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Update app.py
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app.py
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import pandas as pd
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dataset = pd.read_csv('cancer.csv')
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x = dataset.drop(columns=["diagnosis(1=m, 0=b)"])
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y = dataset["diagnosis(1=m, 0=b)"]
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from sklearn.model_selection import train_test_split
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x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2)
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import tensorflow as tf
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model = tf.keras.models.Sequential()
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model.add(tf.keras.layers.Dense(256, input_shape=x_train.shape, activation='sigmoid'))
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model.add(tf.keras.layers.Dense(256, activation='sigmoid'))
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model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
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model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
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model.fit(x_train, y_train, epochs=1000)
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model.evaluate(x_test, y_test)
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model.save("percyAI_model.h5")
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from google.colab import files
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files.download("percyAI_model.h5")
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from tensorflow.keras.models import load_model
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model = load_model("percyAI_model.h5")
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import numpy as np
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import tensorflow as tf
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from tensorflow import keras
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from tensorflow.keras import layers
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x_values = np.random.randint(0, 100, (10000, 2))
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y_values = np.sum(x_values, axis=1)
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x_values = x_values / 100.0
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y_values = y_values / 200.0
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model = keras.Sequential([
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layers.Dense(64, activation='relu', input_shape=(2,)),
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layers.Dense(64, activation='relu'),
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layers.Dense(1)
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])
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model.compile(optimizer='adam', loss='mse', metrics=['mae'])
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model.fit(x_values, y_values, epochs=30, batch_size=32, validation_split=0.2)
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test_input = np.array([[25, 30]]) / 100.0
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prediction = model.predict(test_input) * 200.0
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print("Predicted sum:", prediction[0][0])
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model.save("percyAI_model.h5")
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model.save("percyAI_model.h5")
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import gradio as gr
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import re
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BOT_NAME = "Phu Quy Ho"
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# Basic math evaluator (with safety)
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def handle_math(user_input):
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user_input = user_input.lower().strip()
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if any(greet in user_input for greet in greetings):
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return f"Hello! I am {BOT_NAME}. I can help you with math. Try something like: (3 + 5) * -2"
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# Remove
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math_expression = re.sub(r"[^\d\.\+\-\*/\(\)\s]", "", user_input)
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math_expression = math_expression.replace("what is", "").strip()
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try:
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return "Sorry, I couldn't understand that. Please enter a valid math expression like (2 + 3) * -1"
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# Gradio UI
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gr.Interface(
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fn=handle_math,
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inputs="text",
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outputs="text",
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title="Phu Quy Ho – Smart Math Solver",
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description="Say hello or ask me a math question! I support +, -, *, /, negative numbers, and parentheses."
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import gradio as gr
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import re
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BOT_NAME = "Phu Quy Ho"
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def handle_math(user_input):
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user_input = user_input.lower().strip()
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if any(greet in user_input for greet in greetings):
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return f"Hello! I am {BOT_NAME}. I can help you with math. Try something like: (3 + 5) * -2"
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# Remove everything except math symbols and numbers
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math_expression = re.sub(r"[^\d\.\+\-\*/\(\)\s]", "", user_input)
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math_expression = math_expression.replace("what is", "").strip()
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try:
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return "Sorry, I couldn't understand that. Please enter a valid math expression like (2 + 3) * -1"
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# Gradio UI
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demo = gr.Interface(
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fn=handle_math,
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inputs="text",
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outputs="text",
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title="Phu Quy Ho – Smart Math Solver",
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description="Say hello or ask me a math question! I support +, -, *, /, negative numbers, and parentheses."
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demo.launch()
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