What this category’s data looks like
Civil aviation airport ledger data comes from multiple internal business systems including flight support, equipment maintenance, security clearance, and standard documents required for civil aviation industry regulatory reporting. Data updates follow business cycles. Corresponding ledgers are generated after each single flight support. Daily summaries of that day’s operational data form daily reports. Document formats include PDF operational reports, Excel equipment ledgers, Feishu multi-dimensional table scheduling sheets, and other multi-source formats. Fields include flight number, takeoff and landing time, support duration, equipment number, maintenance status, and more. Units include business-specific ones such as minutes, flight sorties, and equipment counts.
What constraints do these characteristics impose on the document parsing and chunking step
Multi-source and heterogeneous document formats require the parsing process to support PDF, Excel, Feishu multi-dimensional tables, and other formats. This prevents loss of business fields due to format incompatibility. Business-specific fields and units require retaining field association logic during chunking. This avoids splitting continuous content across flight numbers or support durations, ensuring data can be linked during subsequent summarization. The periodic data update feature requires the parsing process to support incremental identification of already processed documents. This reduces redundant calculations. The content structure that combines long-text maintenance logs and short-item scheduling sheets requires chunking strategies to balance retaining long paragraphs and preserving short-item integrity. This prevents excessive splitting or merging of content.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the structure of civil aviation ledgers that combine long maintenance logs and short business entries, avoids splitting cross-field content, and controls semantic integrity of embedding vectors |
chunkSplitter | Paragraph + custom delimiter | Based on the feature that ledger documents contain fixed field delimiters such as "Flight Number:" and "Support Duration:", prioritize splitting by paragraph while retaining field associations, to avoid cross-field chunking |
customPdfParse | Enabled | Adapts to the fixed template format of civil aviation regulatory reporting PDFs, extracts specified fields via custom parsing rules, and prevents generic parsing from losing business-specific content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Addresses parsing time for single large airport maintenance ledger PDFs, ensures large file parsing does not interrupt mid-process |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to large equipment log packages uploaded in batches for airport maintenance ledgers, meets upload requirements for batch summarization of multiple documents |
chunkSettingMode | Manual configuration | For the multi-source and heterogeneous characteristics of civil aviation ledgers, manually adjust chunking parameters to adapt to parsing needs of different format documents |
Three Common Mistakes
- Symptom: When multiple ledger documents are passed when calling the chat interface, only some documents are parsed. Cause: The file ID array is not correctly nested in the array structure of the content field, so the interface cannot recognize all uploaded files.
Reference only; verify against the target FastGPT release and deployment documentation.
- Symptom: Mismatches appear between support duration fields and flight numbers after ledger summarization. Cause: Field association logic is not retained during chunking, and continuous paragraphs containing "Flight Number: XXXXX Support Duration: XX minutes" are split, leading to semantic breaks.
How to confirm configurations are properly set
- Upload a single civil aviation maintenance ledger PDF, check if the parsed text retains exclusive fields such as flight number and support duration, with no missing content or garbled text.
- Call the document parsing API, pass multiple ledger files in different formats, confirm that all files are successfully parsed and corresponding chunks are generated.
- Adjust the
chunkSizeparameter, compare the parsed chunk content, confirm that no cross-business field splitting occurs. - Check backend logs, confirm that no exception errors are triggered by parsing timeouts or file size limits.
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.