What this category's data looks like
Game revenue yield and market data primarily comes from structured export files from game publisher official operation backends, and public API endpoints from third-party game data aggregation platforms. There are two types of data update cadences: full daily data updates at a fixed time each day, and real-time market data refreshes every 15 minutes. Single data documents are stored as structured tables or JSON format, and include fields such as game_id, stat_date, total_revenue, paying_users, avg_revenue_per_user, daily_profit_rate. game_id is a string-type unique identifier. stat_date is a date format field. total_revenue and avg_revenue_per_user use currency units. daily_profit_rate is a numeric field.
What constraints do these characteristics impose on the "model access and configuration" workflow
Game category data has scattered sources and varying formats. This requires configuring multi-data source adaptation rules to support data formats from official exports and third-party API interfaces. Differently paced data needs differentiated scheduling strategies: bind daily full data to a scheduled daily pull task, and configure real-time data with polling parameters set for every 15 minutes. The diversity of field types and units requires configuring field mapping rules to unify fields from different data sources into standardized fields recognizable by the model, avoiding type parsing errors. Third-party API data sources need authentication parameters configured to ensure request legitimacy. For scenarios with large single-batch data volumes, configure thresholds for data sharding processing to prevent memory overflow.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
datasource_type | ["official_export", "third_party_api"] | Covers the two mainstream channels for obtaining game data |
schedule_cron | ["0 2 * * *", "*/15 * * * *"] | Matches the update cadence of daily full data and real-time market data |
field_mapping | Perform one-to-one mapping between actual fields of the data source and standard fields | Unify field naming and types from different data sources |
embedding_model | ["local_embedding", "cloud_embedding"] | Supports flexible switching between local embedding models and cloud models |
api_request_timeout | 600 seconds | Adapts to the response duration requirements of third-party game data APIs |
max_retry_times | 3 times | Meets conventional retry needs for failed API calls |
The parameter values provided on this page are common recommended starting points for configuration setup. Actual values are affected by material format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The local model access entry cannot be found in the interface, or a prompt of "local models are not supported" appears. Cause: The local model access switch is not enabled in the system configuration, or the used version is lower than 4.9.9, which does not adapt to local model deployment requirements.
- The number of returned results from the data interface call does not match expectations. Cause: The configured recall threshold for the number of entries is set incorrectly, or the data source sharding processing parameters do not match the actual data volume.
- Previous revenue query keywords cannot be retained in multi-turn conversations. Cause: A reasonable value for the
maxContextparameter is not configured, resulting in an overly small context window that cannot store historical conversation information.
How to confirm the configuration is complete
- Enter the data source management page, verify that the status of the configured data source shows normal connection.
- Trigger a single data pull task, check that the returned fields fully match the configured mapping rules.
- Test the local embedding model access process, confirm that there are no error prompts for model loading and calling.
- Initiate two or more revenue-related conversations, confirm that historical interaction information is correctly included in the context.
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.