add app and req

app.py

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+from transformers import ViTImageProcessor, ViTForImageClassification
+from PIL import Image
+import streamlit as st
+from groq import Groq
+
+client = Groq(
+    api_key="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",
+)
+
+# Streamlit app title
+st.title("Product Detection App")
+
+# File uploader for image input
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+
+    # Process the image and make predictions
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    predicted_class_idx = logits.argmax(-1).item()
+    predicted_class = model.config.id2label[predicted_class_idx]
+
+    # Display the predicted class
+    st.write(f"Predicted Class: {predicted_class}")
+
+    # Generate keywords using Groq
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "user",
+                "content": f"Generate a comma separated list of high-converting keywords for selling a {predicted_class}.",
+            }
+        ],
+        model="llama3-8b-8192",
+    )
+
+    # Display the generated keywords
+    st.write("Generated Keywords:")
+    st.write(chat_completion.choices[0].message.content)
+

requirements.txt

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+transformers
+Pillow
+streamlit
+groq