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

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    "# 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"
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   "source": [
    "%pip install boto3"
   ]
  },
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   "id": "282239c8-e03a-4abc-86c1-ca6120231a20",
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   "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",
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   "id": "19a46868-4bed-40cd-89ca-9813fbfda9cb",
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   "source": [
    "embeddings.embed_query(\"This is a content of the document\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf0349c4-6408-4342-8691-69276a388784",
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   "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\"])"
   ]
  }
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