Create app.py

app.py

@@ -0,0 +1,19 @@
+import gradio as gr
+from fastembed import SparseTextEmbedding
+
+def sparseembed(docs):
+    model = SparseTextEmbedding(model_name="Qdrant/bm25")
+    embeddings = list(model.embed(docs))
+    return [(x.values, x.indicies) for x in embeddings]
+
+iface = gr.Interface(
+    fn=sparseembed,
+    inputs=[
+        gr.JSON(label="Docs (JSON array of objects)")
+    ],
+    outputs=gr.Dataframe(type="array", headers=["values", "indicies"]),
+    api_name="rerank"
+)
+
+if __name__ == "__main__":
+    iface.launch()