What does data in this category look like?
Thermal energy investment research data primarily comes from real-time monitoring sensors of heating pipelines, thermal production scheduling systems, industry policy documents, heating load forecasting model outputs, and public research reports. Real-time monitoring data updates on a minute-by-minute basis. Policy documents and research reports update irregularly. Single data entries include structured fields: monitoring point ID, collection timestamp, water supply temperature (℃), return water pressure (kPa), heat flow (m³/h). They also include semi-structured regional monitoring reports and unstructured industry analysis documents. All fields must be linked to corresponding heating area and pipeline node identifiers.
Constraints Imposed on Dialogue Logging and Auditing
The real-time requirements of thermal energy investment research data mandate that dialogue logs fully retain original collection timestamps and monitoring point association identifiers. Do not store only processed results. The data includes both structured operating parameters and unstructured research reports. Logs must distinguish between different types of input and output content. Logs must support filtering audit records by monitoring area and collection time period. Thermal energy data is subject to public service compliance requirements. The audit chain must cover specific document IDs and parameters for API calls, user questions, and knowledge base recalls. Log storage periods must be limited to avoid exceeding conventional storage thresholds due to excessive data volume.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 90 days | Meets conventional retention requirements for public service data audits in the thermal energy industry, and balances storage costs and traceability needs |
INCLUDE_SOURCE_DOC_IN_LOG | Enabled | Thermal energy investment research requires tracing source data such as recalled monitoring reports and policy documents. A complete audit chain must include document identifiers |
DAILY_API_LOG_STORAGE_QUOTA | 50 GB | Adapts to the scale of monitoring nodes for a single thermal energy project, and prevents daily log volume from exceeding conventional storage thresholds |
MAX_HISTORY_TOKENS | 8000–12000 | Covers conversation context requirements for comparing multiple parameter sets and conducting cross-period analysis in thermal energy investment research |
LOG_EXPORT_ALLOWED_FIELDS | collection time, monitoring point ID, user question, recalled document ID | Simplifies audit filtering processes, and only retains core traceability and verification fields for thermal energy investment research scenarios |
The parameter values provided on this page are common recommended 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 Mistakes
- Phenomenon: Dialogue records generated by API calls cannot be viewed in the log list of the management backend. Cause: The
API_CALL_LOG_ENABLEconfiguration item is not enabled, resulting in dialogue logs for API interactions not being written to storage. - Phenomenon: Conversation histories of different users cannot be isolated by identity. Any user can view all conversation records. Cause: The
USER_CONVERSATION_ISOLATIONconfiguration is not set to enabled, and logs are not associated with user unique identifiers. - Phenomenon: The
humanfield is empty in log previews. Cause: The original text parameter of the user's question is not passed correctly, or the parameter is not passed to the interface using thehumanfield name, resulting in the log failing to capture the user's input content.
How to Verify Correct Configuration
- Call the test API to generate a dialogue record, check whether the preset core fields of the record are included in the log list.
- Initiate conversations using two different test user identities, verify that each user can only view their own conversation history records.
- Manually export a log sample, confirm that the exported fields include the preset audit required information with no missing entries.
- Trigger a knowledge base recall operation, check whether the unique identifier of the corresponding recalled document is associated in the log.
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.