What the data for this category looks like
Construction machinery yield rate data originates from three primary data sources: on-site IoT working condition sensors, rental management systems, and financial operation ledgers. Full batch synchronization of the previous day’s data runs every early morning, with a fixed daily update schedule. The core structure of a single data entry includes the device unique identifier, working duration, daily operating revenue, consumables and maintenance costs, and daily net profit. All fields are numeric values or unique identifier strings, with units in Chinese Yuan and working hours, and no nested complex structures are present.
What constraints do these characteristics impose on conversation logs and auditing workflows
The multi-source data synchronization feature requires conversation logs to be associated with traceability identifiers from IoT, rental, and financial data sources. This ensures the calculation basis for yield rates can be traced during audits. The daily batch update schedule requires log queries to support filtering by date range. Do not pull full device data for more than 7 days in a single request, as this causes excessive interface load. The device unique identifier field requires log association queries to use device_id as the core key, preventing confusion of yield rate data across different devices. The presence of multi-dimensional cost fields requires audit logs to fully record the source of each cost item, avoiding tampering or omission of key calculation links.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
log_retention_days | 90 days | The conventional audit cycle for the construction machinery industry is quarterly. 90 days covers most compliance requirements while controlling storage resource usage |
export_log_batch_size | 500 entries per request | The volume of device yield rate data exported in a single batch is large. 500 entries balances export speed and interface load, adapting to batch data export scenarios for multiple engineering devices |
context_window_log_enable | Enabled | Full recording of traceability information for device yield rate data referenced in conversations is required to avoid loss of context association |
audit_log_field_whitelist | ["device_id", "date", "revenue", "cost", "net_profit"] | Only retain core fields required for audits to reduce log redundancy while ensuring key traceability-related information is not missing |
log_query_timeout | 30 seconds | When querying batch-synchronized construction machinery data, 30 seconds covers most data pull scenarios and avoids triggering 504 Gateway Timeout errors |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: After increasing the
max_contextconfiguration, associated construction machinery yield rate data context is not fully displayed in conversation logs, only generic replies are shown. Cause: For version V4.8.17,context_window_log_enableis disabled by default, which only caches AI reply text and does not synchronize traceability information for knowledge base-recalled device data. - Symptom: Empty data or only partial records are returned when calling the log export interface. Cause: A reasonable
export_log_batch_sizevalue is not set, and the single pull volume exceeds the interface's carrying limit, resulting in truncation of some data. - Symptom: Corresponding device yield rate raw data cannot be associated in audit logs. Cause: The
device_idfield is not configured inaudit_log_field_whitelist, so log records from different devices cannot be distinguished by unique identifier, leading to failed traceability association.
How to Confirm Configuration Is Successfully Applied
- Access the log management interface, filter by a specified device ID and date range, and verify that the number of returned logs matches the expected number of device operating days.
- Trigger a log export operation, then check that the exported file’s fields exactly match the configured
audit_log_field_whitelist. - Adjust the
max_contextparameter, initiate a conversation, and confirm that the conversation logs fully include recalled device yield rate-related data. - Simulate an audit scenario, query logs for a specified time period, and confirm that each record can be associated with original device operating data.
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.