langchain/docs/modules/models/llms/integrations/anthropic_example.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "9597802c",
"metadata": {},
"source": [
"# Anthropic\n",
"This example goes over how to use LangChain to interact with Anthropic models"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "6fb585dd",
"metadata": {},
"outputs": [],
"source": [
"from langchain.llms import Anthropic\n",
"from langchain import PromptTemplate, LLMChain"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "035dea0f",
"metadata": {},
"outputs": [],
"source": [
"template = \"\"\"Question: {question}\n",
"\n",
"Answer: Let's think step by step.\"\"\"\n",
"\n",
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "3f3458d9",
"metadata": {},
"outputs": [],
"source": [
"llm = Anthropic()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "a641dbd9",
"metadata": {},
"outputs": [],
"source": [
"llm_chain = LLMChain(prompt=prompt, llm=llm)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "9f844993",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\" Step 1: Justin Beiber was born on March 1, 1994\\nStep 2: The NFL season ends with the Super Bowl in January/February\\nStep 3: Therefore, the Super Bowl that occurred closest to Justin Beiber's birth would be Super Bowl XXIX in 1995\\nStep 4: The San Francisco 49ers won Super Bowl XXIX in 1995\\n\\nTherefore, the answer is the San Francisco 49ers won the Super Bowl in the year Justin Beiber was born.\""
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
"\n",
"llm_chain.run(question)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4797d719",
"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
}