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"""
Main application file for the Emoji Mashup app.
This module handles the Gradio interface and application setup.
"""
import gradio as gr
from utils import logger
from emoji_processor import EmojiProcessor
from config import EMBEDDING_MODELS
class EmojiMashupApp:
def __init__(self):
"""Initialize the Gradio application."""
logger.info("Initializing Emoji Mashup App")
self.processor = EmojiProcessor(model_key="mpnet", use_cached_embeddings=True) # Default to mpnet
self.processor.load_emoji_dictionaries()
def create_model_dropdown_choices(self):
"""Create formatted choices for the model dropdown.
Returns:
List of formatted model choices
"""
return [
f"{key} ({info['size']}) - {info['notes']}"
for key, info in EMBEDDING_MODELS.items()
]
def handle_model_change(self, dropdown_value, use_cached_embeddings):
"""Handle model selection change from dropdown.
Args:
dropdown_value: Selected value from dropdown
use_cached_embeddings: Whether to use cached embeddings
Returns:
Status message about model change
"""
# Extract model key from dropdown value (first word before space)
model_key = dropdown_value.split()[0] if dropdown_value else "mpnet"
# Update processor cache setting
self.processor.use_cached_embeddings = use_cached_embeddings
if model_key in EMBEDDING_MODELS:
success = self.processor.switch_model(model_key)
if success:
cache_status = "using cached embeddings" if use_cached_embeddings else "computing fresh embeddings"
return f"Switched to {model_key} model ({cache_status}): {EMBEDDING_MODELS[model_key]['notes']}"
else:
return f"Failed to switch to {model_key} model"
else:
return f"Unknown model: {model_key}"
def process_with_model(self, model_selection, text, use_cached_embeddings):
"""Process text with selected model.
Args:
model_selection: Selected model from dropdown
text: User input text
use_cached_embeddings: Whether to use cached embeddings
Returns:
Tuple of (emotion emoji, event emoji, mashup image)
"""
# Extract model key from dropdown value (first word before space)
model_key = model_selection.split()[0] if model_selection else "mpnet"
# Update processor cache setting
self.processor.use_cached_embeddings = use_cached_embeddings
if model_key in EMBEDDING_MODELS:
self.processor.switch_model(model_key)
# Process text with current model
return self.processor.sentence_to_emojis(text)
def create_interface(self):
"""Create and configure the Gradio interface.
Returns:
Gradio Interface object
"""
with gr.Blocks(title="Sentence → Emoji Mashup") as interface:
gr.Markdown("# Sentence → Emoji Mashup")
gr.Markdown("Get the top emotion and event emoji from your sentence, and view the mashup!")
with gr.Row():
with gr.Column(scale=3):
# Model selection dropdown
model_dropdown = gr.Dropdown(
choices=self.create_model_dropdown_choices(),
value=self.create_model_dropdown_choices()[0], # Default to first model (mpnet)
label="Embedding Model",
info="Select the model used for text-emoji matching"
)
# Cache toggle
cache_toggle = gr.Checkbox(
label="Use cached embeddings",
value=True,
info="When enabled, embeddings will be saved to and loaded from disk"
)
# Text input
text_input = gr.Textbox(
lines=2,
placeholder="Type a sentence...",
label="Your message"
)
# Process button
submit_btn = gr.Button("Generate Emoji Mashup", variant="primary")
with gr.Column(scale=2):
# Model info display
model_info = gr.Textbox(
value=f"Using mpnet model (using cached embeddings): {EMBEDDING_MODELS['mpnet']['notes']}",
label="Model Info",
interactive=False
)
# Output displays
emotion_out = gr.Text(label="Top Emotion Emoji")
event_out = gr.Text(label="Top Event Emoji")
mashup_out = gr.Image(label="Mashup Emoji")
# Set up event handlers
model_dropdown.change(
fn=self.handle_model_change,
inputs=[model_dropdown, cache_toggle],
outputs=[model_info]
)
cache_toggle.change(
fn=self.handle_model_change,
inputs=[model_dropdown, cache_toggle],
outputs=[model_info]
)
submit_btn.click(
fn=self.process_with_model,
inputs=[model_dropdown, text_input, cache_toggle],
outputs=[emotion_out, event_out, mashup_out]
)
# Examples based on Plutchik's Wheel of Emotions
with gr.Accordion("Examples", open=False):
gr.Markdown("### Primary Emotions")
gr.Examples(
examples=[
# Joy vs. Sadness
["I feel so happy and excited today!"],
["I'm feeling really sad and down right now"],
# Trust vs. Disgust
["I completely trust my best friend with my life"],
["That smells absolutely disgusting and makes me nauseous"],
# Fear vs. Anger
["I'm terrified of what might happen next"],
["I'm furious about how they treated me yesterday"],
# Surprise vs. Anticipation
["Wow! I can't believe what just happened - totally unexpected!"],
["I'm eagerly waiting to see what happens next"]
],
inputs=text_input,
label="Primary Emotions"
)
gr.Markdown("### Secondary Emotions")
gr.Examples(
examples=[
# Love (Joy + Trust)
["I deeply love and adore my family more than anything"],
# Submission (Trust + Fear)
["I respect their authority and will follow their instructions"],
# Awe (Fear + Surprise)
["I'm in awe of the magnificent view from the summit"],
# Disapproval (Surprise + Sadness)
["I'm disappointed by the unexpected poor quality of work"],
# Remorse (Sadness + Disgust)
["I feel so guilty and ashamed about what I did"],
# Contempt (Disgust + Anger)
["I have nothing but contempt for their dishonest behavior"],
# Aggressiveness (Anger + Anticipation)
["I'm determined to confront them about this issue"],
# Optimism (Anticipation + Joy)
["I'm optimistic and hopeful about what the future holds"]
],
inputs=text_input,
label="Secondary Emotions"
)
gr.Markdown("### Tertiary Emotions")
gr.Examples(
examples=[
# Anxiety (Anticipation + Fear)
["I'm feeling anxious about my upcoming presentation"],
# Hope (Anticipation + Trust)
["I'm hopeful that everything will work out in the end"],
# Jealousy (Anger + Trust)
["I felt jealous when I saw them together laughing"],
# Sentimentality (Trust + Sadness)
["Looking at old photos makes me feel nostalgic and sentimental"],
# Despair (Fear + Sadness)
["I'm in complete despair and see no way out of this situation"],
# Shame (Fear + Disgust)
["I'm so embarrassed and ashamed of my behavior yesterday"],
# Morbidness (Disgust + Joy)
["I have a strange fascination with creepy abandoned buildings"],
# Delight (Surprise + Joy)
["I was absolutely delighted by the unexpected gift"]
],
inputs=text_input,
label="Tertiary Emotions"
)
return interface
def run(self, share=True):
"""Launch the Gradio application.
Args:
share: Whether to create a public sharing link
"""
logger.info("Starting Emoji Mashup App")
interface = self.create_interface()
interface.launch(share=share)
# Main entry point
if __name__ == "__main__":
app = EmojiMashupApp()
app.run(share=True) |