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HealthAI combines advanced AI with holistic health knowledge, making healthcare accessible and user-friendly. Whether you’re curious about your symptoms or looking for natural treatment options, HealthAI is your go-to digital health assistant.

README.md

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----
-title: HealthAi
-emoji: 🏆
-colorFrom: yellow
-colorTo: gray
-sdk: gradio
-sdk_version: 5.33.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: HealthAI combines advanced AI with holistic health knowledge
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🤖 HealthAI
+
+HealthAI is an intelligent healthcare assistant powered by IBM Granite-3B-Instruct model. It offers:
+
+- 🩺 Disease prediction from symptoms
+- 🌿 Home remedy suggestions
+- 🛡️ Preventive health advice
+- 🥗 Diet recommendations
+- 🆘 First aid instructions
+
+## 🔧 How to Run
+
+1. Install dependencies:
+```
+pip install -r requirements.txt
+```
+
+2. Run the app:
+```
+python app.py
+```
+
+3. Or deploy to Hugging Face with:
+```
+gradio deploy
+```
+
+## 💡 Powered by:
+- IBM Granite 3.3B model
+- Hugging Face Transformers
+- Gradio for UI

app.py

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+
+# ✅ Install dependencies first
+# pip install transformers accelerate gradio translate
+
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import gradio as gr
+from translate import Translator
+
+# Load IBM Granite model
+model_id = "ibm-granite/granite-3.3-2b-instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Translate helpers
+def translate_to_english(text, lang_code):
+    if lang_code != "en":
+        translator = Translator(from_lang=lang_code, to_lang="en")
+        return translator.translate(text)
+    return text
+
+def translate_to_user_lang(text, lang_code):
+    if lang_code != "en":
+        translator = Translator(from_lang="en", to_lang=lang_code)
+        return translator.translate(text)
+    return text
+
+# Core functions
+def identify_disease(symptoms, lang_code="en"):
+    symptoms_en = translate_to_english(symptoms, lang_code)
+    prompt = f"You are a medical assistant. A user reports these symptoms: {symptoms_en}. What possible disease or condition could this indicate?"
+    output = generator(prompt, max_new_tokens=150, do_sample=True)[0]["generated_text"]
+    result = output[len(prompt):].strip()
+    return translate_to_user_lang(result, lang_code)
+
+def suggest_remedy(disease, lang_code="en"):
+    disease_en = translate_to_english(disease, lang_code)
+    prompt = f"Suggest effective natural home remedies for treating {disease_en}."
+    output = generator(prompt, max_new_tokens=150, do_sample=True)[0]["generated_text"]
+    result = output[len(prompt):].strip()
+    return translate_to_user_lang(result, lang_code)
+
+def preventive_measures(disease, lang_code="en"):
+    disease_en = translate_to_english(disease, lang_code)
+    prompt = f"What are the best preventive measures to avoid {disease_en}?"
+    output = generator(prompt, max_new_tokens=150, do_sample=True)[0]["generated_text"]
+    result = output[len(prompt):].strip()
+    return translate_to_user_lang(result, lang_code)
+
+def diet_recommendations(disease, lang_code="en"):
+    disease_en = translate_to_english(disease, lang_code)
+    prompt = f"Suggest a healthy diet plan for someone suffering from {disease_en}."
+    output = generator(prompt, max_new_tokens=150, do_sample=True)[0]["generated_text"]
+    result = output[len(prompt):].strip()
+    return translate_to_user_lang(result, lang_code)
+
+def first_aid_advice(condition, lang_code="en"):
+    condition_en = translate_to_english(condition, lang_code)
+    prompt = f"What first aid steps should be taken immediately for {condition_en}?"
+    output = generator(prompt, max_new_tokens=150, do_sample=True)[0]["generated_text"]
+    result = output[len(prompt):].strip()
+    return translate_to_user_lang(result, lang_code)
+
+# Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("## 🤖 HealthAI - Your Intelligent Healthcare Assistant")
+
+    with gr.Tab("🩺 Symptoms Identifier"):
+        symptoms_input = gr.Textbox(label="Enter your symptoms")
+        disease_output = gr.Textbox(label="Predicted Disease")
+        btn1 = gr.Button("Identify Disease")
+        btn1.click(fn=identify_disease, inputs=symptoms_input, outputs=disease_output)
+
+    with gr.Tab("🌿 Home Remedies"):
+        disease_input = gr.Textbox(label="Enter disease name")
+        remedy_output = gr.Textbox(label="Suggested Home Remedy")
+        btn2 = gr.Button("Get Remedy")
+        btn2.click(fn=suggest_remedy, inputs=disease_input, outputs=remedy_output)
+
+    with gr.Tab("🛡️ Preventive Measures"):
+        prevent_input = gr.Textbox(label="Enter disease name")
+        prevent_output = gr.Textbox(label="Preventive Measures")
+        btn3 = gr.Button("Get Advice")
+        btn3.click(fn=preventive_measures, inputs=prevent_input, outputs=prevent_output)
+
+    with gr.Tab("🥗 Diet Recommendations"):
+        diet_input = gr.Textbox(label="Enter disease name")
+        diet_output = gr.Textbox(label="Recommended Diet")
+        btn4 = gr.Button("Get Diet Plan")
+        btn4.click(fn=diet_recommendations, inputs=diet_input, outputs=diet_output)
+
+    with gr.Tab("🆘 First Aid Help"):
+        first_aid_input = gr.Textbox(label="Enter medical condition or emergency")
+        first_aid_output = gr.Textbox(label="First Aid Advice")
+        btn5 = gr.Button("Get First Aid")
+        btn5.click(fn=first_aid_advice, inputs=first_aid_input, outputs=first_aid_output)
+
+demo.launch()

requirements.txt

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+transformers
+accelerate
+gradio
+translate
+torch