import pandas as pd
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import random
import gradio as gr
import torch

# Check if GPU is available and set the device
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(f"Using device: {device}")

# Path to your model file (adjust this if needed)
model_name = "bhadresh-savani/bert-base-uncased-emotion"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

def predict_emotion(text):
    # Tokenize the input text
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)

    # Perform inference
    outputs = model(**inputs)
    predictions = torch.softmax(outputs.logits, dim=1)

    # Get the predicted emotion label
    predicted_label = torch.argmax(predictions, dim=1).item()

    # Map the label to emotion names
    label_to_emotion = {
        0: 'anger',
        1: 'joy',
        2: 'optimism',
        3: 'sadness',
        4: 'fear',
        5: 'surprise',
    }
    emotion = label_to_emotion[predicted_label]
    confidence = predictions[0][predicted_label].item()

    return emotion, confidence

# Motivational quotes for each emotion
motivational_quotes = {
    "anger": [
        "It’s okay to feel angry when things don’t go as expected. Your emotions are valid and show you care deeply. Take a moment to breathe and channel that energy into finding a solution—you’ve got the strength to turn this around!"
    ],
    "joy": [
        "Your joy is contagious, and it’s wonderful to see you so happy! Celebrate this moment fully, and let it inspire you to keep reaching for more moments like these."
    ],
    "optimism": [
        "Your positive outlook is inspiring! Keep holding onto that hope and belief in yourself—it will guide you through any challenge. The best is yet to come!"
    ],
    "sadness": [
        "It’s okay to feel sad—allow yourself to process and heal. Remember, tough times don’t last forever. Lean on those who care about you, and know that brighter days are ahead."
    ],
    "fear": [
        "Feeling afraid is natural; it shows you’re stepping outside your comfort zone. Trust in your abilities and take things one step at a time. You’re braver than you think!"
    ],
    "surprise": [
        "Life’s surprises can be startling or exciting, but they often bring new opportunities. Embrace the unexpected with an open mind—you might discover something amazing."
    ]
}

# Function to generate motivational quotes
def get_motivational_quote(emotion):
    if emotion in motivational_quotes:
        return random.choice(motivational_quotes[emotion])
    else:
        return "Stay strong and keep moving forward!"

def process_entry(date, text):
    emotion, confidence = predict_emotion(text)
    quote = get_motivational_quote(emotion)
    return f"On {date}, your detected emotion is: {emotion} (Confidence: {confidence:.2f})", quote

interface = gr.Interface(
    fn=process_entry,
    inputs=[
        gr.Textbox(lines=1, placeholder="Enter date of entry (DD/MM/YYYY):", label="Enter date of entry (DD/MM/YYYY):"),
        gr.Textbox(lines=2, placeholder="Enter your thoughts and feelings:", label="Enter your thoughts and feelings:")
    ],
    outputs=[
        gr.Textbox(lines=2, placeholder="Detected Emotion:", label="Detected Emotion:"),
        gr.Textbox(lines=2, placeholder="Motivational Quote:", label="Here is something to tell yourself:")
    ],
    title="Feel Free to Express Yourself!",
    description="A safe space for you to express your feelings and recognize them!"
)

# Launch the Gradio app with public sharing enabled
interface.launch()