Update app.py

app.py

@@ -13,10 +13,13 @@ logging.basicConfig(
 )
 logger = logging.getLogger(__name__)
 
+# Set torch threads
+torch.set_num_threads(4)
+
 class HealthAssistant:
     def __init__(self, use_smaller_model=True):
         if use_smaller_model:
-            self.model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"
+            self.model_name = "facebook/opt-125m"
         else:
             self.model_name = "Qwen/Qwen2-VL-7B-Instruct"
         
@@ -77,76 +80,74 @@ class HealthAssistant:
         
         return "general"
 
-    def _get_specialized_prompt(self, query_type: str, message: str) -> str:
-        """Get specialized medical prompts"""
-        base_context = f"""Current Health Context:
-{self._get_health_context()}
-
-"""
+    def _prepare_medical_prompt(self, message: str, query_type: str) -> str:
+        """Prepare medical prompt based on query type"""
+        base_context = self._get_health_context()
         
         prompts = {
-            "symptom_check": f"""{base_context}
-Analyze these symptoms professionally:
-Patient's Description: {message}
-
-Provide structured analysis:
-1. Symptoms identified
-2. Possible causes
-3. Severity assessment
-4. Recommended actions
+            "symptom_check": f"""You are a medical AI assistant. Based on the following health context and symptoms, provide a careful analysis.
+
+Current Health Context:
+{base_context}
+
+Patient's Symptoms: {message}
+
+Provide a structured response covering:
+1. Key symptoms identified
+2. Possible common causes
+3. General recommendations
+4. Warning signs to watch for
 5. When to seek medical care
-""",
-
-            "medication_info": f"""{base_context}
-Regarding medication inquiry:
-Query: {message}
-
-Provide structured information:
-1. General medication information
-2. Common usage guidelines
-3. Important considerations
-4. General precautions
-5. When to consult healthcare provider
-""",
-
-            "lifestyle_advice": f"""{base_context}
-Health and Lifestyle Query:
-Question: {message}
-
-Provide structured guidance:
-1. Evidence-based recommendations
-2. Implementation steps
-3. Expected benefits
-4. Safety considerations
-5. Progress monitoring tips
-""",
-
-            "emergency_guidance": f"""{base_context}
-URGENT Health Situation:
-Condition: {message}
-
-Critical guidance:
+
+Remember to maintain a professional and careful tone.""",
+
+            "medication_info": f"""You are a medical AI assistant. Provide information about the medication inquiry while noting you cannot give prescription advice.
+
+Current Health Context:
+{base_context}
+
+Medication Query: {message}
+
+Provide general information about:
+1. Basic medication category/purpose
+2. General usage patterns
+3. Common considerations
+4. Important precautions
+5. When to consult a healthcare provider
+
+Remember to emphasize this is general information only.""",
+
+            "emergency_guidance": f"""You are a medical AI assistant. This appears to be an urgent situation.
+
+Current Health Context:
+{base_context}
+
+Urgent Situation: {message}
+
+Provide immediate guidance:
 1. Severity assessment
 2. Immediate actions needed
-3. Emergency signs
-4. When to call emergency services
+3. Emergency warning signs
+4. Whether to call emergency services
 5. Precautions while waiting
-⚠️ SEEK IMMEDIATE MEDICAL ATTENTION FOR EMERGENCIES
-""",
 
-            "general": f"""{base_context}
-Medical Query:
-{message}
+Always emphasize seeking immediate medical care for emergencies.""",
+
+            "general": f"""You are a medical AI assistant. Provide helpful health information based on the query.
 
-Provide structured response:
-1. Understanding of the query
-2. Relevant medical information
-3. Professional guidance
+Current Health Context:
+{base_context}
+
+Health Query: {message}
+
+Provide a structured response covering:
+1. Understanding of the question
+2. Relevant health information
+3. General guidance
 4. Important considerations
-5. Additional recommendations
-"""
+5. Additional recommendations"""
         }
-        
+
         return prompts.get(query_type, prompts["general"])
 
     def generate_response(self, message: str, history: List = None) -> str:
@@ -154,14 +155,16 @@ Provide structured response:
             if not hasattr(self, 'model') or self.model is None:
                 return "System is initializing. Please try again in a moment."
 
-            # Detect query type and get appropriate prompt
+            # Detect query type
             query_type = self._detect_query_type(message)
-            prompt = self._get_specialized_prompt(query_type, message)
             
+            # Prepare prompt
+            prompt = self._prepare_medical_prompt(message, query_type)
+
             # Add conversation history if available
             if history:
-                prompt += "\n\nPrevious conversation context:"
-                for prev_msg, prev_response in history[-2:]:  # Last 2 exchanges
+                prompt += "\n\nRecent conversation context:"
+                for prev_msg, prev_response in history[-2:]:
                     prompt += f"\nQ: {prev_msg}\nA: {prev_response}\n"
 
             # Tokenize
@@ -178,10 +181,9 @@ Provide structured response:
                 outputs = self.model.generate(
                     inputs["input_ids"],
                     max_new_tokens=150,
-                    num_beams=2,
-                    temperature=0.3,
+                    num_beams=1,
+                    temperature=0.7,
                     top_p=0.9,
-                    no_repeat_ngram_size=3,
                     pad_token_id=self.tokenizer.pad_token_id,
                     eos_token_id=self.tokenizer.eos_token_id
                 )
@@ -192,7 +194,7 @@ Provide structured response:
                 skip_special_tokens=True
             )
 
-            # Clean and format response
+            # Format response
             response = self._format_response(response, query_type)
 
             # Cleanup
@@ -207,36 +209,31 @@ Provide structured response:
 
     def _format_response(self, response: str, query_type: str) -> str:
         """Format and clean the response"""
-        # Remove repeated headers and clean up
+        # Remove repeated headers
         lines = [line.strip() for line in response.split('\n') if line.strip()]
         clean_lines = []
         seen = set()
         
         for line in lines:
-            # Skip common headers and duplicates
-            if any(header in line for header in ["Location:", "Date:", "M.D.", "Medical"]):
-                continue
             if line not in seen:
                 seen.add(line)
                 clean_lines.append(line)
         
-        # Add appropriate emoji based on query type
-        emoji_map = {
-            "emergency_guidance": "🚨",
-            "symptom_check": "🔍",
-            "medication_info": "💊",
-            "lifestyle_advice": "💡",
-            "general": "ℹ️"
+        # Add appropriate prefix based on query type
+        prefixes = {
+            "emergency_guidance": "🚨 URGENT: ",
+            "symptom_check": "🔍 Analysis: ",
+            "medication_info": "💊 Medication Info: ",
+            "lifestyle_advice": "💡 Health Advice: ",
+            "general": "ℹ️ "
         }
         
-        emoji = emoji_map.get(query_type, "ℹ️")
-        
-        # Combine and format
-        formatted_response = f"{emoji} " + "\n".join(clean_lines)
+        prefix = prefixes.get(query_type, "ℹ️ ")
+        formatted_response = prefix + "\n".join(clean_lines)
         
-        # Add disclaimer if needed
+        # Add disclaimer for certain types
         if query_type in ["emergency_guidance", "medication_info"]:
-            formatted_response += "\n\n⚠️ This is general information only. Always consult healthcare professionals for medical advice."
+            formatted_response += "\n\n⚠️ Note: This is general information only. Always consult healthcare professionals."
         
         return formatted_response
 
@@ -261,7 +258,8 @@ Provide structured response:
                     med_info += f" | Note: {med['Notes']}"
                 context_parts.append(med_info)
 
-        return "\n".join(context_parts) if context_parts else "No health data available"
+        return "\n".join(context_parts) if context_parts else "No health data recorded"
+
     def add_metrics(self, weight: float, steps: int, sleep: float) -> bool:
         try:
             self.metrics.append({
@@ -301,13 +299,8 @@ class GradioInterface:
         if not message.strip():
             return "", history
         
-        # Generate response
         response = self.assistant.generate_response(message, history)
-        
-        # Update history
         history.append([message, response])
-        
-        # Clear input and return updated history
         return "", history
 
     def add_health_metrics(self, weight: float, steps: int, sleep: float) -> str:
@@ -337,7 +330,7 @@ class GradioInterface:
         return "❌ Error adding medication."
 
     def create_interface(self):
-        with gr.Blocks(title="Medical Health Assistant", theme=gr.themes.Soft()) as demo:
+        with gr.Blocks(title="Medical Health Assistant") as demo:
             gr.Markdown("""
             # 🏥 Medical Health Assistant
             
@@ -351,7 +344,7 @@ class GradioInterface:
                     chatbot = gr.Chatbot(
                         value=[],
                         height=450,
-                        bubble=True
+                        show_label=False
                     )
                     with gr.Row():
                         msg = gr.Textbox(
@@ -360,8 +353,8 @@ class GradioInterface:
                             show_label=False,
                             scale=9
                         )
-                        send_btn = gr.Button("💬 Send", scale=1)
-                    clear_btn = gr.Button("🔄 Clear Chat")
+                        send_btn = gr.Button("Send", scale=1)
+                    clear_btn = gr.Button("Clear Chat")
 
                 # Health Metrics
                 with gr.Tab("📊 Health Metrics"):
@@ -383,7 +376,7 @@ class GradioInterface:
                                 minimum=0,
                                 maximum=24
                             )
-                            metrics_btn = gr.Button("📝 Save Metrics")
+                            metrics_btn = gr.Button("Save Metrics")
                             metrics_status = gr.Markdown()
 
                 # Medication Manager
@@ -407,7 +400,7 @@ class GradioInterface:
                                 label="Notes (optional)",
                                 placeholder="Additional instructions or notes"
                             )
-                            med_btn = gr.Button("💊 Add Medication")
+                            med_btn = gr.Button("Add Medication")
                             med_status = gr.Markdown()
 
             # Event handlers
@@ -427,7 +420,6 @@ class GradioInterface:
                 outputs=[med_status]
             )
 
-            # Add helpful information
             gr.Markdown("""
             ### ⚠️ Important Medical Disclaimer
             This AI assistant provides general health information only.
@@ -436,7 +428,6 @@ class GradioInterface:
             - Seek immediate medical attention for emergencies
             """)
 
-            # Enable queuing for better performance
             demo.queue()
             
         return demo