What Data for This Category Looks Like
Aerospace equipment research report sources include professional defense and aerospace industry research institutions, public project reports from aerospace institutes, and official model test announcement documents. Update frequency fluctuates with model development milestones. Concentrated updates occur at critical milestones such as final assembly and pre-launch. Daily updates primarily consist of quarterly or semi-annual industry review documents. Emergency task-related research reports are released on an ad-hoc basis.
Document structure includes a cover page with model code and issuing institution, a core performance parameter section with fields like thrust, orbital altitude, and payload weight (units typically include kilonewtons, kilometers, and tons), a progress node description, a risk assessment module. Some documents include test data numbers as unique identifiers.
Constraints These Characteristics Impose on Citation Source and Traceability
The multi-source, dispersed nature of aerospace equipment research reports requires traceability systems to connect content across multiple independent knowledge bases, avoiding information gaps from single data sources. Irregular release cycles mean traceability processes must adapt to non-periodic document ingestion, and cannot rely on fixed-schedule synchronization logic.
Documents contain unique identifier fields such as model numbers and test data numbers. Traceability usually uses these fields as anchor points; relying solely on file names or issuing institutions can lead to parameter confusion between different models in the same category.
Long paragraphs of parameter descriptions and test data require that document splitting preserves the binding relationship between parameters and their context. Without this, traceability cannot locate the specific source paragraph for a parameter.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_top_k | Top 8 entries | Aerospace equipment research reports have high precision requirements for parameters. Too many recall results will introduce irrelevant model data, while too few will miss critical traceability information |
similarity_threshold | 0.75–0.85 | Parameter descriptions in aerospace equipment research reports are rigorous. A threshold that is too low will introduce content from non-corresponding models, while a threshold that is too high will miss traceability documents with high relevance |
chunk_max_length | 1000–1200 characters | Aerospace equipment research reports include long paragraphs of parameter descriptions and test data. Splitting chunks that are too long will break the binding between parameters and their context, while chunks that are too short will lose associated information required for traceability |
source_field_extract | Extract issuing institution, model number, release date | The unique identifier for aerospace equipment research reports is the model number. These fields should be used as traceability anchor points, and should not rely solely on file names |
sync_mode | Incremental sync (by release date) | Aerospace equipment research reports have no fixed update cycle. Syncing by release date avoids repeatedly pulling old documents, while ensuring the latest model research reports are ingested in a timely manner |
rag_cite_enable | Enabled | Decision-making related to aerospace equipment requires clear traceability basis. When enabled, it can directly associate recalled chunks with their original documents and paragraph locations |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: Non-corresponding aerospace equipment parameter values appear in retrieval results, and traceability information shows association with incorrect research report documents. Cause: No reasonable range is set for
similarity_threshold, orsource_field_extractis not enabled to extract model numbers as filtering conditions, leading to recall results mixing content from different models in the same category. - Phenomenon: The citation source field returned by the knowledge base search module is empty, and traceability cannot be completed. Cause: The
source_field_extractparameter is not configured, and no traceability fields to extract are specified, leading the system to fail to generate valid citation anchor points. - Phenomenon: Disk usage for locally deployed FastGPT continues to grow beyond expected levels. Cause: Reasonable values for
chunk_max_lengthandrecall_top_kare not configured, or document deduplication is not enabled, leading to excessive redundant storage of original files, split chunks, and embedding vectors.
How to Confirm Proper Configuration
- Enter the model number of a specific aerospace equipment as a retrieval keyword, verify that all recalled result documents include this model number, and that the citation source field displays the correct issuing institution and release date.
- Check the knowledge base sync logs, confirm that only research report documents within the specified date range have been added, with no records of repeated syncing of old documents.
- Search for queries that include core parameters, verify that the returned results include the original document's paragraph location and file name, with direct access to the corresponding document.
- Check the disk usage monitoring dashboard, confirm that the storage volume for newly added documents matches expectations, with no abnormal growth.
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.