What this type of data looks like
Aviation airport investment research data sources include public statistical reports from civil aviation regional administrations, official airport operation ledgers, announcements from air traffic control departments, and public industry research reports. Update cadences vary by data type: flight schedules are updated quarterly, takeoff and landing volumes and passenger throughput are updated daily, and temporary control information is pushed in real time. Document structures include structured daily or monthly operation reports with fielded data, semi-structured policy announcement documents, and unstructured industry analysis manuscripts. Fields and units are as follows: takeoff and landing sorties use sorties as the unit, passenger throughput uses person-times, air traffic control altitude uses meters, and flight times use hours and minutes.
What constraints do these characteristics impose on context and token processing
The multi-source, variable-update cadence characteristics of aviation airport investment research data impose multiple constraints on context and token processing. Field differences across multi-source structured reports must be unified mapped. Otherwise, retrieved context token formats will be chaotic, increasing invalid token consumption. Real-time control information has timeliness requirements for short context windows. Caching for too long will cause information to expire. When splitting long policy announcement documents, field associations must be retained. Excessive token compression will lose the correspondence between professional terms and airspace data. Frequently updated daily data will increase the number of retrieved context fragments. If the number of retrieved entries is not limited, context window tokens will be quickly exhausted.
How to set configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8192–16384 token | Aviation airport investment research data includes multi-source structured reports and real-time control information. A sufficiently large window is required to accommodate multiple sets of retrieved valid data |
chunkSize | 1024–2048 characters | Single records of aviation airport operation reports are moderately long. Overly long segments will destroy field associations, while overly short segments will increase invalid token overhead |
recallTopK | Top 3–5 entries | Valid investment research information from multi-source data is concentrated in the top 3-5 retrieved results. Too many results will exceed the context window limit |
similarityThreshold | 0.65–0.75 | A high proportion of aviation-specific terminology requires filtering low-correlation retrieved content to avoid invalid token consumption |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large monthly operation reports takes a relatively long time. This prevents task interruptions due to timeout |
chunkOverlap | 128 characters | Retain overlapping content during segmentation to avoid losing field association logic in split context |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing against local samples is recommended before finalizing settings.
Three common configuration mistakes
- Symptom: An API call returns a
401 Unauthorizederror, or the interface promptsACCESS_TOKEN invalid. Cause: A third-party service provider's API key was incorrectly entered into theACCESS_TOKENconfiguration item, and it is not bound to the large model service currently in use. - Symptom: Total token consumption exceeds expectations after multi-model orchestration in a workflow, or token limit errors are triggered in a single round of dialogue. Cause: No context sharing rules are configured, causing multiple model nodes to independently occupy token windows without merging valid context content.
- Symptom: Retry limit truncated errors are triggered when parsing large monthly operation reports, and logs show
Reached the max retries p. Cause: Segmentation length is set too small, leading to too many split fragments that exceed the parsing retry limit, orPARSE_FILE_TIMEOUT_SECONDSis not adjusted to adapt to long document parsing.
How to confirm the configuration is correct
- A standard monthly aviation airport operation report is uploaded, and parsed segment results are checked to confirm segment length meets configuration requirements and does not destroy field association logic.
- A targeted investment research dialogue is initiated, and the context retrieval list is checked to confirm the number of retrieved entries does not exceed the configured upper limit range.
- The
ACCESS_TOKENconfiguration item is checked to confirm it matches the key bound to the currently invoked large model service. - A multi-model orchestration workflow is run, and token consumption statistics are checked to confirm no single node independently occupies the entire context window.
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.