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Dockerfile

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+FROM python:3.9-slim
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+# Switch to the "user" user
+USER user
+# Set home to the user's home directory
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+# Install any needed packages specified in requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Expose the default port for Hugging Face Spaces exactly
+EXPOSE 7860
+
+# Run FastAPI using uvicorn on port 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+from transformers import pipeline
+import random
+import logging
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = FastAPI(title="Mental Health Chatbot API Backend")
+
+# Enable CORS for frontend integration
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Adjust this in production to your frontend's actual domain
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+logger.info("Loading emotion classification model...")
+try:
+    classifier = pipeline(
+        "text-classification",
+        model="bhadresh-savani/distilbert-base-uncased-emotion",
+        return_all_scores=True
+    )
+    logger.info("Model loaded successfully.")
+except Exception as e:
+    logger.error(f"Error loading model: {e}")
+    classifier = None
+
+# Defining our request and response models
+class ChatRequest(BaseModel):
+    user_input: str
+
+class ChatResponse(BaseModel):
+    emotion: str
+    response: str
+    is_crisis: bool
+
+# Critical intervention keywords
+CRISIS_KEYWORDS = [
+    "suicide", "kill myself", "want to die", "end my life", 
+    "hurt myself", "better off dead", "no reason to live",
+    "suicidal", "very depressed"
+]
+
+# Multiple responses per emotion so it doesn't give the same response twice
+responses_pool = {
+    "joy": [
+        "I'm so glad to hear you're feeling good! It's wonderful to have moments like this. What’s contributing to your happiness today?",
+        "That's wonderful news! It is great to see you experiencing joy. Cherish these moments.",
+        "Knowing you are happy makes my day! Keep embracing whatever is bringing you this positivity."
+    ],
+    "sadness": [
+        "I'm really sorry to hear you're feeling down. It's okay to feel this way, and I'm here to listen. Remember to be kind to yourself.",
+        "I hear the pain in your words. Please know that it's okay to not be okay. Taking it one day at a time is enough.",
+        "I'm here for you. Sadness can be heavy, but you don't have to carry it all by yourself. Be gentle with yourself."
+    ],
+    "anger": [
+        "It sounds like you're going through a lot of frustration right now. Your feelings are valid. Would it help to talk about what happened?",
+        "I can sense the anger in what you're saying, and it's completely understandable to feel that way. I'm here if you want to vent.",
+        "That sounds really infuriating. It's okay to be upset when things go wrong. Take a deep breath if you need to."
+    ],
+    "fear": [
+        "It sounds like you're feeling quite anxious or worried. Take a slow, deep breath. I'm here with you—what's on your mind?",
+        "Fear can be overwhelming, but you're not alone. Let's try to focus on the present moment. I am here for you.",
+        "I hear your anxiety. It's a tough feeling to deal with, but you are safe right now. What is it that's making you most afraid?"
+    ],
+    "love": [
+        "That's a beautiful sentiment. Feeling connected and full of love is so vital for our well-being.",
+        "Love is such a powerful emotion. It's heartwarming to hear you express it so openly.",
+        "Holding onto feelings of love and connection can bring so much light into your life. Thank you for sharing that."
+    ],
+    "surprise": [
+        "That sounds like a lot to process! Was it a positive surprise, or are you feeling a bit overwhelmed by it?",
+        "Wow! Life definitely has a way of throwing unexpected things at us. How are you adjusting to this?",
+        "I didn't expect that either! Take your time to figure out how you feel about this surprise."
+    ],
+    "neutral": [
+        "I see. How are you holding up otherwise?",
+        "Thank you for sharing. Is there anything else on your mind?",
+        "I'm listening. Feel free to share as much or as little as you'd like."
+    ]
+}
+
+def detect_crisis(text):
+    text_lower = text.lower()
+    for keyword in CRISIS_KEYWORDS:
+        if keyword in text_lower:
+            return True
+    return False
+
+@app.post("/chat", response_model=ChatResponse)
+def get_chat_response(request: ChatRequest):
+    user_input = request.user_input
+    
+    # 1. Severe Depression / Suicidal Check
+    if detect_crisis(user_input):
+        return ChatResponse(
+            emotion="crisis",
+            response="I am a chatbot and not a doctor and you need immediate medical support. Please consult a doctor immediately.",
+            is_crisis=True
+        )
+    
+    # 2. Extract Emotion
+    if classifier:
+        predictions = classifier(user_input)[0]
+        # Sort scores highest to lowest
+        predictions.sort(key=lambda x: x['score'], reverse=True)
+        top_emotion_label = predictions[0]['label']
+    else:
+        top_emotion_label = "neutral"
+
+    # 3. Dynamic Response Selection
+    emotion_list = responses_pool.get(top_emotion_label, responses_pool["neutral"])
+    # Uses random to ensure varied responses (so it doesn't give the same back over and over)
+    selected_response = random.choice(emotion_list)
+
+    return ChatResponse(
+        emotion=top_emotion_label,
+        response=selected_response,
+        is_crisis=False
+    )

requirements.txt

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+transformers
+torch
+fastapi
+uvicorn
+pydantic