wip

README.md

@@ -1,13 +1,14 @@
 ---
 title: Opensearchspace
-emoji: 😻
-colorFrom: gray
-colorTo: yellow
-sdk: streamlit
-sdk_version: 1.10.0
+emoji: ⚡
+colorFrom: green
+colorTo: green
+sdk: gradio
+sdk_version: 3.3.1
 app_file: app.py
 pinned: false
 license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+

app.py

@@ -0,0 +1,37 @@
+import gradio as gr
+from autogluon.multimodal import MultiModalPredictor
+
+
+def text_embedding(query: str):
+    model_name = "sentence-transformers/all-MiniLM-L6-v2"
+
+    predictor = MultiModalPredictor(
+        pipeline="feature_extraction",
+        hyperparameters={
+            "model.hf_text.checkpoint_name": model_name
+        }
+    )
+    query_embedding = predictor.extract_embedding([query])
+    return query_embedding["0"]   
+
+
+def main():
+    with gr.Blocks(title="OpenSearch Demo") as demo:
+        gr.Markdown("# Text Embedding for Search Queries")
+        gr.Markdown("Ask an open question!")
+        with gr.Row():
+            inp = gr.Textbox(show_label=False)
+        with gr.Row():    
+            btn = gr.Button("Generate Embedding")
+        with gr.Row():
+            out = gr.DataFrame(label="Embedding", show_label=True)
+        
+        btn.click(fn=text_embedding, inputs=inp, outputs=out)  
+    
+    demo.launch()   
+
+
+if __name__ == "__main__":
+    main()
+    
+    

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+wheel
+setuptools
+git+https://github.com/awslabs/autogluon.git@master#subdirectory=autogluon