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app.py

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+import os
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load IBM Granite model
+model_id = "ibm/granite-3b-instruct-v1"
+token = os.getenv("HF_TOKEN")  # Use Hugging Face Secrets
+tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=token)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.float32, use_auth_token=token)
+
+def query_granite(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, max_new_tokens=100)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Page functions
+def home():
+    with gr.Blocks() as demo:
+        gr.Markdown("# 🏥 Welcome to HealthAI")
+        gr.Markdown("Your intelligent healthcare assistant with real AI support.")
+    return demo
+
+def symptoms_app():
+    def identify(symptom):
+        return query_granite(f"What illness could cause: {symptom}?")
+    with gr.Blocks() as demo:
+        gr.Markdown("## 🩺 Symptom Identifier")
+        symptom = gr.Textbox(label="Enter your symptom")
+        output = gr.Textbox(label="AI Diagnosis")
+        btn = gr.Button("Analyze")
+        btn.click(identify, inputs=symptom, outputs=output)
+    return demo
+
+def remedies_app():
+    def get_remedies(issue):
+        return query_granite(f"What are home remedies for {issue}?")
+    with gr.Blocks() as demo:
+        gr.Markdown("## 🌿 Home Remedies")
+        issue = gr.Textbox(label="What are you suffering from?")
+        output = gr.Textbox(label="Suggested Remedy")
+        btn = gr.Button("Suggest")
+        btn.click(get_remedies, inputs=issue, outputs=output)
+    return demo
+
+def diet_app():
+    def suggest(goal):
+        return query_granite(f"Suggest a diet for: {goal}")
+    with gr.Blocks() as demo:
+        gr.Markdown("## 🥗 Diet Suggestions")
+        goal = gr.Textbox(label="Your health goal")
+        output = gr.Textbox(label="Diet Plan")
+        btn = gr.Button("Get Plan")
+        btn.click(suggest, inputs=goal, outputs=output)
+    return demo
+
+def mental_app():
+    def tip(topic):
+        return query_granite(f"Mental health advice about: {topic}")
+    with gr.Blocks() as demo:
+        gr.Markdown("## 🧠 Mental Wellness")
+        topic = gr.Textbox(label="Enter mental health topic")
+        output = gr.Textbox(label="Wellness Tip")
+        btn = gr.Button("Get Tip")
+        btn.click(tip, inputs=topic, outputs=output)
+    return demo
+
+def faqs_app():
+    with gr.Blocks() as demo:
+        gr.Markdown("## ❓ FAQs")
+        gr.Markdown("**Q1:** What is HealthAI?")
+        gr.Markdown("**A:** It's an AI assistant to help with health-related queries using IBM Granite model.")
+    return demo
+
+# Multi-page Gradio app
+pages = [
+    gr.Page(title="🏠 Home", path="/", block=home),
+    gr.Page(title="🩺 Symptoms", path="/symptoms", block=symptoms_app),
+    gr.Page(title="🌿 Remedies", path="/remedies", block=remedies_app),
+    gr.Page(title="🥗 Diet", path="/diet", block=diet_app),
+    gr.Page(title="🧠 Mental Wellness", path="/mental", block=mental_app),
+    gr.Page(title="❓ FAQs", path="/faqs", block=faqs_app),
+]
+
+app = gr.App(pages=pages)
+app.launch()

requirements.txt

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+gradio
+transformers
+torch
+accelerate