nomic: init pkg (#16853)

Co-authored-by: Lance Martin <lance@langchain.dev>
This commit is contained in:
Erick Friis
2024-01-31 16:46:35 -08:00
committed by GitHub
parent 2e5949b6f8
commit 17e886388b
24 changed files with 2179 additions and 0 deletions

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Nomic\n",
"\n",
"Nomic currently offers two products:\n",
"\n",
"- Atlas: their Visual Data Engine\n",
"- GPT4All: their Open Source Edge Language Model Ecosystem\n",
"\n",
"Currently, you can import their hosted [embedding model](/docs/integrations/text_embedding/nomic) as follows:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "y8ku6X96sebl"
},
"outputs": [],
"source": [
"from langchain_nomic import NomicEmbeddings"
]
}
],
"metadata": {
"colab": {
"provenance": []
},
"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": "3.10.11"
}
},
"nbformat": 4,
"nbformat_minor": 1
}

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{
"cells": [
{
"cell_type": "raw",
"id": "afaf8039",
"metadata": {},
"source": [
"---\n",
"sidebar_label: Nomic\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "e49f1e0d",
"metadata": {},
"source": [
"# NomicEmbeddings\n",
"\n",
"This notebook covers how to get started with Nomic embedding models.\n",
"\n",
"## Installation"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4c3bef91",
"metadata": {},
"outputs": [],
"source": [
"# install package\n",
"!pip install -U langchain-nomic"
]
},
{
"cell_type": "markdown",
"id": "2b4f3e15",
"metadata": {},
"source": [
"## Environment Setup\n",
"\n",
"Make sure to set the following environment variables:\n",
"\n",
"- `NOMIC_API_KEY`\n",
"\n",
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "62e0dbc3",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain_nomic.embeddings import NomicEmbeddings\n",
"\n",
"embeddings = NomicEmbeddings(model=\"nomic-embed-text-v1\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "12fcfb4b",
"metadata": {},
"outputs": [],
"source": [
"embeddings.embed_query(\"My query to look up\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1f2e6104",
"metadata": {},
"outputs": [],
"source": [
"embeddings.embed_documents(\n",
" [\"This is a content of the document\", \"This is another document\"]\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "46739f68",
"metadata": {},
"outputs": [],
"source": [
"# async embed query\n",
"await embeddings.aembed_query(\"My query to look up\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e48632ea",
"metadata": {},
"outputs": [],
"source": [
"# async embed documents\n",
"await embeddings.aembed_documents(\n",
" [\"This is a content of the document\", \"This is another document\"]\n",
")"
]
}
],
"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": "3.10.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}