File size: 3,119 Bytes
25732fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | 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:
# Check if template is applicable to this topic (simple keyword match for now)
# In a real system, this would be a more robust tag matching
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
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