import streamlit as st import random from tensorflow.keras.preprocessing.text import Tokenizer from tensorflow.keras.preprocessing.sequence import pad_sequences st.title("Addition Equation Generator") # Sidebar for user input num_samples = st.sidebar.number_input("Number of Samples", min_value=100, max_value=100000, value=5000) max_num = st.sidebar.slider("Maximum Number for Addition", min_value=10, max_value=100, value=99) # Function to generate addition data def generate_addition_data(num_samples, max_num, stop_token=';'): input_equations = [] answers = [] for _ in range(num_samples): a = random.randint(0, max_num) b = random.randint(0, max_num) input_eq = f"{a} + {b} =" answer = str(a + b) + stop_token input_equations.append(input_eq) answers.append(answer) return input_equations, answers # Button to generate and process data if st.button('Generate and Process Data'): input_equations, answers = generate_addition_data(num_samples, max_num) # Display some sample data st.write("Sample Generated Data:") for i in range(min(5, len(input_equations))): st.write(f"Input Equation: {input_equations[i]}") st.write(f"Answer: {answers[i]}") # Tokenization tokenizer = Tokenizer(char_level=True) tokenizer.fit_on_texts(input_equations + answers) input_sequences = tokenizer.texts_to_sequences(input_equations) answer_sequences = tokenizer.texts_to_sequences(answers) # Padding sequences max_len = max(max([len(seq) for seq in input_sequences]), max([len(seq) for seq in answer_sequences])) input_sequences_padded = pad_sequences(input_sequences, maxlen=max_len, padding='post') answer_sequences_padded = pad_sequences(answer_sequences, maxlen=max_len, padding='post') # Display tokenization and padding results st.write("Tokenization and Padding Results:") for i in range(min(5, len(input_equations))): st.write(f"Input Equation: {input_equations[i]}") st.write(f"Tokenized Input Sequence: {input_sequences[i]}") st.write(f"Padded Input Sequence: {input_sequences_padded[i]}") st.write(f"Answer: {answers[i]}") st.write(f"Tokenized Answer Sequence: {answer_sequences[i]}") st.write(f"Padded Answer Sequence: {answer_sequences_padded[i]}") # Instruction to run the app st.write("Run the app with `streamlit run .py` in your terminal.")