What the Data Looks Like
Wind power investment research data is sourced from publicly available technical documents of wind turbine manufacturers, quarterly industry association reports, hourly meteorological station monitoring data, daily updated grid operation data, and environmental impact assessment and operation and maintenance archives of wind power projects. Document structures include standardized parameter tables, long-text analysis reports, time-series operation and maintenance logs, and policy documents. Fields cover project unique identifiers, fan serial numbers, power generation hours, operation and maintenance cycles, and more. Units include physical and industry-specific units such as kilowatts, meters, and hours. Update rhythms vary significantly: meteorological and grid data have high real-time requirements, industry reports are updated quarterly, and manufacturer documents are updated alongside product versions.
Constraints on Dialogue Logs and Auditing
The multiple data sources and varying update rhythms of wind power investment research data require dialogue logs to record call timestamps and data source version identifiers, to avoid confusion between new and old data during audits. The combination of long-text documents and time-series logs requires the log system to distinguish between original document fragments, generated content, and intermediate call results, to prevent key information from being truncated. Multi-dimensional associated fields require logs to support filtering by business dimensions, to quickly locate investment research conversations for specific projects. Additionally, wind power investment research involves industry-sensitive parameters and compliance requirements, so complete dialogue context must be retained to ensure full traceability of the decision-making chain during audits.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chat_log_retention_days | 365 days | Wind power project operation and maintenance cycles usually span several years, and audits require retaining conversation records for the full cycle |
log_record_include_tags | ["project_id", "fan_serial_number", "data_source"] | Wind power investment research data is mostly associated with specific projects, fan serial numbers, and data sources. Filtering logs by tags allows quick location of corresponding content |
max_log_context_length | 10000 characters | Wind power investment research documents contain long sections of technical parameters, operation and maintenance logs, and report content, so sufficient length is required for complete recording |
subworkflow_log_sync | Enabled | Wind power investment research often splits workflows to process segmented data, so conversation and call information of sub-workflows must be recorded synchronously |
log_access_permission | Authorized by project group | Wind power investment research data involves industry-sensitive parameters, so log access scope must be restricted by project dimension |
log_auto_purge_threshold | 100 GB | Wind power investment research dialogue logs have a large data volume, and setting a threshold can prevent storage resources from being exhausted |
The parameter values provided on this page are common starting points for configuration setup. Actual values are influenced by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test against your own samples before finalizing settings.
Three Common Configuration Errors
- Phenomenon: Key identifiers such as project ID and fan serial number are not included in dialogue logs, making it impossible to filter audit content by business dimensions. Cause: Corresponding fields are not configured in
log_record_include_tags, so only basic conversation content is recorded in logs. - Phenomenon: Conversation content from sub-workflow or external plugin calls is not synchronized to the main log, so audits cannot cover the full investment research workflow. Cause: The
subworkflow_log_syncconfiguration is not enabled, and the sub-process log synchronization function is not activated. - Phenomenon: The thinking process output by models deployed via AIProxy is not displayed in dialogue logs. Cause: The
thinking_processfield is not added tolog_record_include_tags, or the full log collection switch is not enabled in the proxy configuration.
How to Confirm Proper Configuration
- Initiate a test conversation linked to a preset project ID and fan serial number, view the log details, and confirm that the corresponding tags are correctly recorded.
- Trigger a sub-workflow call, check if the main log includes the sub-process's call records and conversation content, and verify that the synchronization configuration is active.
- Access the background log management panel, confirm that the log retention period matches the preset requirement, and that no abnormal log cleanup has occurred.
- Test a model call deployed via a proxy, confirm that the thinking process field appears in the log details, and verify that the collection configuration is correctly set up.
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.