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Erick Friis
2024-01-23 17:43:06 -07:00
parent 40e85224a8
commit fbe6a5f38f
5 changed files with 7 additions and 422 deletions
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11
libs/partners/nomic/docs/provider.ipynb → docs/docs/integrations/providers/nomic.ipynb
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@@ -6,7 +6,12 @@
"source": [
"# Nomic\n",
"\n",
"Nomic is a platform that offers..."
"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:"
]
},
{
@@ -17,9 +22,7 @@
},
"outputs": [],
"source": [
"from langchain_nomic.chat_models import NomicChat\n",
"from langchain_nomic.llms import NomicLLM\n",
"from langchain_nomic.vectorstores import NomicVectorStore"
"from langchain_nomic import NomicEmbeddings"
]
}
],

97
libs/partners/nomic/docs/chat.ipynb
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@@ -1,97 +0,0 @@
{
"cells": [
{
"cell_type": "raw",
"id": "afaf8039",
"metadata": {},
"source": [
"---\n",
"sidebar_label: Nomic\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "e49f1e0d",
"metadata": {},
"source": [
"# ChatNomic\n",
"\n",
"This notebook covers how to get started with Nomic chat 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",
"- TODO: fill out relevant environment variables or secrets\n",
"\n",
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "62e0dbc3",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain_nomic.chat_models import ChatNomic\n",
"from langchain_core.prompts import ChatPromptTemplate\n",
"\n",
"chat = ChatNomic()\n",
"\n",
"prompt = ChatPromptTemplate.from_messages(\n",
" [\n",
" (\"system\", \"You are a helpful assistant that translates English to French.\"),\n",
" (\"human\", \"Translate this sentence from English to French. {english_text}.\"),\n",
" ]\n",
")\n",
"\n",
"chain = prompt | chat\n",
"chain.invoke({\"english_text\": \"Hello, how are you?\"})"
]
}
],
"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
}

102
libs/partners/nomic/docs/llms.ipynb
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@@ -1,102 +0,0 @@
{
"cells": [
{
"cell_type": "raw",
"id": "67db2992",
"metadata": {},
"source": [
"---\n",
"sidebar_label: Nomic\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "9597802c",
"metadata": {},
"source": [
"# NomicLLM\n",
"\n",
"This example goes over how to use LangChain to interact with `Nomic` models.\n",
"\n",
"## Installation"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "59c710c4",
"metadata": {},
"outputs": [],
"source": [
"# install package\n",
"!pip install -U langchain-nomic"
]
},
{
"cell_type": "markdown",
"id": "0ee90032",
"metadata": {},
"source": [
"## Environment Setup\n",
"\n",
"Make sure to set the following environment variables:\n",
"\n",
"- TODO: fill out relevant environment variables or secrets\n",
"\n",
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "035dea0f",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_nomic.llms import NomicLLM\n",
"\n",
"template = \"\"\"Question: {question}\n",
"\n",
"Answer: Let's think step by step.\"\"\"\n",
"\n",
"prompt = PromptTemplate.from_string(template)\n",
"\n",
"model = NomicLLM()\n",
"\n",
"chain = prompt | model\n",
"\n",
"chain.invoke({\"question\": \"What is LangChain?\"})"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.11.1 64-bit",
"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": "3.9.7"
},
"vscode": {
"interpreter": {
"hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}

132
libs/partners/nomic/docs/text_embedding.ipynb
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@@ -1,132 +0,0 @@
{
"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",
"- TODO: fill out relevant environment variables or secrets\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()"
]
},
{
"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
}

87
libs/partners/nomic/docs/vectorstores.ipynb
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@@ -1,87 +0,0 @@
{
"cells": [
{
"cell_type": "raw",
"id": "1957f5cb",
"metadata": {},
"source": [
"---\n",
"sidebar_label: Nomic\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "ef1f0986",
"metadata": {},
"source": [
"# NomicVectorStore\n",
"\n",
"This notebook covers how to get started with the Nomic vector store.\n",
"\n",
"## Installation"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d97b55c2",
"metadata": {},
"outputs": [],
"source": [
"# install package\n",
"!pip install -U langchain-nomic"
]
},
{
"cell_type": "markdown",
"id": "36fdc060",
"metadata": {},
"source": [
"## Environment Setup\n",
"\n",
"Make sure to set the following environment variables:\n",
"\n",
"- TODO: fill out relevant environment variables or secrets\n",
"- Op\n",
"\n",
"## Usage"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "dc37144c-208d-4ab3-9f3a-0407a69fe052",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain_nomic.vectorstores import NomicVectorStore\n",
"\n",
"# TODO: switch for preferred way to init and use your vector store\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": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}