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{
"cells": [
{
"cell_type": "markdown",
"id": "8f210ec3",
"metadata": {},
"source": [
"# Shell Tool\n",
"\n",
"Giving agents access to the shell is powerful (though risky outside a sandboxed environment).\n",
"\n",
"The LLM can use it to execute any shell commands. A common use case for this is letting the LLM interact with your local file system."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "f7b3767b",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain.tools import ShellTool\n",
"\n",
"shell_tool = ShellTool()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "c92ac832-556b-4f66-baa4-b78f965dfba0",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Hello World!\n",
"\n",
"real\t0m0.000s\n",
"user\t0m0.000s\n",
"sys\t0m0.000s\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/wfh/code/lc/lckg/langchain/tools/shell/tool.py:34: UserWarning: The shell tool has no safeguards by default. Use at your own risk.\n",
" warnings.warn(\n"
]
}
],
"source": [
"print(shell_tool.run({\"commands\": [\"echo 'Hello World!'\", \"time\"]}))"
]
},
{
"cell_type": "markdown",
"id": "2fa952fc",
"metadata": {},
"source": [
"### Use with Agents\n",
"\n",
"As with all tools, these can be given to an agent to accomplish more complex tasks. Let's have the agent fetch some links from a web page."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "851fee9f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mQuestion: What is the task?\n",
"Thought: We need to download the langchain.com webpage and extract all the URLs from it. Then we need to sort the URLs and return them.\n",
"Action:\n",
"```\n",
"{\n",
" \"action\": \"shell\",\n",
" \"action_input\": {\n",
" \"commands\": [\n",
" \"curl -s https://langchain.com | grep -o 'http[s]*://[^\\\" ]*' | sort\"\n",
" ]\n",
" }\n",
"}\n",
"```\n",
"\u001b[0m"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/wfh/code/lc/lckg/langchain/tools/shell/tool.py:34: UserWarning: The shell tool has no safeguards by default. Use at your own risk.\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Observation: \u001b[36;1m\u001b[1;3mhttps://blog.langchain.dev/\n",
"https://discord.gg/6adMQxSpJS\n",
"https://docs.langchain.com/docs/\n",
"https://github.com/hwchase17/chat-langchain\n",
"https://github.com/hwchase17/langchain\n",
"https://github.com/hwchase17/langchainjs\n",
"https://github.com/sullivan-sean/chat-langchainjs\n",
"https://js.langchain.com/docs/\n",
"https://python.langchain.com/en/latest/\n",
"https://twitter.com/langchainai\n",
"\u001b[0m\n",
"Thought:\u001b[32;1m\u001b[1;3mThe URLs have been successfully extracted and sorted. We can return the list of URLs as the final answer.\n",
"Final Answer: [\"https://blog.langchain.dev/\", \"https://discord.gg/6adMQxSpJS\", \"https://docs.langchain.com/docs/\", \"https://github.com/hwchase17/chat-langchain\", \"https://github.com/hwchase17/langchain\", \"https://github.com/hwchase17/langchainjs\", \"https://github.com/sullivan-sean/chat-langchainjs\", \"https://js.langchain.com/docs/\", \"https://python.langchain.com/en/latest/\", \"https://twitter.com/langchainai\"]\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"'[\"https://blog.langchain.dev/\", \"https://discord.gg/6adMQxSpJS\", \"https://docs.langchain.com/docs/\", \"https://github.com/hwchase17/chat-langchain\", \"https://github.com/hwchase17/langchain\", \"https://github.com/hwchase17/langchainjs\", \"https://github.com/sullivan-sean/chat-langchainjs\", \"https://js.langchain.com/docs/\", \"https://python.langchain.com/en/latest/\", \"https://twitter.com/langchainai\"]'"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.agents import initialize_agent\n",
"from langchain.agents import AgentType\n",
"\n",
"llm = ChatOpenAI(temperature=0)\n",
"\n",
"shell_tool.description = shell_tool.description + f\"args {shell_tool.args}\".replace(\"{\", \"{{\").replace(\"}\", \"}}\")\n",
"self_ask_with_search = initialize_agent([shell_tool], llm, agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True)\n",
"self_ask_with_search.run(\"Download the langchain.com webpage and grep for all urls. Return only a sorted list of them. Be sure to use double quotes.\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8d0ea3ac-0890-4e39-9cec-74bd80b4b8b8",
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.8.16"
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"nbformat_minor": 5
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