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docs: update Exa integration examples (#31547)
## Description Updating Exa integration documentation to showcase the latest features and best practices. ## Changes - Added examples for `ExaSearchResults` tool with advanced search options - Added examples for `ExaFindSimilarResults` tool - Updated agent example to use LangGraph - Demonstrated text content options, summaries, and highlights - Included examples of search type control and live crawling ## Additional Context I'm from the Exa team updating our integration documentation to reflect current capabilities and best practices.
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‎docs/docs/integrations/providers/exa_search.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exa\n",
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"\n",
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">[Exa](https://exa.ai/) is a knowledge API for AI and developers.\n",
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">\n",
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"\n",
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"## Installation and Setup\n",
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"\n",
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"`Exa` integration exists in its own [partner package](https://pypi.org/project/langchain-exa/). You can install it with:"
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]
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Exa\n",
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"\n",
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">[Exa](https://exa.ai/) is a knowledge API for AI and developers.\n",
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">\n",
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"\n",
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"## Installation and Setup\n",
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"\n",
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"`Exa` integration exists in its own [partner package](https://pypi.org/project/langchain-exa/). You can install it with:"
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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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"%pip install -qU langchain-exa"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In order to use the package, you will also need to set the `EXA_API_KEY` environment variable to your Exa API key.\n",
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"\n",
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"## Retriever\n",
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"\n",
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"You can use the [`ExaSearchRetriever`](/docs/integrations/tools/exa_search#using-exasearchretriever) in a standard retrieval pipeline. You can import it as follows.\n",
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"\n",
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"See a [usage example](/docs/integrations/tools/exa_search).\n"
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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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"metadata": {
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"id": "y8ku6X96sebl"
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},
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"outputs": [],
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"source": [
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"from langchain_exa import ExaSearchRetriever"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": "## Tools\n\nYou can use Exa as an agent tool as described in the [Exa tool calling docs](/docs/integrations/tools/exa_search#use-within-an-agent).\n\nSee a [usage example](/docs/integrations/tools/exa_search).\n\n### ExaFindSimilarResults\n\nA tool that queries the Metaphor Search API and gets back JSON."
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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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"from langchain_exa.tools import ExaFindSimilarResults"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### ExaSearchResults\n",
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"\n",
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"Exa Search tool."
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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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"from langchain_exa.tools import ExaSearchResults"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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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": "3.10.12"
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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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"%pip install -qU langchain-exa"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"In order to use the package, you will also need to set the `EXA_API_KEY` environment variable to your Exa API key.\n",
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"\n",
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"## Retriever\n",
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"\n",
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"You can use the [`ExaSearchRetriever`](/docs/integrations/tools/exa_search#using-exasearchretriever) in a standard retrieval pipeline. You can import it as follows.\n",
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"\n",
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"See a [usage example](/docs/integrations/tools/exa_search).\n"
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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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"metadata": {
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"id": "y8ku6X96sebl"
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},
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"outputs": [],
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"source": [
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"from langchain_exa import ExaSearchRetriever"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tools\n",
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"\n",
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"You can use Exa as an agent tool as described in the [Exa tool calling docs](/docs/integrations/tools/exa_search#using-the-exa-sdk-as-langchain-agent-tools).\n",
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"\n",
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"See a [usage example](/docs/integrations/tools/exa_search).\n",
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"\n",
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"### ExaFindSimilarResults\n",
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"\n",
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"A tool that queries the Metaphor Search API and gets back JSON."
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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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"from langchain_exa.tools import ExaFindSimilarResults"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### ExaSearchResults\n",
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"\n",
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"Exa Search tool."
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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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"from langchain_exa.tools import ExaSearchResults"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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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": "3.10.12"
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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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"nbformat": 4,
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"nbformat_minor": 4
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}

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