Create app.py

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the model
+model_name = "knowledgator/comprehend_it-base"
+classifier = pipeline("zero-shot-classification", model=model_name, device="cpu")
+
+# Function to classify feedback
+def classify_feedback(feedback_text):
+    # Classify feedback using the loaded model
+    labels = ["High Priority ticket", "Low Priority ticket", "Medium Priority ticket"]
+
+    result = classifier(feedback_text, labels, multi_label=True)
+
+    # Get the top label associated with the feedback
+    top_label = result["labels"][0]
+
+    return top_label
+
+# Create Gradio interface
+feedback_textbox = gr.Textbox(label="Enter your feedback:")
+feedback_output = gr.Label(label="Top Label:")
+
+gr.Interface(
+    fn=classify_feedback,
+    inputs=feedback_textbox,
+    outputs=feedback_output,
+    title="Feedback Classifier",
+    description="Enter your feedback and get the priority label for your ticket."
+).launch()