What the Data for This Category Looks Like
Data related to film theater revenue yield comes from domestic theater box office monitoring platforms and operational data reported by theater POS systems. There are two update schedules for this data:
- Full aggregated operational data for the previous day is compiled and updated each early morning.
- Incremental data for real-time box office fluctuations is pushed hourly.
Data is returned as a structured JSON array. Each entry includes fields such as unique theater identifier, film name, total daily revenue, scheduled showings, average per-venue attendance, and revenue sharing settlement base. Fields related to revenue sharing settlement adjust dynamically based on annual theater settlement policies, so no fixed static field list exists. Field units are yuan, showings, and individual attendees respectively.
Constraints for Tool Calling and Plugins Workflows
The dual update schedule for film theater data requires tool calling to distinguish trigger timing between full data pulls and incremental data pulls. This prevents duplicate pulls or missed fluctuation data.
The dynamically adjusting field structure requires plugins to support dynamic field mapping. Hardcoded field names cannot be used for data parsing.
The high-frequency update characteristic requires tool calling timeout settings to accommodate batch pull processing times. It also requires data deduplication using unique theater and film identifiers to avoid duplicate revenue yield calculations.
Additionally, revenue yield calculation requires linking multiple dimensions of data including box office, scheduled shows, and revenue sharing bases. The tool chain must connect data pulling, cleaning, and calculation steps. This imposes strict requirements on the sequential execution logic of tools.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
tool_sequence_trigger | Triggered by the data_ready field from the output of the preceding tool | Film theater data must execute in pull-clean-calculate order. The output of the preceding tool must be strictly bound as the trigger condition for subsequent tools. |
plugin_dynamic_field_mapping | Enabled | Revenue sharing fields for film theaters adjust dynamically based on settlement policies. Enabling this setting accommodates changes to returned fields. |
tool_request_timeout | 600 seconds | Pulling full national theater data requires processing batch requests across multiple theaters and films. 600 seconds covers response times for most APIs. |
tool_filter_params | Include cinema_id and film_id fields | Precise filtering of revenue yield data for target theaters and films avoids pulling redundant unrelated data. |
stream_tool_call_enabled | Enabled based on model support | Some models do not support non-streaming calls. Adjust configurations to match model capabilities to prevent unresponsive tool calls. |
tool_call_batch_size | 20-30 | Single-batch pulls of film theater data have large volume. 20-30 tool calls balances request latency and concurrency limits. |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: Three chained tools are configured, but only the first tool executes. Subsequent tools do not respond. Cause: The
tool_sequence_triggerparameter is not set correctly. The output of the preceding tool is not bound as a trigger condition, so subsequent tools cannot start. - Symptom: A
413 Request Entity Too Largeerror is returned when initiating a tool call. Cause: Thetool_call_batch_sizeparameter is not adjusted. The single-pull film theater data volume exceeds the request body limit of the API. - Symptom: Revenue sharing fields in pulled film theater data are empty, preventing revenue yield calculation. Cause:
plugin_dynamic_field_mappingis not enabled. Hardcoded legacy field names are used to match fields from dynamically updated data sources.
How to Verify Proper Configuration
- Review tool calling chain logs to confirm all configured tools start and execute in sequence, with no interrupted records.
- In the plugin configuration interface, confirm that
plugin_dynamic_field_mappingis enabled, and field mapping rules do not use hardcoded fixed field names. This accommodates dynamic adjustments to data sources. - Initiate a single test request, and verify that the returned data fields match the public field structure of the current film theater data source. Core fields are not missing.
- Review the billing panel to confirm that tool calling requests are not blocked due to exceptions, and that timeout settings match current API response times.
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.