Update app.py

app.py

@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 classifier = pipeline("text-classification", model="CesarLeblanc/test_model")
 dataset = load_dataset("CesarLeblanc/text_classification_dataset")
 
-def text_classification(text):
+def text_classification(text, typology, confidence):
     result = classifier(text)
     habitat_label = result[0]['label']
     habitat_label = dataset['train'].features['label'].names[int(habitat_label.split('_')[1])]
@@ -30,7 +30,7 @@ def text_classification(text):
 examples=["sparganium erectum, calystegia sepium, persicaria amphibia", "thinopyrum junceum, cakile maritima"]
 
 io = gr.Interface(fn=text_classification, 
-                         inputs= gr.Textbox(lines=2, label="List of comma-separated binomial names of species (see examples)", placeholder="Enter species here..."), 
+                         inputs=[gr.Textbox(lines=2, label="List of comma-separated binomial names of species (see examples)", placeholder="Enter species here..."), gr.Dropdown(["EUNIS"], label="Typology", info="Will add more typologies later!"), gr.Slider(0, 100, value=50, label="Confidence", info="Choose the level of confidence for the prediction")], 
                          outputs=[gr.Textbox(lines=2, label="Vegetation Plot Classification Result"), "image"],
                          title="Pl@ntBERT",
                          description="Vegetation Plot Classification: enter the species found in a vegetation plot and see its EUNIS habitat!",