What the Data for This Category Looks Like
The data sources for commercial property yield data primarily include rent collection records from property lease management systems, energy bills from energy management systems, public area operation ledgers (such as ad space and parking fee revenue), and property valuation reports from third-party valuation agencies. Update cadences vary across data sources: monthly rent collection data is incrementally updated daily, quarterly energy bills are updated monthly, and annual property valuation reports are updated every six months. Each individual data document includes fields such as unique property identifier, lease cycle, per-square-meter rental unit price, actual collection rate, energy cost, total additional revenue, and accounting cycle. The unit for unit price is yuan/square meter/month, the units for cost and revenue are yuan, and rates are values between 0 and 1.
What Constraints These Characteristics Impose on Deployment and Upgrade
The multi-source, heterogeneous data characteristics of commercial properties require configuring connection parameters for multiple data sources during deployment. During upgrade, compatibility with format mapping rules for new data sources must be supported. Data with different update frequencies requires layered synchronization tasks. During deployment, multiple sets of scheduled synchronization rules must be preset. During upgrade, dynamic addition of new synchronization tasks without interrupting existing services must be supported. The complex field structure and specific unit requirements mean field standardization logic must be configured during deployment. During upgrade, unit validation and format conversion rules must be added to avoid field mismatches or unit errors during data import. Additionally, commercial property scenarios typically involve multi-tenant permission management. During deployment and upgrade, tenant-isolated database indexes and permission rules must be configured synchronously.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Commercial property yield documents may include multi-tenant historical data, leading to long parsing times. 900 seconds covers the full parsing process |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Annual valuation reports and full-cycle rent ledgers for commercial properties are usually large in size. 2000 MB meets bulk import requirements |
SYNC_JOB_CRON | 0 0 2 * * * and 0 0 4 1 * * | Monthly rent data is incrementally synced at 2:00 AM daily. Annual valuation data is fully synced at 4:00 AM on the 1st day of each month, adapting to business rules with multiple update frequencies |
RECALL_TOP_K | Top 8 entries | Commercial property yield data has many fields and high correlation. Too many recalled entries increase context redundancy, too few lose critical associated information |
DB_CONNECTION_POOL_SIZE | 15–20 | Most commercial property data sources are enterprise-level databases. The connection pool size must adapt to concurrent sync tasks across multiple jobs |
AIPROXY_ENABLED | true | Starting from version 4.9, aiproxy is used by default instead of One API. It enables unified management of multi-model calls, adapting to multi-data-source model requirements in commercial property scenarios |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Issue: After starting the container, a prompt "index field not configured" appears, and empty results are returned when querying yield data. Cause:
MONGODB_INDEX_AUTO_CREATEis not configured as true in the docker-compose.yml environment variables, or the configuration value is incorrectly set to false. - Issue: Running the
npm listcommand cannot find the mongoose version, but the dependency declaration exists in package.json. Cause: Dependency installation steps were not executed correctly during container build, or the image cached an old dependency list. - Issue: After upgrading to version 4.9, model calls fail, and the log prompts "API key invalid". Cause: Configuration parameters for aiproxy were not updated synchronously, and the old environment variable configuration for One API is still used.
How to Confirm Configuration Is Complete
- Enter the container, run the dependency version check command, and verify that the versions of mongoose and aiproxy-related dependencies match the declarations in the project configuration files.
- Manually trigger an incremental sync task, and check whether the task log includes prompts for successful data source connection and normal field parsing.
- Log in to the admin backend, test creating a new tenant account, confirm that the account creation process has no errors and permission configurations take effect normally.
- Retrieve the test commercial property yield dataset, and verify that the number of recalled results matches the
RECALL_TOP_Kconfiguration value.
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.