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Studio Generator - Uses LLM to generate flashcards and quiz questions
"""
from typing import List, Optional
import json
import re
from models.studio_models import (
Flashcard, FlashcardCreate, FlashcardGenerateRequest,
Quiz, QuizQuestion, QuizGenerateRequest,
DifficultyLevel, QuestionType
)
from utils.llm_generator import LLMGenerator
from utils.studio_manager import StudioManager
class StudioGenerator:
"""Generate flashcards and quizzes using LLM"""
def __init__(self, llm_generator: LLMGenerator, studio_manager: StudioManager):
self.llm = llm_generator
self.studio = studio_manager
async def generate_flashcards(self, request: FlashcardGenerateRequest) -> List[Flashcard]:
"""Generate flashcards from content using LLM"""
# Gather source content
content = await self._gather_content(
request.space_id,
request.source_type,
request.source_ids,
request.text_content
)
if not content:
return []
# Create prompt for LLM
prompt = self._create_flashcard_prompt(content, request.num_cards, request.difficulty)
# Generate flashcards using LLM
response = await self.llm.generate(prompt, max_tokens=2000)
if not response:
return []
# Parse flashcards from response
flashcards = self._parse_flashcards(
response,
request.space_id,
request.source_type,
request.source_ids,
request.difficulty
)
# Save flashcards to storage
saved_cards = []
for card_data in flashcards:
card = self.studio.create_flashcard(card_data)
saved_cards.append(card)
return saved_cards
async def generate_quiz(self, request: QuizGenerateRequest) -> Optional[Quiz]:
"""Generate a quiz from content using LLM"""
# Gather source content
content = await self._gather_content(
request.space_id,
request.source_type,
request.source_ids,
request.text_content
)
if not content:
return None
# Create prompt for LLM
prompt = self._create_quiz_prompt(
content,
request.num_questions,
request.question_types,
request.difficulty
)
# Generate quiz using LLM
response = await self.llm.generate(prompt, max_tokens=3000)
if not response:
return None
# Parse quiz questions from response
questions = self._parse_quiz_questions(response, request.question_types, request.difficulty)
if not questions:
return None
# Create quiz
from models.studio_models import QuizCreate
quiz_data = QuizCreate(
space_id=request.space_id,
title=request.title,
description=f"Generated quiz with {len(questions)} questions",
questions=questions,
source_type=request.source_type,
source_ids=request.source_ids
)
quiz = self.studio.create_quiz(quiz_data)
return quiz
async def _gather_content(
self,
space_id: str,
source_type: str,
source_ids: Optional[List[str]],
text_content: Optional[str]
) -> str:
"""Gather content from various sources"""
if text_content:
return text_content
content_parts = []
if source_type == "notebook" and source_ids:
# Get notebook entries
for entry_id in source_ids:
entry = self.studio.get_notebook_entry(entry_id)
if entry:
content_parts.append(f"# {entry.title}\n\n{entry.content}")
elif source_type == "file" and source_ids:
# TODO: Integrate with file retriever to get file content
# For now, just return a placeholder
content_parts.append("File content retrieval not yet implemented")
return "\n\n---\n\n".join(content_parts)
def _create_flashcard_prompt(self, content: str, num_cards: int, difficulty: DifficultyLevel) -> str:
"""Create prompt for flashcard generation"""
difficulty_desc = {
DifficultyLevel.EASY: "basic concepts and definitions",
DifficultyLevel.MEDIUM: "key concepts and applications",
DifficultyLevel.HARD: "advanced concepts and critical thinking"
}
prompt = f"""Based on the following content, create {num_cards} flashcards focusing on {difficulty_desc[difficulty]}.
Content:
{content[:3000]} # Limit content length
Format your response as a JSON array of flashcards, where each flashcard has:
- "question": The question or prompt (front of card)
- "answer": The answer or explanation (back of card)
Example format:
[
{{"question": "What is...", "answer": "It is..."}},
{{"question": "How does...", "answer": "It works by..."}}
]
Generate exactly {num_cards} flashcards:"""
return prompt
def _create_quiz_prompt(
self,
content: str,
num_questions: int,
question_types: List[QuestionType],
difficulty: DifficultyLevel
) -> str:
"""Create prompt for quiz generation"""
types_str = ", ".join(qt.value for qt in question_types)
prompt = f"""Based on the following content, create a quiz with {num_questions} questions.
Content:
{content[:3000]} # Limit content length
Question types to include: {types_str}
Difficulty level: {difficulty.value}
Format your response as a JSON array of questions, where each question has:
- "question": The question text
- "type": One of: {types_str}
- "options": Array of 4 options (for multiple_choice only)
- "correct_answer": The correct answer
- "explanation": Brief explanation of why this is correct
Example format:
[
{{
"question": "What is...",
"type": "multiple_choice",
"options": ["Option A", "Option B", "Option C", "Option D"],
"correct_answer": "Option A",
"explanation": "This is correct because..."
}},
{{
"question": "True or False: ...",
"type": "true_false",
"options": ["True", "False"],
"correct_answer": "True",
"explanation": "This is true because..."
}}
]
Generate exactly {num_questions} questions:"""
return prompt
def _parse_flashcards(
self,
response: str,
space_id: str,
source_type: str,
source_ids: Optional[List[str]],
difficulty: DifficultyLevel
) -> List[FlashcardCreate]:
"""Parse flashcards from LLM response"""
flashcards = []
try:
# Try to extract JSON from response
json_match = re.search(r'\[[\s\S]*\]', response)
if json_match:
cards_data = json.loads(json_match.group(0))
for card_data in cards_data:
if 'question' in card_data and 'answer' in card_data:
flashcards.append(FlashcardCreate(
space_id=space_id,
question=card_data['question'],
answer=card_data['answer'],
difficulty=difficulty,
source_type=source_type,
source_id=source_ids[0] if source_ids else None
))
except Exception as e:
print(f"Error parsing flashcards: {e}")
# Fallback: Try to parse as simple Q&A pairs
lines = response.split('\n')
current_question = None
for line in lines:
line = line.strip()
if line.startswith('Q:') or line.startswith('Question:'):
current_question = line.split(':', 1)[1].strip()
elif line.startswith('A:') or line.startswith('Answer:'):
if current_question:
answer = line.split(':', 1)[1].strip()
flashcards.append(FlashcardCreate(
space_id=space_id,
question=current_question,
answer=answer,
difficulty=difficulty,
source_type=source_type,
source_id=source_ids[0] if source_ids else None
))
current_question = None
return flashcards
def _parse_quiz_questions(
self,
response: str,
question_types: List[QuestionType],
difficulty: DifficultyLevel
) -> List[QuizQuestion]:
"""Parse quiz questions from LLM response"""
questions = []
try:
# Try to extract JSON from response
json_match = re.search(r'\[[\s\S]*\]', response)
if json_match:
questions_data = json.loads(json_match.group(0))
for idx, q_data in enumerate(questions_data):
import uuid
# Parse question type
q_type = QuestionType.MULTIPLE_CHOICE
if 'type' in q_data:
try:
q_type = QuestionType(q_data['type'])
except ValueError:
q_type = QuestionType.MULTIPLE_CHOICE
questions.append(QuizQuestion(
id=str(uuid.uuid4()),
question=q_data.get('question', ''),
type=q_type,
options=q_data.get('options'),
correct_answer=q_data.get('correct_answer', ''),
explanation=q_data.get('explanation'),
points=1,
difficulty=difficulty
))
except Exception as e:
print(f"Error parsing quiz questions: {e}")
return questions
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