What data looks like for this category
Civil aviation airport business process guidance data primarily comes from internal airport business manuals, check-in counter guidance documents, security check process specifications, temporary control notifications, and terminal navigation system data. Static business manual documents update quarterly or when major process adjustments occur. Flight status and temporary control notifications update in real time when events trigger.
Documents split by business scenario include fields such as scenario ID, applicable terminal number, process step sequence number, operation requirements, and compliance clauses. Terminal numbers use a three-digit numeric format. Step sequence numbers are integers. Operation requirements mark durations in minutes.
What constraints these characteristics impose on vector models and indexes
Static documents with low update frequency require indexes to support batch synchronization capabilities. Real-time data requires incremental indexing to ensure information timeliness.
Fields that classify documents by terminal and scenario require index configurations to use dimension-based chunked storage. This prevents invalid recall across terminals or scenarios.
The ordered nature of process steps requires that chunking does not disrupt operational logic continuity. This avoids splitting complete business processes.
Triggered updates for temporary notifications require indexes to support fast incremental update configurations. This allows synchronization of latest content without full reindexing.
How to set configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the single step group length of civil aviation business process documents, avoiding splitting complete operational logic |
| Overlap Length | 100–150 characters | Retains step connection information for adjacent chunks, preventing process steps from being truncated |
| Similarity Threshold | 0.75–0.85 | Adapts to precise recall needs for business handling scenarios, filtering irrelevant process guidance |
| Maximum Search Results per Request | Top 8 entries | Matches core demand volume when users handle business, avoiding excessive redundant results |
maxToken | 4000 characters | Adapts to average length of civil aviation business documents, ensuring complete recall of process information |
defaultToken | 1000 characters | Used as default chunking benchmark, compatible with process document formats across different terminals |
Three common configuration mistakes
- A 404 status code returns when configuring an external embedding model. Cause: The model's interface address and authentication parameters are not filled correctly, preventing connection to the target embedding service.
- After deploying a vector model on an ARM architecture device without a GPU, the model cannot be added to the platform. Cause: The model's CPU inference mode is not enabled, or a model image that only supports GPU is used.
- Retrieved business steps appear unconnected. Cause: Chunk length settings do not match civil aviation process document structure, splitting complete operational steps into multiple independent chunks and losing step connection logic.
How to confirm configurations are correct
- Upload a civil aviation airport business process document, run a chunk preview test, and check if chunked content retains complete operational steps without forced truncation.
- Initiate a simulated business query such as "How to handle transfer flight procedures", and verify if the number of retrieved results matches the maximum search results per request configuration.
- View vector model call logs, confirm each call's parameters match configured items with no abnormal errors.
- Test retrieval of process documents from different terminals, confirm results only return business guidance for the corresponding terminal with no irrelevant cross-terminal content.
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.