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

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{
"cells": [
{
"cell_type": "markdown",
"id": "42f76e43",
"metadata": {},
"source": [
"# Cohere\n",
"\n",
"Let's load the Cohere Embedding class."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "6b82f59f",
"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings import CohereEmbeddings"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "26895c60",
"metadata": {},
"outputs": [],
"source": [
"embeddings = CohereEmbeddings(cohere_api_key=cohere_api_key)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "eea52814",
"metadata": {},
"outputs": [],
"source": [
"text = \"This is a test document.\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "fbe167bf",
"metadata": {},
"outputs": [],
"source": [
"query_result = embeddings.embed_query(text)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "38ad3b20",
"metadata": {},
"outputs": [],
"source": [
"doc_result = embeddings.embed_documents([text])"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "aaad49f8",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
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},
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"file_extension": ".py",
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"version": "3.9.1"
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"vscode": {
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