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- added missed integration to `docs/ecosystem/integrations/` - updated notebooks to consistent format: changed titles, file names; added descriptions #### Who can review? @hwchase17 @dev2049
107 lines
2.3 KiB
Plaintext
107 lines
2.3 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "c3852491",
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"metadata": {},
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"source": [
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"# Azure OpenAI\n",
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"\n",
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"Let's load the OpenAI Embedding class with environment variables set to indicate to use Azure endpoints."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1b40f827",
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"metadata": {},
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"outputs": [],
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"source": [
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"# set the environment variables needed for openai package to know to reach out to azure\n",
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"import os\n",
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"\n",
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"os.environ[\"OPENAI_API_TYPE\"] = \"azure\"\n",
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"os.environ[\"OPENAI_API_BASE\"] = \"https://<your-endpoint.openai.azure.com/\"\n",
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"os.environ[\"OPENAI_API_KEY\"] = \"your AzureOpenAI key\"\n",
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"os.environ[\"OPENAI_API_VERSION\"] = \"2023-03-15-preview\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bb36d16c",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.embeddings import OpenAIEmbeddings\n",
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"\n",
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"embeddings = OpenAIEmbeddings(deployment=\"your-embeddings-deployment-name\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "228abcbb",
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"metadata": {},
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"outputs": [],
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"source": [
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"text = \"This is a test document.\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "60dd7fad",
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"metadata": {},
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"outputs": [],
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"source": [
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"query_result = embeddings.embed_query(text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "83bc1a72",
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"metadata": {},
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"outputs": [],
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"source": [
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"doc_result = embeddings.embed_documents([text])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aaad49f8",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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},
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"vscode": {
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"interpreter": {
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"hash": "7377c2ccc78bc62c2683122d48c8cd1fb85a53850a1b1fc29736ed39852c9885"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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