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import gradio as gr
from transformers import pipeline
class HealthAssistant:
def __init__(self):
# Using a medical-specific model
self.symptom_checker = pipeline(
"text-classification",
model="palaksharma/bert-base-uncased-medical"
)
# Disease mapping for readable outputs
self.label_mapping = {
"LABEL_0": "Common Cold",
"LABEL_1": "Influenza (Flu)",
"LABEL_2": "Migraine",
"LABEL_3": "Allergic Rhinitis",
"LABEL_4": "Gastroenteritis"
}
# Enhanced knowledge base
self.disease_info = {
"Common Cold": {
"symptoms": ["runny nose", "sneezing", "congestion", "sore throat"],
"advice": "Rest, hydration, OTC cold medicines",
"precautions": ["Hand hygiene", "Disinfect surfaces"]
},
"Influenza (Flu)": {
"symptoms": ["fever", "cough", "body aches", "fatigue"],
"advice": "Antivirals if prescribed, rest, fluids",
"precautions": ["Flu vaccine", "Avoid crowds during outbreaks"]
}
}
def predict_disease(self, symptoms):
try:
# Get model prediction
result = self.symptom_checker(symptoms)
# Map label to readable name
label = result[0]['label']
disease_name = self.label_mapping.get(label, "Unknown Condition")
confidence = result[0]['score']
# Get additional info if available
info = self.disease_info.get(disease_name, {})
response = f"Possible condition: {disease_name} (confidence: {confidence:.2f})\n\n"
if info:
response += f"Common symptoms:\n- " + "\n- ".join(info.get('symptoms', [])) + "\n\n"
response += f"Recommended actions:\n{info.get('advice', 'Consult a doctor')}"
return response
except Exception as e:
return f"Error analyzing symptoms: {str(e)}"
def create_interface():
assistant = HealthAssistant()
with gr.Blocks(title="Medical Symptom Checker", theme=gr.themes.Soft()) as demo:
gr.Markdown("# 🏥 AI Symptom Checker")
with gr.Row():
with gr.Column():
symptoms = gr.Textbox(
label="Describe your symptoms",
placeholder="E.g. headache, fever, cough...",
lines=3
)
analyze_btn = gr.Button("Analyze Symptoms")
with gr.Column():
output = gr.Textbox(
label="Analysis Result",
interactive=False,
lines=10
)
# Examples
gr.Examples(
examples=[
["headache, fever, body aches"],
["runny nose, sneezing, sore throat"],
["nausea, vomiting, diarrhea"]
],
inputs=symptoms
)
analyze_btn.click(
fn=assistant.predict_disease,
inputs=symptoms,
outputs=output
)
gr.Markdown("""
## ⚠️ Important Disclaimer
This AI tool provides general information only and is not a substitute for professional medical advice.
Always consult with a qualified healthcare provider for diagnosis and treatment.
""")
return demo
if __name__ == "__main__":
demo = create_interface()
demo.launch() |