Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,31 +1,79 @@
-# 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)
-
-    # QUOTES section
-    quotes = quotes_data.get(emotion, ["Stay strong, you're doing great!"])
-    selected_quote = random.choice(quotes)
-    st.markdown(f"> 💬 *{selected_quote}*")
+import streamlit as st
+from textblob import TextBlob
+import json
+import os
+import matplotlib.pyplot as plt
+
+# === Load Quotes ===
+QUOTES_PATH = os.path.join(os.path.dirname(__file__), "quotes.json")
+with open(QUOTES_PATH, "r") as f:
+    quotes_data = json.load(f)
+
+# === Emotion Detection via TextBlob ===
+def detect_emotion(text):
+    blob = TextBlob(text)
+    polarity = blob.sentiment.polarity
+
+    if polarity > 0.2:
+        return "positive", polarity
+    elif polarity < -0.2:
+        return "negative", polarity
+    else:
+        return "neutral", polarity
+
+# === Quotes Retrieval ===
+def get_quote(emotion):
+    if isinstance(quotes_data, dict):
+        return quotes_data.get(emotion, ["Stay strong, you're doing great!"])
+    else:
+        return ["Stay strong, you're doing great!"]
+
+# === Page Layout ===
+st.set_page_config(page_title="DilBot - Emotionally Intelligent AI Companion", layout="centered")
+st.title("💖 DilBot: Your Emotional Companion")
+st.markdown("---")
+
+# === Input Section ===
+user_input = st.text_area("🗣️ How are you feeling today?", height=150, placeholder="Type your thoughts here...")
+
+if st.button("Analyze"):
+    if user_input.strip():
+        # Detect Emotion
+        emotion, polarity = detect_emotion(user_input)
+        confidence = abs(polarity) * 100
+
+        # Display Emotion
+        st.subheader("🧠 Detected Emotion:")
+        st.success(f"**{emotion.capitalize()}** with a confidence of **{confidence:.2f}%**")
+
+        # Show a personal quote
+        st.markdown("### 💬 DilBot's Message:")
+        quote = get_quote(emotion)[0]
+        st.info(f"_{quote}_")
+
+        # === Personal Dashboard ===
+        st.markdown("### 📊 Personal Dashboard")
+
+        # Bar & Doughnut Chart
+        fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 4), dpi=100)
+
+        labels = ['Positive', 'Neutral', 'Negative']
+        values = [confidence if emotion == lbl.lower() else 100 - confidence if lbl.lower() == 'neutral' else 0 for lbl in labels]
+        colors = ['#00cc99', '#b0bec5', '#ff6f61']
+
+        # Bar Chart
+        ax1.bar(labels, values, color=colors)
+        ax1.set_title("Confidence by Emotion")
+        ax1.set_ylabel("Percentage")
+        ax1.set_ylim(0, 100)
+
+        # Doughnut Chart
+        wedges, texts, autotexts = ax2.pie(
+            values, labels=labels, autopct='%1.1f%%',
+            colors=colors, startangle=90, wedgeprops=dict(width=0.4)
+        )
+        ax2.set_title("Emotion Distribution")
+
+        st.pyplot(fig)
+    else:
+        st.warning("Please write something to analyze.")