Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+import replicate
+import ast
+import requests
+import io
+
+
+API_URL = "https://api-inference.huggingface.co/models/ZB-Tech/Text-to-Image"
+
+def query(payload):
+    response = requests.post(API_URL, json=payload)
+    return response.content
+
+st.header("Mirror: AI Stylist")
+uploaded_file = st.file_uploader("Upload Your Photo", type=["jpg", "jpeg", "png"])
+image = ""
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption="Uploaded Image.", use_column_width=True)
+
+    st.markdown("Generating Fashion Accessories For You...")
+    with st.spinner("Loading..."):
+        prompt = '''
+                You are a personal stylist recommending fashion advice and clothing combinations.
+                Use the person's dressing style, colour of clothes and appearance from the given
+                image to generate three fashion accessories according to the gender of the person 
+                in an array format.
+                Examples:
+                    Example 1: ["accessory1 name with speicific detail"]
+                '''
+        input = {
+            "image":  uploaded_file,
+            "prompt": prompt
+        }
+
+        output = replicate.run(
+            "yorickvp/llava-13b:b5f6212d032508382d61ff00469ddda3e32fd8a0e75dc39d8a4191bb742157fb",
+            input=input,
+        )
+        arr = "".join(output)
+        output = ast.literal_eval(arr)
+
+        for item in output:
+            image_bytes = query({
+                "inputs": item,
+            })
+
+            image = Image.open(io.BytesIO(image_bytes))
+            st.image(image, caption=item, use_column_width=True)
+    st.success("Generated Fashion Accessories!")
+