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add code snippet for each example (#141)

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<img width="1937" alt="image"
src="https://github.com/lancedb/lancedb/assets/759245/4ee52e4a-5955-47c2-9ffe-84d1bc0062ff">

---------

Co-authored-by: Chang She <chang@lancedb.com>
This commit is contained in:
Chang She
2023-06-02 21:27:02 -07:00
committed by GitHub
parent 12ec29f55b
commit bfa90b35ee
2 changed files with 45 additions and 16 deletions
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2
.gitignore vendored
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@@ -15,7 +15,7 @@ site
python/build
python/dist
notebooks/.ipynb_checkpoints
**/.ipynb_checkpoints
**/.hypothesis

59
docs/src/notebooks/multimodal_search.ipynb
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@@ -25,7 +25,7 @@
},
{
"cell_type": "code",
"execution_count": 60,
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -81,7 +81,7 @@
},
{
"cell_type": "code",
"execution_count": 62,
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
@@ -98,7 +98,7 @@
},
{
"cell_type": "code",
"execution_count": 63,
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
@@ -125,20 +125,41 @@
},
{
"cell_type": "code",
"execution_count": 64,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def find_image_vectors(query):\n",
" emb = embed_func(query)\n",
" return _extract(tbl.search(emb).limit(9).to_df())\n",
" code = (\n",
" \"import lancedb\\n\"\n",
" \"db = lancedb.connect('~/datasets/demo')\\n\"\n",
" \"tbl = db.open_table('diffusiondb')\\n\\n\"\n",
" f\"embedding = embed_func('{query}')\\n\"\n",
" \"tbl.search(embedding).limit(9).to_df()\"\n",
" )\n",
" return (_extract(tbl.search(emb).limit(9).to_df()), code)\n",
"\n",
"def find_image_keywords(query):\n",
" return _extract(tbl.search(query).limit(9).to_df())\n",
" code = (\n",
" \"import lancedb\\n\"\n",
" \"db = lancedb.connect('~/datasets/demo')\\n\"\n",
" \"tbl = db.open_table('diffusiondb')\\n\\n\"\n",
" f\"tbl.search('{query}').limit(9).to_df()\"\n",
" )\n",
" return (_extract(tbl.search(query).limit(9).to_df()), code)\n",
"\n",
"def find_image_sql(query):\n",
" code = (\n",
" \"import lancedb\\n\"\n",
" \"import duckdb\\n\"\n",
" \"db = lancedb.connect('~/datasets/demo')\\n\"\n",
" \"tbl = db.open_table('diffusiondb')\\n\\n\"\n",
" \"diffusiondb = tbl.to_lance()\\n\"\n",
" f\"duckdb.sql('{query}').to_df()\"\n",
" ) \n",
" diffusiondb = tbl.to_lance()\n",
" return _extract(duckdb.query(query).to_df())\n",
" return (_extract(duckdb.sql(query).to_df()), code)\n",
"\n",
"def _extract(df):\n",
" image_col = \"image\"\n",
@@ -154,14 +175,14 @@
},
{
"cell_type": "code",
"execution_count": 65,
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7867\n",
"Running on local URL: http://127.0.0.1:7881\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
@@ -169,7 +190,7 @@
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7867/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
"<div><iframe src=\"http://127.0.0.1:7881/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
@@ -182,7 +203,7 @@
"data": {
"text/plain": []
},
"execution_count": 65,
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
@@ -192,7 +213,6 @@
"\n",
"\n",
"with gr.Blocks() as demo:\n",
"\n",
" with gr.Row():\n",
" with gr.Tab(\"Embeddings\"):\n",
" vector_query = gr.Textbox(value=\"portraits of a person\", show_label=False)\n",
@@ -204,16 +224,25 @@
" sql_query = gr.Textbox(value=\"SELECT * from diffusiondb WHERE image_nsfw >= 2 LIMIT 9\", show_label=False)\n",
" b3 = gr.Button(\"Submit\")\n",
" with gr.Row():\n",
" code = gr.Code(label=\"Code\", language=\"python\")\n",
" with gr.Row():\n",
" gallery = gr.Gallery(\n",
" label=\"Found images\", show_label=False, elem_id=\"gallery\"\n",
" ).style(columns=[3], rows=[3], object_fit=\"contain\", height=\"auto\") \n",
" \n",
" b1.click(find_image_vectors, inputs=vector_query, outputs=gallery)\n",
" b2.click(find_image_keywords, inputs=keyword_query, outputs=gallery)\n",
" b3.click(find_image_sql, inputs=sql_query, outputs=gallery)\n",
" b1.click(find_image_vectors, inputs=vector_query, outputs=[gallery, code])\n",
" b2.click(find_image_keywords, inputs=keyword_query, outputs=[gallery, code])\n",
" b3.click(find_image_sql, inputs=sql_query, outputs=[gallery, code])\n",
" \n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {