What Data for This Category Looks Like
Aviation and airport research report data mainly comes from brokerage industry research reports, Civil Aviation Administration monthly operation briefings, airport annual/half-year financial reports, and temporary industry policy announcements. Update cycles cover three categories: monthly (operation data), quarterly (industry tracking reports), and annual (financial reports and in-depth analysis).
Document structures typically include core operation indicators (flight sorties, passenger throughput, cargo and mail throughput), financial details, industry trend analysis, policy impact interpretation and other modules. Most fields have clear units such as "person-times", "tons", "sorties". Some reports use table formats to present structured data.
Constraints for Document Parsing and Chunking
Structured data in aviation and airport research reports is dense and includes fixed units. When chunking, ensure complete association between fields and units to avoid splitting that damages data readability.
Reports alternate between long chapter analyses and short module data. Some annual collection reports can reach hundreds of megabytes in size, which imposes requirements on parsing efficiency.
Different types of reports (monthly briefings, in-depth research reports) have large structural differences. Parsing logic adapts to multiple document categories. Frequently updated data demands sufficient response speed from the parsing process, to avoid delays that affect retrieval timeliness.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_CHUNK_SIZE | 800–1200 characters | Aviation and airport research reports contain dense structured operation fields. Chunking that is too long will lose contextual association, while chunking that is too short will break the binding relationship between data and units |
PARSE_CHUNK_OVERLAP | 150–200 characters | Ensures continuity of cross-chunk fields, units, and analysis logic, avoiding data gaps after chunking |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the size limit of some airport annual financial reports and multi-issue research report collections |
CUSTOM_SEPARATOR | ["Chapter X", "[Operation Data]", "Unit:", "\n\n"] | Matches the chapter and data module separation identifiers in aviation and airport research reports, enabling precise chunking |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Avoids timeout interruptions during large file parsing |
ENABLE_AUTO_TABLE_PARSE | Enabled | Automatically parses structured tables in research reports, preserving complete association between fields and units |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Issue: Word or PDF files larger than 10 MB take more than 10 minutes to parse and return a 504 timeout status code. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout for version v4.8.12-alpha is only 300 seconds, which is insufficient for large file parsing. - Issue: Airport operation data imported from Excel is merged into a single chunk, with each row of data not split. Cause:
CUSTOM_SEPARATORwas not configured to adapt to line break separation, and the default chunking logic does not recognize table row separation identifiers. - Issue: A query that exactly matches the chunks in the knowledge base fails to retrieve the corresponding content. Cause:
SIMILARITY_THRESHOLDis set too high. Exact matching content fails to meet the threshold requirements due to minor format differences.
How to Confirm Proper Configuration
- Upload a single large file that matches the category characteristics, confirm that parsing completes within a reasonable duration with no timeout errors.
- Import an Excel file containing structured operation tables, confirm that each row of data in the chunk list is an independent entry.
- Enter a precise query that includes specific fields, confirm that the corresponding chunk is normally retrieved with no matching failures.
- Check the parsed chunk content, confirm that fields and units are not split apart.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.