Create app.py

app.py

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+"""
+Basic similarity search example. Used in the original txtai demo.
+"""
+
+import os
+
+import streamlit as st
+
+from txtai.embeddings import Embeddings
+
+
+class Application:
+    """
+    Main application.
+    """
+
+    def __init__(self):
+        """
+        Creates a new application.
+        """
+
+        # Create embeddings model, backed by sentence-transformers & transformers
+        self.embeddings = Embeddings({"path": "sentence-transformers/nli-mpnet-base-v2"})
+
+    def run(self):
+        """
+        Runs a Streamlit application.
+        """
+
+        st.title("Similarity Search")
+        st.markdown("This application runs a basic similarity search that identifies the best matching row for a query.")
+
+        data = [
+            "US tops 5 million confirmed virus cases",
+            "Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg",
+            "Beijing mobilises invasion craft along coast as Taiwan tensions escalate",
+            "The National Park Service warns against sacrificing slower friends in a bear attack",
+            "Maine man wins $1M from $25 lottery ticket",
+            "Make huge profits without work, earn up to $100,000 a day",
+        ]
+
+        data = st.text_area("Data", value="\n".join(data))
+        query = st.text_input("Query")
+
+        data = data.split("\n")
+
+        if query:
+            # Get index of best section that best matches query
+            uid = self.embeddings.similarity(query, data)[0][0]
+            st.write(data[uid])
+
+@st.cache(allow_output_mutation=True)
+def create():
+    """
+    Creates and caches a Streamlit application.
+
+    Returns:
+        Application
+    """
+
+    return Application()
+
+
+if __name__ == "__main__":
+    os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+    # Create and run application
+    app = create()
+    app.run()