What the data for this category looks like
Aerospace equipment investment research data comes primarily from public military industry research reports, official model development announcements, avionics system standard documents, flight test data briefings, and supply chain supporting lists. Update cycles have periodic peaks tied to new model project initiation, flight testing, and formal approval milestones. Daily updates consist of small batches covering industry trends and standard revisions. Documents fall into three structural categories: structured parameter tables, long-form technical analysis, and subsystem specification descriptions. Most fields include dedicated units, such as maximum takeoff weight (kilograms), cruise Mach number, and engine thrust (kilonewtons). Some documents contain multi-page structured tables.
What constraints these characteristics impose on deployment and upgrade
The mixed structure and periodic update peaks of aerospace equipment investment research data create multiple constraints for deployment and upgrade workflows. Large structured parameter tables and long documents require longer parsing and vector generation times. Sufficient resource buffers must be reserved. Periodic bulk updates will cause sudden spikes in vector database write pressure. Upgrade operations must avoid peak windows to prevent service interruptions. Specialized terminology and dedicated units require parsing modules to adapt to custom rules. Vocabulary and unit recognition configurations must be updated synchronously during upgrades. Format differences across multiple data sources require preprocessing configurations during deployment to avoid subsequent parsing errors.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Aerospace equipment technical documents include long-form test analysis. Insufficient timeout settings will cause parsing failures |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Packaged files for complete aircraft parameter manuals and flight test data have large sizes. The upload limit must be adjusted to match |
maxContext | 8000–12000 characters | Aerospace equipment technical description texts are lengthy. A sufficient context window must cover full technical details to ensure retrieval accuracy |
Recall count | Top 8 entries | Investment research scenarios require balancing information comprehensiveness and inference efficiency. Too many results will increase latency |
Similarity threshold | Calibrated via actual testing | Semantic similarity of aerospace specialized terminology is high. Filtering standards must be adjusted based on test results |
RELOAD_KNOWLEDGE_INTERVAL | 3600 seconds | Bulk update peaks occur on an hourly basis. Regular reloads can adapt to dynamic update cycles |
The parameter values provided on this page are standard recommended starting points for configuration. Actual values are affected by material formats, data volumes, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Issue: An OOM error is returned when executing the
docker build -f ./projects/command. Cause: Insufficient memory allocated to the build container. Large aerospace technical documents increase the pressure of dependency loading and parsing preprocessing during the build process. - Issue: Local deployment cannot trigger web searches. Cause: The
ENABLE_WEB_SEARCHconfiguration item is not set totrue, and search source filtering rules for aerospace specialized information are not configured. - Issue: Knowledge base indexes are lost after upgrading from version 4.8.23 to 4.9. Cause: Metadata configurations of the original vector database were not exported before the upgrade, and changes to the vector index format in the new version were not adapted to.
How to confirm proper configuration
- Execute the
docker pscommand. Confirm that all service containers have a running status ofUpand have no abnormal restart records. - Upload an aerospace equipment complete aircraft parameter manual. Check that the parsing task status is
Successand the extracted structured fields include preset specialized parameter items. - Initiate a knowledge base retrieval test. Verify that the number of returned results matches the value set for the
Recall countconfiguration item. - Trigger a knowledge base reload task. Confirm that there are no parsing failed document records in the vector database update logs.
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.