What the data for this category looks like
Civil aviation airport service inquiry data draws from official airport customer service script libraries, real-time flight dispatch systems, terminal service guidance documents, and security check and boarding process specifications. Data update cycles fall into three categories: real-time synchronization for flight dynamic data, quarterly updates for routine service scripts, and immediate synchronization for temporary policy adjustments. Documents are grouped by scenario into modules such as flight delays, baggage check-in, boarding guidance, and special passenger services. Each module includes fields including question keywords, standard replies, effective time, applicable terminals and routes, and more. Reply texts are primarily natural language, with some containing standardized fields such as flight numbers and terminal IDs.
What constraints these characteristics impose on the model access and configuration link
Real-time flight dynamic data updates require model calls to control response latency, preventing delayed replies that harm user experience. The multi-scenario modular knowledge base structure requires configuring sufficient context capacity to splice cross-linkage inquiry information. The effective time and applicable scope fields require the model to match the current time and the user's terminal when generating replies, so trigger conditions for tool calls must be clearly defined. Additionally, the format requirements for standardized fields require ensuring unified input and output formats during retrieval and call links to avoid call failures caused by format mismatches.
How to Configure the Settings
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the context splicing needs of multi-scenario airport service inquiries, accommodating cross-linkage question-answer pairs and real-time flight information |
maxTokens | 2000–3000 token | Ensures reply length covers complete process guidance or flight adjustment explanations, avoiding truncation of critical information |
quoteMaxToken | 1500 characters | Matches the average length of a single standard reply in the airport knowledge base, ensuring complete reference content without omission |
temperature | 0.1–0.3 | Maintains the rigor of service replies, avoiding personalized content that deviates from standard scripts |
toolChoice | auto | Automatically determines whether to call tools such as flight query and terminal guidance, adapting to dynamically changing inquiry scenarios |
AIPROXY_API_ENDPOINT | Fill in according to the private deployment environment | Adapts to the model call path, ensuring transmission security of sensitive airport service data |
Three Common Misconfigurations
- Phenomenon: A custom channel rerank service call returns a 400 status code with no valid results. Cause: The text format of the airport knowledge base does not match the input length required by the custom channel, leading to request interception.
- Phenomenon: The model reply truncates critical process information and fails to fully explain all requirements for baggage check-in. Cause: The
maxTokensvalue is too small and does not cover the complete content of airport service guidance. - Phenomenon: Outdated security check policy content appears in replies. Cause: Real-time policy data in the vector database is not updated regularly, causing the model to call outdated knowledge base entries.
How to Verify Successful Configuration
- Submit test civil aviation service inquiry questions, and check whether the replies returned by the model match the currently effective knowledge base content and real-time flight information.
- View the model call logs in FastGPT v4.17.0, confirm that the actual usage values of
maxContextandmaxTokensdo not exceed the configured limits, and there are no truncation prompts. - Test the custom channel rerank service call, confirm that the number of returned results meets expectations, and there are no 400-level errors.
- Verify the sensitive word filtering function: submit test questions containing sensitive words from airport scenarios, and confirm that the content is correctly intercepted or replaced.
The values provided are common starting points and should be validated against local test 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.