Update app.py
Browse files
app.py
CHANGED
@@ -4,7 +4,6 @@ import requests
|
|
4 |
# FastAPI endpoint URL
|
5 |
API_URL = "https://molinari135-product-return-prediction-api.hf.space/predict/"
|
6 |
|
7 |
-
|
8 |
# Gradio Interface function
|
9 |
def predict_return(selected_products, total_customer_purchases, total_customer_returns):
|
10 |
# Input validation for returns (must be <= purchases)
|
@@ -32,8 +31,6 @@ def predict_return(selected_products, total_customer_purchases, total_customer_r
|
|
32 |
"total_customer_returns": total_customer_returns
|
33 |
}
|
34 |
|
35 |
-
print(data)
|
36 |
-
|
37 |
try:
|
38 |
# Make the POST request to the FastAPI endpoint
|
39 |
response = requests.post(API_URL, json=data)
|
@@ -47,11 +44,16 @@ def predict_return(selected_products, total_customer_purchases, total_customer_r
|
|
47 |
return "Error: No predictions found."
|
48 |
|
49 |
# Format the output to display nicely
|
50 |
-
formatted_result =
|
51 |
-
|
|
|
|
|
|
|
|
|
|
|
52 |
|
53 |
except requests.exceptions.RequestException as e:
|
54 |
-
return f"Error: {str(e)}"
|
55 |
|
56 |
|
57 |
# Predefined list of model-fabric-color combinations
|
@@ -64,16 +66,44 @@ combinations = [
|
|
64 |
]
|
65 |
|
66 |
# Gradio interface elements
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
67 |
interface = gr.Interface(
|
68 |
-
fn=predict_return, # Function
|
69 |
inputs=[
|
70 |
-
|
71 |
-
|
72 |
-
|
|
|
|
|
|
|
|
|
|
|
73 |
],
|
74 |
-
|
75 |
-
live=True # To enable the interface to interact live
|
76 |
)
|
77 |
|
78 |
# Launch the Gradio interface
|
79 |
-
interface.launch()
|
|
|
4 |
# FastAPI endpoint URL
|
5 |
API_URL = "https://molinari135-product-return-prediction-api.hf.space/predict/"
|
6 |
|
|
|
7 |
# Gradio Interface function
|
8 |
def predict_return(selected_products, total_customer_purchases, total_customer_returns):
|
9 |
# Input validation for returns (must be <= purchases)
|
|
|
31 |
"total_customer_returns": total_customer_returns
|
32 |
}
|
33 |
|
|
|
|
|
34 |
try:
|
35 |
# Make the POST request to the FastAPI endpoint
|
36 |
response = requests.post(API_URL, json=data)
|
|
|
44 |
return "Error: No predictions found."
|
45 |
|
46 |
# Format the output to display nicely
|
47 |
+
formatted_result = []
|
48 |
+
for pred in predictions:
|
49 |
+
formatted_result.append(f"{pred['product']} - {pred['prediction']} (Confidence: {pred['confidence']}%)")
|
50 |
+
|
51 |
+
# Calculate total products in cart
|
52 |
+
total = len(predictions)
|
53 |
+
return formatted_result, f"Total Products in Cart: {total}"
|
54 |
|
55 |
except requests.exceptions.RequestException as e:
|
56 |
+
return f"Error: {str(e)}", ""
|
57 |
|
58 |
|
59 |
# Predefined list of model-fabric-color combinations
|
|
|
66 |
]
|
67 |
|
68 |
# Gradio interface elements
|
69 |
+
inventory_checkbox_group = gr.CheckboxGroup(choices=combinations, label="Select Products", type="value")
|
70 |
+
|
71 |
+
# Slider elements for total purchases and returns
|
72 |
+
total_purchases_slider = gr.Slider(0, 10, step=1, label="Total Customer Purchases", value=0)
|
73 |
+
total_returns_slider = gr.Slider(0, 10, step=1, label="Total Customer Returns", value=0)
|
74 |
+
|
75 |
+
# Output elements for predictions and cart details
|
76 |
+
cart_output = gr.Textbox(value="", label="Cart", interactive=False)
|
77 |
+
predictions_output = gr.Textbox(value="", label="Prediction Results", interactive=False)
|
78 |
+
|
79 |
+
# User information output
|
80 |
+
user_info_output = gr.Textbox(value="User Information\nTotal Purchases: 0\nTotal Returns: 0", label="User Info", interactive=False)
|
81 |
+
|
82 |
+
# Layout with two main columns: Left (Inventory) and Right (User Info + Cart)
|
83 |
+
with gr.Row():
|
84 |
+
with gr.Column():
|
85 |
+
inventory_checkbox_group # Left side: Inventory
|
86 |
+
with gr.Column():
|
87 |
+
user_info_output # Right side: User Info
|
88 |
+
cart_output # Right side: Cart & Predictions
|
89 |
+
predictions_output # Right side: Prediction Results
|
90 |
+
|
91 |
+
|
92 |
+
# Gradio Interface
|
93 |
interface = gr.Interface(
|
94 |
+
fn=predict_return, # Function to process predictions
|
95 |
inputs=[
|
96 |
+
inventory_checkbox_group, # Left side: Inventory
|
97 |
+
total_purchases_slider, # Total purchases
|
98 |
+
total_returns_slider # Total returns
|
99 |
+
],
|
100 |
+
outputs=[
|
101 |
+
predictions_output, # Right side: Cart & Predictions
|
102 |
+
user_info_output, # Right side: User Info
|
103 |
+
cart_output # Right side: Cart
|
104 |
],
|
105 |
+
live=True # Enable live interaction
|
|
|
106 |
)
|
107 |
|
108 |
# Launch the Gradio interface
|
109 |
+
interface.launch()
|