Update app.py

app.py

@@ -1,62 +1,147 @@
 from langchain_google_genai import GoogleGenerativeAI
 import streamlit as st
+import re
+from datetime import datetime
 
-# initializing llm
-llm = GoogleGenerativeAI(
-    model="gemini-1.5-flash",
-    google_api_key="AIzaSyDgOkz_5iou4gl5aaDUNyXfhb63W3E27-o",
-    temperature=0.7,
-    top_p=0.9,
-    max_tokens=1000,
-    frequency_penalty=0.5,
-    presence_penalty=0.3,
-    stop_sequences=["User:", "Assistant:"]
-)
-
-# initializing role, requirements
-instruction = "Answer user's(patient) questions politely and provide him accurate information."
-context = (
-    "You are a medical assistant doctor named DoctorX."
-    "You will ask user which might be a patient about his health, get symptoms from him, predicts his disease and suggest him a good and quick remeedy or prescription based on users condition."
-    "Continue Asking more about his condition or health and suggest him a doctor if required."
-    "Also give user you a good line to reduce his tension"
-)
-input_data = (
-    "Additional information:\n",
-    "Hospital Address: John Smith Hospital",
-    "Ambulance Call: 1111",
-    "Doctor Number: +3100-1000-100"
-)
-
-# Streamlit UI Setup
-st.set_page_config(page_title="DoctorX: HealthCare", layout="wide")
-st.title("🧠 DoctorX: HealthCare")
-
-# Enhanced logic for chatbot interaction
-if prompt := st.chat_input("Type your question here..."):
-    with st.chat_message("user"):
-        st.markdown(prompt)
-
-    with st.chat_message("bot"):
-        with st.spinner("🤖 Thinking..."):
-            try:
-                # Constructing the prompt with enhanced context
-                enhanced_prompt = (
-                    f"{instruction}\n\n"
-                    f"{context}\n\n"
-                    f"{input_data}\n\n"
-                    f"User's Query: {prompt}\n\n"
-                    "Follow-up: Ask the user about their symptoms, provide a possible diagnosis, and suggest remedies or prescriptions."
-                )
-
-                # Stream the response from the LLM
-                response = ""
-                for chunk in llm.stream(enhanced_prompt):
-                    response += chunk
-                    st.markdown(response)  # Display the response incrementally
-
-                # Add stress-relief advice
-                st.markdown("\n**Stress-Relief Tip:** Remember to take deep breaths and stay hydrated.")
-
-            except Exception as e:
-                st.error(f"⚠️ Error processing query: {e}")
+# --- Configuration ---
+MODEL_CONFIG = {
+    "model": "gemini-pro",
+    "temperature": 0.7,
+    "top_p": 0.85,
+    "max_tokens": 1024,
+    "safety_settings": {
+        "HARASSMENT":"BLOCK_ONLY_HIGH",
+        "HATE_SPEECH":"BLOCK_ONLY_HIGH",
+        "SEXUAL":"BLOCK_ONLY_HIGH",
+        "DANGEROUS":"BLOCK_ONLY_HIGH"
+    }
+}
+
+EMERGENCY_CONTACTS = {
+    "Hospital Address": "John Smith Hospital, 123 Health St.",
+    "Ambulance": "911 (US) / 112 (EU)",
+    "24/7 Support": "+1-800-123-4567"
+}
+
+# --- Security & Sanitization ---
+def sanitize_input(text):
+    """Remove potentially harmful patterns"""
+    return re.sub(r"[<>{}[\]~`]", "", text[:2000])
+
+# --- AI Response Validation ---
+def validate_medical_response(text):
+    """Basic safety checks for AI responses"""
+    blacklist = ["take your own life", "kill yourself", "hate you"]
+    return not any(phrase in text.lower() for phrase in blacklist)
+
+# --- Streamlit App ---
+def main():
+    st.set_page_config(
+        page_title="DoctorX: AI Health Assistant",
+        page_icon="🩺",
+        layout="centered",
+        initial_sidebar_state="collapsed"
+    )
+
+    # Initialize session state
+    if "history" not in st.session_state:
+        st.session_state.history = []
+    
+    # --- Sidebar with Emergency Info ---
+    with st.sidebar:
+        st.header("🆘 Emergency Contacts")
+        for key, value in EMERGENCY_CONTACTS.items():
+            st.subheader(key)
+            st.caption(value)
+        st.divider()
+        st.caption("⚠️ This is not a substitute for emergency medical care")
+
+    # --- Main Interface ---
+    st.title("🩺 DoctorX Health Assistant")
+    st.caption("AI-powered preliminary health guidance - Always consult a human doctor for final diagnosis")
+
+    # Display chat history
+    for role, message in st.session_state.history:
+        with st.chat_message(role):
+            st.markdown(message)
+
+    # User input with enhanced options
+    with st.form("chat_input"):
+        col1, col2 = st.columns([4, 1])
+        with col1:
+            user_input = st.text_input(
+                "Describe your symptoms or ask a question:",
+                placeholder="E.g., I've had a headache for 3 days...",
+                max_chars=500
+            )
+        with col2:
+            if st.form_submit_button("Send", use_container_width=True):
+                user_input = sanitize_input(user_input.strip())
+                
+                if user_input.lower() in ["emergency", "911", "112"]:
+                    st.session_state.history.append(("user", user_input))
+                    st.session_state.history.append(("bot", "🚨 Please use the emergency contacts in the sidebar immediately!"))
+                    st.rerun()
+
+                elif user_input:
+                    process_user_input(user_input)
+
+    # Quick symptom buttons
+    common_symptoms = ["Fever", "Headache", "Cough", "Rash", "Nausea"]
+    cols = st.columns(len(common_symptoms))
+    for col, symptom in zip(cols, common_symptoms):
+        if col.button(symptom):
+            process_user_input(f"I'm experiencing {symptom.lower()}")
+
+    # Quick response buttons for common queries
+    common_queries = ["What are the symptoms of epilepsy?", "How to manage stress?"]
+    cols = st.columns(len(common_queries))
+    for col, query in zip(cols, common_queries):
+        if col.button(query):
+            process_user_input(query)
+
+def process_user_input(user_input):
+    """Handle user input and generate AI response"""
+    llm = GoogleGenerativeAI(google_api_key=st.secrets["GOOGLE_API_KEY"], **MODEL_CONFIG)
+    
+    # Build medical context
+    system_prompt = f"""
+    You are DoctorX, an AI medical assistant. Follow these rules STRICTLY:
+    1. Never diagnose - suggest POSSIBLE conditions
+    2. Always recommend consulting a human doctor
+    3. Prioritize patient safety over all else
+    4. Maintain professional, empathetic tone
+    5. Disclose your AI nature clearly
+    6. For emergencies, direct to sidebar contacts
+    
+    Current Date: {datetime.now().strftime("%Y-%m-%d")}
+    User Input: {user_input}
+    """
+    
+    try:
+        with st.chat_message("user"):
+            st.markdown(user_input)
+            
+        with st.chat_message("bot"):
+            with st.spinner("🔍 Analyzing symptoms..."):
+                response = llm.invoke(system_prompt)
+                
+                if not validate_medical_response(response):
+                    raise ValueError("Response validation failed")
+                
+                # Format medical information
+                response = response.replace("**Possible Condition:**", "\n🩺 **Possible Condition:**")
+                response = response.replace("**Recommendation:**", "\n📋 **Recommendation:**")
+                
+                st.markdown(response)
+                st.caption("ℹ️ AI-generated suggestion - Verify with healthcare professional")
+
+            st.session_state.history.append(("user", user_input))
+            st.session_state.history.append(("bot", response))
+
+    except Exception as e:
+        st.error(f"⚠️ System Error: {str(e)}")
+        st.session_state.history.append(("bot", "🚨 Error processing request. Please try again later."))
+
+if __name__ == "__main__":
+    main()