Sync App files

READme.md

@@ -0,0 +1,11 @@
+---
+title: First Attempt
+emoji: 💊
+colorFrom: purple
+colorTo: green
+sdk: gradio
+sdk_version: 5.4.0
+app_file: drug_app.py
+pinned: false
+license: apache-2.0
+---

drug_app.py

@@ -1,15 +1,15 @@
 import gradio as gr
 import skops.io as sio
 
-pipe = sio.load("./Model/drug_pipeline.skops", trusted=True)
-
+trusted_types = sio.get_untrusted_types(file="./Model/drug_pipeline.skops")
+pipe = sio.load("./Model/drug_pipeline.skops", trusted=trusted_types)
 
 def predict_drug(age, sex, blood_pressure, cholesterol, na_to_k_ratio):
     """Predict drugs based on patient features.
 
     Args:
         age (int): Age of patient
-        sex (str): Sex of patient
+        sex (str): Sex of patient 
         blood_pressure (str): Blood pressure level
         cholesterol (str): Cholesterol level
         na_to_k_ratio (float): Ratio of sodium to potassium in blood
@@ -19,7 +19,7 @@ def predict_drug(age, sex, blood_pressure, cholesterol, na_to_k_ratio):
     """
     features = [age, sex, blood_pressure, cholesterol, na_to_k_ratio]
     predicted_drug = pipe.predict([features])[0]
-
+    
     label = f"Predicted Drug: {predicted_drug}"
     return label
 
@@ -42,7 +42,7 @@ examples = [
 
 title = "Drug Classification"
 description = "Enter the details to correctly identify Drug type?"
-article = "This app is a part of the **[Beginner's Guide to CI/CD for Machine Learning](https://www.datacamp.com/tutorial/ci-cd-for-machine-learning)**. It teaches how to automate training, evaluation, and deployment of models to Hugging Face using GitHub Actions."
+article = "This app is a part of the Beginner's Guide to CI/CD for Machine Learning. It teaches how to automate training, evaluation, and deployment of models to Hugging Face using GitHub Actions."
 
 
 gr.Interface(

requirements.txt

@@ -1,2 +1,4 @@
 scikit-learn
-skops
+skops
+black
+