Create app.py

app.py

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+import streamlit as st
+from sentence_transformers import SentenceTransformer
+
+# Load the model
+model = SentenceTransformer('sentence-transformers/msmarco-distilbert-dot-v5')
+
+# Define the Streamlit app
+def main():
+    st.title("Text Embedding Generator")
+
+    # Get user input
+    text_input = st.text_area("Enter text to generate embeddings:", "")
+
+    if st.button("Generate Embedding"):
+        if text_input:
+            # Call the function to get the embedding
+            embedding = get_emb(text_input)
+
+            # Display the embedding
+            st.success("Embedding generated successfully:")
+            st.write(embedding)
+        else:
+            st.warning("Please enter text to generate embeddings.")
+
+# Function to get the embedding
+def get_emb(text):
+    text_emb = model.encode(text)
+    return text_emb
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()