Update app.py

app.py

@@ -3,8 +3,8 @@ import os
 import requests
 
 # Mistral API setup
-MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY", "yQdfM8MLbX9uhInQ7id4iUTwN4h4pDLX")  # Replace with your actual API key
-MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"  # Removed the trailing space
+MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY", "your_api_key_here")  # Replace with your actual API key
+MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"
 
 def query_mistral(prompt, max_tokens=1024, temperature=0.7):
     """Query Mistral AI API"""
@@ -25,24 +25,38 @@ def query_mistral(prompt, max_tokens=1024, temperature=0.7):
         response.raise_for_status()
         return response.json()['choices'][0]['message']['content']
     except requests.exceptions.RequestException as e:
-        return f"Sorry, I'm having trouble connecting to my knowledge base. Please try again later. Error: {str(e)}"
+        return f"I apologize, I'm currently unable to access my medical knowledge base. Please try again later."
     except Exception as e:
-        return f"An unexpected error occurred. Please rephrase your question or try again later. Error: {str(e)}"
+        return f"An unexpected error occurred. Please try rephrasing your question."
 
-def personalize_response(name, message):
-    """Personalize the chatbot response"""
-    prompt = f"""You are a friendly and empathetic personal medical assistant named Dr. Alex. 
-    The user {name} asked: "{message}"
+def generate_medical_response(name, message):
+    """Generate structured medical response"""
+    prompt = f"""You are Dr. Alex, an experienced physician. {name} asks: "{message}"
+
+    Provide a detailed response with these sections (use bullet points):
+    
+    [Assessment]
+    - Brief professional assessment of the described condition
+    
+    [Recommended Actions] (3-5 points)
+    - Specific self-care measures
+    - Home remedies
+    - Lifestyle adjustments
+    
+    [Medical Treatments] (if applicable)
+    - OTC medications (with dosage examples)
+    - When to consider prescription treatments
+    
+    [Warning Signs] (Red Flags)
+    - Symptoms that require immediate medical attention
     
-    Respond with:
-    1. A caring, personalized greeting using the user's name
-    2. Helpful medical information (but no definitive diagnoses)
-    3. Follow-up questions if more information is needed
-    4. Clear recommendation on when to see a real doctor
-    5. A warm closing
+    [Follow-up Advice]
+    - When to revisit the issue
+    - Recommended tests or specialist consultation if needed
     
-    Keep the response under 200 words, conversational, and supportive.
-    """
+    Keep the tone professional yet compassionate. Use simple language. 
+    Provide concrete, actionable advice. Limit to 250 words."""
+
     return query_mistral(prompt)
 
 def chatbot_response(message, history, name):
@@ -51,57 +65,74 @@ def chatbot_response(message, history, name):
     
     # Simple greetings
     if any(word in message_lower for word in ['hello', 'hi', 'hey']):
-        return f"Hello {name}! I'm Dr. Alex, your personal medical assistant. How can I help you today?"
+        return f"""Hello {name}! I'm Dr. Alex. How can I assist you today?
+
+Please remember:
+- I can provide general health information
+- For emergencies, contact local emergency services
+- Always consult your personal physician for specific medical advice"""
+    
     elif any(word in message_lower for word in ['thank', 'thanks']):
-        return f"You're very welcome, {name}! I'm happy to help. Is there anything else you'd like to discuss?"
+        return f"You're very welcome, {name}! Wishing you good health. Is there anything else you'd like to discuss today?"
     
-    # Personalize medical responses
-    return personalize_response(name, message)
+    # Medical responses
+    return generate_medical_response(name, message)
 
 # Gradio Interface
-with gr.Blocks(title="Personal Medical Assistant", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 👨‍⚕️ Your Personal Medical Assistant")
+with gr.Blocks(title="Dr. Alex - Personal Medical Consultant", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 👨‍⚕️ Dr. Alex - Your Personal Medical Consultant")
     
     # Get user's name for personalization
     name = gr.Textbox(label="Your Name", placeholder="Please enter your name for personalized care")
     
     with gr.Tabs():
-        with gr.TabItem("Chat with Dr. Alex"):
-            gr.Markdown("## Ask me anything about your health")
+        with gr.TabItem("Consult Dr. Alex"):
+            gr.Markdown("## Describe your health concerns")
             chatbot = gr.ChatInterface(
                 fn=lambda msg, hist: chatbot_response(msg, hist, name.value),
                 examples=[
-                    "I've had a headache for 2 days",
-                    "What are symptoms of dehydration?",
-                    "How can I improve my sleep?"
+                    "I have fever and body aches since yesterday",
+                    "Best home remedies for sore throat",
+                    "How to manage mild back pain?"
                 ],
-                title="Dr. Alex - Your Personal Health Assistant"
+                title="Private Consultation with Dr. Alex"
             )
         
-        with gr.TabItem("Symptom Analysis"):
-            gr.Markdown(f"## {name.value}, let's analyze your symptoms")
+        with gr.TabItem("Structured Symptom Checker"):
+            gr.Markdown(f"## {name.value}, let's thoroughly evaluate your symptoms")
             with gr.Row():
                 with gr.Column():
                     age = gr.Number(label="Your Age", minimum=1, maximum=120)
                     gender = gr.Radio(choices=["Male", "Female", "Other"], label="Gender")
-                    symptoms = gr.Textbox(label="Describe your symptoms", lines=3)
+                    symptoms = gr.Textbox(label="Describe your symptoms in detail", lines=3, 
+                                       placeholder="Include location, nature of pain, triggers, etc.")
                     duration = gr.Dropdown(
-                        choices=["Less than 1 day", "1-3 days", "4-7 days", "1-2 weeks", "More than 2 weeks"],
-                        label="How long have you had these symptoms?"
+                        choices=["Less than 24 hours", "1-3 days", "4-7 days", "1-2 weeks", "2-4 weeks", "More than 1 month"],
+                        label="Duration of symptoms"
                     )
-                    severity = gr.Slider(1, 10, step=1, label="Severity (1-10)")
-                    analyze_btn = gr.Button("Analyze My Symptoms", variant="primary")
+                    severity = gr.Slider(1, 10, step=1, label="Pain/Severity level (1-10)")
+                    aggravating_factors = gr.Textbox(label="What makes it worse?", lines=2)
+                    relieving_factors = gr.Textbox(label="What provides relief?", lines=2)
+                    analyze_btn = gr.Button("Get Detailed Medical Advice", variant="primary")
+                
                 with gr.Column():
-                    analysis_output = gr.Textbox(label="Dr. Alex's Analysis", lines=10, interactive=False)
+                    analysis_output = gr.Textbox(label="Dr. Alex's Professional Evaluation", lines=15, interactive=False)
             
             analyze_btn.click(
-                lambda age, gender, symptoms, duration, severity: personalize_response(
+                lambda age, gender, symptoms, duration, severity, aggravating, relieving: generate_medical_response(
                     name.value,
-                    f"As a {age}-year-old {gender}, I've had these symptoms: {symptoms} for {duration} with severity {severity}/10. What could this be?"
+                    f"As a {age}-year-old {gender}, I've had: {symptoms} for {duration}. Severity: {severity}/10. Gets worse with {aggravating} and better with {relieving}."
                 ),
-                inputs=[age, gender, symptoms, duration, severity],
+                inputs=[age, gender, symptoms, duration, severity, aggravating_factors, relieving_factors],
                 outputs=analysis_output
             )
 
+    gr.Markdown("""
+    <div style='background:#f8f9fa;padding:20px;border-radius:10px;margin-top:20px;'>
+    <h3>Important Disclaimer</h3>
+    <p>This AI provides general health information only, not medical advice. Always consult a qualified healthcare provider for personal medical concerns. In emergencies, contact your local emergency services immediately.</p>
+    </div>
+    """)
+
 # Launch app
 demo.launch()