What This Type of Data Looks Like
Historical query record data is sourced from end-user AI interaction session logs. Updates occur either in real time after a single session ends, or appended after each interaction turn. The structure of a single record includes a session identifier, interaction timestamp, user input text, AI response content, and an operation type field. The query_time field uses the ISO 8601 time format. session_id is a globally unique string identifier. The user_input and ai_response fields support rich text and code block content. operation_type is used to mark operation types such as query, modification, and export. The length of individual records varies widely, ranging from tens of characters to several thousand characters.
Constraints Imposed on Multi-Turn Dialogues and Prompt Engineering
Historical query records are bound to a unique session identifier. Multi-turn dialogue configurations must associate the current session ID, preventing cross-session historical data from being mixed into the current interaction. Individual records vary widely in length and support rich text. Prompt templates must define extraction ranges and truncation rules for historical records, to prevent exceeding the context window and causing abnormal model responses. The real-time update feature requires retrieval logic to dynamically pull the latest interaction records within the current session, ensuring the context matches the current session. The multi-field structure requires prompts to explicitly specify which fields to extract, avoiding redundant data that interferes with the model's understanding of historical query content.
How to Set Configuration Parameters
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
historyRetrieveCount | Top 3-5 entries | Individual historical query records can be lengthy; too many entries will consume excessive context space and impact model response efficiency |
maxContext | 8000-12000 characters | Historical records include user inputs and AI responses; sufficient space must be reserved for retrieved historical content and the current interaction |
contextWindowStrategy | Truncate by session grouping | Prevents cross-session historical records from being mixed into the current conversation, matching the session binding feature of historical query records |
promptTemplate | Includes {{session_id}} and {{history_list}} variables | Accurately pulls historical query records for the current session, filtering data from unrelated sessions |
latexRenderEnable | Enabled | Fixes issues where LaTeX formats fail to display correctly in production environments, matching rendering logic from debug previews |
apiCallTimeout | 60 seconds | Batch retrieval of historical query records may involve multiple rounds of log retrieval; sufficient response time must be reserved |
All 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. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- LaTeX formats only display raw code in production environments. This occurs because the
latexRenderEnableconfiguration item is not enabled. The debug environment enables this setting by default, but it must be manually activated in production environments. - Conversations remain stuck in a loading state after deployment. This happens because the
apiCallTimeoutvalue is set too short, interrupting batch retrieval operations for historical query records before they complete their response. - AI conversation content inserted via Workflows is mixed into the final output. This occurs because the "Synchronize to main conversation" option for that node is not disabled, causing records from intermediate steps to be included in the global context.
How to Verify Successful Configuration
- Access the application debug interface, input a query containing LaTeX syntax, and confirm that LaTeX renders correctly in the production environment dialog box.
- Initiate consecutive multi-turn conversations, and check that conversation logs only pull historical query records for the current session, with no cross-session data included.
- When configuring a Workflow node, disable the "Synchronize to main conversation" option, then run the workflow and confirm that the final output only includes target process results.
- Call the API interface, and check that returned conversation log fields contain complete historical query record 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.