Support custom upload

app.py

@@ -27,7 +27,6 @@ def classify_comments():
     categories = []
     results = []
     for comment in df['customer_comment']:
-        # Classify the sentiment first
         sentiment = classifier(comment)[0]['label']
         prompt = f"What category best describes this comment? '{comment}' Please answer using only the name of the category: Product Experience, Customer Support, Price of Service, Other."
         category = generator(prompt, max_length=30)[0]['generated_text']
@@ -39,10 +38,25 @@ def classify_comments():
 
 # Gradio Interface
 with gr.Blocks() as nps:
+    uploaded_file = gr.File(label="Upload CSV", file_types=["csv"], optional=True)
+    template_btn = gr.Button("Use Template")
     gr.Markdown("# NPS Comment Categorization")
     classify_btn = gr.Button("Classify Comments")
     output = gr.HTML()
 
+    def load_data(file):
+        if file is not None:
+            custom_df = pd.read_csv(file.name)
+            if 'customer_comment' not in custom_df.columns:
+                return "Error: Uploaded CSV must contain a column named 'customer_comment'"
+            global df
+            df = custom_df
+            return "Custom CSV loaded successfully!"
+        else:
+            return "No file uploaded."
+
+    uploaded_file.change(fn=load_data, inputs=uploaded_file, outputs=output)
+    template_btn.click(fn=lambda: "Using Template Dataset", outputs=output)
     classify_btn.click(fn=classify_comments, outputs=output)
 
 nps.launch()