feat: Add configurable content inclusion for spiritual care messages, allowing dynamic selection of patient profile, situation, distress, and conversation context.

src/core/provider_summary_generator.py

@@ -685,31 +685,37 @@ class ProviderSummaryGenerator:
         summary: ProviderSummary,
         language: str = "English",
         session_id: Optional[str] = None,
-        model_override: Optional[str] = None
+        model_override: Optional[str] = None,
+        include_patient_profile: bool = False,
+        include_situation_analysis: bool = False,
+        include_distress_indicators: bool = True,
+        include_conversation_context: bool = True
     ) -> str:
         """
         Generate a compassionate, concise message for spiritual care team using LLM.
         
-        Creates a natural language summary that:
-        - Humanizes the patient's situation
-        - Highlights key emotional/spiritual concerns
-        - Provides essential contact and context information
-        - Uses empathetic, professional tone
-        
         Args:
             summary: ProviderSummary with all case details
             language: Language hint (deprecated - LLM auto-detects from context)
             session_id: Optional session ID for session-specific prompt overrides
             model_override: Optional model name override for this generation
+            include_patient_profile: Whether to include name, phone, age, conditions (Default: False)
+            include_situation_analysis: Whether to include situation description (Default: False)
+            include_distress_indicators: Whether to include indicators and urgency (Default: False)
+            include_conversation_context: Whether to include triage exchanges and chat snippet (Default: True)
             
         Returns:
             Natural language message for spiritual care team
-            
-        Requirements: 7.1, 7.2, 7.3, 7.4, 7.5
         """
         # If no AI client available, return formatted structured message
         if not self.ai_client:
-            return self._generate_fallback_care_message(summary, language)
+            return self._generate_fallback_care_message(
+                summary, language, 
+                include_patient_profile=include_patient_profile,
+                include_situation_analysis=include_situation_analysis,
+                include_distress_indicators=include_distress_indicators,
+                include_conversation_context=include_conversation_context
+            )
         
         # Load system prompt using PromptController for session-aware loading
         try:
@@ -719,18 +725,15 @@ class ProviderSummaryGenerator:
             )
             system_prompt = prompt_config.base_prompt
             
-            # Load user prompt template from file
-            prompts_dir = os.path.join(
-                os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
-                'src', 'config', 'prompts'
-            )
-            template_path = os.path.join(prompts_dir, 'spiritual_care_message_template.txt')
-            with open(template_path, 'r', encoding='utf-8') as f:
-                user_template = f.read().strip()
-        
         except Exception as e:
             print(f"⚠️ Error loading prompt files: {e}")
-            return self._generate_fallback_care_message(summary, language)
+            return self._generate_fallback_care_message(
+                summary, language,
+                include_patient_profile=include_patient_profile,
+                include_situation_analysis=include_situation_analysis,
+                include_distress_indicators=include_distress_indicators,
+                include_conversation_context=include_conversation_context
+            )
         
         # Build context for LLM
         indicators_text = "\n".join(f"- {ind}" for ind in summary.indicators)
@@ -767,75 +770,126 @@ class ProviderSummaryGenerator:
             if goal:
                 patient_goal = str(goal)
         
-        # Fill user prompt template
-        user_prompt = user_template.format(
-            patient_name=summary.patient_name,
-            patient_phone=summary.patient_phone,
-            patient_age=patient_age,
-            patient_conditions=patient_conditions,
-            patient_goal=patient_goal,
-            situation_description=summary.situation_description,
-            indicators=indicators_text,
-            urgency_level=summary.urgency_level,
-            follow_up_timeline=summary.follow_up_timeline,
-            triage_context=triage_section,
-            conversation_snippet=conversation_snippet
-        )
-
-        try:
-            # Use DynamicAIClient with model override if specified
-            from .ai_client import DynamicAIClient
+        # Construct User Prompt dynamically based on flags
+        prompt_parts = []
+        
+        # 1. Patient Profile
+        if include_patient_profile:
+            prompt_parts.append(f"**PATIENT CONTACT:**\nName: {summary.patient_name}\nPhone: {summary.patient_phone}\nAge: {patient_age}")
+            prompt_parts.append(f"**PATIENT BACKGROUND:**\nMedical Conditions: {patient_conditions}\nPrimary Goal: {patient_goal}")
             
-            # Create AI client for spiritual care messages
-            ai_client = DynamicAIClient(
-                agent_name="SpiritualCareMessage",
-                model_override=model_override
-            )
+        # 2. Situation Analysis
+        if include_situation_analysis:
+            prompt_parts.append(f"**SITUATION:**\n{summary.situation_description}")
+
+        # 3. Distress Indicators & Urgency
+        if include_distress_indicators:
+            prompt_parts.append(f"**DISTRESS INDICATORS:**\n{indicators_text}")
+            prompt_parts.append(f"**URGENCY:**\n{summary.urgency_level} - Follow up {summary.follow_up_timeline}")
+
+        # 4. Conversation Context (Triage + Chat)
+        if include_conversation_context:
+            if triage_section:
+                prompt_parts.append(triage_section.strip())
+            prompt_parts.append(f"**CONTEXT:**\n{conversation_snippet}")
             
-            # Generate response
-            response = ai_client.generate_response(
+        user_prompt = "\n\n".join(prompt_parts)
+
+        try:
+            # Use existing ai_client (AIClientManager) to generate response with overrides
+            response = self.ai_client.generate_response(
                 system_prompt=system_prompt,
                 user_prompt=user_prompt,
-                temperature=0.7,  # Slightly creative for natural language
-                call_type="spiritual_care_message"
+                temperature=0.7,
+                call_type="spiritual_care_message",
+                agent_name="SpiritualCareMessage",
+                model_override=model_override
             )
             
             return response.strip()
             
         except Exception as e:
             print(f"⚠️ Error generating LLM message: {e}")
-            return self._generate_fallback_care_message(summary, language)
+            return self._generate_fallback_care_message(
+                summary, language,
+                include_patient_profile=include_patient_profile,
+                include_situation_analysis=include_situation_analysis,
+                include_distress_indicators=include_distress_indicators,
+                include_conversation_context=include_conversation_context
+            )
     
-    def _generate_fallback_care_message(self, summary: ProviderSummary, language: str = "English") -> str:
+    def _generate_fallback_care_message(
+        self, 
+        summary: ProviderSummary, 
+        language: str = "English",
+        include_patient_profile: bool = False,
+        include_situation_analysis: bool = False,
+        include_distress_indicators: bool = True,
+        include_conversation_context: bool = True
+    ) -> str:
         """Generate fallback narrative message when LLM is unavailable."""
         
-        # Prepare components for narrative
-        conditions = "None listed"
-        if summary.medical_context and summary.medical_context.get('conditions'):
-            cond_list = summary.medical_context.get('conditions', [])
-            conditions = ", ".join(cond_list)
-            
-        indicators = ", ".join(summary.indicators) if summary.indicators else "Unspecified distress"
+        parts = []
         
-        action = "Assess and support"
-        if summary.recommended_actions:
-            action = summary.recommended_actions[0]
+        # 1. Patient Profile
+        if include_patient_profile:
+            name_part = f"{summary.patient_name}"
+            if summary.patient_phone:
+                name_part += f" ({summary.patient_phone})"
+            
+            if language.lower() in ['ukrainian', 'uk', 'укр', 'українська']:
+                parts.append(f"Пацієнт: {name_part}.")
+                
+                conditions = "Не вказано"
+                if summary.medical_context and summary.medical_context.get('conditions'):
+                    cond_list = summary.medical_context.get('conditions', [])
+                    conditions = ", ".join(cond_list)
+                parts.append(f"Медичний контекст: {conditions}.")
+            else:
+                parts.append(f"Patient: {name_part}.")
+                
+                conditions = "None listed"
+                if summary.medical_context and summary.medical_context.get('conditions'):
+                    cond_list = summary.medical_context.get('conditions', [])
+                    conditions = ", ".join(cond_list)
+                parts.append(f"Medical Context: {conditions}.")
 
-        # Construct narrative based on language
-        if language.lower() in ['ukrainian', 'uk', 'укр', 'українська']:
-            return (
-                f"Пацієнт {summary.patient_name} ({summary.patient_phone}) виявляє ознаки духовного дистресу, "
-                f"зокрема: {indicators}. Медичний контекст: {conditions}. "
-                f"Клінічна оцінка вказує на рівень серйозності: {summary.severity_level}. "
-                f"Рекомендована ді��: {action}. Будь ласка, забезпечте подальший супровід {summary.follow_up_timeline}."
-            )
-        else:
-            return (
-                f"The patient {summary.patient_name} ({summary.patient_phone}) is presenting with spiritual distress "
-                f"indicators including {indicators}. Relevant medical context includes {conditions}. "
-                f"Clinical assessment indicates {summary.severity_level} severity with {summary.confidence:.0%} confidence. "
-                f"Please review for {action} and follow up {summary.follow_up_timeline.lower()}."
-            )
+        # 2. Clinical Analysis (Situation)
+        # Note: Situation is usually a narrative, fallback might not have it pre-computed well if it depends on LLM summary.
+        # But summary.situation_description exists.
+        if include_situation_analysis and summary.situation_description:
+             if language.lower() in ['ukrainian', 'uk', 'укр', 'українська']:
+                 parts.append(f"Ситуація: {summary.situation_description}")
+             else:
+                 parts.append(f"Situation: {summary.situation_description}")
+
+        # 3. Distress Indicators & Urgency
+        if include_distress_indicators:
+            indicators = ", ".join(summary.indicators) if summary.indicators else "Unspecified"
+            action = summary.recommended_actions[0] if summary.recommended_actions else "Assess"
+            
+            if language.lower() in ['ukrainian', 'uk', 'укр', 'українська']:
+                parts.append(f"Виявлено ознаки дистресу: {indicators}.")
+                parts.append(f"Оцінка: Рівень серйозності {summary.severity_level}.")
+                parts.append(f"План: {action}. Контроль: {summary.follow_up_timeline}.")
+            else:
+                parts.append(f"Distress Indicators: {indicators}.")
+                parts.append(f"Assessment: {summary.severity_level} severity level.")
+                parts.append(f"Plan: {action}. Follow-up: {summary.follow_up_timeline}.")
+                
+        # 4. Conversation Context
+        if include_conversation_context:
+            context_snippet = summary.conversation_context[:200] + "..." if summary.conversation_context else ""
+            if context_snippet:
+                if language.lower() in ['ukrainian', 'uk', 'укр', 'українська']:
+                    parts.append(f"Контекст чату: {context_snippet}")
+                else:
+                    parts.append(f"Chat Context: {context_snippet}")
+
+        if not parts:
+            return "No information selected for display."
+            
+        return " ".join(parts)
     
     def generate_summary_with_validation(self, **kwargs) -> tuple[ProviderSummary, List[str]]:
         """

src/core/simplified_medical_app.py

@@ -761,22 +761,28 @@ Is there anything else I can help you with today?"""
         """
         return getattr(self, '_last_provider_summary', None)
     
-    def generate_spiritual_care_message(self, language: str = "English", session_id: Optional[str] = None) -> Optional[str]:
+    def generate_spiritual_care_message(
+        self, 
+        language: str = "English", 
+        session_id: Optional[str] = None,
+        include_patient_profile: bool = False,
+        include_situation_analysis: bool = False,
+        include_distress_indicators: bool = True,
+        include_conversation_context: bool = True
+    ) -> Optional[str]:
         """
         Generate LLM-based message for spiritual care team.
         
-        Creates a compassionate, concise message summarizing the patient's
-        situation for the spiritual care team. Uses natural language and
-        emphasizes emotional/spiritual aspects.
-        
         Args:
             language: Language for the message (English/Ukrainian)
             session_id: Optional session ID for session-specific prompt overrides
+            include_patient_profile: Include name, phone, age, conditions
+            include_situation_analysis: Include situation description
+            include_distress_indicators: Include indicators and urgency
+            include_conversation_context: Include triage, chat snippet
             
         Returns:
             Generated message if provider summary exists, None otherwise
-            
-        Requirements: 7.1, 7.2, 7.3, 7.4, 7.5
         """
         summary = self.get_last_provider_summary()
         if not summary:
@@ -789,7 +795,11 @@ Is there anything else I can help you with today?"""
             summary=summary,
             language=language,
             session_id=session_id,
-            model_override=model_override
+            model_override=model_override,
+            include_patient_profile=include_patient_profile,
+            include_situation_analysis=include_situation_analysis,
+            include_distress_indicators=include_distress_indicators,
+            include_conversation_context=include_conversation_context
         )
     
     def _detect_language(self, text: str) -> str:

src/interface/simplified_gradio_app.py

@@ -229,6 +229,27 @@ def create_simplified_interface():
                                         label="Message for Spiritual Care Team",
                                         interactive=False
                                     )
+                                    with gr.Row():
+                                        include_conversation_context = gr.Checkbox(
+                                            value=True, 
+                                            label="Include Conversation Context (Chat & Triage)",
+                                            interactive=True
+                                        )
+                                        include_situation_analysis = gr.Checkbox(
+                                            value=False, 
+                                            label="Include Situation Analysis",
+                                            interactive=True
+                                        )
+                                        include_distress_indicators = gr.Checkbox(
+                                            value=True, 
+                                            label="Include Distress Indicators",
+                                            interactive=True
+                                        )
+                                        include_patient_profile = gr.Checkbox(
+                                            value=False, 
+                                            label="Include Patient Profile (Name, Contact)",
+                                            interactive=True
+                                        )
                                     with gr.Row():
                                         generate_message_btn = gr.Button(
                                             "🔄 Regenerate Message",
@@ -2161,7 +2182,13 @@ Use the **Download Summary** button below to access the complete provider summar
             """Clear provider summary panel."""
             return gr.update(visible=False), "No provider summary available", "", ""
         
-        def regenerate_spiritual_care_message(session: SimplifiedSessionData):
+        def regenerate_spiritual_care_message(
+            session: SimplifiedSessionData,
+            include_conversation: bool = True,
+            include_situation: bool = False,
+            include_indicators: bool = False,
+            include_profile: bool = False
+        ):
             """Regenerate LLM-based spiritual care message."""
             if session is None:
                 return ""
@@ -2169,7 +2196,11 @@ Use the **Download Summary** button below to access the complete provider summar
             try:
                 message = session.app_instance.generate_spiritual_care_message(
                     language="English",
-                    session_id=session.session_id
+                    session_id=session.session_id,
+                    include_conversation_context=include_conversation,
+                    include_situation_analysis=include_situation,
+                    include_distress_indicators=include_indicators,
+                    include_patient_profile=include_profile
                 )
                 return message if message else "No provider summary available to generate message from."
             except Exception as e:
@@ -2230,7 +2261,7 @@ Use the **Download Summary** button below to access the complete provider summar
         # Spiritual care message handlers
         generate_message_btn.click(
             regenerate_spiritual_care_message,
-            inputs=[session_data],
+            inputs=[session_data, include_conversation_context, include_situation_analysis, include_distress_indicators, include_patient_profile],
             outputs=[spiritual_care_message]
         )