with the error message truncated to "Only support .txt, .m". Cause: The compatibility rules for customPdfParse are not configured correctly, preventing PDF files with digital signatures or non-standard format files from being recognized.
  • Symptom: Uploaded land redline diagrams have no coordinate field content after parsing. Cause: The chunkSize value is too small, splitting continuous text or vector metadata blocks that contain coordinate information.
  • Symptom: Duplicate project entries appear during ledger summary. Cause: The irregularly updated data characteristics are not adapted to, and duplicate approval document number fields are not filtered during chunking, leading to duplicate matching.

How to Verify Proper Configuration

  • Upload a land pre-examination opinion with a digital signature, check that the parsed result completely extracts core fields such as project name and land location, with no content truncation.
  • Upload a single redline diagram file under 100 MB, confirm that the upload and parsing processes have no timeout errors, and that the parsed result includes coordinate information.
  • Select multiple documents of different formats (text-based planning conditions, vector redline diagrams), switch to manual configuration via chunkSettingMode, and verify that the chunking results preserve the integrity of business logic.
  • Test batch uploading multiple approval files with irregular updates, confirm that the parsing process has no duplicate entries or missing fields.

The values provided are common starting points and should be evaluated against appropriate 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.