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| import streamlit as st | |
| import random | |
| import streamlit as st | |
| import random | |
| import streamlit as st | |
| import random | |
| import time | |
| # Sample questions for each category | |
| questions = { | |
| "Python Basics": [ | |
| {"question": "What is the output of print(type([]))?", "options": ["<class 'list'>", "<class 'dict'>", "<class 'tuple'>"], "answer": "<class 'list'>"}, | |
| {"question": "What keyword is used to define a function in Python?", "options": ["def", "function", "fun"], "answer": "def"}, | |
| {"question": "How do you create a list in Python?", "options": ["[]", "{}", "()"], "answer": "[]"}, | |
| {"question": "What method adds an element to the end of a list?", "options": ["append()", "add()", "insert()"], "answer": "append()"}, | |
| {"question": "What is the purpose of the self keyword in class methods?", "options": ["To refer to the instance", "To refer to the class", "To define a function"], "answer": "To refer to the instance"}, | |
| {"question": "How can you handle exceptions in Python?", "options": ["try/except", "catch", "throw"], "answer": "try/except"}, | |
| {"question": "What is the difference between == and is?", "options": ["Value vs Identity", "Type vs Value", "None"], "answer": "Value vs Identity"}, | |
| {"question": "How do you read a file in Python?", "options": ["open()", "read()", "file()"], "answer": "open()"}, | |
| {"question": "What does the len() function do?", "options": ["Returns the length", "Returns the type", "Returns the sum"], "answer": "Returns the length"}, | |
| {"question": "How can you convert a string to an integer?", "options": ["int()", "str()", "float()"], "answer": "int()"}, | |
| {"question": "What is a lambda function?", "options": ["Anonymous function", "A type of loop", "None"], "answer": "Anonymous function"}, | |
| {"question": "How do you create a dictionary in Python?", "options": ["{}", "[]", "()"], "answer": "{}"}, | |
| {"question": "What is list comprehension?", "options": ["Creating lists from existing lists", "Creating dictionaries", "None"], "answer": "Creating lists from existing lists"}, | |
| {"question": "What does the map() function do?", "options": ["Applies a function to all items", "Filters items", "None"], "answer": "Applies a function to all items"}, | |
| {"question": "How can you remove duplicates from a list?", "options": ["set()", "unique()", "distinct()"], "answer": "set()"}, | |
| {"question": "What is the purpose of the with statement?", "options": ["Resource management", "Looping", "Condition checking"], "answer": "Resource management"}, | |
| {"question": "How do you merge two dictionaries in Python?", "options": ["dict.update()", "dict.merge()", "dict.concat()"], "answer": "dict.update()"}, | |
| {"question": "What is the difference between a list and a tuple?", "options": ["Mutability", "Size", "Type"], "answer": "Mutability"}, | |
| {"question": "How do you iterate over a dictionary?", "options": ["for key in dict", "for dict in key", "for item in dict"], "answer": "for key in dict"}, | |
| {"question": "What is the purpose of the enumerate() function?", "options": ["To get index and value", "To filter lists", "None"], "answer": "To get index and value"}, | |
| {"question": "How can you reverse a list?", "options": ["list.reverse()", "list[::-1]", "None"], "answer": "list.reverse()"}, | |
| {"question": "What is a generator in Python?", "options": ["An iterable", "A function", "Both"], "answer": "Both"}, | |
| {"question": "How do you define a class in Python?", "options": ["class ClassName:", "def ClassName:", "create ClassName:"], "answer": "class ClassName:"}, | |
| {"question": "What is the output of print('Hello' * 3)?", "options": ["HelloHelloHello", "3Hello", "Hello 3"], "answer": "HelloHelloHello"}, | |
| {"question": "How do you check if a key exists in a dictionary?", "options": ["key in dict", "dict.has_key()", "None"], "answer": "key in dict"}, | |
| {"question": "What is the difference between deep copy and shallow copy?", "options": ["Copy level", "Type of data", "None"], "answer": "Copy level"}, | |
| {"question": "How do you sort a list in Python?", "options": ["list.sort()", "sorted(list)", "Both"], "answer": "Both"}, | |
| {"question": "What is the purpose of the __init__ method?", "options": ["Constructor", "Destructor", "None"], "answer": "Constructor"}, | |
| {"question": "How can you concatenate two strings?", "options": ["str1 + str2", "str1.concat(str2)", "None"], "answer": "str1 + str2"}, | |
| {"question": "What is the output of print(bool(''))?", "options": ["False", "True", "None"], "answer": "False"}, | |
| {"question": "What is the output of print(type({}))?", "options": ["<class 'dict'>", "<class 'list'>", "<class 'tuple'>"], "answer": "<class 'dict'>"}, | |
| {"question": "What is the output of print(type(()))?", "options": ["<class 'tuple'>", "<class 'list'>", "<class 'dict'>"], "answer": "<class 'tuple'>"}, | |
| {"question": "What is a decorator in Python?", "options": ["A function that wraps another function", "A type of class", "None"], "answer": "A function that wraps another function"}, | |
| {"question": "How do you create a virtual environment?", "options": ["python -m venv env", "venv create env", "env create"], "answer": "python -m venv env"}, | |
| {"question": "What is the purpose of the global keyword?", "options": ["To access global variables", "To create global variables", "None"], "answer": "To access global variables"}, | |
| {"question": "How can you iterate through a list with index?", "options": ["for i, value in enumerate(list)", "for i in range(len(list))", "None"], "answer": "for i, value in enumerate(list)"}, | |
| {"question": "What is the output of print('Hello'.upper())?", "options": ["HELLO", "Hello", "hello"], "answer": "HELLO"}, | |
| {"question": "How do you remove an item from a list by value?", "options": ["list.remove(value)", "list.pop(value)", "None"], "answer": "list.remove(value)"}, | |
| {"question": "What does the zip() function do?", "options": ["Combines lists", "Filters lists", "None"], "answer": "Combines lists"}, | |
| {"question": "What is the purpose of the assert statement?", "options": ["To check conditions", "To display output", "None"], "answer": "To check conditions"}, | |
| {"question": "How do you create a set in Python?", "options": ["set()", "{}", "Both"], "answer": "Both"}, | |
| {"question": "What is the difference between append() and extend()?", "options": ["Adding single vs multiple items", "Type of item added", "None"], "answer": "Adding single vs multiple items"}, | |
| {"question": "What is a docstring?", "options": ["Documentation string", "Error message", "None"], "answer": "Documentation string"}, | |
| {"question": "How do you sort a dictionary by value?", "options": ["sorted(dict.items())", "dict.sort()", "None"], "answer": "sorted(dict.items())"}, | |
| {"question": "What is the purpose of the pass statement?", "options": ["Placeholder for future code", "To exit a loop", "None"], "answer": "Placeholder for future code"}, | |
| {"question": "What is the use of the in keyword?", "options": ["To check membership", "To iterate", "None"], "answer": "To check membership"}, | |
| {"question": "What is the output of print(bool([]))?", "options": ["False", "True", "None"], "answer": "False"}, | |
| {"question": "How do you copy a list in Python?", "options": ["list.copy()", "list[:] or list.copy()", "None"], "answer": "list[:] or list.copy()"}, | |
| {"question": "What is the output of print(3 == 3.0)?", "options": ["True", "False", "None"], "answer": "True"}, | |
| ], | |
| "Data Science": [ | |
| {"question": "What is the purpose of data normalization?", "options": ["To scale data", "To clean data", "None"], "answer": "To scale data"}, | |
| {"question": "What does EDA stand for?", "options": ["Exploratory Data Analysis", "Effective Data Analytics", "None"], "answer": "Exploratory Data Analysis"}, | |
| {"question": "What library is commonly used for data manipulation in Python?", "options": ["NumPy", "Pandas", "Matplotlib"], "answer": "Pandas"}, | |
| {"question": "What is the difference between supervised and unsupervised learning?", "options": ["Labeled vs Unlabeled data", "Type of algorithms", "None"], "answer": "Labeled vs Unlabeled data"}, | |
| {"question": "What is a confusion matrix used for?", "options": ["Evaluating classification models", "Data visualization", "None"], "answer": "Evaluating classification models"}, | |
| {"question": "What is overfitting?", "options": ["Model learns noise", "Underfitting", "None"], "answer": "Model learns noise"}, | |
| {"question": "How can you handle missing values in a dataset?", "options": ["Drop, fill, or interpolate", "Ignore", "None"], "answer": "Drop, fill, or interpolate"}, | |
| {"question": "What does PCA stand for?", "options": ["Principal Component Analysis", "Partial Correlation Analysis", "None"], "answer": "Principal Component Analysis"}, | |
| {"question": "What is the purpose of feature scaling?", "options": ["To normalize data", "To reduce dimensionality", "None"], "answer": "To normalize data"}, | |
| {"question": "What is a scatter plot used for?", "options": ["Showing relationships", "Data distribution", "None"], "answer": "Showing relationships"}, | |
| {"question": "What is the difference between classification and regression?", "options": ["Categorical vs Continuous", "Type of output", "None"], "answer": "Categorical vs Continuous"}, | |
| {"question": "What library is used for data visualization in Python?", "options": ["Matplotlib", "Pandas", "NumPy"], "answer": "Matplotlib"}, | |
| {"question": "What does 'AI' stand for?", "options": ["Artificial Intelligence", "Automated Interface", "Applied Informatics"], "answer": "Artificial Intelligence"}, | |
| {"question": "What is a hypothesis test?", "options": ["Statistical test", "Data cleaning method", "None"], "answer": "Statistical test"}, | |
| {"question": "What is the purpose of cross-validation?", "options": ["Model evaluation", "Data cleaning", "None"], "answer": "Model evaluation"}, | |
| {"question": "What is a time series analysis?", "options": ["Analyzing data over time", "Data distribution", "None"], "answer": "Analyzing data over time"}, | |
| {"question": "What does the term 'bias' refer to in machine learning?", "options": ["Error due to assumptions", "Data imbalance", "Both"], "answer": "Both"}, | |
| {"question": "What is a decision tree?", "options": ["Model for classification", "Data visualization", "None"], "answer": "Model for classification"}, | |
| {"question": "What is the purpose of the K-means algorithm?", "options": ["Clustering", "Classification", "None"], "answer": "Clustering"}, | |
| {"question": "What is A/B testing?", "options": ["Comparing two versions", "Data cleaning", "None"], "answer": "Comparing two versions"}, | |
| {"question": "What does the term 'outlier' mean?", "options": ["An extreme value", "Average value", "None"], "answer": "An extreme value"}, | |
| {"question": "How can you determine the correlation between two variables?", "options": ["Using correlation coefficient", "Visual inspection", "None"], "answer": "Using correlation coefficient"}, | |
| {"question": "What is the significance of the ROC curve?", "options": ["Evaluating classifiers", "Data visualization", "None"], "answer": "Evaluating classifiers"}, | |
| {"question": "What is a categorical variable?", "options": ["Qualitative variable", "Quantitative variable", "None"], "answer": "Qualitative variable"}, | |
| {"question": "What is the role of a data engineer?", "options": ["Data pipeline construction", "Data analysis", "None"], "answer": "Data pipeline construction"}, | |
| {"question": "How do you evaluate a machine learning model?", "options": ["Using metrics", "Visual inspection", "None"], "answer": "Using metrics"}, | |
| {"question": "What is the purpose of feature engineering?", "options": ["Improving model performance", "Data cleaning", "None"], "answer": "Improving model performance"}, | |
| {"question": "What is a linear regression model?", "options": ["Predicts continuous values", "Classifies data", "None"], "answer": "Predicts continuous values"}, | |
| {"question": "What are the assumptions of linear regression?", "options": ["Linearity, independence", "Normality, homoscedasticity", "Both"], "answer": "Both"}, | |
| {"question": "What does the term 'ensemble learning' mean?", "options": ["Combining multiple models", "Single model", "None"], "answer": "Combining multiple models"}, | |
| {"question": "What is a random forest?", "options": ["Ensemble of decision trees", "Single decision tree", "None"], "answer": "Ensemble of decision trees"}, | |
| {"question": "What is the purpose of data visualization?", "options": ["To convey information", "To clean data", "None"], "answer": "To convey information"}, | |
| {"question": "What is the difference between classification and clustering?", "options": ["Labeled vs Unlabeled data", "Model type", "None"], "answer": "Labeled vs Unlabeled data"}, | |
| {"question": "What does an F1 score measure?", "options": ["Model accuracy", "Balance between precision and recall", "None"], "answer": "Balance between precision and recall"}, | |
| {"question": "What is feature selection?", "options": ["Choosing important features", "Data cleaning", "None"], "answer": "Choosing important features"}, | |
| {"question": "What is the purpose of clustering?", "options": ["Grouping similar items", "Data cleaning", "None"], "answer": "Grouping similar items"}, | |
| {"question": "What is k-fold cross-validation?", "options": ["Dividing data into k subsets", "Data cleaning", "None"], "answer": "Dividing data into k subsets"}, | |
| {"question": "What is the output of linear regression?", "options": ["A line", "A decision tree", "None"], "answer": "A line"}, | |
| ], | |
| "Generative AI": [ | |
| {"question": "What is the primary function of Generative AI models?", "options": ["To generate new data", "To classify data", "To clean data"], "answer": "To generate new data"}, | |
| {"question": "What does GAN stand for in the context of Generative AI?", "options": ["Generative Adversarial Network", "Generalized Automated Network", "None"], "answer": "Generative Adversarial Network"}, | |
| {"question": "What is the role of a generator and discriminator in GANs?", "options": ["Generator creates data, Discriminator evaluates it", "Generator evaluates data, Discriminator creates it", "None"], "answer": "Generator creates data, Discriminator evaluates it"}, | |
| {"question": "How does a Variational Autoencoder (VAE) differ from a GAN?", "options": ["VAE generates data probabilistically", "GAN uses a single model", "None"], "answer": "VAE generates data probabilistically"}, | |
| {"question": "What is the purpose of a Latent Space in a Generative model?", "options": ["To represent data in a compressed form", "To clean data", "None"], "answer": "To represent data in a compressed form"}, | |
| {"question": "How does a Transformer architecture contribute to Generative AI?", "options": ["By processing sequential data", "By generating images", "None"], "answer": "By processing sequential data"}, | |
| {"question": "What is a Markov Chain Monte Carlo (MCMC) used for in Generative AI?", "options": ["For generating synthetic data", "For data clustering", "None"], "answer": "For generating synthetic data"}, | |
| {"question": "How does a text-to-image Generative model work?", "options": ["By converting textual descriptions to visual content", "By using data augmentation", "None"], "answer": "By converting textual descriptions to visual content"}, | |
| {"question": "What are some real-world applications of Generative AI in creative industries?", "options": ["Art generation", "Music composition", "Both"], "answer": "Both"}, | |
| {"question": "What is the significance of the attention mechanism in Generative AI models?", "options": ["It helps the model focus on relevant parts of data", "It improves data cleaning", "None"], "answer": "It helps the model focus on relevant parts of data"}, | |
| {"question": "What are the ethical concerns associated with Generative AI?", "options": ["Deepfakes", "Copyright infringement", "Both"], "answer": "Both"}, | |
| {"question": "How can Generative AI be used in content creation (e.g., art, music, and writing)?", "options": ["By generating new works based on patterns", "By analyzing existing content", "None"], "answer": "By generating new works based on patterns"}, | |
| {"question": "What is the role of reinforcement learning in Generative AI models?", "options": ["It helps the model learn from feedback", "It improves data scaling", "None"], "answer": "It helps the model learn from feedback"}, | |
| {"question": "What are the challenges in training large-scale Generative AI models?", "options": ["Computational resources", "Model complexity", "Both"], "answer": "Both"}, | |
| {"question": "How does GPT (Generative Pretrained Transformer) function in text generation?", "options": ["By using pre-trained knowledge", "By using data from the web", "None"], "answer": "By using pre-trained knowledge"}, | |
| {"question": "What is the significance of unsupervised learning in the context of Generative AI?", "options": ["It allows for learning without labeled data", "It requires labeled data", "None"], "answer": "It allows for learning without labeled data"}, | |
| {"question": "What are some risks of deepfake generation in Generative AI?", "options": ["Misinformation", "Privacy invasion", "Both"], "answer": "Both"}, | |
| {"question": "How does a Diffusion Model in Generative AI generate images?", "options": ["By iteratively refining images", "By using neural networks", "None"], "answer": "By iteratively refining images"}, | |
| {"question": "What is the difference between a Generative model and a Discriminative model?", "options": ["Generative models generate data", "Discriminative models generate data", "None"], "answer": "Generative models generate data"}, | |
| {"question": "What are the key differences between GANs and VAEs in generating images?", "options": ["GANs use adversarial networks, VAEs use probabilistic modeling", "GANs and VAEs are identical", "None"], "answer": "GANs use adversarial networks, VAEs use probabilistic modeling"}, | |
| {"question": "How do generative models contribute to data augmentation in machine learning?", "options": ["By creating new synthetic data", "By labeling data", "None"], "answer": "By creating new synthetic data"}, | |
| {"question": "What are some limitations of Generative AI in text generation?", "options": ["Lack of Human Contextual Understanding", "Overfitting", "None"], "answer": "Lack of Human Contextual Understanding"}, | |
| {"question": "How can Generative AI be applied in drug discovery and biology?", "options": ["By predicting molecular structures", "By generating new drugs", "None"], "answer": "By predicting molecular structures"}, | |
| {"question": "What is the concept of \"sampling\" in the context of Generative AI?", "options": ["Selecting data points to generate new samples", "Cleaning data", "None"], "answer": "Selecting data points to generate new samples"}, | |
| {"question": "How does reinforcement learning improve the performance of generative models?", "options": ["By encouraging exploration", "By reducing data bias", "None"], "answer": "By encouraging exploration"}, | |
| {"question": "What are the applications of GANs in computer vision?", "options": ["Image generation", "Image enhancement", "Both"], "answer": "Both"}, | |
| {"question": "How do large pre-trained models like GPT-3 enable text generation?", "options": ["By leveraging vast amounts of data", "By using unsupervised learning", "None"], "answer": "By leveraging vast amounts of data"}, | |
| {"question": "What role do neural networks play in Generative AI?", "options": ["They model complex data relationships", "They clean data", "None"], "answer": "They model complex data relationships"}, | |
| {"question": "What are some challenges in ensuring diversity in generated outputs by Generative AI?", "options": ["Mode collapse", "Lack of Human Contextual Understanding", "Both"], "answer": "Both"}, | |
| {"question": "How does Conditional Generative AI work in generating targeted outputs?", "options": ["By conditioning on specific inputs", "By using unsupervised learning", "None"], "answer": "By conditioning on specific inputs"}, | |
| {"question": "What is the difference between a Generative AI model and a regular neural network?", "options": ["Generative AI models create data", "Both are the same", "None"], "answer": "Generative AI models create data"}, | |
| {"question": "What is the concept of “mode collapse” in GANs?", "options": ["Generator produces limited outputs", "Discriminator fails to identify fake data", "None"], "answer": "Generator produces limited outputs"}, | |
| {"question": "What are some tools used to evaluate the performance of a Generative AI model?", "options": ["Inception Score", "Fréchet Inception Distance", "Both"], "answer": "Both"}, | |
| {"question": "How can Generative AI assist in designing new architectures or solutions?", "options": ["By proposing new designs based on data patterns", "By cleaning data", "None"], "answer": "By proposing new designs based on data patterns"}, | |
| {"question": "How does text-to-speech generation work in Generative AI models?", "options": ["By converting text to audible speech", "By generating text-based content", "None"], "answer": "By converting text to audible speech"}, | |
| {"question": "What are the implications of Generative AI for intellectual property and copyright?", "options": ["Copyright ownership of generated content", "Unclear legal framework", "Both"], "answer": "Both"}, | |
| {"question": "How can Generative AI models be used to create synthetic data for training?", "options": ["By generating new data similar to real data", "By cleaning existing data", "None"], "answer": "By generating new data similar to real data"}, | |
| {"question": "What is the role of the \"latent vector\" in Generative AI models like GANs?", "options": ["It represents the compressed input data", "It generates random noise", "None"], "answer": "It represents the compressed input data"}, | |
| {"question": "What is the role of fine-tuning in generative models like GPT-3?", "options": ["It helps adapt the model to specific tasks", "It increases model size", "None"], "answer": "It helps adapt the model to specific tasks"}, | |
| {"question": "How does transfer learning enhance the capabilities of Generative AI models?", "options": ["By leveraging pre-trained knowledge", "By increasing model complexity", "None"], "answer": "By leveraging pre-trained knowledge"} | |
| ], | |
| "Agentic AI": [ | |
| {"question": "What does the term “Agentic AI” refer to?", "options": ["AI with autonomous decision-making capabilities", "AI for data classification", "None"], "answer": "AI with autonomous decision-making capabilities"}, | |
| {"question": "How do autonomous agents interact with their environment in Agentic AI?", "options": ["By perceiving and acting based on feedback", "By collecting data", "None"], "answer": "By perceiving and acting based on feedback"}, | |
| {"question": "What is the key difference between reactive AI and Agentic AI?", "options": ["Agentic AI makes autonomous decisions", "Reactive AI makes autonomous decisions", "None"], "answer": "Agentic AI makes autonomous decisions"}, | |
| {"question": "How does decision-making occur in Agentic AI systems?", "options": ["Based on feedback and goal optimization", "By following pre-defined rules", "None"], "answer": "Based on feedback and goal optimization"}, | |
| {"question": "What is reinforcement learning, and how is it used in Agentic AI?", "options": ["A learning method based on rewards and penalties", "A supervised learning technique", "None"], "answer": "A learning method based on rewards and penalties"}, | |
| {"question": "How do Agentic AI systems handle multi-agent environments?", "options": ["By collaborating or competing with other agents", "By acting independently", "None"], "answer": "By collaborating or competing with other agents"}, | |
| {"question": "What is the concept of a reward signal in Agentic AI?", "options": ["A feedback used to guide decision-making", "A measure of performance", "None"], "answer": "A feedback used to guide decision-making"}, | |
| {"question": "What is the role of exploration and exploitation in Agentic AI?", "options": ["Exploration seeks new knowledge, Exploitation maximizes reward", "Both are the same", "None"], "answer": "Exploration seeks new knowledge, Exploitation maximizes reward"}, | |
| {"question": "How does the concept of bounded rationality apply to Agentic AI?", "options": ["AI agents make optimal decisions within limits", "AI agents always make the best decisions", "None"], "answer": "AI agents make optimal decisions within limits"}, | |
| {"question": "How do Agentic AI systems optimize their actions to achieve long-term goals?", "options": ["By evaluating actions over time", "By following fixed rules", "None"], "answer": "By evaluating actions over time"}, | |
| {"question": "What challenges do Agentic AI systems face when dealing with ambiguity or uncertainty?", "options": ["Limited information and unpredictable outcomes", "Too much data", "None"], "answer": "Limited information and unpredictable outcomes"}, | |
| {"question": "How do ethics and responsibility play a role in the design of Agentic AI?", "options": ["Ensuring AI decisions align with human values", "Reducing computational resources", "None"], "answer": "Ensuring AI decisions align with human values"}, | |
| {"question": "What is the difference between deliberative and reactive decision-making in Agentic AI?", "options": ["Deliberative involves planning, Reactive involves immediate responses", "Both are the same", "None"], "answer": "Deliberative involves planning, Reactive involves immediate responses"}, | |
| {"question": "What is the concept of “autonomy” in Agentic AI systems?", "options": ["Ability to make independent decisions", "Ability to collect data", "None"], "answer": "Ability to make independent decisions"}, | |
| {"question": "How does reward shaping affect the behavior of Agentic AI?", "options": ["It modifies the reward signal to guide behavior", "It removes negative rewards", "None"], "answer": "It modifies the reward signal to guide behavior"}, | |
| {"question": "What are some key examples of Agentic AI in real-world applications?", "options": ["Autonomous vehicles", "Chatbots", "Both"], "answer": "Both"}, | |
| {"question": "How can Agentic AI systems learn from past experiences to improve future decisions?", "options": ["Through reinforcement learning", "By observing human actions", "None"], "answer": "Through reinforcement learning"}, | |
| {"question": "What are some of the safety concerns with fully autonomous Agentic AI?", "options": ["Unintended actions", "Lack of Human Oversight", "Both"], "answer": "Both"}, | |
| {"question": "What techniques are used to prevent agent misbehavior in Agentic AI systems?", "options": ["Constraints, monitoring, and reward adjustments", "None", "Both"], "answer": "Constraints, monitoring, and reward adjustments"} | |
| ] | |
| } | |
| def main(): | |
| st.set_page_config(page_title="Smart Quiz Generator", page_icon="🧠", layout="centered") | |
| st.markdown(""" | |
| <style> | |
| /* Main Content Area Background */ | |
| .stApp { | |
| background-image: url('https://images.rawpixel.com/image_800/czNmcy1wcml2YXRlL3Jhd3BpeGVsX2ltYWdlcy93ZWJzaXRlX2NvbnRlbnQvbHIvcm0yODEtYWRqLTA1NC1qb2I1OTguanBn.jpg'); | |
| background-size: cover; | |
| background-position: center; | |
| background-attachment: fixed; | |
| min-height: 100vh; | |
| color: darkred; | |
| } | |
| /* Sidebar Background */ | |
| section[data-testid="stSidebar"] { | |
| background-image: url('https://img.freepik.com/premium-photo/hand-drawn-abstract-background-design_481527-40048.jpg'); | |
| background-size: cover; | |
| background-position: center; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # Sidebar Profile Links | |
| st.sidebar.markdown("## 🎉Author: Maria Nadeem🌟") | |
| st.sidebar.markdown("## 🔗 Connect With Me") | |
| st.sidebar.markdown(""" | |
| <div> | |
| <a href="https://github.com/marianadeem755" target="_blank"> | |
| <img src="https://cdn-icons-png.flaticon.com/512/25/25231.png" width="30px"> GitHub | |
| </a><br><br> | |
| <a href="https://www.kaggle.com/marianadeem755" target="_blank"> | |
| <img src="https://cdn4.iconfinder.com/data/icons/logos-and-brands/512/189_Kaggle_logo_logos-512.png" width="30px"> Kaggle | |
| </a><br><br> | |
| <a href="mailto:marianadeem755@gmail.com"> | |
| <img src="https://cdn-icons-png.flaticon.com/512/561/561127.png" width="30px"> Email | |
| </a><br><br> | |
| <a href="https://huggingface.co/maria355" target="_blank"> | |
| <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" width="30px"> Hugging Face | |
| </a> | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Sidebar domain selection | |
| st.sidebar.markdown("## 🎯 Choose a Focus Area") | |
| selected_domain = st.sidebar.selectbox("Select your Expertise", list(questions.keys())) | |
| st.title("🧠 Quiz Generator") | |
| # Initialize session state | |
| if 'quiz_started' not in st.session_state: | |
| st.session_state.quiz_started = False | |
| if 'current_question_index' not in st.session_state: | |
| st.session_state.current_question_index = 0 | |
| if 'score' not in st.session_state: | |
| st.session_state.score = 0 | |
| if 'selected_category' not in st.session_state: | |
| st.session_state.selected_category = None | |
| if 'answered' not in st.session_state: | |
| st.session_state.answered = False | |
| if 'user_answer' not in st.session_state: | |
| st.session_state.user_answer = None | |
| if 'quiz_questions' not in st.session_state: | |
| st.session_state.quiz_questions = [] | |
| if 'start_time' not in st.session_state: | |
| st.session_state.start_time = None | |
| if not st.session_state.quiz_started: | |
| st.subheader("Get ready to test your knowledge! 🎯") | |
| if st.button("Start Quiz"): | |
| st.session_state.quiz_started = True | |
| st.session_state.selected_category = selected_domain | |
| st.session_state.quiz_questions = random.sample( | |
| questions[selected_domain], | |
| min(30, len(questions[selected_domain])) | |
| ) | |
| st.session_state.current_question_index = 0 | |
| st.session_state.score = 0 | |
| st.session_state.start_time = time.time() | |
| st.rerun() | |
| else: | |
| # Display current question | |
| if st.session_state.current_question_index < len(st.session_state.quiz_questions): | |
| current_question = st.session_state.quiz_questions[st.session_state.current_question_index] | |
| st.subheader(f"Question {st.session_state.current_question_index + 1}") | |
| st.markdown(f"### {current_question['question']}") | |
| elapsed_time = time.time() - st.session_state.start_time | |
| remaining_time = max(60 - int(elapsed_time), 0) | |
| # Timer display | |
| progress = st.progress(0) | |
| progress.progress((60 - remaining_time) / 60) | |
| time_display = st.empty() | |
| time_display.markdown(f"⏳ **Time left: {remaining_time} seconds**") | |
| if not st.session_state.answered: | |
| user_answer = st.radio( | |
| "Select your answer:", | |
| current_question['options'], | |
| key=f"question_{st.session_state.current_question_index}" | |
| ) | |
| submit = st.button("Submit Answer ✅") | |
| if submit: | |
| st.session_state.answered = True | |
| st.session_state.user_answer = user_answer | |
| if user_answer == current_question['answer']: | |
| st.session_state.score += 1 | |
| st.success("✅ Correct Answer!") | |
| else: | |
| st.error(f"❌ Wrong Answer! Correct: **{current_question['answer']}**") | |
| # If time's up and not answered yet | |
| if remaining_time == 0 and not st.session_state.answered: | |
| st.warning("⏰ Time's up!") | |
| st.session_state.answered = True | |
| st.session_state.user_answer = None | |
| # Only show "Next" button AFTER answered OR timeout | |
| if st.session_state.answered: | |
| next_question = st.button("Next Question ➡️") | |
| if next_question: | |
| st.session_state.current_question_index += 1 | |
| st.session_state.answered = False | |
| st.session_state.user_answer = None | |
| st.session_state.start_time = time.time() # reset timer | |
| st.rerun() | |
| # Refresh page every second ONLY if not answered yet | |
| if not st.session_state.answered and remaining_time > 0: | |
| time.sleep(1) | |
| st.rerun() | |
| else: | |
| # Quiz completed | |
| st.success(f"🏁 Quiz completed! Your final score: {st.session_state.score}/{len(st.session_state.quiz_questions)}") | |
| st.balloons() | |
| if st.button("Restart Quiz 🔄"): | |
| for key in list(st.session_state.keys()): | |
| del st.session_state[key] | |
| st.rerun() | |
| if __name__ == "__main__": | |
| main() |