identify patterns and suggest personalized activities

The system must be able to analyze chat logs to identify patterns and suggest personalized activities or coping mechanisms.

could you check "mental_health_agent under agents"?

i used spacy library and made "analyze_chat" and "run" method.

my run method is overriding your run method.

could you check both of them?

server/agents/mental_health_agent.py

@@ -1,5 +1,6 @@
 from datetime import datetime
-
+import spacy
+import json
 from enum import Enum
 from pymongo import ASCENDING
 
@@ -17,6 +18,9 @@
 from services.azure_mongodb import MongoDBClient
 from utils.consts import SYSTEM_MESSAGE
 
+# Load spaCy model
+nlp = spacy.load("en_core_web_sm")
+
 class ChatHistoryScope(Enum):
     ALL = "all",
     PREVIOUS = "previous"
@@ -172,6 +176,108 @@ def run(self, message:str, with_history=True, user_id=None, chat_id=None, turn_i
             self.write_agent_response_to_db(invocation, user_id, chat_id, turn_id)
 
             return invocation["output"]
+
+    def analyze_chat(self, text):
+        """Analyze the chat text to determine emotional state and detect triggers."""
+        doc = nlp(text)
+        emotions = [token for token in doc if token.dep_ == "amod" and token.head.pos_ == "NOUN"]
+        triggers = [ent.text for ent in doc.ents if ent.label_ in ["PERSON", "ORG", "GPE"]]
+
+         # Initialize a dictionary to hold detected patterns and suggested interventions
+        patterns = {}
+
+        # Detecting various emotional states based on keywords
+        lower_text = text.lower()  # Convert text to lower case for case insensitive matching
+        if any(keyword in lower_text for keyword in ["overwhelmed", "stressed", "too much", "can't handle", "pressure"]):
+            patterns['Stress or Overwhelm'] = [
+                "Consider taking a short break to clear your mind.",
+                "Engage in some deep breathing exercises or meditation to relax.",
+                "Explore these resources on time management to help organize your tasks better."
+            ]
+        if any(keyword in lower_text for keyword in ["anxious", "worry", "nervous", "scared", "panic"]):
+            patterns['Anxiety'] = [
+                "Try grounding techniques like the 5-4-3-2-1 method to calm your senses.",
+                "It might be helpful to talk to a friend or counselor about your feelings.",
+                "Check out these tips for managing anxiety and reducing stress."
+            ]
+        if any(word in lower_text for word in ["angry", "mad", "frustrated", "upset", "annoyed"]):
+            patterns['Anger or Frustration'] = [
+                "Try counting to ten or practicing deep breathing.",
+                "Engage in some physical activity to release energy.",
+                "Consider learning more about conflict resolution skills."
+            ]
+        if any(word in lower_text for word in ["lonely", "alone", "isolated", "no one", "abandoned"]):
+            patterns['Loneliness'] = [
+                "Consider joining community groups or online forums to connect with others.",
+                "Reach out to family or friends for a chat.",
+                "Explore resources to develop social skills or find social activities."
+            ]
+        if any(word in lower_text for word in ["scared", "fear", "terrified", "fright", "panic"]):
+            patterns['Fear'] = [
+                "Practice controlled breathing to manage acute fear.",
+                "Explore exposure therapy techniques under professional guidance.",
+                "Seek professional help if fears persist."
+            ]
+        if any(word in lower_text for word in ["confused", "lost", "unclear", "disoriented", "bewildered"]):
+            patterns['Confusion or Disorientation'] = [
+                "Organizational tools or apps might help structure daily tasks.",
+                "Try mindfulness exercises to enhance mental clarity.",
+                "Discussing these feelings with a mentor or counselor could be beneficial."
+            ]
+        if any(word in lower_text for word in ["grief", "loss", "mourn", "bereaved", "miss"]):
+            patterns['Grief or Loss'] = [
+                "Joining support groups for similar experiences might help.",
+                "Consider seeking grief counseling or therapy.",
+                "Healthy grieving practices, such as memorializing the lost one, can be therapeutic."
+            ]
+        if any(word in lower_text for word in ["excited", "nervous", "jittery", "thrilled", "restless"]):
+            patterns['Excitement or Nervousness'] = [
+                "Channel your excitement into productive activities.",
+                "Use techniques like visualization or positive affirmations to calm nerves.",
+                "Balance excitement with downtime to avoid burnout."
+            ]
+
+        return {"emotions": emotions, "triggers": triggers, "patterns": patterns}
+
+    def run(self, message: str, with_history=True, user_id=None, chat_id=None, turn_id=None, history_scope=None):
+        try:
+            if not with_history:
+                return super().run(message)
+
+            memory = self.get_agent_memory(user_id, chat_id, history_scope)
+            if not memory:
+                return "Error: Unable to retrieve conversation history."
+
+            if memory.buffer:
+                addendum = f"""
+                Previous Conversation Summary:
+                {memory.buffer}
+                """        
+                self.system_message.content = f"{self.system_message.content}\n{addendum}"
+
+            agent_with_history = self.get_agent_with_history(memory)
+
+            # Analyze the message for emotional content
+            analysis_results = self.analyze_chat(message)
+            response_addendum = self.format_response_addendum(analysis_results)           
+
+            # Invoke the agent with history context
+            invocation = agent_with_history.invoke({"input": f"{message}\n{response_addendum}"}, config={"configurable": {"user_id": user_id, "chat_id": chat_id}})
+
+            self.write_agent_response_to_db(invocation, user_id, chat_id, turn_id)
+
+            return invocation["output"]
+
+        except Exception as e:
+            return f"An error occurred: {str(e)}"
+
+    def format_response_addendum(self, analysis_results):
+        patterns = analysis_results['patterns']
+        response_addendum = ""
+        for state, suggestions in patterns.items():
+            response_addendum += f"Detected {state}: " + "; ".join(suggestions) + "\n"
+        return response_addendum.strip()
+
 
 
     def prepare_tools():
@@ -245,6 +351,9 @@ def get_initial_greeting(self, user_id):
                 "message": response,
                 "chat_id": new_chat_id
             }
+
+
+
 
 
 # def process_langchain_query(query_string, question, collection_name, system_prompt):