import pandas as pd

print("🧠 Advanced Emotion Detection System (Without TextBlob)")
print("-----------------------------------------------------------")
print("Press 'q' anytime to quit.\n")

# ----------------------------------------------------------
# Emotion Dataset (Pandas DataFrame)
# ----------------------------------------------------------

data = {
    "emotion": [
        "Happy / Positive",
        "Sad / Unhappy",
        "Angry / Frustrated",
        "Scared / Anxious",
        "Surprised / Amazed",
        "Love / Affection",
        "Bored",
        "Confused",
        "Disgusted",
        "Confident / Motivated"
    ],
    
    "keywords": [
        "happy|joy|excited|great|good|awesome|wonderful|delight|fantastic|pleased|amazing|cheerful|content|satisfied|glad|bright",
        "sad|upset|cry|unhappy|depressed|disappointed|hopeless|miserable|gloomy|heartbroken|sorrow|grief|down|lonely",
        "angry|mad|furious|irritated|annoyed|rage|hate|frustrated|offended|aggressive|resent|enraged",
        "scared|afraid|fear|nervous|worried|anxious|terrified|panic|insecure|tense|phobia",
        "surprised|amazed|shocked|astonished|wow|unexpected|stunned|startled|unbelievable",
        "love|like|affection|care|adore|fond|admire|attached|romantic|sweet",
        "bored|boring|tired|nothing|lazy|dull|uninterested",
        "confused|confusing|unsure|unclear|doubt|lost|puzzled|mixed",
        "disgust|gross|nasty|dirty|smelly|yuck|vomit|repulsive",
        "confident|strong|motivated|determined|brave|fearless|focused|ready"
    ]
}

df = pd.DataFrame(data)

# ----------------------------------------------------------
# Sentiment Keyword Dataset (Manual Scoring)
# ----------------------------------------------------------

positive_words = ["happy", "joy", "good", "great", "love", "awesome", "amazing", "fantastic", "bright", "cheerful"]
negative_words = ["sad", "bad", "angry", "cry", "upset", "hate", "fear", "worry", "depressed", "miserable"]

# ----------------------------------------------------------
# LOOP UNTIL USER PRESSES Q
# ----------------------------------------------------------

while True:
    text = input("\nEnter your sentence (or press 'q' to quit): ").lower().strip()

    if text == "q":
        print("\n👋 Thank you for using the Emotion Detection System. Goodbye!")
        break

    detected_emotion = "Neutral / Calm"

    # ---------- Emotion Detection ----------
    for index, row in df.iterrows():
        keyword_list = row['keywords'].split("|")
        
        if any(word in text for word in keyword_list):
            detected_emotion = row['emotion']
            break

    # ---------- Manual Sentiment Score ----------
    sentiment_score = 0
    
    for word in positive_words:
        if word in text:
            sentiment_score += 1

    for word in negative_words:
        if word in text:
            sentiment_score -= 1

    # Assign Sentiment Type
    if sentiment_score > 0:
        sentiment_label = "Positive"
    elif sentiment_score < 0:
        sentiment_label = "Negative"
    else:
        sentiment_label = "Neutral"

    # ---------- Emoji Output ----------
    emoji = {
        "Happy / Positive": "😊",
        "Sad / Unhappy": "😔",
        "Angry / Frustrated": "😠",
        "Scared / Anxious": "😨",
        "Surprised / Amazed": "😲",
        "Love / Affection": "❤️",
        "Bored": "😐",
        "Confused": "🤔",
        "Disgusted": "🤢",
        "Confident / Motivated": "💪",
        "Neutral / Calm": "🙂"
    }

    # ---------- Display Output ----------
    print("\n-----------------------------")
    print(f"Emotion Detected: {emoji[detected_emotion]} {detected_emotion}")
    print(f"Sentiment Score: {sentiment_score}")
    print(f"Sentiment Type: {sentiment_label}")
    print("-----------------------------")