created app.py

first creation of app.py was done here.

app.py

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+import gradio as gr
+import tensorflow as tf
+from tensorflow import keras
+
+# Load the sentiment analysis model
+model = keras.models.load_model("sentimentality.h5")
+
+# Load the tokenizer and max length used during training
+tokenizer = keras.preprocessing.text.tokenizer_from_json(open("tokenizer.json").read())
+max_len = 100
+
+def predict_sentiment(text):
+    # Preprocess the text
+    text = [text]
+    text = tf.keras.preprocessing.sequence.pad_sequences(tokenizer.texts_to_sequences(text), maxlen=max_len)
+
+    # Make a prediction
+    prediction = model.predict(text)[0][0]
+
+    # Return the probabilities of each sentiment
+    positive_prob = round(prediction * 100, 2)
+    negative_prob = round((1 - prediction) * 100, 2)
+    neutral_prob = 100 - positive_prob - negative_prob
+
+    return f"Positive: {positive_prob}%\nNegative: {negative_prob}%\nNeutral: {neutral_prob}%"
+
+# Define the interface of the Gradio app
+iface = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.inputs.Textbox(label="Enter text here:"),
+    outputs=gr.outputs.Textbox(label="Sentiment probabilities:"),
+    title="Sentiment Analysis",
+    description="Enter some text and get the probabilities of the sentiment.",
+)
+
+# Run the Gradio app
+iface.launch()