Workflow Orchestration for In-App Natural Language Search of Historical Query Records

Historical query record data originates from natural language search interaction logs initiated by end users. A single record is generated each time a

What the Data for This Category Looks Like

Historical query record data originates from natural language search interaction logs initiated by end users. A single record is generated each time a user completes a search operation. Updates follow a near-real-time schedule, with a single record generation delay of no more than 2 seconds. Each document uses structured JSON format, containing five core fields: user_id (encrypted string), query_time (ISO 8601 format timestamp), query_content (natural language text entered by the user), result_ids (unique identifiers for returned results in array form), operation_type (enumerated values such as search, detail view). No additional nested levels are present.

Constraints Imposed on Workflow Orchestration by These Data Characteristics

This category's data features impose three core constraints on workflow orchestration. First, the data comes from end-user interaction events, so the workflow must be configured with an event trigger node that connects to the end user's search operation reporting interface to ensure near-real-time data acquisition. Second, the field structure of single records is fixed and has no nesting, so parameters can be passed directly via field mapping without additional JSON parsing steps. Third, the result_ids field is an array type. If subsequent knowledge base searches or model calls need to be associated, an array expansion node must be configured to handle multiple result identifiers. Additionally, the operation_type enumerated value can be used for branch filtering to only process search-type operation records.

How to Set Configuration

Configuration ItemRecommended SettingRationale
trigger_modeevent_basedHistorical query records are near-real-time generated interaction events, and event triggering matches the data update rhythm
field_mapping_strategydirect_extractThe data uses structured JSON format, direct field extraction avoids additional parsing overhead
array_expand_countTop 10result_ids is an array field, limiting to the top 10 entries controls execution load for subsequent processes
branch_filter_conditionoperation_type = "search"Only process search-type operations initiated by users, filter out non-search interaction records
workflow_node_timeout300 secondsFor process steps including parameter verification and data association, 300 seconds covers typical execution durations

The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Configuration Mistakes

  • Phenomenon: The AI chat node does not receive the original user query content, and the generated reply is unrelated to the historical record. Cause: The upstream query_content field was not correctly mapped to the input parameters of the AI chat node.
  • Phenomenon: The knowledge base search node returns a 400 error code, prompting that the knowledge_base_id parameter is missing. Cause: The terminal configuration parameters passed upstream were not correctly bound to the node's parameter mapping configuration.
  • Phenomenon: The workflow only processes a single historical query record and does not cover all interaction data. Cause: No array expansion node was configured, and the result_ids array field was not processed in batches.

How to Confirm Successful Configuration

  • Trigger a test end-user search operation, check the workflow execution logs to confirm that fields such as query_content and user_id are correctly extracted to downstream nodes.
  • Check the workflow's branch node configuration to confirm that only records where operation_type is search are executed for subsequent processes.
  • Review the parameter binding items of the knowledge base search node to confirm that the knowledge_base_id parameter is associated with upstream passed variables.
  • Simulate input of multiple historical query records to confirm that the array expansion node correctly processes multiple sets of result_ids 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.