| import os | |
| import requests | |
| import gradio as gr | |
| API_URL = "https://api-inference.huggingface.co/models/sunnwei/ClinicalBERT-finetuned-disease" | |
| HF_API_TOKEN = os.environ.get("HF_API_TOKEN") | |
| headers = {"Authorization": f"Bearer {HF_API_TOKEN}"} | |
| disease_symptoms = { | |
| "flu": ["fever", "cough", "sore throat", "fatigue"], | |
| "diabetes": ["increased thirst", "frequent urination", "weight loss", "fatigue"], | |
| "covid-19": ["fever", "dry cough", "loss of taste or smell", "difficulty breathing"] | |
| } | |
| medical_guidelines = { | |
| "flu": "Drink warm fluids, rest, and take antiviral medication if severe.", | |
| "diabetes": "Monitor blood sugar, maintain a healthy diet, and exercise regularly.", | |
| "covid-19": "Isolate, monitor oxygen levels, and seek medical attention if necessary." | |
| } | |
| def identify_disease(symptoms): | |
| payload = {"inputs": symptoms} | |
| try: | |
| response = requests.post(API_URL, headers=headers, json=payload, timeout=10) | |
| results = response.json() | |
| if isinstance(results, list) and "label" in results[0]: | |
| return results[0]["label"].lower() | |
| else: | |
| return "unknown" | |
| except Exception as e: | |
| return "Error contacting API." | |
| def get_symptoms(disease): | |
| return disease_symptoms.get(disease.lower(), "No data available.") | |
| def provide_assistance(disease): | |
| return medical_guidelines.get(disease.lower(), "Consult a healthcare professional.") | |
| def assistant(user_input): | |
| user_input = user_input.lower() | |
| if user_input in disease_symptoms: | |
| symptoms = get_symptoms(user_input) | |
| advice = provide_assistance(user_input) | |
| return f"Disease: {user_input.capitalize()}\nSymptoms: {', '.join(symptoms)}\nAdvice: {advice}" | |
| else: | |
| disease = identify_disease(user_input) | |
| if disease == "unknown": | |
| return "Sorry, could not identify the disease. Please consult a healthcare provider." | |
| symptoms = get_symptoms(disease) | |
| advice = provide_assistance(disease) | |
| return f"Predicted Disease: {disease.capitalize()}\nSymptoms: {', '.join(symptoms) if isinstance(symptoms, list) else symptoms}\nAdvice: {advice}" | |
| demo = gr.Interface( | |
| fn=assistant, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter your symptoms or disease name here..."), | |
| outputs="text", | |
| title="AI Health Assistant" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |