langchain/docs/extras/guides/evaluation/qa_generation.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "ee2a3a21",
"metadata": {},
"source": [
"# QA Generation\n",
"This notebook shows how to use the `QAGenerationChain` to come up with question-answer pairs over a specific document.\n",
"This is important because often times you may not have data to evaluate your question-answer system over, so this is a cheap and lightweight way to generate it!"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "33d3f0b4",
"metadata": {},
"outputs": [],
"source": [
"from langchain.document_loaders import TextLoader"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "2029a29c",
"metadata": {},
"outputs": [],
"source": [
"loader = TextLoader(\"../../modules/state_of_the_union.txt\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "87edb84c",
"metadata": {},
"outputs": [],
"source": [
"doc = loader.load()[0]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "04125b6d",
"metadata": {},
"outputs": [],
"source": [
"from langchain.chat_models import ChatOpenAI\n",
"from langchain.chains import QAGenerationChain\n",
"\n",
"chain = QAGenerationChain.from_llm(ChatOpenAI(temperature=0))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "4f1593e4",
"metadata": {},
"outputs": [],
"source": [
"qa = chain.run(doc.page_content)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "ee831f92",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'question': 'What is the U.S. Department of Justice doing to combat the crimes of Russian oligarchs?',\n",
" 'answer': 'The U.S. Department of Justice is assembling a dedicated task force to go after the crimes of Russian oligarchs.'}"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"qa[1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7028754e",
"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
}