Update interface for Gradio 5.8.0

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+ENV/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Logs
+*.log
+
+# Local configuration
+.env
+.env.local
+
+# Model files
+models/*.bin
+models/*.pt
+models/*.pth
+
+# Temporary files
+tmp/
+temp/
+
+# System files
+.DS_Store
+Thumbs.db 

README.md

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+---
+title: Mental Wellness Platform
+emoji: 🧠
+colorFrom: indigo
+colorTo: purple
+sdk: gradio
+sdk_version: "4.4.0"
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

agents/assessment_agent.py

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+from typing import Dict, List
+from .base_agent import BaseWellnessAgent
+import json
+from pathlib import Path
+
+class AssessmentAgent(BaseWellnessAgent):
+    """Agent specialized in mental health assessments"""
+    
+    def __init__(self, model_config: Dict, verbose: bool = False):
+        super().__init__(
+            name="Mental Health Assessment Agent",
+            role="Mental Health Evaluator",
+            goal="Conduct thorough mental health assessments and provide actionable insights",
+            backstory="""I am an AI agent specialized in mental health assessment. 
+            I use validated assessment tools and techniques to evaluate mental well-being 
+            and provide personalized recommendations.""",
+            tools=["emotion_detection", "conversation"],
+            model_config=model_config,
+            verbose=verbose
+        )
+        self.assessment_tools = self._load_assessment_tools()
+        self.current_assessment = None
+        
+    def _load_assessment_tools(self) -> Dict:
+        """Load assessment questionnaires and scoring guides"""
+        tools_path = Path(__file__).parent.parent / "knowledge_base" / "assessment_tools.json"
+        try:
+            with open(tools_path) as f:
+                return json.load(f)
+        except FileNotFoundError:
+            return {
+                "phq9": {
+                    "name": "PHQ-9 Depression Scale",
+                    "questions": [
+                        "Little interest or pleasure in doing things?",
+                        "Feeling down, depressed, or hopeless?",
+                        # Add more questions...
+                    ],
+                    "scoring": {
+                        "ranges": {
+                            "0-4": "Minimal depression",
+                            "5-9": "Mild depression",
+                            "10-14": "Moderate depression",
+                            "15-19": "Moderately severe depression",
+                            "20-27": "Severe depression"
+                        }
+                    }
+                },
+                "gad7": {
+                    "name": "GAD-7 Anxiety Scale",
+                    "questions": [
+                        "Feeling nervous, anxious, or on edge?",
+                        "Not being able to stop or control worrying?",
+                        # Add more questions...
+                    ],
+                    "scoring": {
+                        "ranges": {
+                            "0-4": "Minimal anxiety",
+                            "5-9": "Mild anxiety",
+                            "10-14": "Moderate anxiety",
+                            "15-21": "Severe anxiety"
+                        }
+                    }
+                }
+            }
+            
+    def start_assessment(self, assessment_type: str) -> Dict:
+        """Start a new assessment"""
+        if assessment_type not in self.assessment_tools:
+            raise ValueError(f"Unknown assessment type: {assessment_type}")
+            
+        self.current_assessment = {
+            "type": assessment_type,
+            "tool": self.assessment_tools[assessment_type],
+            "responses": [],
+            "current_question": 0
+        }
+        
+        return self.get_next_question()
+        
+    def process_message(self, message: str) -> Dict:
+        """Process user response and continue assessment"""
+        if not self.current_assessment:
+            return self.format_response(
+                "No active assessment. Please start an assessment first."
+            )
+            
+        # Record response
+        self.current_assessment["responses"].append({
+            "question": self.current_assessment["current_question"],
+            "response": message,
+            "emotion": self.analyze_emotion(message)
+        })
+        
+        # Move to next question or finish assessment
+        return (
+            self.finish_assessment()
+            if self._is_assessment_complete()
+            else self.get_next_question()
+        )
+        
+    def get_next_question(self) -> Dict:
+        """Get the next question in the assessment"""
+        if not self.current_assessment:
+            return self.format_response(
+                "No active assessment. Please start an assessment first."
+            )
+            
+        tool = self.current_assessment["tool"]
+        question_idx = self.current_assessment["current_question"]
+        
+        if question_idx >= len(tool["questions"]):
+            return self.finish_assessment()
+            
+        question = tool["questions"][question_idx]
+        self.current_assessment["current_question"] += 1
+        
+        return self.format_response(question)
+        
+    def _is_assessment_complete(self) -> bool:
+        """Check if all questions have been answered"""
+        if not self.current_assessment:
+            return False
+            
+        return len(self.current_assessment["responses"]) >= len(
+            self.current_assessment["tool"]["questions"]
+        )
+        
+    def finish_assessment(self) -> Dict:
+        """Complete the assessment and generate report"""
+        if not self.current_assessment:
+            return self.format_response(
+                "No active assessment to finish."
+            )
+            
+        # Calculate scores
+        scores = self._calculate_scores()
+        
+        # Generate report
+        report = self._generate_report(scores)
+        
+        # Add to history
+        self.add_to_history({
+            "assessment_type": self.current_assessment["type"],
+            "scores": scores,
+            "report": report
+        })
+        
+        # Reset current assessment
+        self.current_assessment = None
+        
+        return self.format_response(report)
+        
+    def _calculate_scores(self) -> Dict:
+        """Calculate assessment scores"""
+        # Implement scoring logic based on assessment type
+        return {
+            "total_score": 0,  # Calculate actual score
+            "subscores": {},
+            "severity": "Unknown"  # Determine from scoring ranges
+        }
+        
+    def _generate_report(self, scores: Dict) -> str:
+        """Generate detailed assessment report"""
+        report = f"""Assessment Report
+        
+        Type: {self.current_assessment["type"].upper()}
+        Total Score: {scores["total_score"]}
+        Severity: {scores["severity"]}
+        
+        Recommendations:
+        1. Continue monitoring your mental health
+        2. Consider discussing results with a mental health professional
+        3. Practice self-care and stress management techniques
+        
+        Note: This assessment is for screening purposes only and does not constitute 
+        a clinical diagnosis. Please consult with a qualified mental health professional 
+        for proper evaluation and treatment."""
+        
+        return report
+        
+    def get_assessment_history(self) -> List[Dict]:
+        """Get history of completed assessments"""
+        return self.get_history()
+        
+    def get_available_assessments(self) -> List[str]:
+        """Get list of available assessment tools"""
+        return list(self.assessment_tools.keys()) 

agents/base_agent.py

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+from typing import Dict, List, Optional
+from crewai import Agent
+from pydantic import BaseModel
+from transformers import pipeline
+
+class AgentState(BaseModel):
+    """State management for agents"""
+    context: Dict = {}
+    history: List[Dict] = []
+    current_task: Optional[str] = None
+    
+class BaseWellnessAgent(Agent):
+    """Base class for all wellness platform agents"""
+    
+    def __init__(
+        self,
+        name: str,
+        role: str,
+        goal: str,
+        backstory: str,
+        tools: List[str],
+        model_config: Dict,
+        verbose: bool = False
+    ):
+        super().__init__(
+            name=name,
+            role=role,
+            goal=goal,
+            backstory=backstory,
+            verbose=verbose
+        )
+        self.tools = tools
+        self.model_config = model_config
+        self.state = AgentState()
+        self._initialize_models()
+        
+    def _initialize_models(self):
+        """Initialize required AI models for the agent"""
+        self.models = {}
+        if "emotion_detection" in self.tools:
+            self.models["emotion"] = pipeline(
+                "text-classification",
+                model=self.model_config["emotion_detection"]["model_id"]
+            )
+            
+    def update_context(self, new_context: Dict):
+        """Update agent's context with new information"""
+        self.state.context.update(new_context)
+        
+    def add_to_history(self, interaction: Dict):
+        """Add an interaction to agent's history"""
+        self.state.history.append(interaction)
+        
+    def get_context(self) -> Dict:
+        """Get current context"""
+        return self.state.context
+        
+    def get_history(self) -> List[Dict]:
+        """Get interaction history"""
+        return self.state.history
+        
+    def clear_state(self):
+        """Reset agent state"""
+        self.state = AgentState()
+        
+    def analyze_emotion(self, text: str) -> Dict:
+        """Analyze emotion in text if emotion detection is available"""
+        if "emotion" in self.models:
+            result = self.models["emotion"](text)
+            return result[0] if result else {}
+        return {}
+        
+    def format_response(self, response: str) -> Dict:
+        """Format agent response with metadata"""
+        return {
+            "content": response,
+            "agent_name": self.name,
+            "agent_role": self.role,
+            "timestamp": self._get_timestamp(),
+            "context": self.get_context(),
+            "emotion_analysis": self.analyze_emotion(response)
+        }
+        
+    def _get_timestamp(self) -> str:
+        """Get current timestamp"""
+        from datetime import datetime
+        return datetime.now().isoformat()
+        
+    def process_message(self, message: str) -> Dict:
+        """Process incoming message - to be implemented by child classes"""
+        raise NotImplementedError("Child classes must implement process_message") 

agents/conversation_agent.py

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+from typing import Dict, List
+from .base_agent import BaseWellnessAgent
+from transformers import pipeline
+
+class ConversationAgent(BaseWellnessAgent):
+    """Agent specialized in therapeutic conversations"""
+    
+    def __init__(self, model_config: Dict, verbose: bool = False):
+        super().__init__(
+            name="Therapeutic Conversation Agent",
+            role="Mental Health Conversationalist",
+            goal="Engage in supportive therapeutic conversations while maintaining empathy and professionalism",
+            backstory="""I am a specialized AI agent trained in therapeutic conversation techniques. 
+            I use evidence-based approaches to provide emotional support and guidance while maintaining 
+            appropriate boundaries and recognizing when to escalate to crisis intervention.""",
+            tools=["emotion_detection", "conversation"],
+            model_config=model_config,
+            verbose=verbose
+        )
+        self._initialize_conversation_model()
+        
+    def _initialize_conversation_model(self):
+        """Initialize the conversation model"""
+        self.models["conversation"] = pipeline(
+            "text-generation",
+            model=self.model_config["conversation"]["model_id"]
+        )
+        
+    def _generate_response(self, prompt: str) -> str:
+        """Generate response using the conversation model"""
+        response = self.models["conversation"](
+            prompt,
+            max_length=self.model_config["conversation"]["max_length"],
+            temperature=self.model_config["conversation"]["temperature"]
+        )
+        return response[0]["generated_text"] if response else ""
+        
+    def process_message(self, message: str) -> Dict:
+        """Process user message and generate therapeutic response"""
+        # Analyze emotion
+        emotion = self.analyze_emotion(message)
+        
+        # Update context with emotion
+        self.update_context({"last_emotion": emotion})
+        
+        # Generate appropriate response based on emotion and context
+        prompt = self._create_prompt(message, emotion)
+        response = self._generate_response(prompt)
+        
+        # Add to conversation history
+        interaction = {
+            "user_message": message,
+            "emotion": emotion,
+            "response": response
+        }
+        self.add_to_history(interaction)
+        
+        return self.format_response(response)
+        
+    def _create_prompt(self, message: str, emotion: Dict) -> str:
+        """Create context-aware prompt for response generation"""
+        history = self.get_history()
+        context = self.get_context()
+        
+        # Build prompt with context
+        prompt = f"""As a therapeutic conversation agent, respond to the following message with empathy and support.
+        User's message: {message}
+        Detected emotion: {emotion}
+        Conversation history: {history[-3:] if history else 'No history'}
+        Additional context: {context}
+        
+        Response:"""
+        
+        return prompt
+        
+    def get_conversation_summary(self) -> Dict:
+        """Generate summary of the conversation"""
+        history = self.get_history()
+        emotions = [interaction["emotion"] for interaction in history]
+        
+        return {
+            "interaction_count": len(history),
+            "emotional_trajectory": emotions,
+            "key_topics": self._extract_key_topics(history),
+            "recommendations": self._generate_recommendations(history)
+        }
+        
+    def _extract_key_topics(self, history: List[Dict]) -> List[str]:
+        """Extract main topics from conversation history"""
+        # Implement topic extraction logic
+        return []
+        
+    def _generate_recommendations(self, history: List[Dict]) -> List[str]:
+        """Generate recommendations based on conversation"""
+        # Implement recommendation logic
+        return [] 

agents/crisis_agent.py

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+from typing import Dict, List
+from .base_agent import BaseWellnessAgent
+import json
+from pathlib import Path
+
+class CrisisAgent(BaseWellnessAgent):
+    """Agent specialized in crisis intervention and emergency response"""
+    
+    def __init__(self, model_config: Dict, verbose: bool = False):
+        super().__init__(
+            name="Crisis Intervention Agent",
+            role="Crisis Support Specialist",
+            goal="Provide immediate support and intervention in crisis situations",
+            backstory="""I am an AI agent specialized in crisis intervention. 
+            I am trained to recognize and respond to emergency situations, 
+            provide immediate support, and connect users with appropriate resources.""",
+            tools=["emotion_detection", "conversation"],
+            model_config=model_config,
+            verbose=verbose
+        )
+        self.protocols = self._load_protocols()
+        self.current_intervention = None
+        self.emergency_contacts = self._load_emergency_contacts()
+        
+    def _load_protocols(self) -> Dict:
+        """Load crisis intervention protocols"""
+        protocols_path = Path(__file__).parent.parent / "knowledge_base" / "guidelines" / "crisis_protocols.json"
+        try:
+            with open(protocols_path) as f:
+                return json.load(f)
+        except FileNotFoundError:
+            return {
+                "suicide_risk": {
+                    "severity_levels": {
+                        "low": {
+                            "indicators": [
+                                "Passing thoughts of death",
+                                "No specific plan",
+                                "Some protective factors"
+                            ],
+                            "response": "Provide support and resources"
+                        },
+                        "medium": {
+                            "indicators": [
+                                "Frequent thoughts of death",
+                                "Vague plans",
+                                "Some risk factors present"
+                            ],
+                            "response": "Immediate counseling referral"
+                        },
+                        "high": {
+                            "indicators": [
+                                "Specific suicide plan",
+                                "Access to means",
+                                "Multiple risk factors"
+                            ],
+                            "response": "Emergency services contact"
+                        }
+                    },
+                    "immediate_actions": [
+                        "Express concern and care",
+                        "Assess immediate safety",
+                        "Connect with emergency services if needed"
+                    ]
+                },
+                "panic_attack": {
+                    "symptoms": [
+                        "Rapid heartbeat",
+                        "Difficulty breathing",
+                        "Feeling of doom"
+                    ],
+                    "interventions": [
+                        "Grounding techniques",
+                        "Breathing exercises",
+                        "Reassurance and support"
+                    ]
+                }
+            }
+            
+    def _load_emergency_contacts(self) -> Dict:
+        """Load emergency contact information"""
+        return {
+            "emergency_services": "911",
+            "crisis_hotline": "988",
+            "text_line": "741741",
+            "poison_control": "1-800-222-1222"
+        }
+        
+    def process_message(self, message: str) -> Dict:
+        """Process crisis-related message and provide appropriate response"""
+        # Analyze message for crisis indicators
+        risk_assessment = self._assess_risk(message)
+        
+        # Update intervention state
+        self._update_intervention_state(risk_assessment)
+        
+        # Generate appropriate response based on risk level
+        response = self._generate_crisis_response(risk_assessment)
+        
+        # Record interaction
+        self.add_to_history({
+            "message": message,
+            "risk_assessment": risk_assessment,
+            "response": response
+        })
+        
+        return self.format_response(response)
+        
+    def _assess_risk(self, message: str) -> Dict:
+        """Assess risk level from message content"""
+        # Analyze emotion
+        emotion = self.analyze_emotion(message)
+        
+        # Check for critical keywords
+        risk_level = self._determine_risk_level(message.lower())
+        
+        return {
+            "risk_level": risk_level,
+            "emotion": emotion,
+            "timestamp": self._get_timestamp()
+        }
+        
+    def _determine_risk_level(self, message: str) -> str:
+        """Determine risk level based on message content"""
+        high_risk_keywords = [
+            "kill myself", "end my life", "suicide plan",
+            "want to die", "no reason to live"
+        ]
+        medium_risk_keywords = [
+            "want to disappear", "everyone better off",
+            "cant take it", "hopeless"
+        ]
+        
+        if any(keyword in message for keyword in high_risk_keywords):
+            return "high"
+        elif any(keyword in message for keyword in medium_risk_keywords):
+            return "medium"
+        return "low"
+        
+    def _update_intervention_state(self, risk_assessment: Dict):
+        """Update or create intervention state"""
+        if not self.current_intervention:
+            self.current_intervention = {
+                "start_time": self._get_timestamp(),
+                "risk_assessments": [],
+                "escalation_level": "initial"
+            }
+            
+        self.current_intervention["risk_assessments"].append(risk_assessment)
+        self._update_escalation_level(risk_assessment["risk_level"])
+        
+    def _update_escalation_level(self, risk_level: str):
+        """Update intervention escalation level"""
+        if risk_level == "high":
+            self.current_intervention["escalation_level"] = "emergency"
+        elif risk_level == "medium" and self.current_intervention["escalation_level"] == "initial":
+            self.current_intervention["escalation_level"] = "elevated"
+            
+    def _generate_crisis_response(self, risk_assessment: Dict) -> str:
+        """Generate appropriate crisis response"""
+        risk_level = risk_assessment["risk_level"]
+        escalation_level = self.current_intervention["escalation_level"]
+        
+        if risk_level == "high" or escalation_level == "emergency":
+            return self._generate_emergency_response()
+        elif risk_level == "medium" or escalation_level == "elevated":
+            return self._generate_elevated_response()
+        else:
+            return self._generate_supportive_response()
+            
+    def _generate_emergency_response(self) -> str:
+        """Generate response for emergency situations"""
+        return f"""I'm very concerned about your safety right now. This is an emergency situation that requires immediate attention.
+
+EMERGENCY CONTACTS:
+- Emergency Services: {self.emergency_contacts['emergency_services']}
+- Crisis Hotline: {self.emergency_contacts['crisis_hotline']}
+- Crisis Text Line: Text HOME to {self.emergency_contacts['text_line']}
+
+Please:
+1. Call emergency services immediately
+2. Stay on the line with me
+3. If possible, contact a trusted person to be with you
+
+Your life has value and people care about you. Help is available 24/7."""
+        
+    def _generate_elevated_response(self) -> str:
+        """Generate response for elevated risk situations"""
+        return f"""I hear how much pain you're in, and I want to help ensure your safety.
+
+Please consider:
+1. Calling the Crisis Hotline: {self.emergency_contacts['crisis_hotline']}
+2. Texting HOME to {self.emergency_contacts['text_line']}
+3. Reaching out to a trusted friend, family member, or counselor
+
+Would you be willing to talk about what's troubling you? I'm here to listen without judgment."""
+        
+    def _generate_supportive_response(self) -> str:
+        """Generate supportive response for lower risk situations"""
+        return """I can hear that you're going through a difficult time. Your feelings are valid, and you're not alone.
+
+Let's talk about what's happening. I'm here to:
+1. Listen and understand
+2. Help you explore your feelings
+3. Discuss coping strategies
+4. Connect you with resources
+
+What would be most helpful for you right now?"""
+        
+    def end_intervention(self) -> Dict:
+        """End current crisis intervention"""
+        if not self.current_intervention:
+            return self.format_response(
+                "No active crisis intervention to end."
+            )
+            
+        # Generate intervention summary
+        summary = self._generate_intervention_summary()
+        
+        # Add final summary to history
+        self.add_to_history({
+            "intervention_summary": summary,
+            "end_time": self._get_timestamp()
+        })
+        
+        # Reset current intervention
+        self.current_intervention = None
+        
+        return self.format_response(summary)
+        
+    def _generate_intervention_summary(self) -> str:
+        """Generate summary of crisis intervention"""
+        assessments = self.current_intervention["risk_assessments"]
+        max_risk = max(a["risk_level"] for a in assessments)
+        
+        return f"""Crisis Intervention Summary
+        
+        Duration: {self._calculate_duration(
+            self.current_intervention["start_time"],
+            self._get_timestamp()
+        ) // 60} minutes
+        Maximum Risk Level: {max_risk}
+        Escalation Level: {self.current_intervention["escalation_level"]}
+        
+        Follow-up Recommendations:
+        1. Continue monitoring emotional state
+        2. Maintain contact with support system
+        3. Follow up with mental health professional
+        4. Keep crisis resources readily available
+        
+        Remember: Support is always available at {self.emergency_contacts['crisis_hotline']}""" 

agents/mindfulness_agent.py

@@ -0,0 +1,227 @@
+from typing import Dict, List
+from .base_agent import BaseWellnessAgent
+import json
+from pathlib import Path
+
+class MindfulnessAgent(BaseWellnessAgent):
+    """Agent specialized in mindfulness and meditation guidance"""
+    
+    def __init__(self, model_config: Dict, verbose: bool = False):
+        super().__init__(
+            name="Mindfulness & Meditation Agent",
+            role="Mindfulness Guide",
+            goal="Guide users through mindfulness exercises and meditation sessions",
+            backstory="""I am an AI agent specialized in mindfulness and meditation guidance. 
+            I provide calming exercises, breathing techniques, and meditation sessions 
+            tailored to users' needs and experience levels.""",
+            tools=["emotion_detection", "conversation"],
+            model_config=model_config,
+            verbose=verbose
+        )
+        self.exercises = self._load_exercises()
+        self.current_session = None
+        
+    def _load_exercises(self) -> Dict:
+        """Load mindfulness exercises and meditation scripts"""
+        exercises_path = Path(__file__).parent.parent / "knowledge_base" / "resources" / "mindfulness_exercises.json"
+        try:
+            with open(exercises_path) as f:
+                return json.load(f)
+        except FileNotFoundError:
+            return {
+                "breathing": {
+                    "box_breathing": {
+                        "name": "Box Breathing",
+                        "description": "A simple technique to reduce stress and improve focus",
+                        "duration": 300,  # 5 minutes
+                        "steps": [
+                            "Inhale slowly for 4 counts",
+                            "Hold your breath for 4 counts",
+                            "Exhale slowly for 4 counts",
+                            "Hold for 4 counts before the next breath"
+                        ],
+                        "instructions": "Find a comfortable position. We'll practice box breathing for 5 minutes."
+                    },
+                    "deep_breathing": {
+                        "name": "Deep Breathing",
+                        "description": "Calming deep breathing exercise",
+                        "duration": 300,
+                        "steps": [
+                            "Take a deep breath in through your nose",
+                            "Feel your belly expand",
+                            "Exhale slowly through your mouth",
+                            "Feel your body relax"
+                        ],
+                        "instructions": "Sit comfortably with your back straight. Let's begin deep breathing."
+                    }
+                },
+                "meditation": {
+                    "body_scan": {
+                        "name": "Body Scan Meditation",
+                        "description": "Progressive relaxation through body awareness",
+                        "duration": 600,  # 10 minutes
+                        "steps": [
+                            "Focus on your toes and feet",
+                            "Move attention to your legs",
+                            "Progress through torso and arms",
+                            "End with neck and head"
+                        ],
+                        "instructions": "Lie down comfortably. We'll guide you through a full body scan."
+                    },
+                    "loving_kindness": {
+                        "name": "Loving-Kindness Meditation",
+                        "description": "Develop compassion for self and others",
+                        "duration": 600,
+                        "steps": [
+                            "Direct love to yourself",
+                            "Extend to loved ones",
+                            "Include neutral people",
+                            "Embrace all beings"
+                        ],
+                        "instructions": "Sit in a relaxed position. We'll practice sending loving-kindness."
+                    }
+                }
+            }
+            
+    def start_session(self, session_type: str, exercise_name: str = None) -> Dict:
+        """Start a new mindfulness session"""
+        if session_type not in self.exercises:
+            raise ValueError(f"Unknown session type: {session_type}")
+            
+        exercises = self.exercises[session_type]
+        if exercise_name and exercise_name not in exercises:
+            raise ValueError(f"Unknown exercise: {exercise_name}")
+            
+        selected_exercise = exercises[exercise_name] if exercise_name else next(iter(exercises.values()))
+        
+        self.current_session = {
+            "type": session_type,
+            "exercise": selected_exercise,
+            "start_time": self._get_timestamp(),
+            "current_step": 0,
+            "completed_steps": []
+        }
+        
+        return self.format_response(self._create_session_intro())
+        
+    def process_message(self, message: str) -> Dict:
+        """Process user message during mindfulness session"""
+        if not self.current_session:
+            return self.format_response(
+                "No active session. Please start a mindfulness session first."
+            )
+            
+        # Check for session control commands
+        if message.lower() in ["pause", "stop", "end"]:
+            return self.end_session()
+            
+        # Progress through exercise steps
+        return self._progress_session()
+        
+    def _progress_session(self) -> Dict:
+        """Progress through the current session's steps"""
+        exercise = self.current_session["exercise"]
+        current_step = self.current_session["current_step"]
+        
+        if current_step >= len(exercise["steps"]):
+            return self.end_session()
+            
+        step = exercise["steps"][current_step]
+        self.current_session["completed_steps"].append({
+            "step": current_step,
+            "timestamp": self._get_timestamp()
+        })
+        
+        self.current_session["current_step"] += 1
+        
+        return self.format_response(self._create_step_guidance(step))
+        
+    def _create_session_intro(self) -> str:
+        """Create introduction for the session"""
+        exercise = self.current_session["exercise"]
+        return f"""Welcome to {exercise['name']}.
+        
+        {exercise['description']}
+        
+        Duration: {exercise['duration'] // 60} minutes
+        
+        {exercise['instructions']}
+        
+        When you're ready, respond with 'begin' to start."""
+        
+    def _create_step_guidance(self, step: str) -> str:
+        """Create guidance for the current step"""
+        return f"""{step}
+        
+        Take your time with this step.
+        When you're ready to continue, send any message."""
+        
+    def end_session(self) -> Dict:
+        """End the current mindfulness session"""
+        if not self.current_session:
+            return self.format_response(
+                "No active session to end."
+            )
+            
+        # Calculate session statistics
+        stats = self._calculate_session_stats()
+        
+        # Generate session summary
+        summary = self._generate_session_summary(stats)
+        
+        # Add to history
+        self.add_to_history({
+            "session_type": self.current_session["type"],
+            "exercise": self.current_session["exercise"]["name"],
+            "stats": stats,
+            "summary": summary
+        })
+        
+        # Reset current session
+        self.current_session = None
+        
+        return self.format_response(summary)
+        
+    def _calculate_session_stats(self) -> Dict:
+        """Calculate statistics for the completed session"""
+        start_time = self.current_session["start_time"]
+        end_time = self._get_timestamp()
+        completed_steps = len(self.current_session["completed_steps"])
+        total_steps = len(self.current_session["exercise"]["steps"])
+        
+        return {
+            "duration": self._calculate_duration(start_time, end_time),
+            "completion_rate": completed_steps / total_steps,
+            "steps_completed": completed_steps
+        }
+        
+    def _calculate_duration(self, start_time: str, end_time: str) -> int:
+        """Calculate session duration in seconds"""
+        from datetime import datetime
+        start = datetime.fromisoformat(start_time)
+        end = datetime.fromisoformat(end_time)
+        return int((end - start).total_seconds())
+        
+    def _generate_session_summary(self, stats: Dict) -> str:
+        """Generate summary of the completed session"""
+        exercise = self.current_session["exercise"]
+        
+        return f"""Session Complete: {exercise['name']}
+        
+        Duration: {stats['duration'] // 60} minutes
+        Steps Completed: {stats['steps_completed']} of {len(exercise['steps'])}
+        Completion Rate: {stats['completion_rate'] * 100:.1f}%
+        
+        Thank you for practicing mindfulness. Remember to:
+        1. Take these peaceful feelings with you
+        2. Practice regularly for best results
+        3. Be gentle with yourself
+        
+        Would you like to try another exercise?"""
+        
+    def get_available_exercises(self) -> Dict:
+        """Get list of available exercises"""
+        return {
+            category: list(exercises.keys())
+            for category, exercises in self.exercises.items()
+        } 

agents/orchestrator.py

@@ -0,0 +1,128 @@
+from typing import Dict, List, Optional
+from .base_agent import BaseWellnessAgent
+from .conversation_agent import ConversationAgent
+from .assessment_agent import AssessmentAgent
+from .mindfulness_agent import MindfulnessAgent
+from .crisis_agent import CrisisAgent
+
+class WellnessOrchestrator:
+    """Orchestrates multiple specialized agents for mental wellness support"""
+    
+    def __init__(self, config: Dict):
+        self.config = config
+        self.agents = self._initialize_agents()
+        self.current_agent: Optional[BaseWellnessAgent] = None
+        self.session_history: List[Dict] = []
+        
+    def _initialize_agents(self) -> Dict[str, BaseWellnessAgent]:
+        """Initialize all specialized agents"""
+        return {
+            "conversation": ConversationAgent(
+                model_config=self.config["MODEL_CONFIGS"]
+            ),
+            "assessment": AssessmentAgent(
+                model_config=self.config["MODEL_CONFIGS"]
+            ),
+            "mindfulness": MindfulnessAgent(
+                model_config=self.config["MODEL_CONFIGS"]
+            ),
+            "crisis": CrisisAgent(
+                model_config=self.config["MODEL_CONFIGS"]
+            )
+        }
+        
+    def process_message(self, message: str, context: Optional[Dict] = None) -> Dict:
+        """Process incoming message and route to appropriate agent"""
+        # Update context for all agents
+        if context:
+            for agent in self.agents.values():
+                agent.update_context(context)
+                
+        # Check for crisis keywords first
+        if self._is_crisis_situation(message):
+            self.current_agent = self.agents["crisis"]
+            return self.current_agent.process_message(message)
+            
+        # Route to appropriate agent based on message content and context
+        agent_key = self._determine_best_agent(message, context)
+        self.current_agent = self.agents[agent_key]
+        
+        # Process message with selected agent
+        response = self.current_agent.process_message(message)
+        
+        # Record interaction in session history
+        self._record_interaction(message, response, agent_key)
+        
+        return response
+        
+    def _is_crisis_situation(self, message: str) -> bool:
+        """Check if message indicates a crisis situation"""
+        crisis_keywords = [
+            "suicide", "kill myself", "end it all", "self harm",
+            "hurt myself", "die", "death", "emergency"
+        ]
+        return any(keyword in message.lower() for keyword in crisis_keywords)
+        
+    def _determine_best_agent(self, message: str, context: Optional[Dict]) -> str:
+        """Determine the most appropriate agent for the message"""
+        # Check for explicit commands or keywords
+        if any(cmd in message.lower() for cmd in ["assess", "evaluation", "test"]):
+            return "assessment"
+        if any(cmd in message.lower() for cmd in ["meditate", "breathe", "relax"]):
+            return "mindfulness"
+            
+        # Default to conversation agent if no specific needs detected
+        return "conversation"
+        
+    def _record_interaction(self, message: str, response: Dict, agent_key: str):
+        """Record interaction in session history"""
+        self.session_history.append({
+            "timestamp": response.get("timestamp"),
+            "user_message": message,
+            "agent_response": response,
+            "agent_type": agent_key
+        })
+        
+    def start_assessment(self, assessment_type: str) -> Dict:
+        """Start a new assessment"""
+        self.current_agent = self.agents["assessment"]
+        return self.agents["assessment"].start_assessment(assessment_type)
+        
+    def start_mindfulness_session(self, session_type: str) -> Dict:
+        """Start a new mindfulness session"""
+        self.current_agent = self.agents["mindfulness"]
+        return self.agents["mindfulness"].start_session(session_type)
+        
+    def get_session_summary(self) -> Dict:
+        """Generate summary of current session"""
+        return {
+            "interaction_count": len(self.session_history),
+            "agent_usage": self._calculate_agent_usage(),
+            "key_insights": self._generate_insights(),
+            "recommendations": self._generate_recommendations()
+        }
+        
+    def _calculate_agent_usage(self) -> Dict[str, int]:
+        """Calculate how often each agent was used"""
+        usage = {}
+        for interaction in self.session_history:
+            agent_type = interaction["agent_type"]
+            usage[agent_type] = usage.get(agent_type, 0) + 1
+        return usage
+        
+    def _generate_insights(self) -> List[str]:
+        """Generate insights from session history"""
+        # Implement insight generation logic
+        return []
+        
+    def _generate_recommendations(self) -> List[str]:
+        """Generate recommendations based on session history"""
+        # Implement recommendation generation logic
+        return []
+        
+    def reset_session(self):
+        """Reset the current session"""
+        self.session_history = []
+        self.current_agent = None
+        for agent in self.agents.values():
+            agent.clear_state() 

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+from interface.app import WellnessInterface
+from config.config import load_config
+
+def main():
+    # Load configuration
+    config = load_config()
+    
+    # Initialize interface
+    interface = WellnessInterface(config)
+    
+    # Launch the application
+    interface.launch(
+        share=True,
+        enable_queue=True,
+        server_name="0.0.0.0",
+        server_port=7860
+    )
+
+if __name__ == "__main__":
+    main() 

config/config.py

@@ -0,0 +1,47 @@
+from pathlib import Path
+from typing import Dict
+
+def load_config() -> Dict:
+    """Load configuration settings"""
+    return {
+        "MODEL_CONFIGS": {
+            "conversation": {
+                "model_id": "TheBloke/Llama-2-7B-Chat-GGUF",
+                "max_length": 2048,
+                "temperature": 0.7,
+            },
+            "emotion_detection": {
+                "model_id": "bhadresh-savani/bert-base-uncased-emotion",
+            },
+            "speech_to_text": {
+                "model_id": "openai/whisper-base",
+            },
+            "vision": {
+                "model_id": "microsoft/resnet-50",
+            }
+        },
+        "INTERFACE_CONFIG": {
+            "theme": "light",
+            "supported_languages": ["en"],
+            "max_file_size_mb": 10,
+            "supported_file_types": [
+                "text/plain",
+                "audio/wav",
+                "audio/mp3",
+                "image/jpeg",
+                "image/png",
+                "video/mp4"
+            ]
+        },
+        "ANALYTICS_CONFIG": {
+            "metrics": [
+                "user_engagement",
+                "session_duration",
+                "intervention_effectiveness",
+                "crisis_events",
+                "mood_trends"
+            ],
+            "reporting_interval": "daily"
+        }
+    }
+ 

interface/app.py

@@ -0,0 +1,198 @@
+import gradio as gr
+from typing import Dict, List
+import os
+
+class WellnessInterface:
+    def __init__(self, config: Dict):
+        self.config = config
+        self.interface = None
+        self.setup_interface()
+        
+    def setup_interface(self):
+        """Set up the Gradio interface"""
+        with gr.Blocks(theme=gr.themes.Soft()) as self.interface:
+            gr.Markdown("# Mental Wellness Support Platform")
+            gr.Markdown("Welcome to your AI-powered mental wellness support system. "
+                       "Please note that this is not a substitute for professional mental health care.")
+            
+            with gr.Row():
+                with gr.Column(scale=3):
+                    # Chat interface
+                    self.chatbot = gr.Chatbot(
+                        label="Conversation",
+                        height=400
+                    )
+                    with gr.Row():
+                        self.msg = gr.Textbox(
+                            label="Type your message",
+                            placeholder="Share what's on your mind...",
+                            scale=4
+                        )
+                        self.send = gr.Button("Send", scale=1)
+                        
+                    # Voice input
+                    self.audio_input = gr.Audio(
+                        label="Voice Input",
+                        source="microphone",
+                        type="filepath"
+                    )
+                    
+                with gr.Column(scale=1):
+                    # Wellness tools
+                    with gr.Tab("Tools"):
+                        gr.Markdown("### Wellness Tools")
+                        self.meditation_btn = gr.Button("Start Meditation")
+                        self.assessment_btn = gr.Button("Mental Health Check-in")
+                        self.resources_btn = gr.Button("View Resources")
+                        
+                    # Session analytics
+                    with gr.Tab("Analytics"):
+                        self.analytics_display = gr.JSON(
+                            label="Session Analytics",
+                            value={}
+                        )
+                        self.update_analytics_btn = gr.Button("Update Analytics")
+                        
+            # File upload for image/video
+            with gr.Row():
+                self.file_upload = gr.File(
+                    label="Upload Image/Video",
+                    file_types=["image", "video"]
+                )
+                
+            # Emergency resources
+            with gr.Row():
+                gr.Markdown("""
+                ### Emergency Resources
+                If you're experiencing a mental health emergency:
+                - Emergency Services: 911 (US)
+                - National Crisis Hotline: 988
+                - Crisis Text Line: Text HOME to 741741
+                """)
+                
+            # Set up event handlers
+            self.send.click(
+                fn=self._handle_text_input,
+                inputs=[self.msg, self.chatbot],
+                outputs=[self.msg, self.chatbot]
+            )
+            
+            self.audio_input.change(
+                fn=self._handle_voice_input,
+                inputs=[self.audio_input, self.chatbot],
+                outputs=[self.chatbot]
+            )
+            
+            self.file_upload.change(
+                fn=self._handle_file_upload,
+                inputs=[self.file_upload, self.chatbot],
+                outputs=[self.chatbot]
+            )
+            
+            self.update_analytics_btn.click(
+                fn=self._update_analytics,
+                inputs=[],
+                outputs=[self.analytics_display]
+            )
+            
+            # Wellness tool handlers
+            self.meditation_btn.click(
+                fn=self._start_meditation,
+                inputs=[self.chatbot],
+                outputs=[self.chatbot]
+            )
+            
+            self.assessment_btn.click(
+                fn=self._start_assessment,
+                inputs=[self.chatbot],
+                outputs=[self.chatbot]
+            )
+            
+            self.resources_btn.click(
+                fn=self._show_resources,
+                inputs=[self.chatbot],
+                outputs=[self.chatbot]
+            )
+            
+    def _handle_text_input(self, message: str, history: list) -> tuple:
+        """Handle text input from user"""
+        if message:
+            # For now, just echo the message
+            response = f"You said: {message}"
+            history.append((message, response))
+            return "", history
+        return message, history
+        
+    def _handle_voice_input(self, audio_path: str, history: list) -> list:
+        """Handle voice input from user"""
+        if audio_path:
+            response = "Voice message received! (Voice processing coming soon)"
+            history.append(("🎤 Voice message", response))
+        return history
+        
+    def _handle_file_upload(self, file: gr.File, history: list) -> list:
+        """Handle file upload from user"""
+        if file:
+            response = f"Received file: {file.name} (Media processing coming soon)"
+            history.append((f"📎 Uploaded: {file.name}", response))
+        return history
+        
+    def _update_analytics(self) -> Dict:
+        """Update analytics display"""
+        return {
+            "sessions": 1,
+            "messages": len(self.chatbot.value) if self.chatbot.value else 0,
+            "status": "Demo Mode"
+        }
+        
+    def _start_meditation(self, history: list) -> list:
+        """Start meditation session"""
+        response = """Let's begin a simple breathing exercise:
+        1. Find a comfortable position
+        2. Close your eyes or maintain a soft gaze
+        3. We'll practice deep breathing together
+        
+        Are you ready to start? (Reply 'yes' when ready)"""
+        history.append(("🧘 Started meditation session", response))
+        return history
+        
+    def _start_assessment(self, history: list) -> list:
+        """Start mental health assessment"""
+        response = """I'll help you with a quick mental health check-in.
+        We'll use standard screening tools to understand how you're feeling.
+        
+        Would you like to:
+        1. Check anxiety levels (GAD-7)
+        2. Check mood/depression (PHQ-9)
+        3. General well-being assessment
+        
+        Please choose a number (1-3)."""
+        history.append(("📋 Started assessment", response))
+        return history
+        
+    def _show_resources(self, history: list) -> list:
+        """Show mental health resources"""
+        response = """Here are some helpful resources:
+        
+        📱 Quick Tools:
+        - Breathing exercises
+        - Grounding techniques
+        - Meditation guides
+        
+        📚 Educational Resources:
+        - Understanding anxiety
+        - Stress management
+        - Building resilience
+        
+        🤝 Support Services:
+        - Find local therapists
+        - Support groups
+        - Crisis hotlines
+        
+        Which would you like to learn more about?"""
+        history.append(("📚 Resource guide", response))
+        return history
+        
+    def launch(self, **kwargs):
+        """Launch the Gradio interface"""
+        self.interface.launch(**kwargs) 

knowledge_base/guidelines/crisis_protocols.json

@@ -0,0 +1,76 @@
+{
+    "suicide_risk": {
+        "severity_levels": {
+            "low": {
+                "indicators": [
+                    "Passing thoughts of death",
+                    "No specific plan",
+                    "Some protective factors"
+                ],
+                "response": "Provide support and resources"
+            },
+            "medium": {
+                "indicators": [
+                    "Frequent thoughts of death",
+                    "Vague plans",
+                    "Some risk factors present"
+                ],
+                "response": "Immediate counseling referral"
+            },
+            "high": {
+                "indicators": [
+                    "Specific suicide plan",
+                    "Access to means",
+                    "Multiple risk factors"
+                ],
+                "response": "Emergency services contact"
+            }
+        },
+        "immediate_actions": [
+            "Express concern and care",
+            "Assess immediate safety",
+            "Connect with emergency services if needed"
+        ]
+    },
+    "panic_attack": {
+        "symptoms": [
+            "Rapid heartbeat",
+            "Difficulty breathing",
+            "Feeling of doom"
+        ],
+        "interventions": [
+            "Grounding techniques",
+            "Breathing exercises",
+            "Reassurance and support"
+        ]
+    },
+    "emergency_contacts": {
+        "emergency_services": "911",
+        "crisis_hotline": "988",
+        "text_line": "741741",
+        "poison_control": "1-800-222-1222"
+    },
+    "escalation_procedures": {
+        "initial": {
+            "actions": [
+                "Assess immediate risk",
+                "Establish rapport",
+                "Identify support resources"
+            ]
+        },
+        "elevated": {
+            "actions": [
+                "Increase monitoring",
+                "Contact support system",
+                "Prepare for potential escalation"
+            ]
+        },
+        "emergency": {
+            "actions": [
+                "Contact emergency services",
+                "Stay engaged with user",
+                "Document all interactions"
+            ]
+        }
+    }
+}

knowledge_base/resources/mindfulness_exercises.json

@@ -0,0 +1,54 @@
+{
+    "breathing": {
+        "box_breathing": {
+            "name": "Box Breathing",
+            "description": "A simple technique to reduce stress and improve focus",
+            "duration": 300,
+            "steps": [
+                "Inhale slowly for 4 counts",
+                "Hold your breath for 4 counts",
+                "Exhale slowly for 4 counts",
+                "Hold for 4 counts before the next breath"
+            ],
+            "instructions": "Find a comfortable position. We'll practice box breathing for 5 minutes."
+        },
+        "deep_breathing": {
+            "name": "Deep Breathing",
+            "description": "Calming deep breathing exercise",
+            "duration": 300,
+            "steps": [
+                "Take a deep breath in through your nose",
+                "Feel your belly expand",
+                "Exhale slowly through your mouth",
+                "Feel your body relax"
+            ],
+            "instructions": "Sit comfortably with your back straight. Let's begin deep breathing."
+        }
+    },
+    "meditation": {
+        "body_scan": {
+            "name": "Body Scan Meditation",
+            "description": "Progressive relaxation through body awareness",
+            "duration": 600,
+            "steps": [
+                "Focus on your toes and feet",
+                "Move attention to your legs",
+                "Progress through torso and arms",
+                "End with neck and head"
+            ],
+            "instructions": "Lie down comfortably. We'll guide you through a full body scan."
+        },
+        "loving_kindness": {
+            "name": "Loving-Kindness Meditation",
+            "description": "Develop compassion for self and others",
+            "duration": 600,
+            "steps": [
+                "Direct love to yourself",
+                "Extend to loved ones",
+                "Include neutral people",
+                "Embrace all beings"
+            ],
+            "instructions": "Sit in a relaxed position. We'll practice sending loving-kindness."
+        }
+    }
+} 

requirements.txt

@@ -0,0 +1,18 @@
+gradio>=4.4.0
+transformers>=4.35.2
+torch>=2.1.1
+numpy>=1.24.3
+pandas>=2.1.3
+python-dotenv>=1.0.0
+faiss-cpu>=1.7.4
+langchain>=0.0.339
+pydantic>=2.5.2
+python-multipart>=0.0.6
+soundfile>=0.12.1
+librosa>=0.10.1
+opencv-python>=4.8.1.78
+pillow>=10.1.0
+redis>=5.0.1
+pytest>=7.4.3
+crewai>=0.11.0
+huggingface_hub>=0.26.5