mirror of
https://github.com/hwchase17/langchain
synced 2024-10-31 15:20:26 +00:00
fdba711d28
Updated `integrations/embeddings`: fixed titles; added links, descriptions Updated `integrations/providers`.
102 lines
2.4 KiB
Plaintext
102 lines
2.4 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "markdown",
|
|
"id": "75e378f5-55d7-44b6-8e2e-6d7b8b171ec4",
|
|
"metadata": {},
|
|
"source": [
|
|
"# Bedrock\n",
|
|
"\n",
|
|
">[Amazon Bedrock](https://aws.amazon.com/bedrock/) is a fully managed service that makes FMs from leading AI startups and Amazon available via an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case.\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2dbe40fa-7c0b-4bcb-a712-230bf613a42f",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"%pip install boto3"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "282239c8-e03a-4abc-86c1-ca6120231a20",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from langchain.embeddings import BedrockEmbeddings\n",
|
|
"\n",
|
|
"embeddings = BedrockEmbeddings(\n",
|
|
" credentials_profile_name=\"bedrock-admin\", region_name=\"us-east-1\"\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "19a46868-4bed-40cd-89ca-9813fbfda9cb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"embeddings.embed_query(\"This is a content of the document\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "cf0349c4-6408-4342-8691-69276a388784",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"embeddings.embed_documents([\"This is a content of the document\", \"This is another document\"])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9f6b364d",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# async embed query\n",
|
|
"await embeddings.aembed_query(\"This is a content of the document\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c9240a5a",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# async embed documents\n",
|
|
"await embeddings.aembed_documents([\"This is a content of the document\", \"This is another document\"])"
|
|
]
|
|
}
|
|
],
|
|
"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": "3.10.12"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|