changed samples

app.py

@@ -10,13 +10,77 @@ embedder = SentenceTransformer("all-MiniLM-L6-v2")
 
 # Basic emoji dictionary
 emoji_map = {
+    # Food
+    "pizza": "🍕",
+    "burger": "🍔",
+    "fries": "🍟",
+    "sushi": "🍣",
+    "coffee": "☕",
+    "ice cream": "🍦",
+    "cake": "🎂",
+    "beer": "🍺",
+    "wine": "🍷",
+    "apple": "🍎",
+    "banana": "🍌",
+    "taco": "🌮",
+    "chocolate": "🍫",
+
+    # Animals
+    "dog": "🐶",
+    "cat": "🐱",
+    "lion": "🦁",
+    "monkey": "🐒",
+    "panda": "🐼",
+    "elephant": "🐘",
+    "fish": "🐟",
+    "bird": "🐦",
+    "horse": "🐴",
+
+    # Places & activities
     "beach": "🏖️",
+    "mountain": "⛰️",
+    "city": "🏙️",
+    "school": "🏫",
+    "work": "💼",
+    "party": "🎉",
     "swim": "🏊",
-    "dog": "🐶",
-    "pizza": "🍕",
-    "rocket": "🚀"
+    "run": "🏃",
+    "travel": "✈️",
+    "camping": "🏕️",
+    "movie": "🎬",
+
+    # Objects
+    "rocket": "🚀",
+    "book": "📚",
+    "phone": "📱",
+    "computer": "💻",
+    "car": "🚗",
+    "bicycle": "🚲",
+    "guitar": "🎸",
+    "music": "🎵",
+
+    # Emotions
+    "happy": "😄",
+    "sad": "😢",
+    "angry": "😡",
+    "love": "❤️",
+    "laugh": "😂",
+    "sleep": "😴"
 }
 
+# Predefined sentences to transform
+sentences = [
+    "I love pizza and burgers",
+    "My dog and cat are so cute",
+    "Let's go swim at the beach",
+    "The rocket launch was amazing",
+    "I am reading a good book",
+    "We are going camping in the mountains",
+    "Happy birthday! I brought cake",
+    "I need coffee and chocolate",
+    "I want to travel and see new cities"
+]
+
 # Generate the embeddings on the emojis' names
 emoji_names = list(emoji_map.keys())
 emoji_embeddings = embedder.encode(emoji_names)
@@ -39,53 +103,35 @@ def translate_to_emoji(text):
 
     return result
 
-# UI
+# Gradio UI
 with gr.Blocks(theme="soft") as app:
     gr.Markdown("# Emojilator 🦖")
-    gr.Markdown("Transform your text by adding relevant emojis! This tool uses AI to understand your text and adds matching emojis to make it more expressive.")
+    gr.Markdown("AI-powered emoji translator: make your text expressive with semantic emoji matching!")
 
     with gr.Row():
         with gr.Column(scale=1):
             gr.Image("Frida_Dino.png", elem_id="mascot", show_label=False)
         with gr.Column(scale=2):
-            # Embeddings explanation (full version)
             gr.Markdown("""
             ### About this Space 🧠
-            This is a simple Space to help build intuition around the concept of **embeddings**.
-
-            Most of the magic behind LLMs for developers revolves around understanding this concept: converting data into a numeric representation, or a vector.
+            This space explains embeddings in a simple way.
 
-            For example, the word *apple* could become `[8348832, 3423943, 923493294]`. If we use the 🍎 emoji, its embedding might be `[432432, 43423, 3423423]`. When we calculate the distance between them, they're close!
+            An embedding converts words into numeric vectors that capture meaning.
+            For example, the word apple might be `[8348, 3423, 9234]`, while 🍎 could be `[4324, 434, 3423]`.
+            When we calculate the distance, they're close—so we map apple → 🍎.
 
-            In this demo, we use that distance to replace words with relevant emojis. What's interesting is that it's not only about exact matches—if you write "I want ICE CREAM", you might get 🍦, not 🧊 + 🧴.
-
-            This means we're capturing **meaning (semantics)**, not just character-to-character equality.
-
-            Check the [Space source code](https://huggingface.co/spaces/ArturoNereu/emojilator/blob/main/app.py) to learn more about the implementation.
+            This is why "ice cream" gives 🍦 instead of 🧊 + 🧴.
             """)
 
             input_box = gr.Textbox(
-                label="Enter your text",
-                placeholder="Type something like 'I love pizza and going to the beach with my dog'",
-                lines=3
-            )
-            output_box = gr.Textbox(
-                label="Text with emojis",
-                lines=3
+                label="Selected phrase",
+                lines=3,
+                interactive=False  # makes it read-only
             )
-
+            output_box = gr.Textbox(label="Text with emojis", lines=3)
             translate_button = gr.Button("Translate to Emoji")
 
-    examples = gr.Examples(
-        examples=[
-            ["I love pizza and going to the beach with my dog"],
-            ["Let's build a rocket and swim in the ocean"],
-            ["Walking my dog to get pizza at the beach"],
-            ["The rocket launch was amazing to watch"]
-        ],
-        inputs=[input_box]
-    )
-
+    examples = gr.Examples(sentences, inputs=[input_box])
     translate_button.click(translate_to_emoji, inputs=input_box, outputs=output_box)
 
 if __name__ == "__main__":