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langchain/docs/examples/data_augmented_generation/question_answering.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "05859721",
"metadata": {},
"source": [
"# Question Answering\n",
"\n",
"This notebook walks through how to use LangChain for question answering over a list of documents. It covers three different types of chaings: `stuff`, `map_reduce`, and `refine`. For a more in depth explanation of what these chain types are, see [here](../../explanation/combine_docs.md)."
]
},
{
"cell_type": "markdown",
"id": "726f4996",
"metadata": {},
"source": [
"### Prepare Data\n",
"First we prepare the data. For this example we do similarity search over a vector database, but these documents could be fetched in any manner (the point of this notebook to highlight what to do AFTER you fetch the documents)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "17fcbc0f",
"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain.vectorstores.faiss import FAISS\n",
"from langchain.docstore.document import Document"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "291f0117",
"metadata": {},
"outputs": [],
"source": [
"with open('../state_of_the_union.txt') as f:\n",
" state_of_the_union = f.read()\n",
"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
"texts = text_splitter.split_text(state_of_the_union)\n",
"\n",
"embeddings = OpenAIEmbeddings()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "fd9666a9",
"metadata": {},
"outputs": [],
"source": [
"docsearch = FAISS.from_texts(texts, embeddings)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "d1eaf6e6",
"metadata": {},
"outputs": [],
"source": [
"query = \"What did the president say about Justice Breyer\"\n",
"docs = docsearch.similarity_search(query)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a16e3453",
"metadata": {},
"outputs": [],
"source": [
"from langchain.chains.question_answering import load_qa_chain\n",
"from langchain.llms import OpenAI"
]
},
{
"cell_type": "markdown",
"id": "f78787a0",
"metadata": {},
"source": [
"### The `stuff` Chain\n",
"\n",
"This sections shows results of using the `stuff` Chain to do question answering."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "180fd4c1",
"metadata": {},
"outputs": [],
"source": [
"chain = load_qa_chain(OpenAI(temperature=0), chain_type=\"stuff\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "d145ae31",
"metadata": {},
"outputs": [],
"source": [
"docs = [Document(page_content=t) for t in texts[:3]]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "77fdf1aa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'output_text': ' The president did not mention Justice Breyer.'}"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Justice Breyer\"\n",
"chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)"
]
},
{
"cell_type": "markdown",
"id": "91522e29",
"metadata": {},
"source": [
"### The `map_reduce` Chain\n",
"\n",
"This sections shows results of using the `map_reduce` Chain to do question answering."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "b0060f51",
"metadata": {},
"outputs": [],
"source": [
"chain = load_qa_chain(OpenAI(temperature=0), chain_type=\"map_reduce\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "fbdb9137",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'output_text': ' The president did not mention Justice Breyer.'}"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Justice Breyer\"\n",
"chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)"
]
},
{
"cell_type": "markdown",
"id": "6ea50ad0",
"metadata": {},
"source": [
"### The `refine` Chain\n",
"\n",
"This sections shows results of using the `refine` Chain to do question answering."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "fb167057",
"metadata": {},
"outputs": [],
"source": [
"chain = load_qa_chain(OpenAI(temperature=0), chain_type=\"refine\")"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d8b5286e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'output_text': \"\\n\\nThe president did not mention Justice Breyer in his speech to the European Parliament about building a coalition of freedom-loving nations to confront Putin, unifying European allies, countering Russia's lies with truth, and enforcing powerful economic sanctions.\"}"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Justice Breyer\"\n",
"chain({\"input_documents\": docs, \"question\": query}, return_only_outputs=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "49e9c6d7",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
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},
"file_extension": ".py",
"mimetype": "text/x-python",
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