mirror of
https://github.com/hwchase17/langchain
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docs: Add integration doc for postgres vectorstore (#20473)
Adds a postgres vectorstore via langchain-postgres.
This commit is contained in:
Eugene Yurtsev
GitHub
parent
676c68d318
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"cells": [
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"cells": [
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"id": "7679dd7b-7ed4-4755-a499-824deadba708",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"# PGVector\n",
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"# PGVector\n",
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"\n",
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"\n",
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">[PGVector](https://github.com/pgvector/pgvector) is an open-source vector similarity search for `Postgres`\n",
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"> An implementation of LangChain vectorstore abstraction using `postgres` as the backend and utilizing the `pgvector` extension.\n",
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"\n",
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"\n",
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"It supports:\n",
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"The code lives in an integration package called: [langchain_postgres](https://github.com/langchain-ai/langchain-postgres/).\n",
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"- exact and approximate nearest neighbor search\n",
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"- L2 distance, inner product, and cosine distance\n",
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"\n",
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"\n",
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"This notebook shows how to use the Postgres vector database (`PGVector`)."
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"You can run the following command to spin up a a postgres container with the `pgvector` extension:\n",
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"\n",
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"```shell\n",
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"docker run --name pgvector-container -e POSTGRES_USER=langchain -e POSTGRES_PASSWORD=langchain -e POSTGRES_DB=langchain -p 6024:5432 -d pgvector/pgvector:pg16\n",
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"```\n",
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"\n",
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"## Status\n",
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"\n",
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"This code has been ported over from `langchain_community` into a dedicated package called `langchain-postgres`. The following changes have been made:\n",
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"\n",
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"* langchain_postgres works only with psycopg3. Please update your connnecion strings from `postgresql+psycopg2://...` to `postgresql+psycopg://langchain:langchain@...` (yes, it's the driver name is `psycopg` not `psycopg3`, but it'll use `psycopg3`.\n",
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"* The schema of the embedding store and collection have been changed to make add_documents work correctly with user specified ids.\n",
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"* One has to pass an explicit connection object now.\n",
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"\n",
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"\n",
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"Currently, there is **no mechanism** that supports easy data migration on schema changes. So any schema changes in the vectorstore will require the user to recreate the tables and re-add the documents.\n",
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"If this is a concern, please use a different vectorstore. If not, this implementation should be fine for your use case."
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]
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]
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},
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},
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"id": "342cd5e9-f349-42b4-9713-12e63779835b",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"See the [installation instruction](https://github.com/pgvector/pgvector)."
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"## Install dependencies\n",
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"\n",
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"Here, we're using `langchain_cohere` for embeddings, but you can use other embeddings providers."
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]
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]
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "42d42297-11b8-44e3-bf21-7c3d1bce8277",
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"metadata": {
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"metadata": {
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"tags": []
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"tags": []
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"# Pip install necessary package\n",
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"!pip install --quiet -U langchain_cohere\n",
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"%pip install --upgrade --quiet pgvector\n",
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"!pip install --quiet -U langchain_postgres"
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"%pip install --upgrade --quiet langchain-openai\n",
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"%pip install --upgrade --quiet psycopg2-binary\n",
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"%pip install --upgrade --quiet tiktoken"
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]
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]
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},
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},
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{
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{
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"cell_type": "markdown",
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"cell_type": "markdown",
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"id": "eee31ce1-2c28-484d-82be-d22d9f9a31fd",
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"metadata": {},
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"metadata": {},
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"source": [
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"source": [
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"We want to use `OpenAIEmbeddings` so we have to get the OpenAI API Key."
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"## Initialize the vectorstore"
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]
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]
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 2,
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"id": "979a65bd-742f-4b0d-be1e-c0baae245ec6",
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"metadata": {
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-09-09T08:02:16.802456Z",
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"start_time": "2023-09-09T08:02:07.065604Z"
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}
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},
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"outputs": [],
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"source": [
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"import getpass\n",
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"import os\n",
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"\n",
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"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-09-09T08:02:19.742896Z",
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"start_time": "2023-09-09T08:02:19.732527Z"
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},
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": "False"
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"## Loading Environment Variables\n",
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"from dotenv import load_dotenv\n",
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"\n",
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"load_dotenv()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023-09-09T08:02:23.144824Z",
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"start_time": "2023-09-09T08:02:22.047801Z"
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},
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"tags": []
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"tags": []
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"from langchain.docstore.document import Document\n",
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"from langchain_cohere import CohereEmbeddings\n",
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"from langchain_community.document_loaders import TextLoader\n",
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"from langchain_core.documents import Document\n",
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"from langchain_community.vectorstores.pgvector import PGVector\n",
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"from langchain_postgres import PGVector\n",
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"from langchain_openai import OpenAIEmbeddings\n",
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"from langchain_postgres.vectorstores import PGVector\n",
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"from langchain_text_splitters import CharacterTextSplitter"
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"\n",
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"# See docker command above to launch a postgres instance with pgvector enabled.\n",
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"connection = \"postgresql+psycopg://langchain:langchain@localhost:6024/langchain\" # Uses psycopg3!\n",
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"collection_name = \"my_docs\"\n",
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"embeddings = CohereEmbeddings()\n",
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"\n",
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"vectorstore = PGVector(\n",
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" embeddings=embeddings,\n",
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" collection_name=collection_name,\n",
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" connection=connection,\n",
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" use_jsonb=True,\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0fc32168-5a82-4629-a78d-158fe2615086",
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"metadata": {},
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"source": [
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"## Drop tables\n",
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"\n",
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"If you need to drop tables (e.g., updating the embedding to a different dimension or just updating the embedding provider): "
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]
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},
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{
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"cell_type": "markdown",
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"id": "5de5ef98-7dbb-4892-853f-47c7dc87b70e",
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"metadata": {
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"tags": []
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},
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"source": [
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"```python\n",
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"vectorstore.drop_tables()\n",
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"````"
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]
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},
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{
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"cell_type": "markdown",
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"id": "61a224a1-d70b-4daf-86ba-ab6e43c08b50",
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"metadata": {},
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"source": [
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"## Add documents\n",
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"\n",
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"Add documents to the vectorstore"
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]
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]
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 5,
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"id": "88a288cc-ffd4-4800-b011-750c72b9fd10",
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"metadata": {
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"metadata": {
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"ExecuteTime": {
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"tags": []
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"end_time": "2023-09-09T08:02:25.452472Z",
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"start_time": "2023-09-09T08:02:25.441563Z"
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}
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},
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},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"loader = TextLoader(\"../../modules/state_of_the_union.txt\")\n",
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"docs = [\n",
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"documents = loader.load()\n",
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" Document(\n",
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"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
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" page_content=\"there are cats in the pond\",\n",
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"docs = text_splitter.split_documents(documents)\n",
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" metadata={\"id\": 1, \"location\": \"pond\", \"topic\": \"animals\"},\n",
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"\n",
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" ),\n",
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"embeddings = OpenAIEmbeddings()"
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" Document(\n",
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" page_content=\"ducks are also found in the pond\",\n",
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" metadata={\"id\": 2, \"location\": \"pond\", \"topic\": \"animals\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"fresh apples are available at the market\",\n",
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" metadata={\"id\": 3, \"location\": \"market\", \"topic\": \"food\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"the market also sells fresh oranges\",\n",
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" metadata={\"id\": 4, \"location\": \"market\", \"topic\": \"food\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"the new art exhibit is fascinating\",\n",
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" metadata={\"id\": 5, \"location\": \"museum\", \"topic\": \"art\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"a sculpture exhibit is also at the museum\",\n",
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" metadata={\"id\": 6, \"location\": \"museum\", \"topic\": \"art\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"a new coffee shop opened on Main Street\",\n",
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" metadata={\"id\": 7, \"location\": \"Main Street\", \"topic\": \"food\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"the book club meets at the library\",\n",
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" metadata={\"id\": 8, \"location\": \"library\", \"topic\": \"reading\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"the library hosts a weekly story time for kids\",\n",
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" metadata={\"id\": 9, \"location\": \"library\", \"topic\": \"reading\"},\n",
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" ),\n",
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" Document(\n",
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" page_content=\"a cooking class for beginners is offered at the community center\",\n",
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" metadata={\"id\": 10, \"location\": \"community center\", \"topic\": \"classes\"},\n",
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" ),\n",
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"]"
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]
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]
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 6,
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"id": "73aa9124-9d49-4e10-8ed3-82255e7a4106",
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"metadata": {
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"metadata": {
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"ExecuteTime": {
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"tags": []
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"end_time": "2023-09-09T08:02:28.174088Z",
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},
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"start_time": "2023-09-09T08:02:28.162698Z"
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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}
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},
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],
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"outputs": [],
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"source": [
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"source": [
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"# PGVector needs the connection string to the database.\n",
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"vectorstore.add_documents(docs, ids=[doc.metadata[\"id\"] for doc in docs])"
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"CONNECTION_STRING = \"postgresql+psycopg2://harrisonchase@localhost:5432/test3\"\n",
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"\n",
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"# # Alternatively, you can create it from environment variables.\n",
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"# import os\n",
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"\n",
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"# CONNECTION_STRING = PGVector.connection_string_from_db_params(\n",
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"# driver=os.environ.get(\"PGVECTOR_DRIVER\", \"psycopg2\"),\n",
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"# host=os.environ.get(\"PGVECTOR_HOST\", \"localhost\"),\n",
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"# port=int(os.environ.get(\"PGVECTOR_PORT\", \"5432\")),\n",
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"# database=os.environ.get(\"PGVECTOR_DATABASE\", \"postgres\"),\n",
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"# user=os.environ.get(\"PGVECTOR_USER\", \"postgres\"),\n",
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"# password=os.environ.get(\"PGVECTOR_PASSWORD\", \"postgres\"),\n",
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"# )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"## Similarity Search with Euclidean Distance (Default)"
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]
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]
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 7,
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"id": "a5b2b71f-49eb-407d-b03a-dea4c0a517d6",
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"metadata": {
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"metadata": {
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"ExecuteTime": {
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"tags": []
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"end_time": "2023-09-09T08:04:16.696625Z",
|
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"start_time": "2023-09-09T08:02:31.817790Z"
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}
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},
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},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Document(page_content='there are cats in the pond', metadata={'id': 1, 'topic': 'animals', 'location': 'pond'}),\n",
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" Document(page_content='the book club meets at the library', metadata={'id': 8, 'topic': 'reading', 'location': 'library'}),\n",
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" Document(page_content='the library hosts a weekly story time for kids', metadata={'id': 9, 'topic': 'reading', 'location': 'library'}),\n",
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" Document(page_content='the new art exhibit is fascinating', metadata={'id': 5, 'topic': 'art', 'location': 'museum'}),\n",
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" Document(page_content='ducks are also found in the pond', metadata={'id': 2, 'topic': 'animals', 'location': 'pond'}),\n",
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" Document(page_content='the market also sells fresh oranges', metadata={'id': 4, 'topic': 'food', 'location': 'market'}),\n",
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" Document(page_content='a cooking class for beginners is offered at the community center', metadata={'id': 10, 'topic': 'classes', 'location': 'community center'}),\n",
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" Document(page_content='fresh apples are available at the market', metadata={'id': 3, 'topic': 'food', 'location': 'market'}),\n",
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" Document(page_content='a sculpture exhibit is also at the museum', metadata={'id': 6, 'topic': 'art', 'location': 'museum'}),\n",
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" Document(page_content='a new coffee shop opened on Main Street', metadata={'id': 7, 'topic': 'food', 'location': 'Main Street'})]"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"source": [
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"# The PGVector Module will try to create a table with the name of the collection.\n",
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"vectorstore.similarity_search(\"kitty\", k=10)"
|
||||||
"# So, make sure that the collection name is unique and the user has the permission to create a table.\n",
|
]
|
||||||
"\n",
|
},
|
||||||
"COLLECTION_NAME = \"state_of_the_union_test\"\n",
|
{
|
||||||
"\n",
|
"cell_type": "markdown",
|
||||||
"db = PGVector.from_documents(\n",
|
"id": "1d87a413-015a-4b46-a64e-332f30806524",
|
||||||
" embedding=embeddings,\n",
|
"metadata": {},
|
||||||
" documents=docs,\n",
|
"source": [
|
||||||
" collection_name=COLLECTION_NAME,\n",
|
"Adding documents by ID will over-write any existing documents that match that ID."
|
||||||
" connection_string=CONNECTION_STRING,\n",
|
|
||||||
")"
|
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 8,
|
"execution_count": 8,
|
||||||
|
"id": "13c69357-aaee-4de0-bcc2-7ab4419c920e",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"tags": []
|
||||||
"end_time": "2023-09-09T08:05:11.104135Z",
|
|
||||||
"start_time": "2023-09-09T08:05:10.548998Z"
|
|
||||||
}
|
|
||||||
},
|
},
|
||||||
"outputs": [],
|
"outputs": [],
|
||||||
"source": [
|
"source": [
|
||||||
"query = \"What did the president say about Ketanji Brown Jackson\"\n",
|
"docs = [\n",
|
||||||
"docs_with_score = db.similarity_search_with_score(query)"
|
" Document(\n",
|
||||||
|
" page_content=\"there are cats in the pond\",\n",
|
||||||
|
" metadata={\"id\": 1, \"location\": \"pond\", \"topic\": \"animals\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"ducks are also found in the pond\",\n",
|
||||||
|
" metadata={\"id\": 2, \"location\": \"pond\", \"topic\": \"animals\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"fresh apples are available at the market\",\n",
|
||||||
|
" metadata={\"id\": 3, \"location\": \"market\", \"topic\": \"food\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"the market also sells fresh oranges\",\n",
|
||||||
|
" metadata={\"id\": 4, \"location\": \"market\", \"topic\": \"food\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"the new art exhibit is fascinating\",\n",
|
||||||
|
" metadata={\"id\": 5, \"location\": \"museum\", \"topic\": \"art\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"a sculpture exhibit is also at the museum\",\n",
|
||||||
|
" metadata={\"id\": 6, \"location\": \"museum\", \"topic\": \"art\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"a new coffee shop opened on Main Street\",\n",
|
||||||
|
" metadata={\"id\": 7, \"location\": \"Main Street\", \"topic\": \"food\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"the book club meets at the library\",\n",
|
||||||
|
" metadata={\"id\": 8, \"location\": \"library\", \"topic\": \"reading\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"the library hosts a weekly story time for kids\",\n",
|
||||||
|
" metadata={\"id\": 9, \"location\": \"library\", \"topic\": \"reading\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
" Document(\n",
|
||||||
|
" page_content=\"a cooking class for beginners is offered at the community center\",\n",
|
||||||
|
" metadata={\"id\": 10, \"location\": \"community center\", \"topic\": \"classes\"},\n",
|
||||||
|
" ),\n",
|
||||||
|
"]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "59f82250-7903-4279-8300-062542c83416",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Filtering Support\n",
|
||||||
|
"\n",
|
||||||
|
"The vectorstore supports a set of filters that can be applied against the metadata fields of the documents.\n",
|
||||||
|
"\n",
|
||||||
|
"| Operator | Meaning/Category |\n",
|
||||||
|
"|----------|-------------------------|\n",
|
||||||
|
"| \\$eq | Equality (==) |\n",
|
||||||
|
"| \\$ne | Inequality (!=) |\n",
|
||||||
|
"| \\$lt | Less than (<) |\n",
|
||||||
|
"| \\$lte | Less than or equal (<=) |\n",
|
||||||
|
"| \\$gt | Greater than (>) |\n",
|
||||||
|
"| \\$gte | Greater than or equal (>=) |\n",
|
||||||
|
"| \\$in | Special Cased (in) |\n",
|
||||||
|
"| \\$nin | Special Cased (not in) |\n",
|
||||||
|
"| \\$between | Special Cased (between) |\n",
|
||||||
|
"| \\$like | Text (like) |\n",
|
||||||
|
"| \\$ilike | Text (case-insensitive like) |\n",
|
||||||
|
"| \\$and | Logical (and) |\n",
|
||||||
|
"| \\$or | Logical (or) |"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 9,
|
"execution_count": 9,
|
||||||
|
"id": "f15a2359-6dc3-4099-8214-785f167a9ca4",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"tags": []
|
||||||
"end_time": "2023-09-09T08:05:13.532334Z",
|
|
||||||
"start_time": "2023-09-09T08:05:13.523191Z"
|
|
||||||
}
|
|
||||||
},
|
},
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"name": "stdout",
|
"data": {
|
||||||
"output_type": "stream",
|
"text/plain": [
|
||||||
"text": [
|
"[Document(page_content='there are cats in the pond', metadata={'id': 1, 'topic': 'animals', 'location': 'pond'}),\n",
|
||||||
"--------------------------------------------------------------------------------\n",
|
" Document(page_content='the library hosts a weekly story time for kids', metadata={'id': 9, 'topic': 'reading', 'location': 'library'}),\n",
|
||||||
"Score: 0.18456886638850434\n",
|
" Document(page_content='the new art exhibit is fascinating', metadata={'id': 5, 'topic': 'art', 'location': 'museum'}),\n",
|
||||||
"Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
|
" Document(page_content='ducks are also found in the pond', metadata={'id': 2, 'topic': 'animals', 'location': 'pond'})]"
|
||||||
"\n",
|
]
|
||||||
"Tonight, I’d 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",
|
},
|
||||||
"\n",
|
"execution_count": 9,
|
||||||
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
|
"metadata": {},
|
||||||
"\n",
|
"output_type": "execute_result"
|
||||||
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.21742627672631343\n",
|
|
||||||
"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 she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by Democrats and Republicans. \n",
|
|
||||||
"\n",
|
|
||||||
"And if we are to advance liberty and justice, we need to secure the Border and fix the immigration system. \n",
|
|
||||||
"\n",
|
|
||||||
"We can do both. At our border, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. \n",
|
|
||||||
"\n",
|
|
||||||
"We’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. \n",
|
|
||||||
"\n",
|
|
||||||
"We’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. \n",
|
|
||||||
"\n",
|
|
||||||
"We’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.22641793174529334\n",
|
|
||||||
"And for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. \n",
|
|
||||||
"\n",
|
|
||||||
"As 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",
|
|
||||||
"\n",
|
|
||||||
"While it often appears that we never agree, that isn’t 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",
|
|
||||||
"\n",
|
|
||||||
"And soon, we’ll 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",
|
|
||||||
"\n",
|
|
||||||
"So tonight I’m offering a Unity Agenda for the Nation. Four big things we can do together. \n",
|
|
||||||
"\n",
|
|
||||||
"First, beat the opioid epidemic.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.22670040608054465\n",
|
|
||||||
"Tonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers. \n",
|
|
||||||
"\n",
|
|
||||||
"And as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up. \n",
|
|
||||||
"\n",
|
|
||||||
"That ends on my watch. \n",
|
|
||||||
"\n",
|
|
||||||
"Medicare is going to set higher standards for nursing homes and make sure your loved ones get the care they deserve and expect. \n",
|
|
||||||
"\n",
|
|
||||||
"We’ll also cut costs and keep the economy going strong by giving workers a fair shot, provide more training and apprenticeships, hire them based on their skills not degrees. \n",
|
|
||||||
"\n",
|
|
||||||
"Let’s pass the Paycheck Fairness Act and paid leave. \n",
|
|
||||||
"\n",
|
|
||||||
"Raise the minimum wage to $15 an hour and extend the Child Tax Credit, so no one has to raise a family in poverty. \n",
|
|
||||||
"\n",
|
|
||||||
"Let’s increase Pell Grants and increase our historic support of HBCUs, and invest in what Jill—our First Lady who teaches full-time—calls America’s best-kept secret: community colleges.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n"
|
|
||||||
]
|
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"for doc, score in docs_with_score:\n",
|
"vectorstore.similarity_search(\"kitty\", k=10, filter={\"id\": {\"$in\": [1, 5, 2, 9]}})"
|
||||||
" print(\"-\" * 80)\n",
|
|
||||||
" print(\"Score: \", score)\n",
|
|
||||||
" print(doc.page_content)\n",
|
|
||||||
" print(\"-\" * 80)"
|
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "markdown",
|
"cell_type": "markdown",
|
||||||
"metadata": {
|
"id": "d92ea049-1b1f-4ae9-9525-35750fe2e52e",
|
||||||
"collapsed": false
|
"metadata": {},
|
||||||
},
|
|
||||||
"source": [
|
"source": [
|
||||||
"## Maximal Marginal Relevance Search (MMR)\n",
|
"If you provide a dict with multiple fields, but no operators, the top level will be interpreted as a logical **AND** filter"
|
||||||
"Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents."
|
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 10,
|
"execution_count": 10,
|
||||||
|
"id": "88f919e4-e4b0-4b5f-99b3-24c675c26d33",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"tags": []
|
||||||
"end_time": "2023-09-09T08:05:23.276819Z",
|
|
||||||
"start_time": "2023-09-09T08:05:21.972256Z"
|
|
||||||
},
|
|
||||||
"collapsed": false
|
|
||||||
},
|
},
|
||||||
"outputs": [],
|
"outputs": [
|
||||||
|
{
|
||||||
|
"data": {
|
||||||
|
"text/plain": [
|
||||||
|
"[Document(page_content='ducks are also found in the pond', metadata={'id': 2, 'topic': 'animals', 'location': 'pond'}),\n",
|
||||||
|
" Document(page_content='there are cats in the pond', metadata={'id': 1, 'topic': 'animals', 'location': 'pond'})]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"execution_count": 10,
|
||||||
|
"metadata": {},
|
||||||
|
"output_type": "execute_result"
|
||||||
|
}
|
||||||
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"docs_with_score = db.max_marginal_relevance_search_with_score(query)"
|
"vectorstore.similarity_search(\n",
|
||||||
|
" \"ducks\",\n",
|
||||||
|
" k=10,\n",
|
||||||
|
" filter={\"id\": {\"$in\": [1, 5, 2, 9]}, \"location\": {\"$in\": [\"pond\", \"market\"]}},\n",
|
||||||
|
")"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 11,
|
"execution_count": 11,
|
||||||
|
"id": "88f423a4-6575-4fb8-9be2-a3da01106591",
|
||||||
"metadata": {
|
"metadata": {
|
||||||
"ExecuteTime": {
|
"tags": []
|
||||||
"end_time": "2023-09-09T08:05:27.478580Z",
|
|
||||||
"start_time": "2023-09-09T08:05:27.470138Z"
|
|
||||||
},
|
|
||||||
"collapsed": false
|
|
||||||
},
|
},
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.18453882564037527\n",
|
|
||||||
"Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n",
|
|
||||||
"\n",
|
|
||||||
"Tonight, I’d 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",
|
|
||||||
"\n",
|
|
||||||
"One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n",
|
|
||||||
"\n",
|
|
||||||
"And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.23523731441720075\n",
|
|
||||||
"We can’t change how divided we’ve been. But we can change how we move forward—on COVID-19 and other issues we must face together. \n",
|
|
||||||
"\n",
|
|
||||||
"I recently visited the New York City Police Department days after the funerals of Officer Wilbert Mora and his partner, Officer Jason Rivera. \n",
|
|
||||||
"\n",
|
|
||||||
"They were responding to a 9-1-1 call when a man shot and killed them with a stolen gun. \n",
|
|
||||||
"\n",
|
|
||||||
"Officer Mora was 27 years old. \n",
|
|
||||||
"\n",
|
|
||||||
"Officer Rivera was 22. \n",
|
|
||||||
"\n",
|
|
||||||
"Both Dominican Americans who’d grown up on the same streets they later chose to patrol as police officers. \n",
|
|
||||||
"\n",
|
|
||||||
"I spoke with their families and told them that we are forever in debt for their sacrifice, and we will carry on their mission to restore the trust and safety every community deserves. \n",
|
|
||||||
"\n",
|
|
||||||
"I’ve worked on these issues a long time. \n",
|
|
||||||
"\n",
|
|
||||||
"I know what works: Investing in crime prevention and community police officers who’ll walk the beat, who’ll know the neighborhood, and who can restore trust and safety.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.2448441215698569\n",
|
|
||||||
"One was stationed at bases and breathing in toxic smoke from “burn pits” that incinerated wastes of war—medical and hazard material, jet fuel, and more. \n",
|
|
||||||
"\n",
|
|
||||||
"When they came home, many of the world’s fittest and best trained warriors were never the same. \n",
|
|
||||||
"\n",
|
|
||||||
"Headaches. Numbness. Dizziness. \n",
|
|
||||||
"\n",
|
|
||||||
"A cancer that would put them in a flag-draped coffin. \n",
|
|
||||||
"\n",
|
|
||||||
"I know. \n",
|
|
||||||
"\n",
|
|
||||||
"One of those soldiers was my son Major Beau Biden. \n",
|
|
||||||
"\n",
|
|
||||||
"We don’t know for sure if a burn pit was the cause of his brain cancer, or the diseases of so many of our troops. \n",
|
|
||||||
"\n",
|
|
||||||
"But I’m committed to finding out everything we can. \n",
|
|
||||||
"\n",
|
|
||||||
"Committed to military families like Danielle Robinson from Ohio. \n",
|
|
||||||
"\n",
|
|
||||||
"The widow of Sergeant First Class Heath Robinson. \n",
|
|
||||||
"\n",
|
|
||||||
"He was born a soldier. Army National Guard. Combat medic in Kosovo and Iraq. \n",
|
|
||||||
"\n",
|
|
||||||
"Stationed near Baghdad, just yards from burn pits the size of football fields. \n",
|
|
||||||
"\n",
|
|
||||||
"Heath’s widow Danielle is here with us tonight. They loved going to Ohio State football games. He loved building Legos with their daughter.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"--------------------------------------------------------------------------------\n",
|
|
||||||
"Score: 0.2513994424701056\n",
|
|
||||||
"And I’m taking robust action to make sure the pain of our sanctions is targeted at Russia’s economy. And I will use every tool at our disposal to protect American businesses and consumers. \n",
|
|
||||||
"\n",
|
|
||||||
"Tonight, I can announce that the United States has worked with 30 other countries to release 60 Million barrels of oil from reserves around the world. \n",
|
|
||||||
"\n",
|
|
||||||
"America will lead that effort, releasing 30 Million barrels from our own Strategic Petroleum Reserve. And we stand ready to do more if necessary, unified with our allies. \n",
|
|
||||||
"\n",
|
|
||||||
"These steps will help blunt gas prices here at home. And I know the news about what’s happening can seem alarming. \n",
|
|
||||||
"\n",
|
|
||||||
"But I want you to know that we are going to be okay. \n",
|
|
||||||
"\n",
|
|
||||||
"When the history of this era is written Putin’s war on Ukraine will have left Russia weaker and the rest of the world stronger. \n",
|
|
||||||
"\n",
|
|
||||||
"While it shouldn’t have taken something so terrible for people around the world to see what’s at stake now everyone sees it clearly.\n",
|
|
||||||
"--------------------------------------------------------------------------------\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"for doc, score in docs_with_score:\n",
|
|
||||||
" print(\"-\" * 80)\n",
|
|
||||||
" print(\"Score: \", score)\n",
|
|
||||||
" print(doc.page_content)\n",
|
|
||||||
" print(\"-\" * 80)"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "markdown",
|
|
||||||
"metadata": {},
|
|
||||||
"source": [
|
|
||||||
"## Working with vectorstore\n",
|
|
||||||
"\n",
|
|
||||||
"Above, we created a vectorstore from scratch. However, often times we want to work with an existing vectorstore.\n",
|
|
||||||
"In order to do that, we can initialize it directly."
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 8,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"store = PGVector(\n",
|
|
||||||
" collection_name=COLLECTION_NAME,\n",
|
|
||||||
" connection_string=CONNECTION_STRING,\n",
|
|
||||||
" embedding_function=embeddings,\n",
|
|
||||||
")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "markdown",
|
|
||||||
"metadata": {},
|
|
||||||
"source": [
|
|
||||||
"### Add documents\n",
|
|
||||||
"We can add documents to the existing vectorstore."
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 19,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"['048c2e14-1cf3-11ee-8777-e65801318980']"
|
"[Document(page_content='ducks are also found in the pond', metadata={'id': 2, 'topic': 'animals', 'location': 'pond'}),\n",
|
||||||
|
" Document(page_content='there are cats in the pond', metadata={'id': 1, 'topic': 'animals', 'location': 'pond'})]"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 19,
|
"execution_count": 11,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"store.add_documents([Document(page_content=\"foo\")])"
|
"vectorstore.similarity_search(\n",
|
||||||
]
|
" \"ducks\",\n",
|
||||||
},
|
" k=10,\n",
|
||||||
{
|
" filter={\n",
|
||||||
"cell_type": "code",
|
" \"$and\": [\n",
|
||||||
"execution_count": 20,
|
" {\"id\": {\"$in\": [1, 5, 2, 9]}},\n",
|
||||||
"metadata": {},
|
" {\"location\": {\"$in\": [\"pond\", \"market\"]}},\n",
|
||||||
"outputs": [],
|
" ]\n",
|
||||||
"source": [
|
" },\n",
|
||||||
"docs_with_score = db.similarity_search_with_score(\"foo\")"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 21,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"(Document(page_content='foo', metadata={}), 3.3203430005457335e-09)"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 21,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"docs_with_score[0]"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 22,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"data": {
|
|
||||||
"text/plain": [
|
|
||||||
"(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 she’s been nominated, she’s 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, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. \\n\\nWe’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. \\n\\nWe’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. \\n\\nWe’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders.', metadata={'source': '../../../state_of_the_union.txt'}),\n",
|
|
||||||
" 0.2404395365581814)"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
"execution_count": 22,
|
|
||||||
"metadata": {},
|
|
||||||
"output_type": "execute_result"
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"docs_with_score[1]"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "markdown",
|
|
||||||
"metadata": {},
|
|
||||||
"source": [
|
|
||||||
"### Overriding a vectorstore\n",
|
|
||||||
"\n",
|
|
||||||
"If you have an existing collection, you override it by doing `from_documents` and setting `pre_delete_collection` = True"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 23,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"db = PGVector.from_documents(\n",
|
|
||||||
" documents=docs,\n",
|
|
||||||
" embedding=embeddings,\n",
|
|
||||||
" collection_name=COLLECTION_NAME,\n",
|
|
||||||
" connection_string=CONNECTION_STRING,\n",
|
|
||||||
" pre_delete_collection=True,\n",
|
|
||||||
")"
|
")"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
{
|
{
|
||||||
"cell_type": "code",
|
"cell_type": "code",
|
||||||
"execution_count": 24,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"id": "65133340-2acd-4957-849e-029b6b5d60f0",
|
||||||
"outputs": [],
|
"metadata": {
|
||||||
"source": [
|
"tags": []
|
||||||
"docs_with_score = db.similarity_search_with_score(\"foo\")"
|
},
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 25,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
"outputs": [
|
||||||
{
|
{
|
||||||
"data": {
|
"data": {
|
||||||
"text/plain": [
|
"text/plain": [
|
||||||
"(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 she’s been nominated, she’s 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, we’ve installed new technology like cutting-edge scanners to better detect drug smuggling. \\n\\nWe’ve set up joint patrols with Mexico and Guatemala to catch more human traffickers. \\n\\nWe’re putting in place dedicated immigration judges so families fleeing persecution and violence can have their cases heard faster. \\n\\nWe’re securing commitments and supporting partners in South and Central America to host more refugees and secure their own borders.', metadata={'source': '../../../state_of_the_union.txt'}),\n",
|
"[Document(page_content='the book club meets at the library', metadata={'id': 8, 'topic': 'reading', 'location': 'library'}),\n",
|
||||||
" 0.2404115088144465)"
|
" Document(page_content='the new art exhibit is fascinating', metadata={'id': 5, 'topic': 'art', 'location': 'museum'}),\n",
|
||||||
|
" Document(page_content='the library hosts a weekly story time for kids', metadata={'id': 9, 'topic': 'reading', 'location': 'library'}),\n",
|
||||||
|
" Document(page_content='a sculpture exhibit is also at the museum', metadata={'id': 6, 'topic': 'art', 'location': 'museum'}),\n",
|
||||||
|
" Document(page_content='the market also sells fresh oranges', metadata={'id': 4, 'topic': 'food', 'location': 'market'}),\n",
|
||||||
|
" Document(page_content='a cooking class for beginners is offered at the community center', metadata={'id': 10, 'topic': 'classes', 'location': 'community center'}),\n",
|
||||||
|
" Document(page_content='a new coffee shop opened on Main Street', metadata={'id': 7, 'topic': 'food', 'location': 'Main Street'}),\n",
|
||||||
|
" Document(page_content='fresh apples are available at the market', metadata={'id': 3, 'topic': 'food', 'location': 'market'})]"
|
||||||
]
|
]
|
||||||
},
|
},
|
||||||
"execution_count": 25,
|
"execution_count": 12,
|
||||||
"metadata": {},
|
"metadata": {},
|
||||||
"output_type": "execute_result"
|
"output_type": "execute_result"
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
"source": [
|
"source": [
|
||||||
"docs_with_score[0]"
|
"vectorstore.similarity_search(\"bird\", k=10, filter={\"location\": {\"$ne\": \"pond\"}})"
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "markdown",
|
|
||||||
"metadata": {},
|
|
||||||
"source": [
|
|
||||||
"### Using a VectorStore as a Retriever"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 26,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [],
|
|
||||||
"source": [
|
|
||||||
"retriever = store.as_retriever()"
|
|
||||||
]
|
|
||||||
},
|
|
||||||
{
|
|
||||||
"cell_type": "code",
|
|
||||||
"execution_count": 27,
|
|
||||||
"metadata": {},
|
|
||||||
"outputs": [
|
|
||||||
{
|
|
||||||
"name": "stdout",
|
|
||||||
"output_type": "stream",
|
|
||||||
"text": [
|
|
||||||
"tags=None metadata=None vectorstore=<langchain_community.vectorstores.pgvector.PGVector object at 0x29f94f880> search_type='similarity' search_kwargs={}\n"
|
|
||||||
]
|
|
||||||
}
|
|
||||||
],
|
|
||||||
"source": [
|
|
||||||
"print(retriever)"
|
|
||||||
]
|
]
|
||||||
}
|
}
|
||||||
],
|
],
|
||||||
@ -612,9 +457,9 @@
|
|||||||
"name": "python",
|
"name": "python",
|
||||||
"nbconvert_exporter": "python",
|
"nbconvert_exporter": "python",
|
||||||
"pygments_lexer": "ipython3",
|
"pygments_lexer": "ipython3",
|
||||||
"version": "3.9.1"
|
"version": "3.11.4"
|
||||||
}
|
}
|
||||||
},
|
},
|
||||||
"nbformat": 4,
|
"nbformat": 4,
|
||||||
"nbformat_minor": 4
|
"nbformat_minor": 5
|
||||||
}
|
}
|
||||||
|
|||||||
Loading…
Reference in New Issue
Block a user