Update app.py

app.py

@@ -1,49 +1,43 @@
 import gradio as gr
 from transformers import pipeline
 import re
-from PIL import Image, ImageDraw, ImageFont
 
 text_pipe = pipeline("text-classification", model="karalif/myTestModel", return_all_scores=True)
 
-def draw_text_with_highlight(text):
-    font_path = "path/to/your/font.ttf"  # Make sure this path is correct
-    font_size = 24
-
-    image = Image.new("RGB", (1000, 60), "white")
-    draw = ImageDraw.Draw(image)
-
-    # Check if the font file exists and fallback to default if not
-    try:
-        font = ImageFont.truetype(font_path, font_size)
-    except IOError:
-        print(f"Font file not found: {font_path}. Falling back to default font.")
-        font = ImageFont.load_default()
-
-    words = text.split()
-    x, y = 10, 10
-    if len(words) >= 3:
-        for i, word in enumerate(words):
-            if i == 2:  # Highlight the third word
-                width, height = draw.textsize(word, font=font)
-                draw.rectangle((x, y, x + width, y + height), fill='yellow')
-            draw.text((x, y), word, fill="black", font=font)
-            x += draw.textsize(word + " ", font=font)[0]  # Update x position
-    else:
-        draw.text((10, 10), text, fill="black", font=font)
-
-    return image
+def mark_text(text, tag):
+    """Helper for marking the text, returns a tuple with the text and the tag"""
+    return (text, tag)
 
 def predict(text):
-    # Your existing prediction logic here
-    # For demonstration, we'll just create an image with the highlighted third word
-    image = draw_text_with_highlight(text)
-    return image
+    greeting_pattern = r"^(Halló|Hæ|Sæl|Góðan dag|Kær kveðja|Daginn|Kvöldið|Ágæt|Elsku)"
+    greeting_feedback = "Heilsaðu dóninn þinn"
+    
+    results = text_pipe(text)
+    all_scores = results[0]
+    response = [mark_text(text, None)]  # Original text without any tag
+    
+    if not re.match(greeting_pattern, text, re.IGNORECASE):
+        response.append(mark_text(greeting_feedback, "breytt"))  # Appending feedback with a tag
+    
+    return response
+
+description_html = """
+    <center>
+        <img src='http://www.ru.is/media/HR_logo_vinstri_transparent.png' width='250' height='auto'>
+    </center>
+    """
 
-# Update the Gradio interface to use the image output
 gr.Interface(
     fn=predict,
     inputs=gr.TextArea(label="Enter text here:"),
-    outputs="image",  # Changed to image output
+    outputs=gr.HighlightedText(
+        label="Feedback on text input:",
+        show_label=False,
+        show_legend=True,
+        combine_adjacent=True,
+        adjacent_separator=" ",
+    ).style(color_map={"breytt": "red"}),  # "breytt" tagged text will be red
+    description=description_html,
     examples=[
         ["Það voru vitni að árásinni sem tilkynntu málið til lögreglu sem kom skjótt á vettvang."],
         ["Ég held þetta sé ekki góður tími fara heimsókn."],