langchain/docs/extras/integrations/text_embedding/cohere.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "42f76e43",
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"metadata": {},
"source": [
"# Cohere\n",
"\n",
"Let's load the Cohere Embedding class."
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]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "6b82f59f",
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"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings import CohereEmbeddings"
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]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "26895c60",
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"metadata": {},
"outputs": [],
"source": [
"embeddings = CohereEmbeddings(cohere_api_key=cohere_api_key)"
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]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "eea52814",
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"metadata": {},
"outputs": [],
"source": [
"text = \"This is a test document.\""
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]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "fbe167bf",
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"metadata": {},
"outputs": [],
"source": [
"query_result = embeddings.embed_query(text)"
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]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "38ad3b20",
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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": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.1"
},
"vscode": {
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}
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}
},
"nbformat": 4,
"nbformat_minor": 5
}