created app.py

app.py

@@ -0,0 +1,89 @@
+import streamlit as st
+import pandas as pd
+import pickle
+
+# Load the preprocessor and model from the pickle files
+with open('preprocesor.pkl', 'rb') as file:
+    preprocessor = pickle.load(file)
+
+with open('model.pkl', 'rb') as file:
+    model = pickle.load(file)
+
+# Define the app
+def run():
+    st.title("Model Testing App")
+
+    # Create inputs for all features
+    Timestamp = st.date_input("Timestamp")
+    Age = st.number_input("Age", min_value=0, max_value=100)
+    Gender = st.selectbox("Gender", ["Male", "Female", "M"])
+    Country = st.text_input("Country")
+    state = st.text_input("State")
+    self_employed = st.checkbox("Self Employed")
+    family_history = st.checkbox("Family History")
+    treatment = st.selectbox("Treatment", ["Yes", "No"])
+    work_interfere = st.selectbox("Work Interfere", ["Sometimes", "Never", "Often"])
+    no_employees = st.selectbox("No. of Employees", ["1-5", "6-25", "26-100", "100-500", "500-1000", "More than 1000"])
+    remote_work = st.checkbox("Remote Work")
+    tech_company = st.checkbox("Tech Company")
+    benefits = st.selectbox("Benefits", ["Yes", "No", "Don't know"])
+    care_options = st.selectbox("Care Options", ["Yes", "No", "Not sure"])
+    wellness_program = st.selectbox("Wellness Program", ["Yes", "No", "Don't know"])
+    seek_help = st.selectbox("Seek Help", ["Yes", "No", "Don't know"])
+    anonymity = st.selectbox("Anonymity", ["Yes", "No", "Don't know"])
+    leave = st.selectbox("Leave", ["Somewhat easy","Somewhat difficult","Very difficult","Don't know"])
+    mental_health_consequence = st.selectbox("Mental Health Consequence", ["Yes","No","Maybe"])
+    phys_health_consequence = st.selectbox("Physical Health Consequence", ["Yes","No","Maybe"])
+    coworkers = st.selectbox("Coworkers", ["Yes","No","Some of them"])
+    supervisor = st.selectbox("Supervisor", ["Yes","No","Some of them"])
+    mental_health_interview = st.selectbox("Mental Health Interview", ["Yes","No","Maybe"])
+    phys_health_interview = st.selectbox("Physical Health Interview", ["Yes","No","Maybe"])
+    mental_vs_physical = st.selectbox("Mental vs Physical", ["Yes","No","Don't know"])
+    obs_consequence = st.selectbox("Obs Consequence", ["Yes","No"])
+
+    # Create a new data point
+    new_data = pd.DataFrame({
+        "Timestamp": [Timestamp],
+        "Age": [Age],
+        "Gender": [Gender],
+        "Country": [Country],
+        "state": [state],
+        "self_employed": [self_employed],
+        "family_history": [family_history],
+        "treatment": [treatment],
+        "work_interfere": [work_interfere],
+        "no_employees": [no_employees],
+        "remote_work": [remote_work],
+        "tech_company": [tech_company],
+        "benefits": [benefits],
+        "care_options": [care_options],
+        "wellness_program": [wellness_program],
+        "seek_help": [seek_help],
+        "anonymity": [anonymity],
+        "leave": [leave],
+        "mental_health_consequence": [mental_health_consequence],
+        "phys_health_consequence": [phys_health_consequence],
+        "coworkers": [coworkers],
+        "supervisor": [supervisor],
+        "mental_health_interview": [mental_health_interview],
+        "phys_health_interview": [phys_health_interview],
+        "mental_vs_physical": [mental_vs_physical],
+        "obs_consequence": [obs_consequence]
+    })
+
+    # Preprocess the new data
+    new_data_transformed = preprocessor.transform(new_data.drop(columns=['treatment'],axis=1))
+
+    # Make a prediction
+    prediction = model.predict(new_data_transformed)[0]
+
+    if st.button('Predict'):
+        if prediction == 1:
+            result ='Yes'
+            st.success('The output is {}'.format(result))
+        else:
+            result ='No'
+            st.success('The output is {}'.format(result))
+
+if __name__=='__main__':
+	run()