Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,117 +1,31 @@
-import streamlit as st
-from textblob import TextBlob
-import json
-import os
-import matplotlib.pyplot as plt
-
-# Set page config
-st.set_page_config(
-    page_title="DilBot – Emotional AI Companion",
-    layout="wide",
-    page_icon="🤖"
-)
-
-# Apply background image via custom CSS
-st.markdown(
-    f"""
-    <style>
-    .stApp {{
-        background-image: url("https://i.pinimg.com/1200x/f0/ca/71/f0ca7163efb2ecc676426ae5ba1c1723.jpg");
-        background-size: cover;
-        background-attachment: fixed;
-    }}
-    h1, h2, h3, h4, h5, h6, .stTextInput > label, .stTextArea > label, .stMarkdown {{
-        color: white !important;
-    }}
-    .main-title {{
-        text-align: center;
-        font-size: 3em;
-        font-weight: bold;
-        color: white;
-    }}
-    .sub-title {{
-        font-size: 1.3em;
-        color: white;
-    }}
-    .quote-box {{
-        padding: 15px;
-        border-radius: 10px;
-        font-weight: bold;
-        font-size: 1.2em;
-        margin-top: 15px;
-    }}
-    </style>
-    """,
-    unsafe_allow_html=True
-)
-
-# Title
-st.markdown('<h1 class="main-title">🤖 DilBot – Your Emotional AI Companion</h1>', unsafe_allow_html=True)
-st.markdown('<div class="sub-title">📝 What\'s on your mind today?</div>', unsafe_allow_html=True)
-
-# User input
-user_input = st.text_area("", height=150, placeholder="Type here...")
-
-# Load quotes based on emotion
-def load_quotes():
-    json_path = os.path.join(os.path.dirname(__file__), "quotes.json")
-    with open(json_path, "r") as f:
-        return json.load(f)
-
-quotes_data = load_quotes()
-
-# Sentiment analyzer
-def analyze_sentiment(text):
-    blob = TextBlob(text)
-    polarity = blob.sentiment.polarity
-    if polarity > 0.2:
-        return "happy", polarity
-    elif polarity < -0.2:
-        return "sad", abs(polarity)
-    elif 0 <= polarity <= 0.2:
-        return "neutral", polarity
-    else:
-        return "angry", abs(polarity)
-
-# Emotion colors
-emotion_colors = {
-    "happy": "#FFD700",   # Yellow
-    "sad": "#000000",     # Black
-    "angry": "#FF0000",   # Red
-    "neutral": "#800080"  # Purple
-}
-
-if user_input:
-    emotion, score = analyze_sentiment(user_input)
-    percent_score = round(score * 100, 1)
-
-    # Styled sentiment result
-    st.markdown(f"""
-        <div style='margin-top: 25px;'>
-            <p style='font-size: 28px; font-weight: bold; font-style: italic; color: white;'>
-                Sentiment: {emotion.upper()}<br>
-                Confidence Score: {percent_score}%
-            </p>
-        </div>
-    """, unsafe_allow_html=True)
-
-    # Emotion indicator graph
-    fig, ax = plt.subplots(figsize=(8, 1.2))
-    ax.barh([0], [score], color=emotion_colors.get(emotion, "#800080"))
-    ax.set_xlim(0, 1)
-    ax.set_xticks([])
-    ax.set_yticks([])
-    ax.set_title("Emotion Indicator", fontsize=14, color='white')
-    ax.spines['top'].set_visible(False)
-    ax.spines['right'].set_visible(False)
-    ax.spines['left'].set_visible(False)
-    ax.spines['bottom'].set_visible(False)
+# Page layout
+st.set_page_config(page_title="DilBot", layout="centered")
+
+# Centered and styled title
+st.markdown("<h1 style='text-align: center; color: white;'>🤖 DilBot – Your Emotional AI Companion</h1>", unsafe_allow_html=True)
+st.markdown("<h3 style='text-align: center; color: white;'>📝 What's on your mind today?</h3>", unsafe_allow_html=True)
+
+# Rest of your app logic (Text Input etc...)
+
+# AFTER prediction and confidence calculation
+if emotion:
+    st.markdown("---")
+    st.markdown("### 🎯 PERSONAL DASHBOARD")
+    st.markdown(f"**Detected Emotion:** `{emotion.capitalize()}`")
+    st.markdown(f"**Confidence Score:** `{confidence * 100:.1f}%`")
+
+    # Proper Graph like reference image
+    st.markdown("#### Emotion Confidence Graph")
+    fig, ax = plt.subplots()
+    ax.bar(["Confidence"], [confidence], color="#1f77b4", width=0.4)
+    ax.set_ylim(0, 1)
+    ax.set_ylabel("Confidence (0-1)")
+    ax.set_title("Emotion Detection Confidence")
+    for i, v in enumerate([confidence]):
+        ax.text(i, v + 0.02, f"{v*100:.1f}%", ha='center', fontweight='bold')
     st.pyplot(fig)
 
-    # Quote Display
+    # QUOTES section
     quotes = quotes_data.get(emotion, ["Stay strong, you're doing great!"])
-    for quote in quotes:
-        st.markdown(
-            f"<div class='quote-box' style='background-color: {emotion_colors.get(emotion, '#800080')}; color: white;'>{quote}</div>",
-            unsafe_allow_html=True
-        )
+    selected_quote = random.choice(quotes)
+    st.markdown(f"> 💬 *{selected_quote}*")