What the data for this category looks like
Data primarily comes from official attraction announcement systems, ticket management backends, tourist service feedback repositories, and surrounding supporting business APIs. This differs from financial category data, which focuses on product holdings and transaction records. Update frequency is adjusted based on passenger flow cycles: updates are frequent during holidays and event preparation periods, and stable during regular daily cycles. Most documents are a mix of structured and semi-structured data, including fields such as attraction name, opening hours, ticket pricing, event details, tour routes, and real-time passenger flow alerts. Units include person-times, yuan, hours, kilometers, etc. The field structure has notable differences from other categories in the same business direction.
What constraints these characteristics impose on model integration and configuration
The multi-source heterogeneous nature of attraction data requires configuring multi-channel access adaptation rules. Connections must be made to multiple APIs including ticketing, passenger flow, and event systems, which differs from the single data source adaptation logic used for financial categories. The high-frequency update characteristic requires configuring real-time or near-real-time data synchronization parameters to avoid delays in marketing content. Product data for financial categories typically has a fixed update frequency, so frequent adjustments to synchronization cycles are unnecessary. Fields include specific units such as person-times and yuan, so field mapping verification rules must be configured to ensure parameter units match during model calls. Field units for financial categories mostly include metrics such as yield rate and monetary amount, so the mapping rule logic is different. Semi-structured event announcements and tour documents require configuring text parsing parameters that support mixed formats to ensure accuracy of content extraction.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
stream mode toggle | Enabled | Tourist attraction marketing content often requires real-time generation of event notifications and passenger flow broadcasts. Stream mode enables segmented content output, which improves user reception experience |
maxContext | 8000–12000 characters | Attraction data includes multiple sections of event details and tour routes. A longer context ensures the model-generated content covers all complete information |
requestTimeout | 30–60 seconds | Real-time passenger flow data APIs for attractions may experience network delays. A longer timeout prevents call failures due to temporary network fluctuations |
apiRetryCount | 2–3 times | Intranet or third-party ticketing APIs occasionally experience fluctuations. Limited retries improve call success rates and avoid frequent errors disrupting marketing content generation |
fieldMappingRule | Map according to preset attraction fields | Attraction data fields include exclusive units and identifiers. Mapping according to preset rules ensures accurate parameter matching during model calls |
dataSyncInterval | 15 minutes (event period) / 1 hour (regular period) | Adapts to the attraction's update rhythm. High-frequency synchronization during event periods ensures content timeliness, while reducing synchronization frequency during regular periods saves resources |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Enabling the
stream mode togglebut failing to obtain segmented output content. The cause is that the stream-compatible parameter was not simultaneously enabled in the model channel configuration, resulting in a mismatched interface return format. - Receiving a 304 status code when switching model channels locally. The cause is that local cache stores old model configuration information, and no new interface request verification is triggered.
- Receiving an "data acquisition exception" error when calling the model. The cause is that no proxy or whitelist allowance rules were configured for the intranet environment, preventing access to the intranet-deployed large model API.
How to confirm successful configuration
- Manually trigger a model call, and check if the returned content includes attraction-specific fields and units to verify that the field mapping configuration is effective.
- View the model call logs to confirm that the returned content is segmented streaming output when stream mode is enabled, with no complete packet delay issues.
- Test cross-server model interface connectivity in the intranet environment to confirm that there are no firewall or routing interceptions causing call failures.
- Adjust the data synchronization interval parameter, observe the backend data update logs, and confirm that the synchronization frequency matches the preset attraction update rhythm.
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.