Delete app.py

app.py

@@ -1,133 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
-import nltk
-import re
-
-# -------------------------
-# Safety Disclaimer
-# -------------------------
-DISCLAIMER = """
-⚠️ I’m not a therapist. I provide emotional support, not medical advice.
-If you're in crisis, please seek professional help immediately.
-India Helpline: AASRA 9820466726
-US: Call or text 988
-"""
-
-# -------------------------
-# Load NLP Models
-# -------------------------
-@st.cache_resource
-def load_models():
-    sentiment_model = pipeline("sentiment-analysis")
-    vader = SentimentIntensityAnalyzer()
-    return sentiment_model, vader
-
-sentiment_model, vader = load_models()
-
-# -------------------------
-# Crisis Detection
-# -------------------------
-CRISIS_KEYWORDS = [
-    "suicide", "kill myself", "end my life",
-    "self harm", "die", "hopeless", "no reason to live"
-]
-
-def detect_crisis(text):
-    text_lower = text.lower()
-    return any(keyword in text_lower for keyword in CRISIS_KEYWORDS)
-
-# -------------------------
-# Mood Detection
-# -------------------------
-def detect_mood(text):
-    if detect_crisis(text):
-        return "critical"
-    
-    vader_score = vader.polarity_scores(text)['compound']
-    
-    if vader_score >= 0.5:
-        return "positive"
-    elif vader_score <= -0.5:
-        if "anxious" in text.lower() or "panic" in text.lower():
-            return "anxious"
-        return "sad"
-    elif "stress" in text.lower() or "exam" in text.lower():
-        return "stressed"
-    else:
-        return "neutral"
-
-# -------------------------
-# Empathetic Responses
-# -------------------------
-def generate_response(mood, user_text):
-    
-    if mood == "critical":
-        return (
-            "I'm really sorry you're feeling this much pain. "
-            "You deserve support right now. Please consider reaching out to "
-            "AASRA (India: 9820466726) or 988 (US). "
-            "If you're in immediate danger, call emergency services. "
-            "You're not alone, even if it feels that way."
-        )
-
-    elif mood == "sad":
-        return (
-            "I hear that you're feeling low. It’s completely okay to feel this way. "
-            "Would you like to share what’s weighing on you? "
-            "Even small steps count. You’ve handled difficult days before."
-        )
-
-    elif mood == "anxious":
-        return (
-            "It sounds like you're feeling anxious. That can be really overwhelming. "
-            "Let’s try something simple: inhale for 4 seconds, hold for 7, "
-            "exhale for 8. Repeat 3 times. "
-            "Your mind deserves calm."
-        )
-
-    elif mood == "stressed":
-        return (
-            "I hear you're feeling stressed—maybe exams or placements? "
-            "Break it into small tasks. Study 25 minutes, rest 5. "
-            "You’ve tackled tough assignments before—you’ve got this!"
-        )
-
-    elif mood == "positive":
-        return (
-            "That’s great to hear! 😊 "
-            "Keep nurturing what’s working for you. "
-            "Would you like a quick productivity boost or gratitude exercise?"
-        )
-
-    else:
-        return (
-            "Thanks for sharing. How are you feeling today? "
-            "You can talk freely here—this space is for you."
-        )
-
-# -------------------------
-# Streamlit UI
-# -------------------------
-st.set_page_config(page_title="Mental Health Companion", page_icon="🧠")
-
-st.title("🧠 Student Mental Health Companion")
-st.write(DISCLAIMER)
-
-if "chat_history" not in st.session_state:
-    st.session_state.chat_history = []
-
-user_input = st.text_input("How are you feeling today?")
-
-if user_input:
-    mood = detect_mood(user_input)
-    response = generate_response(mood, user_input)
-    
-    st.session_state.chat_history.append(("You", user_input))
-    st.session_state.chat_history.append(("Companion", response))
-
-for sender, message in st.session_state.chat_history:
-    if sender == "You":
-        st.markdown(f"**You:** {message}")
-    else:
-        st.markdown(f"**Companion:** {message}")