Upload 6 files

app.py

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+import gradio as gr
+import re
+import joblib
+p_spam = joblib.load("p_spam.pkl")
+p_non_spam = joblib.load("p_non_spam.pkl")
+parameters_spam = joblib.load("parameters_spam.pkl")
+parameters_non_spam = joblib.load("parameters_non_spam.pkl")
+def classify(message):
+    message = re.sub("\W", " ", message)
+    message = message.lower().split()
+    p_spam_given_message = p_spam
+    p_non_spam_given_message = p_non_spam
+    for word in message:
+        if word in parameters_spam:
+            p_spam_given_message *= parameters_spam[word]
+        if word in parameters_non_spam:
+            p_non_spam_given_message *= parameters_non_spam[word]
+    if p_spam_given_message > p_non_spam_given_message:
+        return "Spam"
+    elif p_non_spam_given_message > p_spam_given_message:
+        return "Non-Spam"
+    else:
+        return "Equal probabilities, human needed to classify this!"
+ir = gr.Interface(classify,inputs="text",outputs="text")
+ir.launch()

p_non_spam.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dd63c725e9626560f36b327a0f3864a8392d5d7665a69f81bbae95231242c4d9
+size 21

p_spam.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1b44f97c87b342e7764d3da770f79569c2a93d0663af741f297ed873fb983e3a
+size 21

parameters_non_spam.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5205c780118f80d13daed2516c16db9fca1e905a6064a00c110e4cdf2cb67a3b
+size 216055

parameters_spam.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:69368b482721c833a9ec39077fd34b8c425c81163e26103fceb438c24e0b451a
+size 216055

requirements.txt

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+re
+joblib
+gradio
+pandas