What Does Data for This Category Look Like?
Communication towers and infrastructure document data comes from four main sources: operation and maintenance inspection records, project completion documents, daily maintenance ledgers, and industry standard documents. Data update frequency aligns with business nodes. Inspection reports are updated monthly. Completion documents are updated when projects are delivered. Ledger data is adjusted in real time alongside maintenance actions. Document formats include structured table ledgers, long-text fault analysis reports, and design specification PDFs with embedded formulas. Common fields include tower height (unit: meters), longitude and latitude coordinates, inspection date, fault type, and resistance value (unit: megaohms). Some documents contain nested tables and formulas.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking?
The document characteristics of communication towers and infrastructure create multiple constraints for parsing and chunking. For structured ledger tables with nested content and field correspondences, chunking must preserve full table integrity. It must not split associated data across cells. Long-text fault analysis reports have coherent paragraph logic. Splitting must not separate key fault judgments and handling measures into separate chunks. Design documents with engineering formulas and unit labels require accurate identification of formulas and units. This prevents loss of unit information after parsing. Layout differences across multi-source documents require parsing to support multiple formats. It also requires controlling individual chunk lengths to fit subsequent processing needs.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the length of long paragraphs and table blocks in communication tower documents, avoiding splitting critical associated content |
chunkSplitter | Split by paragraph + heading | Matches the heading hierarchy of inspection reports and fault documents, retaining contextual logic |
customPdfParse | Enable Marker parsing mode | Accurately identifies engineering formulas and tables in PDFs, resolving issues of lost unit and formula information during parsing |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the parsing duration of large completion documents, preventing timeout interruptions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch uploads of large project completion PDFs and multi-page inspection ledgers |
chunkSettingMode | Manual mode | Adjusts chunking parameters for different document types (ledgers, reports, specifications) to fit scenario requirements |
Three Common Misconfigurations
- Timeout errors with 504 status codes occur after uploading large completion PDFs. The cause is failure to adjust
PARSE_FILE_TIMEOUT_SECONDSto a duration suitable for large documents. The default timeout is insufficient to complete parsing of multi-page complex documents. - Chunk previews of inspection ledger PDFs in the knowledge base fail to return file content. The cause is failure to enable the Marker parsing mode for
customPdfParse. The default parsing cannot recognize structured tables and nested fields, leading to parsing failure. - Local deployment instances cannot return engineering formula parsing results normally. The cause is a mismatch between the deployed FastGPT version and the Marker parsing image version. Older image versions do not support the formula recognition logic of the new document parsing feature.
How to Confirm Proper Configuration
FastGPT v4.17.0 is the recommended deployment version for this scenario. Use these steps to check configuration effects:
- Upload a communication tower design specification PDF that includes engineering formulas. Confirm the parsed text retains formulas and unit labels.
- Upload a single completion document larger than 500 MB. Confirm no timeout error occurs during parsing.
- Select a structured inspection ledger PDF. Check that the chunk preview preserves complete table cells and their corresponding fields.
- Switch between different document types: inspection reports, ledgers, and specifications. Verify the chunking logic adapts to each document’s structure.
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.