Create app.py

app.py

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+import os
+import torch
+import streamlit as st
+from PIL import Image
+from transformers import AutoModelForImageClassification, AutoImageProcessor
+from groq import Groq
+
+# Set page config
+st.set_page_config(page_title="DermaBot - AI Skin Disease Detector", page_icon="🩺", layout="wide")
+
+# Load model and processor
+MODEL_NAME = "Jayanth2002/dinov2-base-finetuned-SkinDisease"
+DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
+
+model = AutoModelForImageClassification.from_pretrained(MODEL_NAME).to(DEVICE)
+processor = AutoImageProcessor.from_pretrained(MODEL_NAME)
+
+# Set up the Groq API key (replace with your actual key or use an environment variable)
+GROQ_API_KEY = os.getenv("GROQ_API_KEY", "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")  
+client = Groq(api_key=GROQ_API_KEY)
+
+# Function to predict skin disease
+def predict_skin_disease(image):
+    image = image.convert("RGB")
+    inputs = processor(images=image, return_tensors="pt").to(DEVICE)
+
+    with torch.no_grad():
+        outputs = model(**inputs)
+
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    predicted_label = model.config.id2label[predicted_class_idx]
+    
+    return predicted_label
+
+# Function to get disease details from Groq API
+def get_disease_info(disease_name):
+    prompt = f"Provide a detailed explanation about the skin disease '{disease_name}', including description of disease, causes, precausions, risk and treatment options."
+
+    chat_completion = client.chat.completions.create(
+        messages=[{"role": "user", "content": prompt}],
+        model="llama-3.3-70b-versatile",
+    )
+
+    return chat_completion.choices[0].message.content
+
+# Function to handle chatbot queries
+def chatbot_response(disease_name, user_query):
+    prompt = f"The detected skin disease is '{disease_name}'. {user_query}"
+    
+    chat_completion = client.chat.completions.create(
+        messages=[{"role": "user", "content": prompt}],
+        model="llama-3.3-70b-versatile",
+    )
+
+    return chat_completion.choices[0].message.content
+
+# Streamlit UI
+st.image("https://huggingface.co/spaces/your-huggingface-space/logo.png", width=200)
+st.title("🩺 DermaBot - AI Skin Disease Detector")
+st.write("Upload an image of a skin condition to get a diagnosis and ask questions about it.")
+
+# Upload image section
+uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if uploaded_image:
+    image = Image.open(uploaded_image)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    if st.button("Detect Disease"):
+        with st.spinner("Analyzing..."):
+            disease_name = predict_skin_disease(image)
+            disease_info = get_disease_info(disease_name)
+            st.success(f"**Detected Disease:** {disease_name}")
+            st.write(f"**Details:** {disease_info}")
+
+# Chatbot section
+st.subheader("💬 Ask DermaBot")
+user_query = st.text_input("Ask about the detected disease:")
+
+if st.button("Ask"):
+    if uploaded_image:
+        with st.spinner("Thinking..."):
+            response = chatbot_response(disease_name, user_query)
+            st.write(response)
+    else:
+        st.warning("Please upload an image first.")
+
+st.markdown("---")
+st.write("🔍 Powered by **AI & Groq API** | © 2025 DermaBot")
+