What the Data for This Category Looks Like
Marketing content data for educational services originates primarily from financial planning course development documents, student investment feedback records, teaching script materials, offline financial salon materials, and online community interaction content. Update frequency is adjusted based on business milestones. Bulk updates occur during course iterations or activity launches. Sporadic updates are used for minor tweaks to daily scripts. Each marketing content document includes fields such as title, applicable investment experience level, teaching subject, core knowledge point summary, registration link, and estimated number of participants. Duration-related fields use minutes as the unit. Text content uses characters as the statistical unit. Link fields follow standard HTTP format.
What Constraints Do These Characteristics Impose on Tool Calling and Plugins
The multi-source, multi-field nature of educational service marketing content creates clear constraints for tool calling and plugins. Multi-source materials require plugins to support parsing input content in different formats. This includes structured text aligned with financial planning course outlines and unstructured colloquial content from community interactions. Fields include dynamic links and real-time participant count data. Plugin request parameters must bind updatable business fields instead of using hard-coded static content. Long-text teaching script materials require tool calling configurations to adapt to long-context segmentation rules. This prevents truncation of core knowledge points. Temporary updates to activity-related marketing content require plugins to support trigger-based synchronization. Fixed-period polling must not be used, to ensure content timeliness.
How to Configure the Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
plugin_request_timeout | 30-60 seconds | Educational service marketing content material parsing and activity data pulling typically take a short time. Excessive timeout duration will block conversation flows |
tool_call_max_context_length | 8000-12000 characters | Educational marketing content often includes long-text teaching scripts or course details. This range is needed to cover complete core information |
plugin_content_type | application/json or application/x-www-form-urlencoded | This adapts to format requirements of different business interfaces. Event registration interfaces support form format. Material pulling interfaces support JSON format |
tool_call_max_tool_num | 3-5 | Educational marketing scenarios typically require calling three types of tools: material pulling, data query, and form submission. Excessive calls will increase conversation delay |
vector_model_embedding_dim | 1024 | This matches the vector model dimensions optimized for mainstream educational scenarios such as bge-large-zh-1.5, ensuring semantic recall accuracy |
tool_call_hide_ai_reply | Enabled | When only the marketing content results generated by tool calls need to be returned, native AI conversation content can be hidden to focus on business output |
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 targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- A
415 Unsupported Media Typeerror is returned when calling a plugin. This occurs becauseplugin_content_typeis not correctly configured, and the request format does not match the requirements of the target interface. - Native AI conversation text is still returned after tool calling is completed, without hiding the specified content. This happens because the
tool_call_hide_ai_replyconfiguration is not enabled, or the configuration was not saved and activated after being modified. - Marketing content returned by the plugin cannot be rendered as a custom card style. This occurs because the response data is only returned as plain text instead of following the structured format required by the platform.
How to Confirm the Configuration Is Correct
- Enter the plugin management page, check the
plugin_content_typeconfiguration item, and confirm it matches the requirements of the target interface. - Initiate a simulated call, check whether the returned response format meets the expectations of the business interface, and confirm that 415 errors no longer appear.
- After enabling the
tool_call_hide_ai_replyconfiguration, initiate a test conversation, and confirm that native AI conversation text is not displayed in the results. - Call the tool to pull educational marketing content data, check whether the returned fields include business-appropriate information such as links and audience levels, and confirm that parameter binding is correct.
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.