langchain/docs/modules/models/text_embedding/examples/azureopenai.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "c3852491",
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"metadata": {},
"source": [
"# AzureOpenAI\n",
"\n",
"Let's load the OpenAI Embedding class with environment variables set to indicate to use Azure endpoints."
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1b40f827",
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"metadata": {},
"outputs": [],
"source": [
"# set the environment variables needed for openai package to know to reach out to azure\n",
"import os\n",
"\n",
"os.environ[\"OPENAI_API_TYPE\"] = \"azure\"\n",
"os.environ[\"OPENAI_API_BASE\"] = \"https://<your-endpoint.openai.azure.com/\"\n",
"os.environ[\"OPENAI_API_KEY\"] = \"your AzureOpenAI key\"\n",
"os.environ[\"OPENAI_API_VERSION\"] = \"2023-03-15-preview\""
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bb36d16c",
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"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings import OpenAIEmbeddings\n",
"\n",
"embeddings = OpenAIEmbeddings(model=\"your-embeddings-deployment-name\")"
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "228abcbb",
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"metadata": {},
"outputs": [],
"source": [
"text = \"This is a test document.\""
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "60dd7fad",
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"metadata": {},
"outputs": [],
"source": [
"query_result = embeddings.embed_query(text)"
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "83bc1a72",
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"metadata": {},
"outputs": [],
"source": [
"doc_result = embeddings.embed_documents([text])"
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]
},
{
"cell_type": "code",
"execution_count": null,
"id": "aaad49f8",
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"metadata": {},
"outputs": [],
"source": []
}
],
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"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
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"file_extension": ".py",
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}
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"nbformat": 4,
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}