Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+from datetime import datetime
+from huggingface_hub import InferenceClient
+import json
+import os
+from typing import Optional
+
+# Initialize LLM client
+def init_llm():
+    try:
+        client = InferenceClient(
+            model="meta-llama/Llama-2-7b-chat-hf",  
+            token=os.getenv("HF_TOKEN")
+        )
+        return client, True
+    except Exception as e:
+        print(f"LLM initialization failed: {str(e)}")
+        return None, False
+
+llm_client, has_llm = init_llm()
+
+# Global storage (in production, use a database)
+metrics_data = []
+medication_data = []
+chat_history = []
+
+def generate_prompt(instruction: str, context: str = "") -> str:
+    """Generate prompt for LLaMA format"""
+    system_prompt = """You are a helpful healthcare assistant. Provide accurate information while noting 
+    you're not a replacement for professional medical advice. Always include relevant medical disclaimers."""
+    
+    return f"""<s>[INST] <<SYS>>{system_prompt}<</SYS>>
+    
+    {context}
+    
+    {instruction} [/INST]"""
+
+def get_llm_response(prompt: str, temperature: float = 0.7) -> str:
+    """Get response from LLM"""
+    if not has_llm:
+        return "Service is running in fallback mode. Using basic response templates."
+        
+    try:
+        formatted_prompt = generate_prompt(prompt)
+        response = llm_client.text_generation(
+            formatted_prompt,
+            max_new_tokens=512,
+            temperature=temperature,
+            repetition_penalty=1.1
+        )
+        return response
+    except Exception as e:
+        return f"Error accessing LLM: {str(e)}"
+
+def analyze_symptoms(symptoms: str) -> str:
+    """Analyze symptoms using LLM"""
+    if not symptoms:
+        return "Please describe your symptoms."
+        
+    prompt = f"""Analyze these symptoms and provide a detailed assessment:
+    Symptoms: {symptoms}
+    
+    Please provide:
+    1. Risk Level (Low/Medium/High)
+    2. Possible causes
+    3. Recommendations
+    4. Whether immediate medical attention is needed
+    
+    Format the response in a clear, structured way."""
+    
+    response = get_llm_response(prompt, temperature=0.3)
+    return response if response else "Unable to analyze symptoms. Please try again."
+
+def get_health_advice(topic: str, question: str) -> str:
+    """Get health advice using LLM"""
+    if not question:
+        return "Please enter a question."
+        
+    context = f"Topic: {topic}\nContext: {HEALTH_KNOWLEDGE.get(topic, '')}"
+    prompt = f"""Based on this health topic and context, answer the following question:
+    Question: {question}
+    
+    Provide a clear, informative answer with relevant health recommendations."""
+    
+    response = get_llm_response(prompt)
+    return response if response else "Unable to provide advice at the moment. Please try again."
+
+def chat_with_assistant(message: str, history: list) -> str:
+    """Chat with the health assistant"""
+    if not message:
+        return ""
+        
+    # Format history for context
+    context = "\n".join([f"User: {h[0]}\nAssistant: {h[1]}" for h in history[-3:]])
+    
+    prompt = f"""Previous conversation:
+    {context}
+    
+    User's new message: {message}
+    
+    Provide a helpful response about their health question or concern."""
+    
+    response = get_llm_response(prompt)
+    return response if response else "I apologize, but I'm unable to process your request at the moment."
+
+# Gradio Interface
+with gr.Blocks(title="Virtual Health Assistant", theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 🏥 Virtual Health Assistant
+        Powered by AI to provide health information, track metrics, and manage medications.
+        
+        ⚕️ This is an AI assistant and not a replacement for professional medical advice.
+        """
+    )
+    
+    with gr.Tabs():
+        # Chat Interface Tab
+        with gr.Tab("💬 Health Chat"):
+            chatbot = gr.Chatbot(label="Chat History")
+            msg = gr.Textbox(label="Type your message", placeholder="Ask about health topics...")
+            clear = gr.Button("Clear Chat")
+            
+            def respond(message, history):
+                bot_message = chat_with_assistant(message, history)
+                history.append((message, bot_message))
+                return "", history
+            
+            msg.submit(respond, [msg, chatbot], [msg, chatbot])
+            clear.click(lambda: None, None, chatbot, queue=False)
+
+        # Symptom Checker Tab
+        with gr.Tab("🔍 Symptom Checker"):
+            with gr.Row():
+                with gr.Column():
+                    symptoms_input = gr.Textbox(
+                        label="Describe your symptoms",
+                        placeholder="Enter your symptoms here...",
+                        lines=3
+                    )
+                    symptoms_button = gr.Button("Analyze Symptoms")
+                    symptoms_output = gr.Markdown(label="Analysis")
+                
+                with gr.Column():
+                    gr.Markdown("""
+                    ### How to use:
+                    1. Describe your symptoms in detail
+                    2. Include duration and severity
+                    3. Mention any relevant medical history
+                    
+                    ⚠️ For emergencies, call emergency services immediately
+                    """)
+                    
+            symptoms_button.click(
+                analyze_symptoms,
+                inputs=[symptoms_input],
+                outputs=[symptoms_output]
+            )
+
+        # 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_button = gr.Button("Save Metrics")
+                    metrics_output = gr.Textbox(
+                        label="Status",
+                        readonly=True
+                    )
+                
+                with gr.Column():
+                    view_metrics_button = gr.Button("View Metrics")
+                    metrics_plot = gr.Plot(label="Your Health Trends")
+                    
+                    def save_metrics(weight, steps, sleep):
+                        metrics_data.append({
+                            'date': datetime.now().strftime('%Y-%m-%d'),
+                            'weight': weight,
+                            'steps': steps,
+                            'sleep': sleep
+                        })
+                        return "✅ Metrics saved successfully!"
+                    
+                    def view_metrics():
+                        if not metrics_data:
+                            return None
+                        df = pd.DataFrame(metrics_data)
+                        fig = df.plot(x='date', figsize=(10, 6), title="Health Metrics Over Time")
+                        return fig
+                    
+                    metrics_button.click(
+                        save_metrics,
+                        inputs=[weight_input, steps_input, sleep_input],
+                        outputs=[metrics_output]
+                    )
+                    view_metrics_button.click(
+                        view_metrics,
+                        outputs=[metrics_plot]
+                    )
+
+        # Medication Manager Tab
+        with gr.Tab("💊 Medication Manager"):
+            with gr.Row():
+                with gr.Column():
+                    med_name = gr.Textbox(label="Medication Name")
+                    med_dosage = gr.Textbox(label="Dosage")
+                    med_time = gr.Textbox(label="Time (e.g., 9:00 AM)")
+                    med_notes = gr.Textbox(label="Notes (optional)")
+                    med_button = gr.Button("Add Medication")
+                    med_output = gr.Textbox(
+                        label="Status",
+                        readonly=True
+                    )
+
+                with gr.Column():
+                    view_meds_button = gr.Button("View Medications")
+                    meds_table = gr.Dataframe(
+                        headers=["Medication", "Dosage", "Time", "Notes"],
+                        label="Your Medications"
+                    )
+                    
+                    def add_med(name, dosage, time, notes):
+                        if not all([name, dosage, time]):
+                            return "❌ Please fill in all required fields."
+                        medication_data.append({
+                            'Medication': name,
+                            'Dosage': dosage,
+                            'Time': time,
+                            'Notes': notes
+                        })
+                        return f"✅ Added {name} to medications!"
+                    
+                    def view_meds():
+                        return pd.DataFrame(medication_data)
+                    
+                    med_button.click(
+                        add_med,
+                        inputs=[med_name, med_dosage, med_time, med_notes],
+                        outputs=[med_output]
+                    )
+                    view_meds_button.click(
+                        view_meds,
+                        outputs=[meds_table]
+                    )
+
+    gr.Markdown(
+        """
+        ### ⚠️ Important Disclaimer
+        This Virtual Health Assistant uses AI to provide general health information. 
+        It is not a substitute for professional medical advice, diagnosis, or treatment.
+        Always seek the advice of qualified healthcare providers with questions about medical conditions.
+        """
+    )
+
+# Launch the app
+demo.launch()