{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# DuckDB\n", "This notebook shows how to use `DuckDB` as a vector store." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "! pip install duckdb" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We want to use OpenAIEmbeddings so we have to get the OpenAI API Key. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import getpass\n", "import os\n", "\n", "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from langchain.embeddings import OpenAIEmbeddings\n", "from langchain.vectorstores import DuckDB" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from langchain.document_loaders import TextLoader\n", "from langchain_text_splitters import CharacterTextSplitter\n", "\n", "loader = TextLoader(\"../../modules/state_of_the_union.txt\")\n", "documents = loader.load()\n", "\n", "documents = CharacterTextSplitter().split_documents(documents)\n", "embeddings = OpenAIEmbeddings()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "docsearch = DuckDB.from_documents(documents, embeddings)\n", "\n", "query = \"What did the president say about Ketanji Brown Jackson\"\n", "docs = docsearch.similarity_search(query)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(docs[0].page_content)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.2" } }, "nbformat": 4, "nbformat_minor": 2 }