What the data for this category looks like
Data related to hotel and catering revenue yield comes from in-store POS cash registers, property management systems (PMS), and third-party business data integration interfaces. Full daily data is typically synchronized between 02:00 and 04:00 daily. Real-time business data such as period revenue and takeout orders updates every 30 minutes. Data is stored in structured CSV or JSON formats. Core fields include store unique identifier, statistical cycle (daily/ morning/ midday/ evening sessions/ time period), total revenue amount, fixed cost amount, variable cost amount, average customer spending, table turnover count. Units are Renminbi yuan, number of customers, and times respectively.
Constraints for Tool Calling and Plugins
The time-segmented update schedule of data requires tool calls to differentiate between real-time data and historical data interfaces. Historical data calls must avoid the early-morning synchronization window, otherwise incomplete, unupdated data will be retrieved. The binding relationship between structured fields, stores, and cycles requires that store unique identifier and statistical cycle must be passed as required parameters for tool calls. Without these parameters, corresponding data cannot be accurately matched. For multi-store batch query scenarios, the number of stores per call must be limited to avoid interface response timeouts. The short-cycle update of real-time data requires plugins to configure a reasonable cache duration to balance data freshness and call frequency.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
tool call timeout period | 300 seconds | Hotel and catering data source interfaces typically have response delays of 1-2 minutes. 300 seconds covers normal call durations |
maximum number of stores for batch queries | 20 stores | Batch queries exceeding 20 stores will cause most third-party interfaces to time out |
data synchronization trigger timing | after 05:00 daily | Full daily data is typically synchronized between 02:00 and 04:00. Calling after 05:00 ensures complete daily data is retrieved |
field mapping rule | associate core fields using store identifier + statistical cycle | Data source documents use store code and statistical cycle as unique keys, ensuring accurate data matching |
real-time data cache duration | 25 minutes | Real-time business data updates every 30 minutes. A 25-minute cache balances freshness and call efficiency |
error retry count | 2 times | Interface fluctuation probability is low. Retrying 2 times effectively reduces failure rates |
The parameter values provided on this page are common recommended 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 self-provided samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After tool calling returns structured data, the generated chart only displays JSON/XML code blocks with no visual rendering. Cause: The prompt does not explicitly require passing tool return data to the chart generation plugin, or the data source binding parameters of the chart plugin are not associated with the output fields of the tool call.
- Phenomenon: Tool returns empty data during API calls, but normal results are obtained in online chats. Cause: The API call does not correctly carry required parameters such as
store unique identifierorstatistical cycle, or the request header does not have correct access permissions configured. - Phenomenon: Profit amount fields returned by tool calls are empty. Cause: The field mapping rule configured in the plugin omits the profit amount field, or the connected data source interface does not open query permissions for this field.
How to Confirm Proper Configuration
- Initiate a tool call test for a single store and single date, check if the returned data fields match the core fields listed in the data source documentation.
- Configure the chart plugin, bind the output fields of the tool call, initiate a test conversation, and check if a visual chart is generated instead of pure code blocks.
- Send identical test requests via online chat and API calls respectively, compare whether the returned tool call results and chart rendering results are consistent.
- Initiate a historical data query after 05:00 daily, check if complete full daily data is obtained.
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.