mirror of
https://github.com/hwchase17/langchain
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Description: Updates for Nomic AI Atlas and GPT4All integrations documentation. --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
194 lines
4.1 KiB
Plaintext
194 lines
4.1 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Atlas\n",
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"\n",
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"\n",
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">[Atlas](https://docs.nomic.ai/index.html) is a platform by Nomic made for interacting with both small and internet scale unstructured datasets. It enables anyone to visualize, search, and share massive datasets in their browser.\n",
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"\n",
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"This notebook shows you how to use functionality related to the `AtlasDB` vectorstore."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"!pip install spacy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"is_executing": true
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},
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"scrolled": true,
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"tags": []
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},
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"outputs": [],
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"source": [
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"!python3 -m spacy download en_core_web_sm"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"!pip install nomic"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Load Packages"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"pycharm": {
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"is_executing": true
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"import time\n",
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"from langchain.embeddings.openai import OpenAIEmbeddings\n",
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"from langchain.text_splitter import SpacyTextSplitter\n",
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"from langchain.vectorstores import AtlasDB\n",
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"from langchain.document_loaders import TextLoader"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"ATLAS_TEST_API_KEY = \"7xDPkYXSYDc1_ErdTPIcoAR9RNd8YDlkS3nVNXcVoIMZ6\""
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Prepare the Data"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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"loader = TextLoader(\"../../../state_of_the_union.txt\")\n",
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"documents = loader.load()\n",
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"text_splitter = SpacyTextSplitter(separator=\"|\")\n",
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"texts = []\n",
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"for doc in text_splitter.split_documents(documents):\n",
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" texts.extend(doc.page_content.split(\"|\"))\n",
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"\n",
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"texts = [e.strip() for e in texts]"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Map the Data using Nomic's Atlas"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"pycharm": {
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"is_executing": true
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"db = AtlasDB.from_texts(\n",
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" texts=texts,\n",
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" name=\"test_index_\" + str(time.time()), # unique name for your vector store\n",
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" description=\"test_index\", # a description for your vector store\n",
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" api_key=ATLAS_TEST_API_KEY,\n",
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" index_kwargs={\"build_topic_model\": True},\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"db.project.wait_for_project_lock()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"db.project"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Here is a map with the result of this code. This map displays the texts of the State of the Union.\n",
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"https://atlas.nomic.ai/map/3e4de075-89ff-486a-845c-36c23f30bb67/d8ce2284-8edb-4050-8b9b-9bb543d7f647"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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