Rename healthAI to healthAI-chatbot

healthAI-chatbot

@@ -0,0 +1,147 @@
+import gradio as gr
+from transformers import pipeline
+
+class HealthAssistant:
+    def __init__(self):
+        # Initialize with smaller models for faster loading
+        self.symptom_checker = pipeline("text-classification", model="distilbert-base-uncased")
+        self.medical_qa = pipeline("text-generation", model="gpt2")
+        
+        # Knowledge base (in production, connect to a medical database)
+        self.disease_db = {
+            "flu": {
+                "symptoms": ["fever", "cough", "sore throat", "muscle aches", "headache", "fatigue"],
+                "advice": """1. Get plenty of rest
+2. Stay hydrated
+3. Use over-the-counter fever reducers like acetaminophen
+4. See a doctor if symptoms worsen or last more than 10 days""",
+                "precautions": [
+                    "Get annual flu vaccine",
+                    "Wash hands frequently with soap",
+                    "Avoid close contact with sick individuals",
+                    "Cover coughs and sneezes"
+                ]
+            },
+            "common cold": {
+                "symptoms": ["runny nose", "sneezing", "congestion", "sore throat", "cough", "mild headache"],
+                "advice": """1. Rest and hydrate
+2. Use saline nasal drops
+3. Gargle with warm salt water for sore throat
+4. Over-the-counter cold medicines may help""",
+                "precautions": [
+                    "Wash hands often with soap and water",
+                    "Avoid touching your face with unwashed hands",
+                    "Stay away from people who are sick",
+                    "Disinfect frequently touched surfaces"
+                ]
+            },
+            "migraine": {
+                "symptoms": ["severe headache", "nausea", "sensitivity to light", "sensitivity to sound", "aura"],
+                "advice": """1. Rest in a quiet, dark room
+2. Apply cold compress to forehead
+3. Take prescribed migraine medication
+4. Try relaxation techniques""",
+                "precautions": [
+                    "Identify and avoid triggers (certain foods, stress, etc.)",
+                    "Maintain regular sleep schedule",
+                    "Stay hydrated",
+                    "Consider preventive medications if frequent"
+                ]
+            }
+        }
+    
+    def predict_disease(self, symptoms):
+        symptoms = symptoms.lower()
+        matched = []
+        
+        # Simple matching for demo (replace with actual model in production)
+        for disease, data in self.disease_db.items():
+            symptom_count = sum(1 for s in data["symptoms"] if s in symptoms)
+            if symptom_count >= 2:
+                matched.append((disease, symptom_count))
+        
+        matched.sort(key=lambda x: x[1], reverse=True)
+        
+        if matched:
+            return f"Possible conditions:\n" + "\n".join(
+                f"- {disease} ({count} matching symptoms)" 
+                for disease, count in matched[:3]  # Show top 3
+            )
+        
+        # Fallback to model if no matches
+        result = self.symptom_checker(symptoms)
+        return f"The model suggests this might be related to: {result[0]['label']} (confidence: {result[0]['score']:.2f})"
+    
+    def get_symptoms(self, disease):
+        disease = disease.lower()
+        if disease in self.disease_db:
+            return "Common symptoms:\n" + "\n".join(
+                f"- {symptom}" for symptom in self.disease_db[disease]["symptoms"]
+            )
+        
+        # Fallback to model
+        prompt = f"What are the common symptoms of {disease}?"
+        result = self.medical_qa(prompt, max_length=100)
+        return result[0]["generated_text"]
+    
+    def get_advice(self, condition):
+        condition = condition.lower()
+        if condition in self.disease_db:
+            data = self.disease_db[condition]
+            return (
+                "Medical Advice:\n" + data["advice"] + "\n\n" +
+                "Precautions:\n" + "\n".join(f"- {p}" for p in data["precautions"])
+            )
+        
+        # Fallback to model
+        prompt = f"What is the recommended medical advice and precautions for {condition}?"
+        result = self.medical_qa(prompt, max_length=200)
+        return result[0]["generated_text"]
+
+# Initialize assistant
+assistant = HealthAssistant()
+
+# Create Gradio interface
+with gr.Blocks(title="AI Health Assistant", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🤖 AI Health Assistant")
+    gr.Markdown("Describe your symptoms or ask about a disease to get information.")
+    
+    with gr.Tab("Diagnose from Symptoms"):
+        symptom_input = gr.Textbox(label="Describe your symptoms (e.g., headache, fever, cough)")
+        symptom_output = gr.Textbox(label="Possible Conditions", interactive=False)
+        symptom_button = gr.Button("Analyze Symptoms")
+    
+    with gr.Tab("Disease Information"):
+        disease_input = gr.Textbox(label="Enter a disease name")
+        disease_symptoms = gr.Textbox(label="Common Symptoms", interactive=False)
+        disease_advice = gr.Textbox(label="Medical Advice", interactive=False)
+        disease_button = gr.Button("Get Disease Info")
+    
+    # Event handlers
+    symptom_button.click(
+        fn=assistant.predict_disease,
+        inputs=symptom_input,
+        outputs=symptom_output
+    )
+    
+    disease_button.click(
+        fn=assistant.get_symptoms,
+        inputs=disease_input,
+        outputs=disease_symptoms
+    )
+    
+    disease_button.click(
+        fn=assistant.get_advice,
+        inputs=disease_input,
+        outputs=disease_advice
+    )
+
+    # Disclaimer
+    gr.Markdown("""
+    ## ⚠️ Important Disclaimer
+    This AI assistant provides general health information only and is not a substitute for professional medical advice. 
+    Always consult with a qualified healthcare provider for diagnosis and treatment.
+    """)
+
+# For Hugging Face Spaces
+demo.launch()