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Add dashvector self query retriever (#9684)

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## Description
Add `Dashvector` retriever and self-query retriever

## How to use
```python
from langchain.vectorstores.dashvector import DashVector

vectorstore = DashVector.from_documents(docs, embeddings)
retriever = SelfQueryRetriever.from_llm(
    llm, vectorstore, document_content_description, metadata_field_info, verbose=True
)
```

---------

Co-authored-by: smallrain.xuxy <smallrain.xuxy@alibaba-inc.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Xiaoyu Xee
2023-09-04 11:51:04 +08:00
committed by GitHub
parent 056e59672b
commit 9bcfd58580
6 changed files with 577 additions and 2 deletions
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docs/extras/modules/data_connection/retrievers/self_query/dashvector.ipynb Normal file
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{
"cells": [
{
"cell_type": "markdown",
"source": [
"# DashVector self-querying\n",
"\n",
"> [DashVector](https://help.aliyun.com/document_detail/2510225.html) is a fully-managed vectorDB service that supports high-dimension dense and sparse vectors, real-time insertion and filtered search. It is built to scale automatically and can adapt to different application requirements.\n",
"\n",
"In this notebook we'll demo the `SelfQueryRetriever` with a `DashVector` vector store."
],
"metadata": {
"collapsed": false
},
"id": "59895c73d1a0f3ca"
},
{
"cell_type": "markdown",
"source": [
"## Create DashVector vectorstore\n",
"\n",
"First we'll want to create a `DashVector` VectorStore and seed it with some data. We've created a small demo set of documents that contain summaries of movies.\n",
"\n",
"To use DashVector, you have to have `dashvector` package installed, and you must have an API key and an Environment. Here are the [installation instructions](https://help.aliyun.com/document_detail/2510223.html).\n",
"\n",
"NOTE: The self-query retriever requires you to have `lark` package installed."
],
"metadata": {
"collapsed": false
},
"id": "539ae9367e45a178"
},
{
"cell_type": "code",
"execution_count": 1,
"outputs": [],
"source": [
"# !pip install lark dashvector"
],
"metadata": {
"collapsed": false
},
"id": "67df7e1f8dc8cdd0"
},
{
"cell_type": "code",
"execution_count": 1,
"outputs": [],
"source": [
"import os\n",
"import dashvector\n",
"\n",
"client = dashvector.Client(api_key=os.environ[\"DASHVECTOR_API_KEY\"])"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:58:46.905337Z",
"start_time": "2023-08-24T02:58:46.252566Z"
}
},
"id": "ff61eaf13973b5fe"
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [
"from langchain.schema import Document\n",
"from langchain.embeddings import DashScopeEmbeddings\n",
"from langchain.vectorstores import DashVector\n",
"\n",
"embeddings = DashScopeEmbeddings()\n",
"\n",
"# create DashVector collection\n",
"client.create(\"langchain-self-retriever-demo\", dimension=1536)"
],
"metadata": {
"collapsed": false
},
"id": "de5c77957ee42d14"
},
{
"cell_type": "code",
"execution_count": 3,
"outputs": [],
"source": [
"docs = [\n",
" Document(\n",
" page_content=\"A bunch of scientists bring back dinosaurs and mayhem breaks loose\",\n",
" metadata={\"year\": 1993, \"rating\": 7.7, \"genre\": \"action\"},\n",
" ),\n",
" Document(\n",
" page_content=\"Leo DiCaprio gets lost in a dream within a dream within a dream within a ...\",\n",
" metadata={\"year\": 2010, \"director\": \"Christopher Nolan\", \"rating\": 8.2},\n",
" ),\n",
" Document(\n",
" page_content=\"A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea\",\n",
" metadata={\"year\": 2006, \"director\": \"Satoshi Kon\", \"rating\": 8.6},\n",
" ),\n",
" Document(\n",
" page_content=\"A bunch of normal-sized women are supremely wholesome and some men pine after them\",\n",
" metadata={\"year\": 2019, \"director\": \"Greta Gerwig\", \"rating\": 8.3},\n",
" ),\n",
" Document(\n",
" page_content=\"Toys come alive and have a blast doing so\",\n",
" metadata={\"year\": 1995, \"genre\": \"animated\"},\n",
" ),\n",
" Document(\n",
" page_content=\"Three men walk into the Zone, three men walk out of the Zone\",\n",
" metadata={\n",
" \"year\": 1979,\n",
" \"director\": \"Andrei Tarkovsky\",\n",
" \"genre\": \"science fiction\",\n",
" \"rating\": 9.9,\n",
" },\n",
" ),\n",
"]\n",
"vectorstore = DashVector.from_documents(\n",
" docs, embeddings, collection_name=\"langchain-self-retriever-demo\"\n",
")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:08.090031Z",
"start_time": "2023-08-24T02:59:05.660295Z"
}
},
"id": "8f40605548a4550"
},
{
"cell_type": "markdown",
"source": [
"## Create your self-querying retriever\n",
"\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."
],
"metadata": {
"collapsed": false
},
"id": "eb1340adafac8993"
},
{
"cell_type": "code",
"execution_count": 4,
"outputs": [],
"source": [
"from langchain.llms import Tongyi\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\", description=\"A 1-10 rating for the movie\", type=\"float\"\n",
" ),\n",
"]\n",
"document_content_description = \"Brief summary of a movie\"\n",
"llm = Tongyi(temperature=0)\n",
"retriever = SelfQueryRetriever.from_llm(\n",
" llm, vectorstore, document_content_description, metadata_field_info, verbose=True\n",
")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:11.003940Z",
"start_time": "2023-08-24T02:59:10.476722Z"
}
},
"id": "d65233dc044f95a7"
},
{
"cell_type": "markdown",
"source": [
"## Testing it out\n",
"\n",
"And now we can try actually using our retriever!"
],
"metadata": {
"collapsed": false
},
"id": "a54af0d67b473db6"
},
{
"cell_type": "code",
"execution_count": 6,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='dinosaurs' filter=None limit=None\n"
]
},
{
"data": {
"text/plain": "[Document(page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose', metadata={'year': 1993, 'rating': 7.699999809265137, 'genre': 'action'}),\n Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'}),\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': 8.199999809265137}),\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': 8.600000381469727})]"
},
"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\")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:28.577901Z",
"start_time": "2023-08-24T02:59:26.780184Z"
}
},
"id": "dad9da670a267fe7"
},
{
"cell_type": "code",
"execution_count": 7,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query=' ' filter=Comparison(comparator=<Comparator.GTE: 'gte'>, attribute='rating', value=8.5) limit=None\n"
]
},
{
"data": {
"text/plain": "[Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'director': 'Andrei Tarkovsky', 'rating': 9.899999618530273, 'genre': 'science fiction'}),\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': 8.600000381469727})]"
},
"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\")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:32.370774Z",
"start_time": "2023-08-24T02:59:30.614252Z"
}
},
"id": "d486a64316153d52"
},
{
"cell_type": "code",
"execution_count": 8,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='Greta Gerwig' filter=Comparison(comparator=<Comparator.EQ: 'eq'>, attribute='director', value='Greta Gerwig') limit=None\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': 8.300000190734863})]"
},
"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\")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:35.353439Z",
"start_time": "2023-08-24T02:59:33.278255Z"
}
},
"id": "e05919cdead7bd4a"
},
{
"cell_type": "code",
"execution_count": 9,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='science fiction' 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)]) limit=None\n"
]
},
{
"data": {
"text/plain": "[Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'director': 'Andrei Tarkovsky', 'rating': 9.899999618530273, '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?\")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:38.913707Z",
"start_time": "2023-08-24T02:59:36.659271Z"
}
},
"id": "ac2c7012379e918e"
},
{
"cell_type": "markdown",
"source": [
"## Filter k\n",
"\n",
"We can also use the self query retriever to specify `k`: the number of documents to fetch.\n",
"\n",
"We can do this by passing `enable_limit=True` to the constructor."
],
"metadata": {
"collapsed": false
},
"id": "af6aa93ae44af414"
},
{
"cell_type": "code",
"execution_count": 10,
"outputs": [],
"source": [
"retriever = SelfQueryRetriever.from_llm(\n",
" llm,\n",
" vectorstore,\n",
" document_content_description,\n",
" metadata_field_info,\n",
" enable_limit=True,\n",
" verbose=True,\n",
")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:41.594073Z",
"start_time": "2023-08-24T02:59:41.563323Z"
}
},
"id": "a8c8f09bf5702767"
},
{
"cell_type": "code",
"execution_count": 11,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"query='dinosaurs' filter=None limit=2\n"
]
},
{
"data": {
"text/plain": "[Document(page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose', metadata={'year': 1993, 'rating': 7.699999809265137, 'genre': 'action'}),\n Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'})]"
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# This example only specifies a relevant query\n",
"retriever.get_relevant_documents(\"what are two movies about dinosaurs\")"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2023-08-24T02:59:48.450506Z",
"start_time": "2023-08-24T02:59:46.252944Z"
}
},
"id": "b1089a6043980b84"
},
{
"cell_type": "code",
"execution_count": null,
"outputs": [],
"source": [],
"metadata": {
"collapsed": false
},
"id": "6d2d64e2ebb17d30"
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
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"nbformat": 4,
"nbformat_minor": 5
}