Okay, the user previously asked for a rubric template to evaluate system roles in their AI teaching chatbot. Now they need a template for the system roles themselves, specifically for the JSON messages sent to the AI model API. Let me break down their requirements.
First, the JSON message includes user message, memory (past messages), system role, and a knowledge base with content, videos, and pictures. The user wants a structured template for these system roles.
I need to consider the components of a system role in an AI chatbot context. The system role would define the AI’s behavior, responsibilities, and how it uses the provided data. The template should be in JSON format as that’s the data interchange format mentioned.
Looking at the previous response, I created a rubric with categories like Content Accuracy and Adaptability. Now, the focus is on the structure of the system role configuration. The user probably wants each system role (like Instructor, Tutor, Moderator) to have specific configurations that dictate how the AI behaves when that role is active.
I should start by outlining the possible system roles. For each role, parameters like role_name, description, instructions, allowed_content_types, interaction_style, etc., would be important. The instructions need to be clear prompts for the AI to follow. The knowledge base should include sources and how to handle media like videos and pictures.
Also, the memory component needs to be addressed. How much context should the AI retain? Maybe a max_context_length parameter. The response format should specify if it’s text, markdown, or includes multimedia. Error handling is another aspect—what should the AI do if it doesn’t know an answer or encounters technical issues.
Security and accessibility are important too. Ensuring that the AI adheres to FERPA or GDPR if applicable. Accessibility features like alt text for images.
Including examples will help the user understand how to implement the template. Maybe an example for an Instructor role explaining physics, using a video from the knowledge base.
I should structure the JSON template with all these sections, making sure each part is optional where necessary. Also, provide guidance on how to use the template, like defining roles based on educational needs and iterating based on feedback.
I need to ensure the template is comprehensive yet flexible, allowing the user to customize it for different roles and scenarios. Checking if all the components mentioned in the user’s query are covered: user message, memory, system role, knowledge base with multimedia. Yes, the template includes memory with max_context_length, system_role configuration, knowledge_base with content_sources and media_handling.
I should also mention best practices, like keeping instructions clear and testing roles thoroughly. This helps the user avoid common pitfalls when setting up their system roles.
Finally, the example use case will illustrate how the template is applied in a real scenario, making it easier for the user to visualize. Including an example for a Tutor role assisting with algebra homework shows practical application.
Make sure the JSON structure is valid and properly formatted. Use comments if necessary, but since JSON doesn’t support comments, maybe include notes in the explanation instead. Also, consider optional parameters to allow flexibility, so not all fields are required unless necessary.
Alright, putting it all together into a JSON template with explanations and examples should meet the user’s needs. They can then customize this template for each system role in their AI teaching chatbot.
Here’s a structured JSON template for system roles in an AI teaching chatbot, designed to organize inputs like user messages, memory, system roles, and knowledge base content. This template ensures the AI model API can dynamically adapt its behavior for different teaching scenarios.
System Role Configuration Template
{
"system_role": {
"role_name": "Instructor", // E.g., Tutor, Moderator, Technical Support, Quizmaster
"description": "Defines the AI's behavior and responsibilities for this role.",
"parameters": {
"instructions": {
"primary_goal": "Teach algebra concepts to high school students",
"tone": "Encouraging and patient",
"allowed_content_types": ["text", "equations", "diagrams", "videos"],
"interaction_style": "Socratic questioning with step-by-step explanations",
"constraints": [
"Avoid solving problems directly; guide learners instead",
"Use only curriculum-approved materials from the knowledge base"
]
},
"knowledge_base": {
"content_sources": [
{
"type": "textbook",
"reference": "Algebra 101 (Chapter 3: Linear Equations)",
"sections": ["3.1", "3.2", "3.4"]
},
{
"type": "video",
"title": "Solving Linear Equations by Khan Academy",
"url": "https://example.com/linear-equations-video",
"key_concepts": ["slope", "intercepts"]
},
{
"type": "diagram",
"title": "Graphing Linear Equations",
"file": "graph.png",
"description": "Visual guide to plotting equations"
}
],
"media_handling": {
"images": "Describe visuals in detail for accessibility",
"videos": "Summarize key points if the student can't watch"
}
},
"memory": {
"max_context_length": 5, // Number of past messages to retain
"persistent_memory_keys": ["student_name", "learning_style", "weakness_areas"]
},
"response_rules": {
"format": "markdown", // Options: text, markdown, html
"structure": {
"example_solution": "Required for math problems",
"feedback_type": "Constructive with emojis",
"multimedia_inclusion": "Embed diagrams or videos when relevant"
},
"error_handling": {
"unknown_queries": "Redirect to human teacher after 2 attempts",
"technical_errors": "Apologize and suggest restarting the conversation"
}
}
},
"security": {
"data_privacy": "FERPA-compliant (no personal data storage)",
"accessibility": "WCAG 2.1 AA standards (alt text for images)"
}
},
"user_message": "How do I solve 2x + 5 = 15?",
"memory": [
{ "role": "student", "content": "I struggle with isolating variables." },
{ "role": "AI", "content": "Let's review inverse operations. What undoes '+ 5'?" }
]
}Key Components Explained
- System Role
- Defines the AI’s behavior (e.g., strict tutor vs. friendly mentor).
- Includes instructions, knowledge base (videos, diagrams, text), memory settings, and response rules.
- Knowledge Base
- Curated content (e.g., textbook chapters, videos) the AI can reference.
- Rules for handling multimedia (e.g., describing images for accessibility).
- Memory
- Retains conversation history and persistent student data (e.g., learning style).
- Adjust
max_context_lengthto balance context vs. performance.
- Response Rules
- Formatting guidelines (e.g., Markdown for equations).
- Error-handling protocols (e.g., redirecting unresolved queries).
- Security & Accessibility
- Ensures compliance with privacy laws (e.g., FERPA) and accessibility standards.
Example Use Cases
- Role: Tutor “role_name”: “Homework Tutor”, “instructions”: (“primary_goal”: “Provide hints for coding assignments”, “allowed_content_types”: (“code_snippets”, “debugging_tips”))
- Role: Moderator “role_name”: “Discussion Moderator”, “instructions”: ( “primary_goal”: “Facilitate group debates on climate change”, “constraints”: (“Enforce respectful language”, “Flag off-topic comments”))
- Role: Quizmaster “response_rules”: ( “structure”: “Include multiple-choice questions after each topic”, “feedback_type”: “Immediate correctness feedback” )
Implementation Tips
- Dynamic Role Switching: Use metadata to trigger role changes (e.g.,
"role": "Tutor"when a student asks for help). - Testing: Validate each role’s performance with sample student queries (e.g., confusion about a video).
- Iterate: Update the knowledge base and memory rules based on student feedback.
This template ensures your AI chatbot can adapt to diverse teaching scenarios while maintaining consistency and compliance. Let me know if you need help refining specific roles!
Leave a Reply