Upload mentalchatbot.py

mentalchatbot.py

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+from transformers import pipeline
+import numpy as np
+import matplotlib.pyplot as plt
+from lime.lime_text import LimeTextExplainer
+
+class MentalHealthChatbot:
+    def __init__(self, sentiment_model_path, disorder_model_path):
+        # Load sentiment and classification models
+        self.sentiment_pipeline = pipeline("text-classification", model=sentiment_model_path)
+        self.classify_pipeline = pipeline("text-classification", model=disorder_model_path)
+
+        # Label mappings
+        self.label_mapping = {
+            "LABEL_0": "ADHD",
+            "LABEL_1": "BPD",
+            "LABEL_2": "OCD",
+            "LABEL_3": "PTSD",
+            "LABEL_4": "Anxiety",
+            "LABEL_5": "Autism",
+            "LABEL_6": "Bipolar",
+            "LABEL_7": "Depression",
+            "LABEL_8": "Eating Disorders",
+            "LABEL_9": "Health",
+            "LABEL_10": "Mental Illness",
+            "LABEL_11": "Schizophrenia",
+            "LABEL_12": "Suicide Watch"
+        }
+
+        self.sentiment_mapping = {
+            "POS": "Positive",
+            "NEG": "Negative",
+            "NEU": "Neutral"
+        }
+
+        self.exercise_recommendations = {
+            # Exercise recommendations data as defined in the original code
+        }
+
+        # Initialize the LIME explainer
+        self.explainer = LimeTextExplainer(class_names=list(self.sentiment_mapping.values()) + list(self.label_mapping.values()))
+
+    def get_sentiment(self, text):
+        results = self.sentiment_pipeline(text)
+        if results and isinstance(results, list):  
+            best_result = results[0]
+            label = self.sentiment_mapping.get(best_result["label"], "Unknown")
+            confidence = best_result["score"] * 100
+            return label, confidence
+        return "Unknown", 0
+
+    def get_disorder(self, text, threshold=50):
+        results = self.classify_pipeline(text)
+        if results and isinstance(results, list):  
+            best_result = results[0]
+            disorder_confidence = best_result["score"] * 100
+            if disorder_confidence > threshold:
+                disorder_label = self.label_mapping.get(best_result["label"], "Unknown")
+
+                if disorder_confidence < 50:
+                    risk_level = "Low Risk"
+                elif 50 <= disorder_confidence <= 75:
+                    risk_level = "Moderate Risk"
+                else:
+                    risk_level = "High Risk"
+
+                if risk_level == "High Risk":
+                    print("✔ 🚨 Alert Notification Triggered: High risk detected!\n")
+                
+                return disorder_label, disorder_confidence, risk_level
+
+        return "No significant disorder detected", 0.0, "No Risk"
+
+    def predict_fn(self, texts):
+        sentiment_output = self.sentiment_pipeline(texts)
+        sentiment_probs = np.array([[item['score']] for item in sentiment_output])
+
+        disorder_output = self.classify_pipeline(texts)
+        disorder_probs = np.vstack([np.array([item['score']]) for item in disorder_output])
+
+        result = np.hstack([sentiment_probs, disorder_probs])
+        return result
+
+    def explain_text(self, text):
+        explanation = self.explainer.explain_instance(text, self.predict_fn, num_features=5, num_samples=25)
+        explanation.as_pyplot_figure()  # Display the plot
+        plt.show()
+
+        explanation_str = "The model's prediction is influenced by the following factors: "
+        explanation_str += "; ".join([f'"{feature}" contributes with a weight of {weight:.4f}' 
+                                      for feature, weight in explanation.as_list()]) + "."
+        return explanation_str
+
+    def get_recommendations(self,condition, risk_level):
+        exercise_recommendations = {
+            "Depression": {
+            "High Risk": ["Try 10 minutes of deep breathing.", "Go for a 15-minute walk in nature.", "Practice guided meditation."],
+            "Moderate Risk": ["Write down 3 things you’re grateful for.", "Do light stretching or yoga for 10 minutes.", "Listen to calming music."],
+            "Low Risk": ["Engage in a hobby you enjoy.", "Call a friend and have a short chat.", "Do a short 5-minute mindfulness exercise."]
+            },
+            "Anxiety": {
+            "High Risk": ["Try progressive muscle relaxation.", "Use the 4-7-8 breathing technique.", "Write down your thoughts to clear your mind."],
+            "Moderate Risk": ["Listen to nature sounds or white noise.", "Take a 15-minute break from screens.", "Try a short visualization exercise."],
+            "Low Risk": ["Practice slow, deep breathing for 5 minutes.", "Drink herbal tea and relax.", "Read a book for 10 minutes."]
+            },
+            "Bipolar": {
+            "High Risk": ["Engage in grounding techniques like 5-4-3-2-1.", "Try slow-paced walking in a quiet area.", "Listen to calm instrumental music."],
+            "Moderate Risk": ["Do a 10-minute gentle yoga session.", "Keep a mood journal for self-awareness.", "Practice self-affirmations."],
+            "Low Risk": ["Engage in light exercise like jogging.", "Practice mindful eating for a meal.", "Do deep breathing exercises."]
+            },
+            "OCD": {
+            "High Risk": ["Use exposure-response prevention techniques.", "Try 5 minutes of guided meditation.", "Write down intrusive thoughts and challenge them."],
+            "Moderate Risk": ["Take a short break from triggers.", "Practice progressive relaxation.", "Engage in a calming activity like drawing."],
+            "Low Risk": ["Practice deep breathing with slow exhales.", "Listen to soft music and relax.", "Try focusing on one simple task at a time."]
+              },
+              "PTSD": {
+            "High Risk": ["Try grounding techniques (hold an object, describe it).", "Do 4-7-8 breathing for relaxation.", "Write in a trauma journal."],
+            "Moderate Risk": ["Practice mindfulness for 5 minutes.", "Engage in slow, rhythmic movement (walking, stretching).", "Listen to soothing music."],
+            "Low Risk": ["Try positive visualization techniques.", "Engage in light exercise or stretching.", "Spend time in a quiet, safe space."]
+            },
+            "Suicide Watch": {
+            "High Risk": ["Immediately reach out to a mental health professional.", "Call a trusted friend or family member.", "Try a grounding exercise like cold water on hands."],
+            "Moderate Risk": ["Write a letter to your future self.", "Listen to uplifting music.", "Practice self-care (take a bath, make tea, etc.)."],
+            "Low Risk": ["Watch a motivational video.", "Write down your emotions in a journal.", "Spend time with loved ones."]
+            },
+            "ADHD": {
+            "High Risk": ["Try structured routines for the day.", "Use a timer for focus sessions.", "Engage in short bursts of physical activity."],
+            "Moderate Risk": ["Do a quick exercise routine (jumping jacks, stretches).", "Use fidget toys to channel energy.", "Try meditation with background music."],
+            "Low Risk": ["Practice deep breathing.", "Listen to classical or instrumental music.", "Organize your workspace."]
+            },
+            "BPD": {
+            "High Risk": ["Try dialectical behavior therapy (DBT) techniques.", "Practice mindfulness.", "Use a weighted blanket for comfort."],
+            "Moderate Risk": ["Write down emotions and analyze them.", "Engage in creative activities like painting.", "Listen to calming podcasts."],
+            "Low Risk": ["Watch a lighthearted movie.", "Do breathing exercises.", "Call a friend for a short chat."]
+            },
+            "Autism": {
+            "High Risk": ["Engage in deep-pressure therapy (weighted blanket).", "Use noise-canceling headphones.", "Try sensory-friendly relaxation techniques."],
+            "Moderate Risk": ["Do repetitive physical activities like rocking.", "Practice structured breathing exercises.", "Engage in puzzles or memory games."],
+            "Low Risk": ["Spend time in a quiet space.", "Listen to soft instrumental music.", "Follow a structured schedule."]
+            },
+            "Schizophrenia": {
+            "High Risk": ["Seek immediate support from a trusted person.", "Try simple grounding exercises.", "Use distraction techniques like puzzles."],
+            "Moderate Risk": ["Engage in light physical activity.", "Listen to calming sounds or music.", "Write thoughts in a journal."],
+            "Low Risk": ["Read a familiar book.", "Do a 5-minute breathing exercise.", "Try progressive muscle relaxation."]
+            },
+            "Eating Disorders": {
+            "High Risk": ["Seek professional help immediately.", "Try self-affirmations.", "Practice intuitive eating (listen to body cues)."],
+            "Moderate Risk": ["Engage in mindful eating.", "Write down your emotions before meals.", "Do light stretching after meals."],
+            "Low Risk": ["Try a gentle walk after eating.", "Listen to calming music.", "Write a gratitude journal about your body."]
+            },
+            "Mental Health": {
+            "High Risk": ["Reach out to a mental health professional.", "Engage in deep relaxation techniques.", "Talk to a support group."],
+            "Moderate Risk": ["Write in a daily journal.", "Practice guided meditation.", "Do light physical activities like walking."],
+            "Low Risk": ["Try deep breathing exercises.", "Watch an uplifting video.", "Call a friend for a chat."]
+            }
+            
+        }
+        if condition in exercise_recommendations:
+            if risk_level in exercise_recommendations[condition]:
+                return exercise_recommendations[condition][risk_level]
+        return ["No specific recommendations available."]
+
+    def run_chat(self, text):
+        sentiment, sentiment_confidence = self.get_sentiment(text)
+        disorder_label, disorder_confidence, risk_level = self.get_disorder(text)
+
+        print(f"\nText: {text}")
+        print(f"Sentiment: {sentiment} ({sentiment_confidence:.2f}%)")
+        print(f"Disorder: {disorder_label} ({disorder_confidence:.2f}%)")
+        print(f"Risk Level: {risk_level}")
+        print("\nLIME Explanation:")
+        explanation_str = self.explain_text(text)
+        print(f"\nExplanation:\n{explanation_str}")
+
+        # Provide recommendations
+        recommendations = self.get_recommendations(disorder_label, risk_level)
+        print("\nRecommended Actions:")
+        for action in recommendations:
+            print(f"  - {action}")
+        print("-" * 50)
+
+# Example of how to run the chatbot
+if __name__ == "__main__":
+    # Replace the paths with actual paths to your models
+    chatbot = MentalHealthChatbot(sentiment_model_path="../ai_models/sentiment_model", 
+                                  disorder_model_path="../ai_models/mental_health_model")
+    
+    text = input("Enter your text: ")
+    chatbot.run_chat(text)
+    print("Thanks")
+