Update app.py

app.py

@@ -10,10 +10,17 @@ from openai import OpenAI
 app = Flask(__name__)
 
 # Initialize OpenAI client
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+api_key = os.getenv("OPENAI_API_KEY")
+if not api_key:
+    print("Warning: OPENAI_API_KEY not set. Fallback responses will be used.")
+client = OpenAI(api_key=api_key) if api_key else None
 
 # Emotion analysis model
-emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")
+try:
+    emotion_model = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base")
+except Exception as e:
+    print(f"Emotion model error: {e}. Using fallback.")
+    emotion_model = None
 
 # Load or create user data
 USER_FILE = "user_data.json"
@@ -29,7 +36,7 @@ def save_user(data):
     with open(USER_FILE, "w") as f:
         json.dump(data, f)
 
-# Helpline data (expanded for better coverage)
+# Helpline data
 HELPLINES = {
     "US": "National Suicide Prevention Lifeline: 988",
     "UK": "Samaritans: 116 123",
@@ -54,57 +61,70 @@ def detect_critical_situation(message):
     keywords = ["suicide", "kill myself", "end my life", "self harm", "hurt myself", "crisis", "emergency", "harm others", "panic attack", "overdose"]
     return any(keyword in message.lower() for keyword in keywords)
 
+def get_fallback_reply(mode, emotion):
+    if mode == "emotional_support":
+        return "I hear you. You're not alone—let's talk more." if emotion == "sadness" else "That sounds tough. I'm here to support you."
+    else:
+        return "For knowledge, ask a specific question. I'm here to help."
+
 @app.route("/chat", methods=["POST"])
 def chat():
     try:
         data = request.get_json()
         user_message = data.get("message", "")
         mode = data.get("mode", "emotional_support")
-        voice_tone = data.get("voice_tone", "neutral tone")  # New: Voice tone for response style
-        user_ip = request.remote_addr  # Get user's IP for country detection
+        voice_tone = data.get("voice_tone", "neutral tone")
+        user_ip = request.remote_addr
         user = load_user()
 
-        # Update last interaction, mode, and collect IP if not set
         now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         user["last_interaction"] = now
         user["mode"] = mode
         user["ip"] = user_ip
         user["conversation_history"].append({"role": "user", "content": user_message, "timestamp": now})
 
-        # Detect emotion
-        emotion = emotion_model(user_message)[0]["label"]
+        emotion = "neutral"
+        if emotion_model:
+            try:
+                emotion = emotion_model(user_message)[0]["label"]
+            except Exception as e:
+                print(f"Emotion analysis error: {e}")
         user["mood"] = emotion
 
-        # Check for critical situation
         if detect_critical_situation(user_message):
             country = get_country_from_ip(user_ip)
             helpline = HELPLINES.get(country, HELPLINES["default"])
-            reply = f"I'm really concerned about what you're sharing. Your safety is the most important thing. Please reach out to professionals immediately: {helpline}. You're not alone—talk to someone who can help right now. Can you tell me more about what's going on, or is there someone I can suggest you contact?"
+            reply = f"I'm concerned. Call {helpline} now. Talk to someone."
             user["conversation_history"].append({"role": "assistant", "content": reply, "timestamp": now})
             save_user(user)
             return jsonify({"reply": reply, "emotion": emotion})
 
-        # Build conversation context from history (limit to last 10 for precision)
         history = user["conversation_history"][-10:]
-        messages = [
-            {"role": "system", "content": f"You are an emotional support companion — warm, human-like, understanding, and caring. Respond in a smooth, gentle, and calm tone. Your goal is to listen, understand feelings, comfort gently, and motivate naturally. Do NOT act like a professional therapist — act like a kind, emotionally intelligent friend who truly cares. Guiding principles: 1. Listen first: Always acknowledge feelings before motivating (e.g., 'That sounds really hard, I can understand why you’d feel that way.'). 2. Don’t repeat phrases; use varied, natural language (e.g., 'That must have been tough.' or 'It’s okay to feel this way sometimes.'). 3. Show curiosity and care with gentle questions (e.g., 'Do you want to tell me more?' or 'What helps you usually?'). 4. Give small, practical comfort or reflection (e.g., 'You’ve already taken a brave step by talking about it.'). 5. Then move to soft motivation (e.g., 'Yes, you definitely can do this. You’ve got more strength than you realize.'). 6. Sound natural — use contractions, vary tone (gentle, warm, slightly humorous, hopeful), occasional emojis if fitting. 7. Avoid robotic patterns; be conversational like a real person. 8. Keep conversation alive with open questions (e.g., 'What usually helps you feel better?'). 9. Balance empathy + motivation in every response (e.g., 'It’s okay to doubt yourself sometimes. But I promise, you have it in you.'). 10. Be warm, not formal. Adapt to voice tone '{voice_tone}' for style. If in 'knowledge' mode, provide informative answers to curiosities about the world while staying friendly. Current user mood: {emotion}. Adapt to mode: '{mode}'. Ensure responses are precise, accurate, and high-quality — avoid verbosity, follow up naturally, and simulate human communication."}
-        ] + history
-
-        # Generate AI response (adjusted for precision)
-        response = client.chat.completions.create(
-            model="gpt-4o-mini",
-            messages=messages,
-            max_tokens=120,  # Shorter for precision
-            temperature=0.6  # Balanced for accuracy and variety
-        )
-
-        reply = response.choices[0].message.content.strip()
+        system_prompt = f"You are a supportive friend. Respond briefly, accurately, and calmly. In emotional_support mode: empathize and motivate gently. In knowledge mode: give short, factual answers. Avoid repetition. Current mood: {emotion}. Mode: {mode}. Voice tone: {voice_tone}."
+        messages = [{"role": "system", "content": system_prompt}] + history
+
+        if client:
+            try:
+                response = client.chat.completions.create(
+                    model="gpt-3.5-turbo",
+                    messages=messages,
+                    max_tokens=80,
+                    temperature=0.5
+                )
+                reply = response.choices[0].message.content.strip()
+            except Exception as e:
+                print(f"OpenAI API error: {e}. Using fallback.")
+                reply = get_fallback_reply(mode, emotion)
+        else:
+            reply = get_fallback_reply(mode, emotion)
+
         user["conversation_history"].append({"role": "assistant", "content": reply, "timestamp": now})
         save_user(user)
 
         return jsonify({"reply": reply, "emotion": emotion})
     except Exception as e:
-        return jsonify({"reply": "Oops, something went wrong on my end. Please try again or check your connection.", "emotion": "neutral"}), 500
+        print(f"General error: {e}")
+        return jsonify({"reply": "Something went wrong. Please check your setup and try again.", "emotion": "neutral"}), 500
 
 @app.route("/")
 def index():