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import os
import json
import logging
import random
from langchain_groq import ChatGroq
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import JsonOutputParser
# Configure Logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(levelname)s - %(message)s",
handlers=[
logging.FileHandler("test.log"),
logging.StreamHandler()
]
)
# Set API Key (Ensure you have this set as an environment variable)
GROQ_API_KEY = os.getenv("GROQ_API_KEY", "your_api_key")
# Initialize LangChain LLM with Groq
llm = ChatGroq(
model_name="llama-3.3-70b-versatile",
temperature=0.7, # Increased randomness for variety
api_key=GROQ_API_KEY
)
# Define JSON Output Format
parser = JsonOutputParser(pydantic_object={
"type": "object",
"properties": {
"theme": {"type": "string"},
"question": {"type": "string"},
"options": {
"type": "array",
"items": {"type": "string"},
"minItems": 4,
"maxItems": 4
},
"correct_answer": {"type": "string"},
"difficulty": {"type": "string", "enum": ["Easy", "Medium", "Hard"]}
},
"required": ["theme", "question", "options", "correct_answer", "difficulty"]
})
# **🔹 FIXED Prompt Template (Escaped Theme & Proper Variable Passing)**
prompt = ChatPromptTemplate.from_messages([
("system", "You are a quiz generator that ensures each generated question is unique."),
("user", """Generate a unique multiple-choice quiz question for the theme: {{theme}}.
- Ensure the question is unique and has never been asked before in this session.
- The question should have 4 answer choices labeled A, B, C, D.
- Clearly specify the correct answer (one of A, B, C, D).
- Assign a difficulty level (Easy, Medium, Hard).
- Do not generate a question similar to the ones listed below.
Previously generated questions:
{{previous_questions}}
Return the result in this JSON format:
{{
"theme": "{{theme}}",
"question": "The generated quiz question",
"options": ["A) Option 1", "B) Option 2", "C) Option 3", "D) Option 4"],
"correct_answer": "Correct option letter",
"difficulty": "Easy/Medium/Hard"
}}
""")
])
# **🔹 Create Chain with History to Prevent Duplicates**
chat_history = [] # Stores previous questions
chain = prompt | llm | parser
# **List of Fixed Themes**
fixed_themes = ["Science", "History", "Geography", "Technology", "Mathematics"]
def generate_unique_question(theme):
"""
Generates a quiz question ensuring uniqueness within a session.
Theme is manually passed as input.
"""
try:
previous_questions = "\n".join(chat_history) if chat_history else "None"
# **🔹 Ensure Correct Input Variables Are Passed**
response = chain.invoke({
"theme": theme,
"previous_questions": previous_questions
})
if "theme" not in response or "question" not in response:
logging.error("Invalid response from LLM: %s", response)
return None
# Extract theme and question
question_text = response["question"]
# Ensure the question is unique
if question_text in chat_history:
logging.warning("Duplicate question detected, regenerating...")
return generate_unique_question(theme) # Retry with the same theme
chat_history.append(question_text) # Store to avoid duplicates
logging.info("Generated Question:\n%s", json.dumps(response, indent=2))
return response
except Exception as e:
logging.error("Error generating quiz question: %s", e)
return None
# **🔹 Run Test for 10 Questions Using Fixed Themes**
if __name__ == "__main__":
total_questions = 10 # Generate 10 questions
for i in range(total_questions):
theme = random.choice(fixed_themes) # Pick a random theme from the list
print(f"\n📝 Generating Question {i+1} for Theme: {theme}\n")
question = generate_unique_question(theme)
if question:
print(json.dumps(question, indent=2))
else:
print(f"❌ Failed to generate a question for {theme}.")
print("\n✅ Test completed! Check test.log for details.")
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