forked from Archives/langchain
705431aecc
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
218 lines
5.6 KiB
Plaintext
218 lines
5.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "683953b3",
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"metadata": {},
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"source": [
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"# OpenSearch\n",
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"\n",
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"This notebook shows how to use functionality related to the OpenSearch database.\n",
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"\n",
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"To run, you should have the opensearch instance up and running: [here](https://opensearch.org/docs/latest/install-and-configure/install-opensearch/index/)\n",
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"`similarity_search` by default performs the Approximate k-NN Search which uses one of the several algorithms like lucene, nmslib, faiss recommended for\n",
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"large datasets. To perform brute force search we have other search methods known as Script Scoring and Painless Scripting.\n",
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"Check [this](https://opensearch.org/docs/latest/search-plugins/knn/index/) for more details."
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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": 1,
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"id": "aac9563e",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.embeddings.openai import OpenAIEmbeddings\n",
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"from langchain.text_splitter import CharacterTextSplitter\n",
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"from langchain.vectorstores import OpenSearchVectorSearch\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": 2,
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"id": "a3c3999a",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.document_loaders import TextLoader\n",
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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 = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
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"docs = text_splitter.split_documents(documents)\n",
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"\n",
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"embeddings = OpenAIEmbeddings()"
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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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"id": "db3fa309",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"docsearch = OpenSearchVectorSearch.from_texts(texts, embeddings, opensearch_url=\"http://localhost:9200\")\n",
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"\n",
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"query = \"What did the president say about Ketanji Brown Jackson\"\n",
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"docs = docsearch.similarity_search(query)"
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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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"id": "c160d5bb",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"print(docs[0].page_content)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "01a9a035",
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"metadata": {},
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"source": [
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"#### similarity_search using Approximate k-NN Search with Custom Parameters"
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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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"id": "96215c90",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"docsearch = OpenSearchVectorSearch.from_texts(texts, embeddings, opensearch_url=\"http://localhost:9200\", engine=\"faiss\", space_type=\"innerproduct\", ef_construction=256, m=48)\n",
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"\n",
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"query = \"What did the president say about Ketanji Brown Jackson\"\n",
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"docs = docsearch.similarity_search(query)"
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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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"id": "62a7cea0",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"print(docs[0].page_content)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0d0cd877",
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"metadata": {},
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"source": [
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"#### similarity_search using Script Scoring with Custom Parameters"
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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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"id": "0a8e3c0e",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"docsearch = OpenSearchVectorSearch.from_texts(texts, embeddings, opensearch_url=\"http://localhost:9200\", is_appx_search=False)\n",
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"\n",
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"query = \"What did the president say about Ketanji Brown Jackson\"\n",
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"docs = docsearch.similarity_search(\"What did the president say about Ketanji Brown Jackson\", k=1, search_type=\"script_scoring\")"
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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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"id": "92bc40db",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"print(docs[0].page_content)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a4af96cc",
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"metadata": {},
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"source": [
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"#### similarity_search using Painless Scripting with Custom Parameters"
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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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"id": "6d9f436e",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"docsearch = OpenSearchVectorSearch.from_texts(texts, embeddings, opensearch_url=\"http://localhost:9200\", is_appx_search=False)\n",
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"filter = {\"bool\": {\"filter\": {\"term\": {\"text\": \"smuggling\"}}}}\n",
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"query = \"What did the president say about Ketanji Brown Jackson\"\n",
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"docs = docsearch.similarity_search(\"What did the president say about Ketanji Brown Jackson\", search_type=\"painless_scripting\", space_type=\"cosineSimilarity\", pre_filter=filter)"
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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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"id": "8ca50bce",
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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}
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},
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"outputs": [],
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"source": [
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"print(docs[0].page_content)"
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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": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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