What the data for this category looks like
Data sources for the unified entry all-in-one AI platform include aggregated multi-branch AI application session logs, associated knowledge base recall records, and user interaction behavior data. Data updates are triggered by real-time session submissions, and synchronized for archiving after a single session ends. The document structure uses structured JSON format, including the following fields: session identifier string, user identity identifier, associated application ID, multi-turn context array, prompt template ID, returned result text, and interaction timestamp. Context length is measured in characters, and timestamps are measured in milliseconds.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" link
The aggregated nature of multi-branch applications requires multi-turn context to be synchronized across applications, so total context length must be limited to avoid exceeding the model's supported window limits. Real-time updated session data means prompt configuration must be dynamically adjusted with sessions, and cannot rely on static preset templates to cover all scenarios. Structured session fields require multi-turn dialogue to associate corresponding knowledge bases and application branches by identifier, and prompts must embed context variables at the application dimension to ensure independent interaction logic for different branches. Additionally, millisecond-level timestamp fields require precise timeout detection for dialogues that matches the session lifecycle, to avoid cross-session context contamination.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–16000 characters | Adapts to the context window limits of mainstream large models, preventing content truncation in cross-application aggregated multi-turn dialogues |
disableMarkdownOutput | Yes / No | Configured according to compliance output requirements for financial scenarios. Enable this switch if regulations require plain text output |
multiAppContextSync | Enabled | Ensures consistent multi-turn dialogue context across branch applications under the unified entry, preventing session logic breaks |
sessionTimeout | 1800 seconds | Covers the full business cycle of financial wealth management consultations, preventing mid-session interruptions due to timeout |
contextRecallTopN | Top 3–5 turns | Focuses on the latest interaction context, reducing interference from redundant historical information on prompt logic |
promptVariableScope | Global + session dimension | Supports embedding variables such as user identity and application ID, adapting to differentiated prompt requirements for multi-branch applications |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Symptom: The AI returned result always contains Markdown syntax, and cannot output plain text as required. Cause: The
disableMarkdownOutputparameter is not configured correctly, or the parameter value does not match the scenario requirements. - Symptom: It is impossible to initiate conversations with multiple AI applications at the same time, and the session context is only bound to a single application. Cause: The
multiAppContextSyncparameter is not enabled, or the context synchronization logic for multi-application association is not configured. - Symptom: After the AI dialogue returns, it is impossible to return to the question classification node, and the workflow execution is interrupted. Cause: The session jump identifier is not configured in the prompt, or the branch callback parameters of the workflow are not bound.
How to confirm the configuration is complete
- Initiate a multi-turn dialogue across branches, check whether the context is synchronized across different applications, and confirm that it complies with the configured context length limits.
- Trigger an AI dialogue, check whether the format of the returned result matches the configuration of
disableMarkdownOutput. - Wait for the session to exceed the configured timeout period, check whether the session is automatically archived or interrupted, and complies with the preset timeout logic.
- Switch to different branch applications to initiate a dialogue, check whether the prompt takes effect according to the application dimension, and there are no cross-application logic conflicts.
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.