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{
"cells": [
{
"cell_type": "markdown",
"id": "991b1cc1",
"metadata": {},
"source": [
"# Loading from LangChainHub\n",
"\n",
"This notebook covers how to load agents from [LangChainHub](https://github.com/hwchase17/langchain-hub)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "bd4450a2",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"No `_type` key found, defaulting to `prompt`.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
"\u001b[32;1m\u001b[1;3m Yes.\n",
"Follow up: Who is the reigning men's U.S. Open champion?\u001b[0m\n",
"Intermediate answer: \u001b[36;1m\u001b[1;3m2016 路 SUI 路 Stan Wawrinka ; 2017 路 ESP 路 Rafael Nadal ; 2018 路 SRB 路 Novak Djokovic ; 2019 路 ESP 路 Rafael Nadal.\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mSo the reigning men's U.S. Open champion is Rafael Nadal.\n",
"Follow up: What is Rafael Nadal's hometown?\u001b[0m\n",
"Intermediate answer: \u001b[36;1m\u001b[1;3mIn 2016, he once again showed his deep ties to Mallorca and opened the Rafa Nadal Academy in his hometown of Manacor.\u001b[0m\n",
"\u001b[32;1m\u001b[1;3mSo the final answer is: Manacor, Mallorca, Spain.\u001b[0m\n",
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"'Manacor, Mallorca, Spain.'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain import OpenAI, SerpAPIWrapper\n",
"from langchain.agents import initialize_agent, Tool\n",
"\n",
"llm = OpenAI(temperature=0)\n",
"search = SerpAPIWrapper()\n",
"tools = [\n",
" Tool(\n",
" name=\"Intermediate Answer\",\n",
" func=search.run\n",
" )\n",
"]\n",
"\n",
"self_ask_with_search = initialize_agent(tools, llm, agent_path=\"lc://agents/self-ask-with-search/agent.json\", verbose=True)\n",
"self_ask_with_search.run(\"What is the hometown of the reigning men's U.S. Open champion?\")"
]
},
{
"cell_type": "markdown",
"id": "3aede965",
"metadata": {},
"source": [
"# Pinning Dependencies\n",
"\n",
"Specific versions of LangChainHub agents can be pinned with the `lc@<ref>://` syntax."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e679f7b6",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"No `_type` key found, defaulting to `prompt`.\n"
]
}
],
"source": [
"self_ask_with_search = initialize_agent(tools, llm, agent_path=\"lc@2826ef9e8acdf88465e1e5fc8a7bf59e0f9d0a85://agents/self-ask-with-search/agent.json\", verbose=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9d3d6697",
"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": "3.9.1"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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