What the data for this category looks like
Education service marketing content data primarily comes from course development documents, student feedback materials, enrollment brochures, trial lecture scripts, and teaching research handouts. The data update rhythm is adjusted alongside new quarterly class openings, course iterations, or enrollment deadlines. Individual documents typically include fields such as teaching duration, target enrollment population, fee standards, teacher qualifications, and course outlines. Some long documents include per-session teaching objectives and content breakdowns, with units such as class hours, headcount, and monetary amounts as concrete metrics.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The multi-source data characteristics of education service marketing content require that multi-turn dialogue distinguish between official standardized scripts and unstructured context from real student feedback, to avoid mixing up enrollment messaging. Frequently updated course and enrollment information requires that prompts be bound to dynamically updated knowledge base nodes, to prevent outdated content from being output. The per-session structure of long documents requires that the context window adapt to long texts retrieved in segments, while prompts must explicitly associate corresponding marketing content with teaching modules to avoid misalignment of cross-module information. The metrical attributes of multiple fields require that the dialogue process fix field calling rules, to ensure that output enrollment information matches the units and values in the documents.
How to set configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Education service marketing documents often include per-session breakdowns; long texts require complete enrollment and course context to be retained |
recallTopK | Top 6–8 results | Education service marketing content covers multiple dimensions such as courses, teachers, and student feedback; additional retrievals can match potential needs from users’ multi-turn questions |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | 10MB-level education Word documents contain per-session content, which requires a longer parsing time |
similarityThreshold | 0.75–0.85 | Course and enrollment information for education services have similar phrasing; low-relevance redundant content must be filtered out |
enableRerank | Enabled | Multi-dimensional marketing content must be sorted by relevance to ensure user questions match the most relevant teaching modules |
promptTemplate | "Based on the education service marketing content in the current knowledge base, prioritize calling the latest updated course and enrollment documents, distinguish between official scripts and user feedback" | Education service messaging must strictly match official materials, while adapting to context switching in multi-turn dialogue |
The parameter values provided on this page are general recommendations used as starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- The phenomenon: Conversation logs during API calls carry redundant document title fields, while external link calls do not exhibit this issue. Cause: The API request does not correctly configure context filtering rules, and does not specify that only marketing-related content fragments should be retrieved.
- The phenomenon: Intermediate steps of the thinking process are displayed on the conversation interface. Cause: The
showThoughtconfiguration item is not disabled, causing the reasoning chain to be output directly. - The phenomenon: Parsing of 10MB-level Word documents takes too long and cannot be completed. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to the value range suitable for long education documents, causing the parsing task to time out and terminate.
How to confirm the configuration is complete
- Launch multi-round test questions covering course inquiries, teacher inquiries, and enrollment requirements, and check whether the output content matches the currently updated marketing documents.
- View the conversation log to confirm that no unconfigured redundant fields or irrelevant document fragments appear.
- Upload a single 10MB-level education Word document, and check whether the parsing task can be completed within the preset duration.
- Check the conversation interface to confirm that intermediate steps of the thinking process are not displayed.
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.