initial commit

app.py

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+import gradio as gr
+import joblib
+
+model = joblib.load("crop_predict.pkl")
+
+def crop_predict(N, P, K, temperature, humidity, ph, rainfall):
+    vals = [float(N), float(P), float(K), float(temperature), float(humidity), float(ph), float(rainfall)]
+    out = model.predict([vals])
+    return str(out[0])
+
+demo = gr.Interface(
+fn=crop_predict,
+inputs=[
+gr.Textbox(label="N"),
+gr.Textbox(label="P"),
+gr.Textbox(label="K"),
+gr.Textbox(label="temperature"),
+gr.Textbox(label="humidity"),
+gr.Textbox(label="ph"),
+gr.Textbox(label="rainfall")
+],
+outputs=gr.Textbox()
+)

crop_predict.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:645f2d63bc44623a002f8a8722783229fe7c793c3c019c2e20c941f8b9e4535e
+size 2558

requirements.txt

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+gradio
+joblib
+scikit-learn
+numpy