What the data for this category looks like
Photovoltaic investment research data mainly comes from public industry research reports, component manufacturer public financial reports, distributed power station operation logs, national-level new energy policy documents, and meteorological observation datasets. Research reports are updated weekly or at sudden policy milestones. Financial reports are released quarterly. Power station operation data is synchronized at minute-level intervals. Document structures include technical parameter modules, market supply and demand analysis, and policy interpretation chapters. Fields include irradiance unit W/㎡, power generation capacity unit kW, installed capacity unit MW. Some power station logs also include inverter temperature unit ℃.
What constraints do these characteristics impose on the "conversation logs and auditing" workflow
Accurately mark the data source type for each interaction in conversation logs. This addresses the multi-source, heterogeneous nature of photovoltaic investment research data.
Minute-level updated power station operation data generates high-frequency interactions, leading to a sharp increase in log storage volume. Configure reasonable log sharding rules to avoid single-node overload.
For technical fields with specific units, verify that field units match preset standards during auditing. This prevents invalid data from entering the knowledge base.
Store logs categorized by update batches for data sources with multiple update cycles. This supports easier tracing of investment research conversation basis for specific time periods.
Fully record associated data source IDs in logs for cross-source interactions, such as conversations combining policy and power station data. This supports audit traceability.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
LOG_STORAGE_SHARD_COUNT | 8–12 shards | Matches log storage volume from high-frequency photovoltaic power station data to avoid single-node overload |
LOG_FIELD_VALIDATION_ENABLE | Enabled | Verifies units and formats of photovoltaic-specific fields to ensure audit data compliance |
CONVERSATION_HISTORY_MAX_SIZE | 20000 entries | Adapts to scenarios where photovoltaic investment research conversations often link to multiple long documents, retaining sufficient historical context |
MONGODB_SOURCE_TAG_FIELD | source_type | Uses this field to distinguish between different data sources such as research reports and power station data, facilitating audit traceability |
LOG_AUDIT_TIMEOUT | 300 seconds | Reserves sufficient time to verify multi-dimensional photovoltaic data fields, avoiding audit timeout failures |
WEBHOOK_RETRY_COUNT | 3 retries | Reduces missed audit notification rates under high concurrency, adapting to temporary network fluctuations for Feishu webhooks |
The parameter values provided on this page are standard starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing against local samples is recommended before finalizing settings.
Three common configuration mistakes
- Phenomenon: Generated investment research responses in conversations are not written to historical records, and content is empty when the session is reopened. Cause: The
CONVERSATION_HISTORY_PERSISTconfiguration is not enabled, causing session data to only be stored in memory and not persisted to disk. - Phenomenon: Interactions cannot be distinguished between photovoltaic research reports and power station data in logs, making traceability impossible during audits. Cause: The
MONGODB_SOURCE_TAG_FIELDparameter is not configured, and no data source type field is marked in logs. - Phenomenon: High-concurrency calls to the auditing workflow return no results, or Feishu webhook sending of spliced audit content fails. Cause: The
WEBHOOK_RETRY_COUNTandLOG_AUDIT_TIMEOUTparameters are not adjusted. Failures occur due to timeouts without retries under high concurrency.
How to confirm configurations are properly set
- Generate a test conversation that includes photovoltaic power station data and industry research reports. Check whether the session history fully records interaction content and data source tags, and verify that the
source_typefield exists. - Simulate high-concurrency requests of 2-3 times per second. Check whether the shard load of log storage nodes is balanced, with no obvious overload error messages.
- Manually trigger an audit process. Verify that the Feishu webhook can normally send audit reports, with no empty content returned.
- Check alerts in the log verification module. Confirm that unit verification rules for photovoltaic-specific fields are active, and no invalid fields are mixed into logs.
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.