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Update elastic search cookbook to use latest API #1899

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Merged
merged 2 commits into from
Jun 16, 2025
Merged

Update elastic search cookbook to use latest API #1899

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12f5e2b
Update elastic search cookbook to use responses API
robtinn Jun 13, 2025
6e70086
Change registry to only have embeddings tag
robtinn Jun 16, 2025
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28 changes: 12 additions & 16 deletions examples/vector_databases/elasticsearch/elasticsearch-semantic-search.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -37,14 +37,14 @@
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "8c304b93",
"metadata": {},
"outputs": [],
"source": [
"# install packages\n",
"\n",
"!python3 -m pip install -qU openai pandas wget elasticsearch\n",
"! python3 -m pip install -qU openai pandas wget elasticsearch\n",
"\n",
"# import modules\n",
"\n",
Expand All @@ -54,7 +54,7 @@
"import zipfile\n",
"import pandas as pd\n",
"import json\n",
"import openai"
"from openai import OpenAI"
]
},
{
Expand Down Expand Up @@ -321,25 +321,21 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": null,
"id": "57385c69",
"metadata": {},
"outputs": [],
"source": [
"# Get OpenAI API key\n",
"OPENAI_API_KEY = getpass(\"Enter OpenAI API key\")\n",
"\n",
"# Set API key\n",
"openai.api_key = OPENAI_API_KEY\n",
"\n",
"# Define model\n",
"EMBEDDING_MODEL = \"text-embedding-3-small\"\n",
"# Create OpenAI client\n",
"openai_client = OpenAI()\n",
"\n",
"# Define question\n",
"question = 'Is the Atlantic the biggest ocean in the world?'\n",
"\n",
"# Create embedding\n",
"question_embedding = openai.Embedding.create(input=question, model=EMBEDDING_MODEL)\n"
"question_embedding = openai_client.embeddings.create(\n",
" input=question,\n",
" model=\"text-embedding-3-small\"\n",
")"
]
},
{
Expand Down Expand Up @@ -383,7 +379,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"id": "fc834fdd",
"metadata": {},
"outputs": [
Expand Down Expand Up @@ -764,7 +760,7 @@
" index = \"wikipedia_vector_index\",\n",
" knn={\n",
" \"field\": \"content_vector\",\n",
" \"query_vector\": question_embedding[\"data\"][0][\"embedding\"],\n",
" \"query_vector\": question_embedding.data[0].embedding,\n",
" \"k\": 10,\n",
" \"num_candidates\": 100\n",
" }\n",
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4 changes: 2 additions & 2 deletions registry.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -861,12 +861,12 @@

- title: Semantic search using Elasticsearch and OpenAI
path: examples/vector_databases/elasticsearch/elasticsearch-semantic-search.ipynb
date: 2023-08-29
date: 2025-06-13
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wouldn't change it

authors:
- leemthompo
tags:
- embeddings
- completions
- responses

- title: Using Hologres as a vector database for OpenAI embeddings
path: >-
Expand Down