What the data for this category looks like
Data related to baijiu marketing is primarily collected from official brand product manuals, tasting guides, and compliance publicity guidelines; e-commerce platform user reviews and consultation records; flavor classification standards released by industry associations; and customer consultation records from financial channels, including baijiu gift requests from private banking clients and gift recommendation needs from insurance clients.
Data updates follow no fixed schedule. New data is added when new products launch. Industry compliance guidelines are updated every 1 to 2 years. User reviews are generated in real time.
Single product document structures include fields such as flavor type, alcohol content, net content, brewing process, recommended tasting lines, applicable scenarios, and compliance reminders. Field units use standard formats including %vol, ml, and yuan.
Constraints imposed on multi-turn dialogue and prompt engineering
Compliance fields require mandatory compliance check logic to be included in prompts. The system automatically intercepts user messages that mention prohibited terms during multi-turn dialogue.
Tasting scripts vary significantly across different flavor types. Retain context information such as the user’s mentioned flavor type, budget, and usage scenario to avoid repeating basic introductions in every response.
New product data is updated irregularly. Refresh the knowledge base on a regular basis, and call the latest entries when new products are referenced in multi-turn dialogue.
Standardized field units require prompts to explicitly mandate the use of standard units in responses to prevent unit confusion.
Customer consultations from financial channels typically center on gift scenarios. Adapt scripts for segmented scenarios including gifts and business banquets.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000-12000 characters | Baijiu product documents and tasting scripts have relatively long content. Sufficient context must be retained to avoid losing key information such as the user’s mentioned flavor type and scenarios. |
systemPrompt | Embed compliance check rules + scenario adaptation template | Must include mandatory compliance requirements such as "no health efficacy claims" and "must clearly indicate alcohol content unit %vol". Match corresponding recommended scripts based on user-mentioned scenarios to adapt to gift and business needs from financial channels. |
knowledgeBaseRefreshInterval | 7 days | New baijiu product launch cycles are not fixed, and industry standard update frequency is low. Regular refresh ensures the knowledge base contains the latest product information. |
blockedKeywords | Includes terms such as health care, disease treatment, health preservation | Baijiu advertising has strict compliance requirements. Prohibited publicity keywords must be automatically intercepted. |
multiTurnMaxRounds | 10 rounds | Baijiu marketing conversations typically revolve around products, scenarios, and prices. Excessive rounds lead to redundant context. Limiting rounds improves conversation efficiency. |
enableSessionHistory | Enabled | Users must be able to view their own historical conversations. Session context data must be persistently stored. |
aiNodeHideOutput | Enabled for non-core nodes | Hide the output of AI nodes used for parameter verification and knowledge base recall in the workflow. Only display core recommended content. |
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 specific analysis. Testing on local samples is recommended before finalizing settings.
Three Common Misconfigurations
- Issue: Flavor type information mentioned by the user is lost during multi-turn dialogue, and subsequent responses do not match the corresponding tasting script. Cause: The
maxContextparameter is not configured, and the context window is too small, causing key information from early user input to be truncated. - Issue: Responses from multiple AI dialogue nodes in the workflow are all displayed on the final conversation interface. Cause: The
aiNodeHideOutputparameter is not configured for non-core nodes, or the trigger conditions for this parameter are not set correctly. - Issue: Users cannot view their own historical conversation records. Cause: The
enableSessionHistoryparameter is not enabled, resulting in session data not being persistently stored and unable to call historical information in subsequent conversations.
How to Verify Correct Configuration
- Initiate a test conversation, mention sauce-flavored baijiu and wedding banquet scenarios, confirm that subsequent responses match sauce-flavored tasting scripts and wedding banquet recommendation scenarios.
- Submit a query containing the term "health care", confirm that the system automatically intercepts the request and returns a compliance prompt.
- After completing a multi-turn conversation, check that only the responses from core recommended nodes are displayed on the interface, and the content of non-core parameter verification nodes is hidden.
- Exit the conversation and re-enter, confirm that all previous conversation history can be viewed.
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.