langchain/docs/modules/indexes/retrievers/examples/chroma_self_query_retriever.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"id": "13afcae7",
"metadata": {},
"source": [
"# Self-querying retriever with Chroma\n",
"In the notebook we'll demo the `SelfQueryRetriever` wrapped around a Chroma vector store. "
]
},
{
"cell_type": "markdown",
"id": "68e75fb9",
"metadata": {},
"source": [
"## Creating a Pinecone index\n",
"First we'll want to create a Chroma VectorStore and seed it with some data. We've created a small demo set of documents that contain summaries of movies.\n",
"\n",
"NOTE: The self-query retriever requires you to have `lark` installed (`pip install lark`)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "63a8af5b",
"metadata": {},
"outputs": [],
"source": [
"# !pip install lark"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "cb4a5787",
"metadata": {},
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
"from langchain.vectorstores import Chroma\n",
"\n",
"embeddings = OpenAIEmbeddings()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "bcbe04d9",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Using embedded DuckDB without persistence: data will be transient\n"
]
}
],
"source": [
"docs = [\n",
" Document(page_content=\"A bunch of scientists bring back dinosaurs and mayhem breaks loose\", metadata={\"year\": 1993, \"rating\": 7.7, \"genre\": \"science fiction\"}),\n",
" Document(page_content=\"Leo DiCaprio gets lost in a dream within a dream within a dream within a ...\", metadata={\"year\": 2010, \"director\": \"Christopher Nolan\", \"rating\": 8.2}),\n",
" Document(page_content=\"A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea\", metadata={\"year\": 2006, \"director\": \"Satoshi Kon\", \"rating\": 8.6}),\n",
" Document(page_content=\"A bunch of normal-sized women are supremely wholesome and some men pine after them\", metadata={\"year\": 2019, \"director\": \"Greta Gerwig\", \"rating\": 8.3}),\n",
" Document(page_content=\"Toys come alive and have a blast doing so\", metadata={\"year\": 1995, \"genre\": \"animated\"}),\n",
" Document(page_content=\"Three men walk into the Zone, three men walk out of the Zone\", metadata={\"year\": 1979, \"rating\": 9.9, \"director\": \"Andrei Tarkovsky\", \"genre\": \"science fiction\", \"rating\": 9.9})\n",
"]\n",
"vectorstore = Chroma.from_documents(\n",
" docs, embeddings\n",
")"
]
},
{
"cell_type": "markdown",
"id": "5ecaab6d",
"metadata": {},
"source": [
"# Creating our self-querying retriever\n",
"Now we can instantiate our retriever. To do this we'll need to provide some information upfront about the metadata fields that our documents support and a short description of the document contents."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "86e34dbf",
"metadata": {},
"outputs": [],
"source": [
"from langchain.llms import OpenAI\n",
"from langchain.retrievers.self_query.base import SelfQueryRetriever\n",
"from langchain.chains.query_constructor.base import AttributeInfo\n",
"\n",
"metadata_field_info=[\n",
" AttributeInfo(\n",
" name=\"genre\",\n",
" description=\"The genre of the movie\", \n",
" type=\"string or list[string]\", \n",
" ),\n",
" AttributeInfo(\n",
" name=\"year\",\n",
" description=\"The year the movie was released\", \n",
" type=\"integer\", \n",
" ),\n",
" AttributeInfo(\n",
" name=\"director\",\n",
" description=\"The name of the movie director\", \n",
" type=\"string\", \n",
" ),\n",
" AttributeInfo(\n",
" name=\"rating\",\n",
" description=\"A 1-10 rating for the movie\",\n",
" type=\"float\"\n",
" ),\n",
"]\n",
"document_content_description = \"Brief summary of a movie\"\n",
"llm = OpenAI(temperature=0)\n",
"retriever = SelfQueryRetriever.from_llm(llm, vectorstore, document_content_description, metadata_field_info, verbose=True)"
]
},
{
"cell_type": "markdown",
"id": "ea9df8d4",
"metadata": {},
"source": [
"# Testing it out\n",
"And now we can try actually using our retriever!"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "38a126e9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='dinosaur' filter=None\n"
]
},
{
"data": {
"text/plain": [
"[Document(page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose', metadata={'year': 1993, 'rating': 7.7, 'genre': 'science fiction'}),\n",
" Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'}),\n",
" Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6}),\n",
" Document(page_content='Leo DiCaprio gets lost in a dream within a dream within a dream within a ...', metadata={'year': 2010, 'director': 'Christopher Nolan', 'rating': 8.2})]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example only specifies a relevant query\n",
"retriever.get_relevant_documents(\"What are some movies about dinosaurs\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "fc3f1e6e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query=' ' filter=Comparison(comparator=<Comparator.GT: 'gt'>, attribute='rating', value=8.5)\n"
]
},
{
"data": {
"text/plain": [
"[Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6}),\n",
" Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'})]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example only specifies a filter\n",
"retriever.get_relevant_documents(\"I want to watch a movie rated higher than 8.5\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "b19d4da0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='women' filter=Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='director', value='Greta Gerwig')\n"
]
},
{
"data": {
"text/plain": [
"[Document(page_content='A bunch of normal-sized women are supremely wholesome and some men pine after them', metadata={'year': 2019, 'director': 'Greta Gerwig', 'rating': 8.3})]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example specifies a query and a filter\n",
"retriever.get_relevant_documents(\"Has Greta Gerwig directed any movies about women\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f900e40e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query=' ' filter=Operation(operator=<Operator.AND: 'and'>, arguments=[Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='science fiction'), Comparison(comparator=<Comparator.GT: 'gt'>, attribute='rating', value=8.5)])\n"
]
},
{
"data": {
"text/plain": [
"[Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'})]"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example specifies a composite filter\n",
"retriever.get_relevant_documents(\"What's a highly rated (above 8.5) science fiction film?\")"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "12a51522",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='toys' filter=Operation(operator=<Operator.AND: 'and'>, arguments=[Comparison(comparator=<Comparator.GT: 'gt'>, attribute='year', value=1990), Comparison(comparator=<Comparator.LT: 'lt'>, attribute='year', value=2005), Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='genre', value='animated')])\n"
]
},
{
"data": {
"text/plain": [
"[Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'})]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example specifies a query and composite filter\n",
"retriever.get_relevant_documents(\"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\")"
]
}
],
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