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import gradio as gr
import autokeras as ak
import numpy as np
from tensorflow.keras.models import load_model
loaded_model = load_model("text_model", custom_objects=ak.CUSTOM_OBJECTS)
def tweet_tester(tweet1, tweet2):
pred1 = loaded_model.predict(np.array([[tweet1]]))[0][0]
pred2 = loaded_model.predict(np.array([[tweet2]]))[0][0]
print(pred1, pred2)
diff_pct = (pred1 - pred2) / pred1 * 100
# truncate diff_pct to 2 decimal places
diff_pct = round(diff_pct, 3)
if diff_pct > 0:
return f"tweet2 is {diff_pct}% better than tweet1"
else:
return f"tweet2 is {abs(diff_pct)}% worse than tweet1"
interface = gr.Interface(
title="Tweet A/B Test",
description="Enter the text of two tweets you'd like to A/B test. The output number represents the percent difference in expected likes between the two tweets.",
fn=tweet_tester,
inputs=["text", "text"],
outputs=["text"]
)
interface.launch()
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