| import json |
| import os |
| import random |
|
|
| class AssessmentRuleEngine: |
| """ |
| Expert system for assessment decisions. |
| Selects questions and formats quizzes based on rules and templates. |
| """ |
| |
| def __init__(self, knowledge_base_path=None): |
| if knowledge_base_path is None: |
| base_dir = os.path.dirname(os.path.dirname(__file__)) |
| knowledge_base_path = os.path.join(base_dir, 'knowledge_bases', 'question_templates.json') |
| |
| self.question_templates = [] |
| self.rubrics = {} |
| self._load_knowledge_base(knowledge_base_path) |
| |
| def _load_knowledge_base(self, path): |
| try: |
| with open(path, 'r') as f: |
| data = json.load(f) |
| self.question_templates = data.get('question_templates', []) |
| self.rubrics = data.get('assessment_rubrics', {}) |
| except Exception as e: |
| print(f"Error loading assessment knowledge base: {e}") |
|
|
| def select_question_types(self, knowledge_level, topic_difficulty): |
| """ |
| Determine the mix of question types/difficulties. |
| """ |
| mix = {"beginner": 0, "intermediate": 0, "advanced": 0} |
| |
| if knowledge_level < 0.3: |
| mix["beginner"] = 3 |
| mix["intermediate"] = 1 |
| elif knowledge_level < 0.7: |
| mix["beginner"] = 1 |
| mix["intermediate"] = 2 |
| mix["advanced"] = 1 |
| else: |
| mix["intermediate"] = 2 |
| mix["advanced"] = 3 |
| |
| return mix |
|
|
| def get_template_for_topic(self, topic_name, difficulty): |
| """ |
| Find a question template suitable for the topic and difficulty. |
| """ |
| candidates = [] |
| for t in self.question_templates: |
| |
| |
| is_applicable = "all" in t['applicable_topics'] |
| if not is_applicable: |
| for keyword in t['applicable_topics']: |
| if keyword in topic_name.lower(): |
| is_applicable = True |
| break |
| |
| if is_applicable: |
| candidates.append(t) |
| |
| if not candidates: |
| return None |
| |
| return random.choice(candidates) |
|
|
| def formulate_question_prompt(self, template, topic_name, difficulty): |
| """ |
| Use a template to create a specific prompt for the LLM to fill. |
| This reduces the LLM's work to just filling blanks/generating code. |
| """ |
| modifier = template['difficulty_modifiers'].get(difficulty, "Standard") |
| |
| prompt = f""" |
| Generate a specific question about "{topic_name}" using this pattern: |
| "{template['pattern']}" |
| |
| Constraint: {modifier} |
| Cognitive Level: {template['cognitive_level']} |
| |
| Return the Code Snippet (if applicable), Options, Correct Answer, and Explanation. |
| """ |
| return prompt |
|
|
