Upload counselor_assistant.py

counselor_assistant.py

@@ -0,0 +1,416 @@
+import streamlit as st
+import torch
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+from transformers import pipeline
+pipe = pipeline("text-classification", model="distilbert-base-uncased")  # 67MB vs BERT's 440MB
+
+classifier = pipeline("text-classification", model="distilbert-base-uncased-finetuned-sst-2-english")
+
+import time
+from datetime import datetime
+
+@st.cache_data
+def load_model():
+    return pipeline("text-classification", model="distilbert-base-uncased")  # Cached after first run
+
+
+# from transformers import pipeline
+# pipe = pipeline('text-generation', model='gpt2', device=0 if torch.cuda.is_available() else -1)
+
+# from transformers import pipeline
+# classifier = pipeline("text-classification", model="distilbert-base-uncased", device="cpu")  # Faster init
+
+#########
+
+# import os
+# from fastapi import FastAPI
+# from fastapi.middleware.wsgi import WSGIMiddleware
+# from streamlit.web.server import Server
+
+# app = FastAPI()
+# app.mount("/", WSGIMiddleware(Server._get_app().wsgi_app))
+
+# @app.get("/health")
+# def health_check():
+#     return {"status": "healthy"}
+
+# if os.getenv("STREAMLIT_CLOUD"):
+#     import uvicorn
+#     uvicorn.run(app, host="0.0.0.0", port=8501)
+
+# @st.cache_resource(ttl=3600, max_entries=3)
+# def load_model():
+#  return pipeline('text-generation', model='gpt2')  # Use smaller models
+
+########## health check for server
+
+# 1. APP CONFIGURATION ================================================
+st.set_page_config(
+    page_title="Counselor Guidance Assistant",
+    page_icon="🧠",
+    layout="centered",
+    initial_sidebar_state="expanded"
+)
+
+# 2. CUSTOM STYLING ==================================================
+st.markdown("""
+<style>
+ :root {
+  --primary_clr: #43a573;
+  --secondary: #f8f9fa;
+  --font_clr: #1a1a1a;
+  --bg_clr: #e9f5ef;
+  --bg_clr_g2: #d9ede3;
+  --bg_clr_g3: #1b422e;
+  --border_clr: #1b422e;
+
+
+  /* Dark Mode Overrides */
+  --dark-primary: #43a573;
+  --dark-secondary: #2d3748;
+  --dark-font: #e2e8f0;
+  --dark-bg: #1a202c;
+  --dark-bg2: #2d3748;
+  --dark-bg3: #38a169;
+  --dark-border: #4a5568;
+ }
+
+
+
+ * {
+  box-sizing: border-box;
+ }
+
+ html,body {
+  font-family: sans-serif;
+  line-height: 1.5;
+  -webkit-text-size-adjust: 100%;
+  -ms-text-size-adjust: 100%;
+  -ms-overflow-style: scrollbar;
+  -webkit-tap-highlight-color: transparent;
+  margin:0;
+  height: 100%;
+  color: var(--font_clr);
+  background-color: var(--bg_clr)
+ }
+
+ @-ms-viewport {
+ width: device-width;
+ }
+
+ .stAppHeader, .stMain{
+  background-color: var(--bg_clr)
+ }
+
+ .stSidebar{
+  background-color: var(--bg_clr_g2);
+ }
+
+  .stTextArea textarea, .stTextArea > textarea {
+  min-height: 250px;
+  font-size: 16px;
+  background-color: var(--bg_clr_g2);
+  border-color: var(--border_clr);
+  resize: none;
+ }
+
+ .responseCard {
+  background-color: var(--bg_clr);
+  border-radius: 10px;
+  padding: 1.5rem;
+  margin: 1rem 0;
+  border-left: 4px solid var(--primary_clr);
+ }
+ 
+ .stButton button, .stButton > button {
+  background-color: var(--primary_clr);
+  color: white;
+  transition: all 0.3s;
+  border: 1px solid var(--border_clr);
+ }
+ 
+ .stButton button:hover, .stButton button:focus:not(:active) {
+  opacity: 0.9;
+  transform: translateY(-1px);
+  color: white;
+  background-color: var(--bg_clr_g3);
+  border: 1px solid var(--border_clr);
+ }
+
+ /*
+ .stSlider [role="slider"]{
+  background-color: var(--bg_clr_g3);
+ }
+
+ .stSlider [role="slider"] .st-an, .stSlider [role="slider"] .st-ap, .stSlider [role="slider"] .st-aq,
+ .stSlider [role="slider"] .st-ao, .stSlider [role="slider"] .st-cu, .stSlider [role="slider"] .st-cv,
+ .stSlider [role="slider"] .st-am, .stSlider [role="slider"] .st-cw, .stSlider [role="slider"] .st-cx{
+  background: linear-gradient(to right, rgb(27, 66, 46) 0%, 
+  rgb(27, 66, 46) 72.2222%,
+  rgba(151, 166, 195, 0.25) 72.2222%,
+  rgba(151, 166, 195, 0.25) 100%) !important;
+ }*/
+
+ 
+ .progress-container {
+  margin-top: -10px;
+  margin-bottom: 15px;
+ }
+
+ summary[class*="st-emotion-cache-"]:hover{
+  font-weight:800;
+  color: var(--font_clr);
+ }
+ 
+ .crisis-alert {
+  background-color: #fff8f8;
+  border-left: 5px solid #ff4b4b;
+  padding: 1.5rem;
+  margin: 1rem 0;
+  border-radius: 0 8px 8px 0;
+  box-shadow: 0 2px 8px rgba(255, 75, 75, 0.15);
+  animation: pulse 2s infinite;
+ }
+ 
+ @keyframes pulse {
+  0% { border-left-color: #ff4b4b; }
+  50% { border-left-color: #ff9999; }
+  100% { border-left-color: #ff4b4b; }
+ }
+ 
+ .crisis-alert strong {
+  color: #d10000;
+ }
+</style>
+""", unsafe_allow_html=True)
+
+# 3. MODEL LOADING ===================================================
+@st.cache_resource(show_spinner=False)
+def load_model():
+    return pipeline("text2text-generation", model="google/flan-t5-base")
+
+
+# 4. PROMPT ENGINEERING ==============================================
+def generate_prompt(user_input, counseling_style):
+    """Generate context-aware prompts for different counseling approaches"""
+    style_prompts = {
+        "Cognitive Behavior Therapy": (
+            "As a CBT therapist, suggest techniques to address: '{input}'. "
+            "Focus on identifying cognitive distortions and suggest behavioral experiments. "
+            "Provide 2-3 concrete interventions."
+        ),
+        "Psychodynamic": (
+            "From a psychodynamic perspective, analyze: '{input}'. "
+            "Consider unconscious patterns and childhood influences. "
+            "Suggest exploratory questions to reveal underlying conflicts."
+        ),
+        "Humanistic": (
+            "Using humanistic approach, respond to: '{input}'. "
+            "Focus on unconditional positive regard and self-actualization. "
+            "Provide empathetic reflections and growth-oriented suggestions."
+        ),
+        "Solution-Focused": (
+            "Using solution-focused therapy, address: '{input}'. "
+            "Identify exceptions to the problem and small achievable steps. "
+            "Suggest 2-3 scaling questions or miracle questions."
+        )
+    }
+    return style_prompts[counseling_style].format(input=user_input)
+
+def get_references(approach):
+    """Return evidence-based references with clinical guidelines"""
+    references = {
+        "Cognitive Behavior Therapy": {
+            "text": "Beck, J. S. (2011). Cognitive Behavior Therapy: Basics and Beyond",
+            "guide": "https://www.apa.org/pubs/books/cognitive-behavior-therapy"
+        },
+        "Psychodynamic": {
+            "text": "McWilliams, N. (2020). Psychoanalytic Diagnosis",
+            "guide": "https://www.guilford.com/books/Psychoanalytic-Diagnosis/McWilliams/9781462543694"
+        },
+        "Humanistic": {
+            "text": "Rogers, C. (1951). Client-Centered Therapy",
+            "guide": "https://www.nationalcounsellingsociety.org/about-therapy/types/humanistic"
+        },
+        "Solution-Focused": {
+            "text": "De Shazer, S. (1988). Clues: Investigating Solutions in Brief Therapy",
+            "guide": "https://www.solutionfocused.net/what-is-sfbt/"
+        }
+    }
+    ref = references.get(approach, {
+        "text": "Evidence-Based Practice in Psychology",
+        "guide": "https://www.apa.org/practice/guidelines/evidence-based"
+    })
+    return f"{ref['text']} | [Clinical Guidelines]({ref['guide']})"
+
+# 5. MAIN APPLICATION ================================================
+def main():
+ # Initialize session history
+ if 'history' not in st.session_state:
+     st.session_state.history = []
+ 
+ st.title("🧠 Counselor Guidance Assistant")
+ st.markdown("""
+ *Professional support for mental health practitioners*  
+
+ Enter a patient scenario below for evidence-based intervention suggestions.
+ """)
+ 
+ # Sidebar configuration
+ with st.sidebar:
+  st.title("Session Settings")
+  counseling_style = st.selectbox(
+      "Therapeutic Approach",
+      ["Cognitive Behavior Therapy", "Psychodynamic", "Humanistic", "Solution-Focused"],
+      index=0
+  )
+  creativity = st.slider("Response Creativity", 0.1, 1.0, 0.7)
+  st.markdown("---")
+  
+  st.caption("""
+  **Best Practices:**
+  1. Describe specific behaviors/symptoms
+  2. Include relevant history
+  3. Note attempted interventions
+  """)
+
+  # Session history viewer
+  if st.session_state.history:
+   with st.expander("📚 Session History (Last 5)"):
+    for i, session in enumerate(st.session_state.history[-5:][::-1]):
+        st.markdown(f"""
+        **Session {len(st.session_state.history)-i}** ({session['timestamp']})
+        - Approach: {session['approach']}
+        - Case: {session['case']}
+        """)
+        if st.button(f"View Details #{len(st.session_state.history)-i}", key=f"view_{i}"):
+            st.session_state.current_session = session
+     
+ # Example cases for quick testing
+ with st.expander("💡 Quick Start : Explore most commons challenges!! "):
+  examples = {
+    "Depression": "45yo male with treatment-resistant depression, expresses hopelessness about ever improving",
+    "Anxiety": "College student experiencing panic attacks before exams despite knowing the material well",
+    "Relationship": "Couple stuck in pursue-withdraw pattern, escalating arguments about household responsibilities"
+  }
+  cols = st.columns(3)
+  for i, (label, example) in enumerate(examples.items()):
+   with cols[i]:
+    if st.button(label):
+     case_description = example    
+ 
+ # Main input area
+ case_description = st.text_area(
+  "Type your challenge below:",
+  placeholder="My 28-year-old patient with social anxiety avoids all group situations despite previous exposure work...",
+  height=250
+ )
+ 
+ # Crisis keywords detection
+ CRISIS_KEYWORDS = ['suicide', 'self-harm', 'homicide', 'abuse', 'abused', 'kill myself', 'kill', 
+          'want to die', 'end my life', 'hurt myself', 'hurt someone','suicidal']
+ 
+ # Response generation
+ if st.button("Analyze && Suggest", type="primary"):
+  if not case_description.strip():
+   st.warning("Please describe the clinical situation")
+  else:
+   # Crisis detection
+   if any(keyword in case_description.lower() for keyword in CRISIS_KEYWORDS):
+    st.markdown("""
+    <div class="crisis-alert">
+        <div style="font-size: 1.3rem;">⚠️ <strong>CRISIS ALERT</strong> - Immediate Action Required</div>
+        <br>
+        <div><strong>Clinical Protocols:</strong></div>
+        <ol>
+            <li>Assess immediate safety risk using direct questioning</li>
+            <li>Implement safety planning if risk is present</li>
+            <li>Do not leave patient alone if active suicidal/homicidal ideation exists</li>
+        </ol>
+        <div><strong>Emergency Resources:</strong></div>
+        <ul>
+            <li>🇺🇸 <strong>988 Suicide & Crisis Lifeline</strong> (24/7)</li>
+            <li>📱 <strong>Crisis Text Line</strong>: Text HOME to 741741</li>
+            <li>🌎 <strong>International Association for Suicide Prevention</strong>: <a href="https://www.iasp.info/resources/Crisis_Centres/">Find Local Help</a></li>
+        </ul>
+    </div>
+    """, unsafe_allow_html=True)
+    
+    with st.expander("📋 Clinician Guidance (Click for Protocol Details)"):
+     st.markdown("""
+     **Standard Crisis Response Protocol:**
+     1. **Direct Assessment**  
+        "Are you having thoughts of ending your life?"  
+        "Do you have a plan?"  
+        "Have you ever attempted before?"
+     
+     2. **Safety Planning**  
+        - Remove access to means  
+        - Identify support contacts  
+        - Create step-by-step coping strategies
+     
+     3. **Documentation**  
+        - Risk assessment findings  
+        - Actions taken  
+        - Follow-up plan
+     """)
+    
+    # Log crisis event
+    st.session_state.history.append({
+        'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M"),
+        'approach': "CRISIS INTERVENTION",
+        'case': "CRISIS DETECTED - " + case_description[:50] + "...",
+        'recommendations': "Session halted - emergency protocols activated"
+    })
+    st.stop()
+   
+   with st.spinner("Generating evidence-based suggestions..."):
+    try:
+        llm = load_model()
+        prompt = generate_prompt(case_description, counseling_style)
+        
+        # Simulate processing steps for better UX
+        progress_bar = st.progress(0)
+        for percent in range(0, 101, 20):
+            time.sleep(0.1)
+            progress_bar.progress(percent)
+        
+        response = llm(
+            prompt,
+            max_length=500,
+            do_sample=True,
+            temperature=creativity
+        )[0]['generated_text']
+        
+        # Store session in history
+        st.session_state.history.append({
+            'timestamp': datetime.now().strftime("%Y-%m-%d %H:%M"),
+            'approach': counseling_style,
+            'case': case_description[:100] + "..." if len(case_description) > 100 else case_description,
+            'recommendations': response
+        })
+        
+        # Display formatted response
+        st.markdown("## Clinical Recommendations")
+        with st.container():
+            st.markdown(f'<div class="responseCard">{response}</div>', 
+                       unsafe_allow_html=True)
+            
+            # Add references
+            st.markdown("---")
+            st.caption(f"**Reference:** {get_references(counseling_style)}")
+            
+            # Response tools
+            st.download_button(
+                "Save Recommendations",
+                data=f"Approach: {counseling_style}\n\n{response}",
+                file_name=f"clinical_suggestions_{counseling_style}.txt"
+            )
+        
+    except Exception as e:
+        st.error(f"Error generating suggestions: {str(e)}")
+
+if __name__ == "__main__":
+    main()
+