What the Data for This Category Looks Like
Data related to construction machinery yield rate comes from three main channels: equipment manufacturer operation and maintenance backends, engineering rental platform ledgers, and project settlement systems.
Daily job data updates daily. It includes detailed information per single device, such as operating hours, shift unit price, fuel consumption, and daily revenue. Monthly rental settlement data updates monthly. It includes full-month revenue, costs, and cumulative earnings for a device.
Data is stored in structured CSV or JSON format. Each record corresponds to daily yield details for a single device. Fields include device unique identifier, device model, operating parameters, cost items, and revenue items. Units use basic measurement units such as hours and yuan. No aggregated percentage statistics are included.
Constraints Imposed on Model Access and Configuration
Multi-field associated yield calculation logic requires configuring association matching rules for multi-source data. This avoids errors from single-field calculations.
Differences in update rhythms across data sources require configuring switch parameters for incremental and full pull. This distinguishes pull cycles for daily job data and monthly settlement data.
Large differences exist in field values corresponding to device models and operating scenarios. Configuring model-to-field mapping rules is needed to unify statistical calibers across different devices.
Decentralized data source access requires configuring multi-route request distribution parameters. This ensures accurate merging of data from different sources into the yield calculation workflow.
Data timeliness requirements demand configuring reasonable pull timeout thresholds. This avoids distortion of daily report content caused by pulling old data.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
vectorModel | bge-large-zh-v1.5 (local deployment) or text-embedding-3-small (cloud) | This model has good adaptability for vector encoding of structured numerical and mixed text fields, matching the field characteristics of construction machinery yield rate data |
recallTopK | Top 8 entries | Construction machinery yield rate data has many associated fields. Recalling 8 entries covers core associated dimensions and avoids missing key calculation parameters |
similarityThreshold | 0.72–0.78 | This interval filters low-correlation device data while retaining yield comparison data for the same model, adapting to the needs of parallel calculation across multiple models |
dataSourceRefreshInterval | Every 600 seconds | Matches the update frequency of daily job data for construction machinery, ensuring real-time performance of daily yield data |
multiSourceMatchThreshold | 0.85 | Used to match the same device ID across different data sources, ensuring accurate association between rental data and operation and maintenance data |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Adapts to the time consumption requirements of structured data parsing, avoiding timeout failures caused by parsing multiple fields |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Errors
- Phenomenon: Model call returns 403 status code (no body). Cause: Correct model access key and request domain whitelist are not configured, and access permissions for the corresponding port are not enabled during local deployment.
- Phenomenon: Yield calculation results have empty fields or abnormal numerical values. Cause: Multi-source data matching threshold is not configured, leading to failure to correctly associate device IDs across different data sources and missing core calculation fields.
- Phenomenon: Prompt fails to recognize device models separated by spaces in input. Cause: Recognition rules for spaces as separators are not configured in the prompt template, leading to the model being unable to correctly split multiple device identifiers.
How to Confirm Configuration Is Complete
- Perform a yield calculation test for a single device. Check whether the yield rate output by the model matches the manual calculation benchmark value. Adjust the similarity threshold and number of recalled entries until the matching results meet expectations.
- View the data source refresh log. Confirm that the pull time of daily job data and monthly settlement data conforms to the configured refresh interval, and there are no timeout or pull failure records.
- Test the scenario of parallel calculation for multiple devices. Check whether the model can correctly associate device data from different data sources, with no missing fields or matching errors.
- Call the model interface to test input containing device models separated by spaces. Confirm that the model can correctly recognize and process the input content.
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.