Update app.py

app.py

@@ -7,7 +7,6 @@ import gc
 from typing import List, Dict, Optional
 import os
 
-# ================== Model Configuration ==================
 class ModelHandler:
     def __init__(self):
         self.model_name = "google/flan-t5-large"
@@ -32,12 +31,10 @@ class ModelHandler:
 
     def generate_response(self, prompt: str, max_length: int = 512) -> str:
         try:
-            # Clear memory
             gc.collect()
             if torch.cuda.is_available():
                 torch.cuda.empty_cache()
 
-            # Prepare input
             inputs = self.tokenizer(
                 prompt,
                 return_tensors="pt",
@@ -45,7 +42,6 @@ class ModelHandler:
                 max_length=512
             ).to(self.device)
 
-            # Generate response
             with torch.no_grad():
                 outputs = self.model.generate(
                     inputs.input_ids,
@@ -58,7 +54,6 @@ class ModelHandler:
 
             response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-            # Clear memory
             del outputs, inputs
             gc.collect()
             if torch.cuda.is_available():
@@ -73,7 +68,6 @@ class ModelHandler:
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
 
-# ================== Data Management ==================
 class HealthData:
     def __init__(self):
         self.metrics = []
@@ -116,65 +110,43 @@ class HealthData:
 
         return "\n".join(context_parts) if context_parts else "No health data available."
 
-# ================== Health Assistant ==================
 class HealthAssistant:
     def __init__(self):
         self.model = ModelHandler()
         self.data = HealthData()
         self.request_count = 0
 
-    def _create_prompt(self, message: str, context: str = "", history: List = None) -> str:
-        prompt_parts = [
-            "You are a helpful healthcare assistant. Provide accurate and helpful information.",
-            f"User Health Information:\n{context}" if context else "",
-            "Previous conversation:",
-        ]
+    def _create_prompt(self, message: str, history: List = None) -> str:
+        prompt_parts = ["You are a helpful healthcare assistant."]
         
+        # Add health context
+        health_context = self.data.get_health_context()
+        if health_context != "No health data available.":
+            prompt_parts.append(f"Current health information:\n{health_context}")
+        
+        # Add conversation history
         if history:
-            for h in history[-3:]:  # Last 3 messages for context
-                prompt_parts.append(f"User: {h['content']}" if h['role'] == 'user' 
-                                 else f"Assistant: {h['content']}")
+            prompt_parts.append("Previous conversation:")
+            for user_msg, bot_msg in history[-3:]:
+                prompt_parts.append(f"User: {user_msg}")
+                prompt_parts.append(f"Assistant: {bot_msg}")
+        
+        # Add current question
+        prompt_parts.append(f"User: {message}")
+        prompt_parts.append("Assistant:")
         
-        prompt_parts.append(f"Current question: {message}")
-        return "\n\n".join(filter(None, prompt_parts))
+        return "\n\n".join(prompt_parts)
 
     def get_response(self, message: str, history: List = None) -> str:
-        # Increment request counter
         self.request_count += 1
-        
-        # Get health context
-        context = self.data.get_health_context()
-        
-        # Create prompt
-        prompt = self._create_prompt(message, context, history)
-        
-        # Get response
+        prompt = self._create_prompt(message, history)
         response = self.model.generate_response(prompt)
         
-        # Periodic memory cleanup
         if self.request_count % 5 == 0:
             self.model.clear_memory()
             
         return response
 
-    def analyze_symptoms(self, symptoms: str) -> str:
-        if not symptoms:
-            return "Please describe your symptoms."
-            
-        prompt = (
-            "Analyze these symptoms as a medical professional:\n"
-            f"{symptoms}\n\n"
-            "Provide analysis with:\n"
-            "1. Risk Level\n"
-            "2. Key Symptoms\n"
-            "3. Possible Causes\n"
-            "4. Recommended Actions\n"
-            "5. When to Seek Medical Care"
-        )
-        
-        return self.model.generate_response(prompt)
-
-# ================== Gradio Interface ==================
 class HealthAssistantUI:
     def __init__(self):
         self.assistant = HealthAssistant()
@@ -184,8 +156,7 @@ class HealthAssistantUI:
             return "", history
         
         bot_message = self.assistant.get_response(message, history)
-        history.append({"role": "user", "content": message})
-        history.append({"role": "assistant", "content": bot_message})
+        history.append([message, bot_message])
         return "", history
 
     def save_metrics(self, weight: float, steps: int, sleep: float) -> tuple:
@@ -220,58 +191,36 @@ class HealthAssistantUI:
             with gr.Tabs():
                 # Chat Interface
                 with gr.Tab("💬 Health Chat"):
-                    with gr.Row():
-                        with gr.Column(scale=3):
-                            chatbot = gr.Chatbot(
-                                show_label=False,
-                                height=450,
-                                container=True,
-                            )
-                        with gr.Column(scale=1):
-                            gr.Markdown("### Your Health Info")
-                            context_display = gr.Markdown(
-                                value=self.assistant.data.get_health_context()
-                            )
-                    
+                    chatbot = gr.Chatbot(
+                        height=450,
+                        show_label=False,
+                    )
                     with gr.Row():
                         msg = gr.Textbox(
                             placeholder="Type your health question... (Press Enter)",
                             lines=2,
-                            max_lines=2,
                             show_label=False,
-                            container=False,
                             scale=9
                         )
                         send_btn = gr.Button("Send", scale=1)
-                    
                     clear_btn = gr.Button("Clear Chat")
-                
-                # Symptom Checker
-                with gr.Tab("🔍 Symptom Checker"):
-                    symptoms_input = gr.Textbox(
-                        label="Describe your symptoms",
-                        placeholder="Enter your symptoms in detail...",
-                        lines=4
-                    )
-                    analyze_btn = gr.Button("Analyze Symptoms", variant="primary")
-                    symptoms_output = gr.Markdown()
-                
-                # Health Metrics
+
+                # Health Metrics Tab
                 with gr.Tab("📊 Health Metrics"):
                     with gr.Row():
                         with gr.Column():
                             weight_input = gr.Number(label="Weight (kg)")
                             steps_input = gr.Number(label="Steps")
                             sleep_input = gr.Number(label="Hours Slept")
-                            metrics_btn = gr.Button("Save Metrics", variant="primary")
+                            metrics_btn = gr.Button("Save Metrics")
                             metrics_status = gr.Markdown()
                         
                         with gr.Column():
                             metrics_display = gr.Dataframe(
                                 headers=["Date", "Weight", "Steps", "Sleep"]
                             )
-                
-                # Medication Manager
+
+                # Medication Manager Tab
                 with gr.Tab("💊 Medication Manager"):
                     with gr.Row():
                         with gr.Column():
@@ -279,7 +228,7 @@ class HealthAssistantUI:
                             med_dosage = gr.Textbox(label="Dosage")
                             med_time = gr.Textbox(label="Time")
                             med_notes = gr.Textbox(label="Notes (optional)")
-                            med_btn = gr.Button("Add Medication", variant="primary")
+                            med_btn = gr.Button("Add Medication")
                             med_status = gr.Markdown()
                         
                         with gr.Column():
@@ -290,13 +239,7 @@ class HealthAssistantUI:
             # Event handlers
             msg.submit(self.user_chat, [msg, chatbot], [msg, chatbot])
             send_btn.click(self.user_chat, [msg, chatbot], [msg, chatbot])
-            clear_btn.click(lambda: None, None, chatbot)
-            
-            analyze_btn.click(
-                self.assistant.analyze_symptoms,
-                inputs=[symptoms_input],
-                outputs=[symptoms_output]
-            )
+            clear_btn.click(lambda: [], None, chatbot)
             
             metrics_btn.click(
                 self.save_metrics,
@@ -310,12 +253,6 @@ class HealthAssistantUI:
                 outputs=[med_status, meds_display]
             )
 
-            gr.Markdown(
-                """### ⚠️ Medical Disclaimer
-                This AI assistant provides general health information only. 
-                Always consult healthcare professionals for medical advice."""
-            )
-
         return demo
 
 def main():