Dialogue Logging and Audit for Refractory Material Investment Research Knowledge Base Construction

Refractory material investment research data primarily comes from composition test reports from raw material suppliers, kiln operation logs from

What the data for this category looks like

Refractory material investment research data primarily comes from composition test reports from raw material suppliers, kiln operation logs from production enterprises, standard documents released by industry associations, and operating condition feedback data from downstream applications. Raw material composition data is updated with production batches, kiln operation logs are generated per shift, and industry standard documents are revised irregularly. Each document typically includes material grade, chemical composition (e.g., Al₂O₃, MgO content), physical performance indicators (refractoriness, compressive strength), application scenario adaptation parameters, and batch traceability information. For fields and units: Chemical composition uses percentage units, refractoriness uses degrees Celsius, strength uses megapascals, and batch IDs are string type.

The multi-field, professional unit, and batch association characteristics of refractory material investment research data impose clear constraints on dialogue logging and audit. First, complete records of names and units for all professional fields are required to avoid confusion of parameter meanings during audits. Second, batch traceability information must be bound to each dialogue log to meet traceability requirements for compliance audits. Third, data update frequencies vary, so the knowledge base version or document update time of the called dialogue must be marked in the log to ensure traceability of data timeliness during audits. Fourth, professional parameters have high precision requirements, and logs must retain exact values of original call parameters and returned results to avoid data deviations during audits.

How to set the configurations

Configuration ItemRecommended SettingRationale
log_retention_days180 daysRefractory material investment research involves compliance audit requirements, so conversation and operation logs must be retained for at least six months to meet industry traceability needs
log_include_field_list["material_grade", "content_value", "batch_id", "update_time"]Refractory material data includes professional grades, parameter values, batch numbers, and update times; these fields must be included in logs to ensure audit traceability
max_log_entry_length2000 charactersSingle records of refractory material test reports and operating condition data are lengthy, so limiting single log length prevents storage overflow
audit_trigger_modeAutomatically trigger after dialogue completionInvestment research conversations require full traceability; automatic audit triggering prevents manual omission of key conversation steps
log_storage_quota500 GBThe total volume of documents and dialogue logs for refractory material knowledge bases is large, so sufficient storage quota must be reserved to avoid insufficient storage
log_exclude_plugin_logEnabledRedundant logs from plugin execution must be filtered to avoid interference from non-investment research content during audits

The parameter values provided on this page are common starting points for configuration. Actual values are affected 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.

Three common configuration errors

  • Phenomenon: The model returns empty after a call, and the log shows that the message field is truncated or missing. Cause: The log_include_field_list configuration is not set to include the original response fields of the model, resulting in loss of key error information in audit logs.
  • Phenomenon: The loop returns null after the loop body executes index increment, and the loop context parameters are not recorded in the log. Cause: The context tracking configuration for dialogue logs is not enabled, so the intermediate state of loop operations is not retained, making it impossible to locate abnormal nodes during audits.
  • Phenomenon: Redundant content from specified reply plugins is included during historical memory calls. Cause: The log_exclude_plugin_log configuration is not enabled, so plugin execution logs are included in the dialogue history, interfering with subsequent context calls.

How to confirm the configuration is correct

  • Access the log management interface, view the log of a single refractory material investment research dialogue, and confirm that preset fields such as material_grade and batch_id are included.
  • Initiate an investment research dialogue with loop logic, and check whether the log fully records each intermediate result and parameter of the loop.
  • Trigger a dialogue with a specified reply plugin, and confirm that redundant log content from plugin execution is not included during historical memory calls.
  • Check the log storage quota usage, and confirm that the threshold set by log_storage_quota has not been reached.

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.