What This Category’s Data Looks Like
Data for aerospace equipment research reports comes primarily from securities firms’ military industry research reports, public materials from national defense and military industry associations, and publicly disclosed information from main aircraft manufacturers and supporting suppliers. Update cycles include regular quarterly and annual industry review reports, plus ad-hoc special reports issued when major models are finalized, air shows are held, or policies are released. Document structures typically include modules such as overall industry trends, core model parameters, industrial chain supporting details, market size estimates, and risk warnings. Fields include model codes, delivery cycles, production capacity scales, supporting manufacturer names, revenue estimates, and more. Units include units such as aircraft, years, and 100 million yuan.
Constraints on Knowledge Base Retrieval and Recall
The multi-source nature and irregular update cycle of aerospace equipment research reports require the knowledge base retrieval system to support incremental synchronization and rapid access to ad-hoc reports, to avoid missing updates on the latest model dynamics. Complex document structures and long lengths require that core fields such as model codes and production capacity data are fully retained during segment parsing, to avoid truncation of critical information. The need for precise matching of specific fields such as supporting manufacturers and delivery cycles requires prioritizing entity recognition-based associated recall, to avoid matching errors that occur with full-text keyword matching alone. The clear unit system for industry data requires retaining original unit annotations in recall results, to avoid confusion over parameter calibers across different models.
Configuration Settings
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
PARSE_CHUNK_SIZE | 800–1200 characters | Aerospace equipment research reports contain long paragraphs of industry data and model parameters. This range retains the integrity of core fields and avoids truncation of critical parameters |
RECALL_TOP_K | 8–12 entries | Core information for aerospace equipment research reports is scattered across multiple paragraphs. This range covers all industrial chain-related content while avoiding redundant results |
SIMILARITY_THRESHOLD | 0.72–0.85 | Precise matching of specific entities such as model codes and delivery cycles is required. This range filters irrelevant results while retaining relevant content |
UPLOAD_FILE_MAX_SIZE | 200 MB | Single aerospace equipment research reports may contain multiple pages of charts and detailed data. This range supports uploads of large file sizes |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large research reports takes extended time. This range avoids parsing failures caused by premature timeout |
RERANK_TOP_N | 3–5 entries | Reranking filters redundant results from initial recall, retaining the most relevant research report fragments for user queries |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Retrieval results only return 1 entry, failing to cover all relevant research reports. This occurs when
RECALL_TOP_Kis set to 1, which does not match the scattered core information characteristic of aerospace equipment research reports. - Knowledge base access speed is excessively slow. This occurs when
UPLOAD_FILE_MAX_SIZEis set too large and incremental update is not enabled, causing excessive redundant files to be loaded during each retrieval. - Research report images returned in Q&A fail to render properly. This occurs when the
ENABLE_PARSE_IMAGEparameter is not enabled, causing image links or embedded identifiers to not be extracted during the parsing phase.
How to Verify Proper Configuration
- Upload a typical aerospace equipment research report, and check that parsed text segments retain core fields such as model codes and production capacity data without obvious truncation.
- Enter precise queries such as "XX model delivery cycle", and verify that the number of recall results and similarity scores match the preset configuration.
- Upload a research report containing images, and confirm that parsed image content can be displayed normally during Q&A.
- Simulate batch retrieval requests, and confirm that system response has no obvious abnormal delays.
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.