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			233 lines
		
	
	
		
			7.9 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			233 lines
		
	
	
		
			7.9 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
{
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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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    "# Gmail Toolkit\n",
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    "\n",
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    "This notebook walks through connecting a LangChain email to the Gmail API.\n",
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    "\n",
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    "To use this toolkit, you will need to set up your credentials explained in the [Gmail API docs](https://developers.google.com/gmail/api/quickstart/python#authorize_credentials_for_a_desktop_application). Once you've downloaded the `credentials.json` file, you can start using the Gmail API. Once this is done, we'll install the required libraries."
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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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   "metadata": {},
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   "outputs": [],
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   "source": [
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    "!pip install --upgrade google-api-python-client > /dev/null\n",
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    "!pip install --upgrade google-auth-oauthlib > /dev/null\n",
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    "!pip install --upgrade google-auth-httplib2 > /dev/null\n",
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    "!pip install beautifulsoup4 > /dev/null # This is optional but is useful for parsing HTML messages"
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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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    "## Create the Toolkit\n",
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    "\n",
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    "By default the toolkit reads the local `credentials.json` file. You can also manually provide a `Credentials` object."
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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": 3,
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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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    "from langchain.agents.agent_toolkits import GmailToolkit\n",
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    "\n",
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    "toolkit = GmailToolkit() "
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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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    "## Customizing Authentication\n",
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    "\n",
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    "Behind the scenes, a `googleapi` resource is created using the following methods. \n",
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    "you can manually build a `googleapi` resource for more auth control. "
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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": 4,
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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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    "from langchain.tools.gmail.utils import build_resource_service, get_gmail_credentials\n",
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    "\n",
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    "# Can review scopes here https://developers.google.com/gmail/api/auth/scopes\n",
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    "# For instance, readonly scope is 'https://www.googleapis.com/auth/gmail.readonly'\n",
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    "credentials = get_gmail_credentials(\n",
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    "    token_file='token.json',\n",
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    "    scopes=[\"https://mail.google.com/\"],\n",
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    "    client_secrets_file=\"credentials.json\",\n",
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    ")\n",
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    "api_resource = build_resource_service(credentials=credentials)\n",
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    "toolkit = GmailToolkit(api_resource=api_resource)"
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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": 5,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [
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    {
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     "data": {
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      "text/plain": [
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       "[GmailCreateDraft(name='create_gmail_draft', description='Use this tool to create a draft email with the provided message fields.', args_schema=<class 'langchain.tools.gmail.create_draft.CreateDraftSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, api_resource=<googleapiclient.discovery.Resource object at 0x10e5c6d10>),\n",
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       " GmailSendMessage(name='send_gmail_message', description='Use this tool to send email messages. The input is the message, recipents', args_schema=None, return_direct=False, verbose=False, callbacks=None, callback_manager=None, api_resource=<googleapiclient.discovery.Resource object at 0x10e5c6d10>),\n",
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       " GmailSearch(name='search_gmail', description=('Use this tool to search for email messages or threads. The input must be a valid Gmail query. The output is a JSON list of the requested resource.',), args_schema=<class 'langchain.tools.gmail.search.SearchArgsSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, api_resource=<googleapiclient.discovery.Resource object at 0x10e5c6d10>),\n",
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       " GmailGetMessage(name='get_gmail_message', description='Use this tool to fetch an email by message ID. Returns the thread ID, snipet, body, subject, and sender.', args_schema=<class 'langchain.tools.gmail.get_message.SearchArgsSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, api_resource=<googleapiclient.discovery.Resource object at 0x10e5c6d10>),\n",
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       " GmailGetThread(name='get_gmail_thread', description=('Use this tool to search for email messages. The input must be a valid Gmail query. The output is a JSON list of messages.',), args_schema=<class 'langchain.tools.gmail.get_thread.GetThreadSchema'>, return_direct=False, verbose=False, callbacks=None, callback_manager=None, api_resource=<googleapiclient.discovery.Resource object at 0x10e5c6d10>)]"
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      ]
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     },
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     "execution_count": 5,
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     "metadata": {},
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     "output_type": "execute_result"
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    }
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   ],
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   "source": [
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    "tools = toolkit.get_tools()\n",
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    "tools"
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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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    "## Use within an Agent"
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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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    "tags": []
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   },
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   "outputs": [],
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   "source": [
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    "from langchain import OpenAI\n",
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    "from langchain.agents import initialize_agent, AgentType"
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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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    "llm = OpenAI(temperature=0)\n",
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    "agent = initialize_agent(\n",
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    "    tools=toolkit.get_tools(),\n",
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    "    llm=llm,\n",
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    "    agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,\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": 19,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [
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    {
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     "name": "stderr",
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     "output_type": "stream",
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     "text": [
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      "WARNING:root:Failed to load default session, using empty session: 0\n",
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      "WARNING:root:Failed to persist run: {\"detail\":\"Not Found\"}\n"
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     ]
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    },
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    {
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     "data": {
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      "text/plain": [
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       "'I have created a draft email for you to edit. The draft Id is r5681294731961864018.'"
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      ]
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     },
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     "execution_count": 19,
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     "metadata": {},
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     "output_type": "execute_result"
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    }
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   ],
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   "source": [
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    "agent.run(\"Create a gmail draft for me to edit of a letter from the perspective of a sentient parrot\"\n",
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    "          \" who is looking to collaborate on some research with her\"\n",
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    "          \" estranged friend, a cat. Under no circumstances may you send the message, however.\")"
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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": 24,
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   "metadata": {
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    "tags": []
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   },
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   "outputs": [
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    {
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     "name": "stderr",
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     "output_type": "stream",
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     "text": [
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      "WARNING:root:Failed to load default session, using empty session: 0\n",
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      "WARNING:root:Failed to persist run: {\"detail\":\"Not Found\"}\n"
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     ]
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    },
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    {
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     "data": {
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      "text/plain": [
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       "\"The latest email in your drafts is from hopefulparrot@gmail.com with the subject 'Collaboration Opportunity'. The body of the email reads: 'Dear [Friend], I hope this letter finds you well. I am writing to you in the hopes of rekindling our friendship and to discuss the possibility of collaborating on some research together. I know that we have had our differences in the past, but I believe that we can put them aside and work together for the greater good. I look forward to hearing from you. Sincerely, [Parrot]'\""
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      ]
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     },
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     "execution_count": 24,
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     "metadata": {},
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     "output_type": "execute_result"
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    }
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   ],
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   "source": [
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    "agent.run(\"Could you search in my drafts for the latest email?\")"
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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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  }
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 ],
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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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