langchain/docs/modules/indexes/chain_examples/vector_db_qa.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "07c1e3b9",
"metadata": {},
"source": [
"# Vector DB Question/Answering\n",
"\n",
"This example showcases question answering over a vector database."
]
},
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{
"cell_type": "code",
"execution_count": 1,
"id": "82525493",
"metadata": {},
"outputs": [],
"source": [
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
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"from langchain.vectorstores import Chroma\n",
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"from langchain.text_splitter import CharacterTextSplitter\n",
"from langchain import OpenAI, VectorDBQA"
]
},
{
"cell_type": "code",
"execution_count": 2,
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"id": "5c7049db",
"metadata": {},
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"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running Chroma using direct local API.\n",
"Using DuckDB in-memory for database. Data will be transient.\n"
]
}
],
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"source": [
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"from langchain.document_loaders import TextLoader\n",
"loader = TextLoader('../../state_of_the_union.txt')\n",
"documents = loader.load()\n",
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"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
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"texts = text_splitter.split_documents(documents)\n",
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"\n",
"embeddings = OpenAIEmbeddings()\n",
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"docsearch = Chroma.from_documents(texts, embeddings)"
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]
},
{
"cell_type": "code",
"execution_count": 3,
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"id": "3018f865",
"metadata": {},
"outputs": [],
"source": [
"qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", vectorstore=docsearch)"
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]
},
{
"cell_type": "code",
"execution_count": 4,
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"id": "032a47f8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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"\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice and federal public defender, from a family of public school educators and police officers, a consensus builder, and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
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]
},
"execution_count": 4,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"qa.run(query)"
]
},
{
"cell_type": "markdown",
"id": "c28f1f64",
"metadata": {},
"source": [
"## Chain Type\n",
"You can easily specify different chain types to load and use in the VectorDBQA chain. For a more detailed walkthrough of these types, please see [this notebook](question_answering.ipynb).\n",
"\n",
"There are two ways to load different chain types. First, you can specify the chain type argument in the `from_chain_type` method. This allows you to pass in the name of the chain type you want to use. For example, in the below we change the chain type to `map_reduce`."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "22d2417d",
"metadata": {},
"outputs": [],
"source": [
"qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"map_reduce\", vectorstore=docsearch)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "43204ad1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, from a family of public school educators and police officers, a consensus builder, and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"qa.run(query)"
]
},
{
"cell_type": "markdown",
"id": "60368f38",
"metadata": {},
"source": [
"The above way allows you to really simply change the chain_type, but it does provide a ton of flexibility over parameters to that chain type. If you want to control those parameters, you can load the chain directly (as you did in [this notebook](question_answering.ipynb)) and then pass that directly to the the VectorDBQA chain with the `combine_documents_chain` parameter. For example:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "7b403f0d",
"metadata": {},
"outputs": [],
"source": [
"from langchain.chains.question_answering import load_qa_chain\n",
"qa_chain = load_qa_chain(OpenAI(temperature=0), chain_type=\"stuff\")\n",
"qa = VectorDBQA(combine_documents_chain=qa_chain, vectorstore=docsearch)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "9e04a9ac",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, and from a family of public school educators and police officers. He also said that she is a consensus builder and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"qa.run(query)"
]
},
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{
"cell_type": "markdown",
"id": "90c7899a",
"metadata": {},
"source": [
"## Custom Prompts\n",
"You can pass in custom prompts to do question answering. These prompts are the same prompts as you can pass into the [base question answering chain](./question_answering.ipynb)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a45232a2",
"metadata": {},
"outputs": [],
"source": [
"from langchain.prompts import PromptTemplate\n",
"prompt_template = \"\"\"Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n",
"\n",
"{context}\n",
"\n",
"Question: {question}\n",
"Answer in Italian:\"\"\"\n",
"PROMPT = PromptTemplate(\n",
" template=prompt_template, input_variables=[\"context\", \"question\"]\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "9b5c8d1d",
"metadata": {},
"outputs": [],
"source": [
"chain_type_kwargs = {\"prompt\": PROMPT}\n",
"qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", vectorstore=docsearch, chain_type_kwargs=chain_type_kwargs)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "26ee7671",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\" Il Presidente ha detto che Ketanji Brown Jackson è uno dei pensatori legali più importanti del nostro Paese, che continuerà l'eccellente eredità di giustizia Breyer. È un ex principale litigante in pratica privata, un ex difensore federale pubblico e appartiene a una famiglia di insegnanti e poliziotti delle scuole pubbliche. È un costruttore di consenso che ha ricevuto un ampio supporto da parte di Fraternal Order of Police e giudici designati da democratici e repubblicani.\""
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"qa.run(query)"
]
},
{
"cell_type": "markdown",
"id": "0b8c37f7",
"metadata": {},
"source": [
"## Return Source Documents\n",
"Additionally, we can return the source documents used to answer the question by specifying an optional parameter when constructing the chain."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "af093aba",
"metadata": {},
"outputs": [],
"source": [
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"qa = VectorDBQA.from_chain_type(llm=OpenAI(), chain_type=\"stuff\", vectorstore=docsearch, return_source_documents=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "eac11321",
"metadata": {},
"outputs": [],
"source": [
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
"result = qa({\"query\": query})"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "7d75945a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\" The president said that Ketanji Brown Jackson is one of our nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\""
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result[\"result\"]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "35b4f31f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[Document(page_content='In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections. \\n\\nWe cannot let this happen. \\n\\nTonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while youre at it, pass the Disclose Act so Americans can know who is funding our elections. \\n\\nTonight, Id like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \\n\\nOne of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \\n\\nAnd I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nations top legal minds, who will continue Justice Breyers legacy of excellence.', lookup_str='', metadata={}, lookup_index=0),\n",
" Document(page_content='A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since shes been nominated, shes received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. \\n\\nAnd if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \\n\\nWe can do both. At our border, weve installed new technology like cutting-edge scanners to better detect drug smuggling. \\n\\nWeve set up joint patrols with Mexico and Guatemala to catch more human traffickers. \\n\\nWere putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. \\n\\nWere securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders.', lookup_str='', metadata={}, lookup_index=0),\n",
" Document(page_content='And for our LGBTQ+ Americans, lets finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. \\n\\nAs I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \\n\\nWhile it often appears that we never agree, that isnt true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice. \\n\\nAnd soon, well strengthen the Violence Against Women Act that I first wrote three decades ago. It is important for us to show the nation that we can come together and do big things. \\n\\nSo tonight Im offering a Unity Agenda for the Nation. Four big things we can do together. \\n\\nFirst, beat the opioid epidemic.', lookup_str='', metadata={}, lookup_index=0),\n",
" Document(page_content='As Ive told Xi Jinping, it is never a good bet to bet against the American people. \\n\\nWell create good jobs for millions of Americans, modernizing roads, airports, ports, and waterways all across America. \\n\\nAnd well do it all to withstand the devastating effects of the climate crisis and promote environmental justice. \\n\\nWell build a national network of 500,000 electric vehicle charging stations, begin to replace poisonous lead pipes—so every child—and every American—has clean water to drink at home and at school, provide affordable high-speed internet for every American—urban, suburban, rural, and tribal communities. \\n\\n4,000 projects have already been announced. \\n\\nAnd tonight, Im announcing that this year we will start fixing over 65,000 miles of highway and 1,500 bridges in disrepair. \\n\\nWhen we use taxpayer dollars to rebuild America we are going to Buy American: buy American products to support American jobs.', lookup_str='', metadata={}, lookup_index=0)]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result[\"source_documents\"]"
]
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{
"cell_type": "code",
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