Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this use case looks like
The data sources for civil aviation airport business process guidance primarily come from internal airport operation systems, airline collaboration platforms, and public travel service databases. Data is split into two categories: flight dynamic data that is synchronized in real time, and business process rule data that is updated daily.
Document structures include structured fields and unstructured guidance scripts. Structured fields cover flight number, takeoff and landing time, terminal, counter number, security check lane, boarding gate, and more. Unstructured content consists of standard guidance scripts for each process step.
Field unit specifications are unified as follows: time uses the 24-hour format, identifiers are pure numbers or letter combinations, and duration uses minutes as the unit.
What constraints these characteristics impose on the model integration and configuration link
Real-time updates for flight dynamic data require that the synchronization delay of the model-integrated data source is maintained within a reasonable range. Otherwise, guidance information will lag behind actual business status.
The large number of structured fields and standardized units require model configuration to support accurate structured data extraction and matching, to avoid generating incorrect process guidance.
The daily update rhythm of business rules requires the knowledge base synchronization cycle to align with this schedule, to prevent the use of expired process data.
The collaborative needs of multi-source system data require configuring a unified call entry, to avoid fragmentation of business data across different process links.
How to set the configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Airport business processes include multi-link flight, counter, and lane information; sufficient context must be retained to ensure coherent guidance logic |
maxTokens | 4000 token | The output of a single business guidance must be controlled in length to avoid exceeding interface display limits, while adapting to the processing upper limit of real-time data |
quoteMaxToken | 2000–3000 characters | The length of flight data and counter location information that needs to be referenced is limited; this ensures referenced content is complete without occupying main context space |
temperature | 0.1–0.3 | Business process guidance requires accuracy and rigor to avoid generating misleading process information |
AIPROXY_API_ENDPOINT | Airport-exclusive internal proxy address | Ensures the security of sensitive business information transmission and avoids data leaks |
AIPROXY_API_TOKEN | Exclusive token generated by airport operation and maintenance | Restricts unauthorized model calls to ensure system operation security |
Three common configuration mistakes
- An error is returned when uploading some flight boarding pass or security credential images, while some images are recognized normally. Cause: The image processing threshold for the
visionparameter is not adapted, and token consumption and processing logic for different resolution images are not differentiated. - An image upload error still occurs after configuring a large
maxTokensparameter. Cause: The consumption upper limit of text tokens and image tokens is not differentiated, and token occupancy for image processing is not separately restricted. - Generated business guidance does not match real-time flight data. Cause: The knowledge base synchronization cycle is not aligned with the update rhythm of flight data, and expired process rules are used.
How to confirm the configuration is complete
- Trigger a check-in process guidance request, verify whether the flight information included in the returned content matches real-time system data, and adjust the data source synchronization configuration until the match is achieved.
- Upload business credential images of different resolutions, confirm that the recognition results have no errors and field extraction is complete, and adjust
vision-related configurations until all test images can be processed normally. - Test guidance requests for different flight time periods, verify that the generated process steps are consistent with current airport business rules, and adjust the knowledge base synchronization cycle until it meets the update rhythm.
- View model call logs, confirm that all call records for
AIPROXY_API_TOKENare authorized requests, with no unauthorized access records.
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.