import streamlit as st

# --- App Configuration ---
st.set_page_config(
    page_title="Basic Python Sentiment Analyzer",
    page_icon="✍️",
    layout="centered",
    initial_sidebar_state="auto"
)

# --- Define Sentiment Keywords (Pure Python Logic) ---
# These are very basic lists for demonstration purposes.
# A real-world rule-based system would be much more extensive and nuanced.
POSITIVE_KEYWORDS = [
    "good", "great", "excellent", "amazing", "fantastic", "love", "happy",
    "joy", "wonderful", "positive", "awesome", "beautiful", "perfect", "like",
    "enjoy", "best", "super", "nice", "pleased", "delightful", "brilliant"
]

NEGATIVE_KEYWORDS = [
    "bad", "terrible", "horrible", "awful", "hate", "sad", "unhappy",
    "poor", "negative", "disappointing", "worst", "ugly", "frustrating",
    "dislike", "annoying", "miserable", "stressful", "difficult", "problem",
    "fail", "ruin", "never"
]

# --- Sentiment Analysis Function (Pure Python) ---
def analyze_sentiment_basic(text):
    """
    Performs a very basic sentiment analysis based on predefined positive and negative keywords.
    This function does not use any external NLP models or libraries.
    """
    if not text:
        return "Neutral", 0, 0 # Return neutral if no text

    text_lower = text.lower()
    positive_count = 0
    negative_count = 0

    # Count positive keywords
    for keyword in POSITIVE_KEYWORDS:
        positive_count += text_lower.count(keyword)

    # Count negative keywords
    for keyword in NEGATIVE_KEYWORDS:
        negative_count += text_lower.count(keyword)

    # Determine sentiment
    if positive_count > negative_count:
        return "Positive", positive_count, negative_count
    elif negative_count > positive_count:
        return "Negative", positive_count, negative_count
    else:
        return "Neutral", positive_count, negative_count

# --- Streamlit UI ---

# Header Section
st.markdown(
    """
    <div style="text-align: center; padding: 20px; background-color: #f0f2f6; border-radius: 10px; margin-bottom: 30px;">
        <h1 style="color: #333; font-size: 2.5em;">✍️ Sentiment Analyzer</h1>
        <p style="color: #555; font-size: 1.1em;">
            Discover the sentiment of your text with a simple keyword-based analysis.
        </p>
    </div>
    """,
    unsafe_allow_html=True
)

st.markdown(
    """
    <p style="font-size: 1.1em; text-align: center; margin-bottom: 20px;">
    Enter any text below, and I'll tell you if its sentiment is positive, negative, or neutral based on a predefined list of keywords.
    </p>
    """,
    unsafe_allow_html=True
)

# Text input from the user
user_input = st.text_area(
    "📝 Enter your text here:",
    "This is a good example, but it could be even better. I really enjoy using Streamlit!",
    height=180,
    key="user_text_input" # Added a key for better control
)

col1, col2 = st.columns([1, 1])

with col1:
    analyze_button = st.button("✨ Analyze Sentiment", key="analyze_btn")
with col2:
    clear_button = st.button("🗑️ Clear Text", key="clear_btn")

# Clear button functionality
if clear_button:
    st.session_state.user_text_input = "" # Clear the text area
    st.experimental_rerun() # Rerun to clear the output

# Analyze button logic
if analyze_button:
    if user_input:
        sentiment, pos_count, neg_count = analyze_sentiment_basic(user_input)

        st.markdown("---")
        st.subheader("📊 Analysis Result:")

        # Display result with appropriate styling and icons
        if sentiment == "Positive":
            st.success(f"**Sentiment:** Positive 😊")
        elif sentiment == "Negative":
            st.error(f"**Sentiment:** Negative 😠")
        else:
            st.warning(f"**Sentiment:** Neutral 😐")

        st.markdown(f"<p style='font-size: 1.05em;'>Positive keyword matches: <strong>{pos_count}</strong></p>", unsafe_allow_html=True)
        st.markdown(f"<p style='font-size: 1.05em;'>Negative keyword matches: <strong>{neg_count}</strong></p>", unsafe_allow_html=True)

        st.markdown("---")
        st.write(f"**Original Text:**")
        st.markdown(f"<div style='background-color: #e9ecef; padding: 15px; border-radius: 8px; border-left: 5px solid #007bff;'><em>{user_input}</em></div>", unsafe_allow_html=True)
    else:
        st.warning("Please enter some text to analyze.")

# Custom CSS for enhanced styling
st.markdown(
    """
    <style>
    /* General body and font */
    body {
        font-family: 'Inter', sans-serif;
        background-color: #f8f9fa;
        color: #343a40;
    }

    /* Streamlit widgets styling */
    .stButton>button {
        background-color: #28a745; /* Green for analyze */
        color: white;
        padding: 12px 25px;
        border-radius: 10px;
        border: none;
        cursor: pointer;
        font-size: 1.1em;
        font-weight: bold;
        box-shadow: 0 5px 15px rgba(40, 167, 69, 0.3);
        transition: all 0.3s ease-in-out;
        width: 100%; /* Make buttons full width in columns */
    }
    .stButton>button:hover {
        background-color: #218838;
        box-shadow: 0 8px 20px rgba(40, 167, 69, 0.4);
        transform: translateY(-2px);
    }

    /* Clear button specific style */
    .stButton[key="clear_btn"] > button {
        background-color: #dc3545; /* Red for clear */
        box-shadow: 0 5px 15px rgba(220, 53, 69, 0.3);
    }
    .stButton[key="clear_btn"] > button:hover {
        background-color: #c82333;
        box-shadow: 0 8px 20px rgba(220, 53, 69, 0.4);
    }

    .stTextArea>div>div>textarea {
        border-radius: 10px;
        border: 1px solid #ced4da;
        padding: 15px;
        font-size: 1.05em;
        box-shadow: inset 0 1px 3px rgba(0,0,0,0.1);
        transition: border-color 0.3s ease-in-out;
    }
    .stTextArea>div>div>textarea:focus {
        border-color: #007bff;
        outline: none;
    }

    /* Streamlit message boxes */
    .stSuccess {
        background-color: #d4edda;
        color: #155724;
        border-radius: 8px;
        padding: 15px;
        border: 1px solid #c3e6cb;
        font-weight: bold;
    }
    .stError {
        background-color: #f8d7da;
        color: #721c24;
        border-radius: 8px;
        padding: 15px;
        border: 1px solid #f5c6cb;
        font-weight: bold;
    }
    .stWarning {
        background-color: #fff3cd;
        color: #856404;
        border-radius: 8px;
        padding: 15px;
        border: 1px solid #ffeeba;
        font-weight: bold;
    }
    .stInfo {
        background-color: #d1ecf1;
        color: #0c5460;
        border-radius: 8px;
        padding: 10px;
        border: 1px solid #bee5eb;
        margin-top: 10px;
    }

    /* Markdown styling for titles and text */
    h1 {
        color: #007bff;
        text-align: center;
        font-weight: 700;
        margin-bottom: 20px;
    }
    h2, h3, h4, h5, h6 {
        color: #343a40;
        margin-top: 25px;
        margin-bottom: 15px;
    }
    p {
        line-height: 1.6;
    }
    </style>
    """,
    unsafe_allow_html=True
)

# Footer
st.markdown(
    """
    <div style="text-align: center; margin-top: 50px; padding: 20px; border-top: 1px solid #eee; color: #6c757d;">
        <p>Built with ❤️ using Streamlit and pure Python.</p>
    </div>
    """,
    unsafe_allow_html=True
)