Update app.py

app.py

@@ -1,91 +1,98 @@
 # app.py
 import streamlit as st
-from groq import Groq
 import torch
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import random
+import altair as alt
+import pandas as pd
+from datetime import datetime
 from reportlab.lib.pagesizes import letter
 from reportlab.pdfgen import canvas
 import io
-import random
-from datetime import datetime
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+from groq import Groq
 
-# Initialize Groq client
+# Initialize components
 try:
     groq_client = Groq(api_key=st.secrets["GROQ_API_KEY"])
-except KeyError:
-    st.error("GROQ_API_KEY missing in secrets! Add it in Hugging Face settings.")
-    st.stop()
-
-# Load personality model
-try:
-    model = AutoModelForSequenceClassification.from_pretrained(
-        "KevSun/Personality_LM", 
-        ignore_mismatched_sizes=True
-    )
+    model = AutoModelForSequenceClassification.from_pretrained("KevSun/Personality_LM", ignore_mismatched_sizes=True)
     tokenizer = AutoTokenizer.from_pretrained("KevSun/Personality_LM")
 except Exception as e:
-    st.error(f"Model loading error: {str(e)}")
+    st.error(f"Initialization error: {str(e)}")
     st.stop()
 
 # Configure Streamlit
-st.set_page_config(page_title="🧠 Mind Mapper Pro", layout="wide", page_icon="🤖")
+st.set_page_config(page_title="🧠 PersonaCraft", layout="wide", page_icon="🌟")
 
 # Custom CSS
 st.markdown("""
 <style>
-@keyframes rainbow {
-  0% { color: #ff0000; }
-  20% { color: #ff8000; }
-  40% { color: #ffff00; }
-  60% { color: #00ff00; }
-  80% { color: #0000ff; }
-  100% { color: #ff00ff; }
+@keyframes fadeIn {
+  from { opacity: 0; }
+  to { opacity: 1; }
 }
-.personality-title {
-  animation: rainbow 3s infinite;
-  font-size: 2.5em !important;
+
+.quote-box {
+    animation: fadeIn 1s ease-in;
+    border-left: 5px solid #4CAF50;
+    padding: 20px;
+    margin: 20px 0;
+    background: #f8fff9;
+    border-radius: 10px;
+    box-shadow: 0 4px 6px rgba(0,0,0,0.1);
 }
+
+.tip-card {
+    padding: 15px;
+    margin: 10px 0;
+    background: #fff3e0;
+    border-radius: 10px;
+    border: 1px solid #ffab40;
+}
+
 .social-post {
-  border: 2px solid #4CAF50;
-  border-radius: 15px;
-  padding: 20px;
-  margin: 15px 0;
-  background: #f8fff9;
+    background: #e3f2fd;
+    padding: 20px;
+    border-radius: 15px;
+    margin: 15px 0;
+}
+
+.viz-box {
+    background: white;
+    padding: 20px;
+    border-radius: 15px;
+    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
 }
 </style>
 """, unsafe_allow_html=True)
 
-# Personality traits
+# Personality configuration
 OCEAN_TRAITS = ["agreeableness", "openness", "conscientiousness", "extraversion", "neuroticism"]
-
-# Enhanced question bank with mix of serious and funny questions
 QUESTION_BANK = [
-    {"text": "If you were a kitchen appliance, which would you be and why? 🥄", "trait": "openness"},
-    {"text": "Describe your ideal Sunday vs your actual last Sunday 📆", "trait": "conscientiousness"},
-    {"text": "How would you survive a zombie apocalypse? 🧟", "trait": "neuroticism"},
-    {"text": "What's your spirit animal during tax season? 🦁", "trait": "agreeableness"},
-    {"text": "Plan a perfect date... with yourself! 💃", "trait": "extraversion"},
-    {"text": "If emotions were weather patterns, what's your forecast? ⛅", "trait": "neuroticism"},
-    {"text": "What would your childhood toy say about you? 🧸", "trait": "openness"},
-    {"text": "Describe your email inbox as a movie title 📧", "trait": "conscientiousness"},
-    {"text": "How do you react when someone says 'We need to talk'? 😬", "trait": "agreeableness"},
-    {"text": "What's your superpower in group projects? 🦸", "trait": "extraversion"}
+    {"text": "If your personality was a pizza topping, what would it be? 🍕", "trait": "openness"},
+    {"text": "Describe your ideal alarm clock vs reality ⏰", "trait": "conscientiousness"},
+    {"text": "How would you survive a surprise party? 🎉", "trait": "neuroticism"},
+    {"text": "What's your spirit animal during deadlines? 🐾", "trait": "agreeableness"},
+    {"text": "Plan a perfect day... for your nemesis! 😈", "trait": "extraversion"},
+    {"text": "If stress was a color, what's your current shade? 🎨", "trait": "neuroticism"},
+    {"text": "What would your browser history say about you? 🌐", "trait": "openness"},
+    {"text": "Describe your phone's home screen as a poem 📱", "trait": "conscientiousness"},
+    {"text": "React to 'Your idea is interesting, but...' 💡", "trait": "agreeableness"},
+    {"text": "What's your superpower in awkward situations? 🦸", "trait": "extraversion"}
 ]
 
-def analyze_psychology(text):
-    """Analyze personality traits using the specified model"""
-    encoded_input = tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=64)
-    with torch.no_grad():
-        outputs = model(**encoded_input)
-    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
-    return {trait: score.item() for trait, score in zip(OCEAN_TRAITS, predictions[0])}
+# Session state management
+if 'started' not in st.session_state:
+    st.session_state.started = False
+if 'current_q' not in st.session_state:
+    st.session_state.current_q = 0
+if 'responses' not in st.session_state:
+    st.session_state.responses = []
+if 'page' not in st.session_state:
+    st.session_state.page = "🏠 Home"
 
-def generate_social_post(platform, traits):
-    """Generate platform-specific social media post"""
-    prompt = f"""Create a {platform} post about personal growth based on these personality scores:
-{traits}
-Include relevant emojis and make it {platform}-appropriate. Keep it under 280 characters."""
-    
+# Functions
+def generate_quote():
+    prompt = "Generate a fresh motivational quote about self-discovery with an emoji"
     response = groq_client.chat.completions.create(
         model="mixtral-8x7b-32768",
         messages=[{"role": "user", "content": prompt}],
@@ -93,121 +100,166 @@ Include relevant emojis and make it {platform}-appropriate. Keep it under 280 ch
     )
     return response.choices[0].message.content
 
-def create_pdf_report(report):
-    """Generate downloadable PDF report"""
+def analyze_personality(text):
+    encoded_input = tokenizer(text, return_tensors='pt', padding=True, truncation=True, max_length=64)
+    with torch.no_grad():
+        outputs = model(**encoded_input)
+    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
+    return {trait: score.item() for trait, score in zip(OCEAN_TRAITS, predictions[0])}
+
+def create_pdf_report(traits, quote):
     buffer = io.BytesIO()
     p = canvas.Canvas(buffer, pagesize=letter)
-    
     p.setFont("Helvetica-Bold", 16)
-    p.drawString(100, 750, "🌟 Psychological Profile Report 🌟")
+    p.drawString(100, 750, "🌟 PersonaCraft Psychological Report 🌟")
     p.setFont("Helvetica", 12)
     
     y_position = 700
-    content = [
-        f"Generated on: {datetime.now().strftime('%Y-%m-%d %H:%M')}",
-        "",
-        "Personality Traits:",
-        *[f"- {trait.upper()}: {score:.2f}" for trait, score in report['traits'].items()],
-        "",
-        "Personalized Quote:",
-        report['quote'],
-    ]
-    
-    for line in content:
-        p.drawString(100, y_position, line)
-        y_position -= 15
+    for trait, score in traits.items():
+        p.drawString(100, y_position, f"{trait.upper()}: {score:.2f}")
+        y_position -= 20
     
+    p.drawString(100, y_position-40, "Motivational Quote:")
+    p.drawString(100, y_position-60, quote)
     p.save()
     buffer.seek(0)
     return buffer
 
-# Session state management
-if 'responses' not in st.session_state:
-    st.session_state.responses = []
-if 'current_q' not in st.session_state:
-    st.session_state.current_q = 0
-if 'selected_questions' not in st.session_state:
-    st.session_state.selected_questions = random.sample(QUESTION_BANK, 5)
-
-# Main UI
-st.title("🧠 Mind Mapper Pro")
-st.markdown("### Your Advanced Psychology Assistant 🔍✨")
-
-# Progress tracker
-progress = st.session_state.current_q / 5
-st.markdown(f"""
-<div style="background: #f0f2f6; border-radius: 15px; padding: 5px;">
-    <div style="width: {progress*100}%; height: 25px; border-radius: 15px; background: linear-gradient(90deg, #FF6B6B 0%, #4ECDC4 100%);"></div>
-</div>
-""", unsafe_allow_html=True)
-
-# Question flow
-if st.session_state.current_q < 5:
-    q = st.session_state.selected_questions[st.session_state.current_q]
-    
-    with st.chat_message("assistant"):
-        st.markdown(f"### {q['text']}")
-        user_input = st.text_input("Your response:", key=f"q{st.session_state.current_q}")
-        
-        if st.button("Next ➡️"):
-            st.session_state.responses.append(user_input)
-            st.session_state.current_q += 1
-            st.rerun()
-else:
-    # Generate report
-    combined_text = "\n".join(st.session_state.responses)
-    traits = analyze_psychology(combined_text)
-    
-    report = {
-        "traits": traits,
-        "quote": generate_social_post("general", traits)  # Initial quote
+def generate_social_post(platform, traits):
+    platform_formats = {
+        "LinkedIn": "professional tone with industry hashtags",
+        "Instagram": "visual storytelling with emojis",
+        "Facebook": "friendly community-oriented style",
+        "WhatsApp": "casual conversational format",
+        "Twitter": "concise with trending hashtags"
     }
+    prompt = f"""Create a {platform} post about personal growth with these personality traits:
+{traits}
+Format: {platform_formats[platform]}
+Include relevant emojis and keep under 280 characters."""
     
-    st.balloons()
-    st.markdown(f"## <div class='personality-title'>🌟 Your Personality Profile 🌟</div>", unsafe_allow_html=True)
-    
-    # Trait Visualization
-    with st.expander("🧩 Personality Breakdown"):
-        cols = st.columns(5)
-        for i, (trait, score) in enumerate(report['traits'].items()):
-            cols[i].metric(label=trait.upper(), value=f"{score:.2f}")
-
-    # Social Media Post Generation
-    st.markdown("### 📱 Create Social Media Post")
-    platform = st.selectbox("Choose platform:", ["LinkedIn", "Instagram", "Facebook", "WhatsApp"])
-    
-    if st.button("Generate Post 🚀"):
-        post = generate_social_post(platform, report['traits'])
-        st.session_state.post = post
-    
-    if 'post' in st.session_state:
-        st.markdown(f"""
-        <div class="social-post">
-            {st.session_state.post}
-        </div>
-        """, unsafe_allow_html=True)
-        st.button("📋 Copy Post", on_click=lambda: st.write(st.session_state.post))
-
-    # PDF Report
-    pdf_buffer = create_pdf_report(report)
-    st.download_button(
-        "📥 Download Full Report", 
-        data=pdf_buffer, 
-        file_name="personality_profile.pdf",
-        mime="application/pdf"
+    response = groq_client.chat.completions.create(
+        model="mixtral-8x7b-32768",
+        messages=[{"role": "user", "content": prompt}],
+        temperature=0.7
     )
+    return response.choices[0].message.content
 
-# Sidebar
-with st.sidebar:
-    st.markdown("## 🌈 Features Overview")
-    st.markdown("""
-    - **Enhanced Personality Assessment**
-    - **Social Media Post Generator**
-    - **Interactive Question Flow**
-    - **PDF Report Download**
+# Main UI
+if not st.session_state.started:
+    st.markdown(f"""
+    <div class="quote-box">
+        <h2>🌟 Welcome to PersonaCraft! 🌟</h2>
+        <h3>{generate_quote()}</h3>
+    </div>
+    """, unsafe_allow_html=True)
     
-    **New Features:**
-    - 🎭 Fun psychological questions
-    - 📱 Platform-specific post crafting
-    - 🧠 Advanced personality modeling
-    """)
+    if st.button("🚀 Start Personality Journey!", use_container_width=True):
+        st.session_state.started = True
+        st.session_state.selected_questions = random.sample(QUESTION_BANK, 5)
+        st.rerun()
+else:
+    # Sidebar navigation
+    with st.sidebar:
+        st.title("🧭 Navigation")
+        st.session_state.page = st.radio("Choose Section:", [
+            "📋 Personality Report", 
+            "📊 Visual Analysis",
+            "📱 Social Media Post",
+            "💡 Success Tips",
+            "📥 Download Report"
+        ])
+
+    # Question flow
+    if st.session_state.current_q < 5:
+        q = st.session_state.selected_questions[st.session_state.current_q]
+        st.progress(st.session_state.current_q/5, text="Assessment Progress")
+        
+        with st.chat_message("assistant"):
+            st.markdown(f"### {q['text']}")
+            user_input = st.text_input("Your response:", key=f"q{st.session_state.current_q}")
+            
+            if st.button("Next ➡️"):
+                st.session_state.responses.append(user_input)
+                st.session_state.current_q += 1
+                st.rerun()
+    else:
+        # Process responses
+        traits = analyze_personality("\n".join(st.session_state.responses))
+        quote = generate_quote()
+        
+        # Current page display
+        if st.session_state.page == "📋 Personality Report":
+            st.header("📋 Personality Breakdown")
+            cols = st.columns(5)
+            for i, (trait, score) in enumerate(traits.items()):
+                cols[i].metric(label=trait.upper(), value=f"{score:.2f}")
+            
+            st.divider()
+            st.header("🎭 Emotional Landscape")
+            emotion_data = pd.DataFrame({
+                "Trait": traits.keys(),
+                "Score": traits.values()
+            })
+            st.altair_chart(alt.Chart(emotion_data).mark_bar().encode(
+                x="Trait",
+                y="Score",
+                color=alt.Color("Trait", legend=None)
+            ), use_container_width=True)
+
+        elif st.session_state.page == "📊 Visual Analysis":
+            st.header("📊 Personality Visualization")
+            radar_data = pd.DataFrame({
+                "Trait": list(traits.keys()) * 2,
+                "Score": list(traits.values()) * 2,
+                "Type": ["Base"]*5 + ["Current"]*5
+            })
+            st.altair_chart(alt.Chart(radar_data).mark_line().encode(
+                theta="Trait",
+                r="Score",
+                color="Type"
+            ).project(type='radial'), use_container_width=True)
+
+        elif st.session_state.page == "📱 Social Media Post":
+            st.header("📱 Create Social Post")
+            platform = st.selectbox("Select Platform:", ["LinkedIn", "Instagram", "Facebook", "WhatsApp", "Twitter"])
+            
+            if st.button("Generate Post 🚀"):
+                post = generate_social_post(platform, traits)
+                st.session_state.post = post
+            
+            if 'post' in st.session_state:
+                st.markdown(f"""
+                <div class="social-post">
+                    <p>{st.session_state.post}</p>
+                </div>
+                """, unsafe_allow_html=True)
+                st.button("��� Copy to Clipboard", on_click=lambda: st.write(st.session_state.post))
+
+        elif st.session_state.page == "💡 Success Tips":
+            st.header("💡 Personality Success Tips")
+            tips = [
+                "🌱 Practice daily self-reflection journaling",
+                "🤝 Seek diverse social interactions weekly",
+                "🎯 Set SMART goals for personal development",
+                "🧘♂️ Incorporate mindfulness practices daily",
+                "📚 Engage in cross-disciplinary learning",
+                "🗣️ Practice active listening techniques",
+                "🔄 Embrace constructive feedback regularly",
+                "⚖️ Maintain work-life harmony",
+                "🌟 Develop emotional granularity skills",
+                "🚀 Challenge comfort zones monthly"
+            ]
+            for tip in tips:
+                st.markdown(f"<div class='tip-card'>{tip}</div>", unsafe_allow_html=True)
+
+        elif st.session_state.page == "📥 Download Report":
+            st.header("📥 Download Complete Report")
+            pdf_buffer = create_pdf_report(traits, quote)
+            st.download_button(
+                "⬇️ Download PDF Report",
+                data=pdf_buffer,
+                file_name="personacraft_report.pdf",
+                mime="application/pdf",
+                use_container_width=True
+            )