SVM retriever (#2947) (#2949)

Add SVM retriever class, based on
https://github.com/karpathy/randomfun/blob/master/knn_vs_svm.ipynb.

Testing still WIP, but the logic is correct (I have a local
implementation outside of Langchain working).

---------

Co-authored-by: Lance Martin <122662504+PineappleExpress808@users.noreply.github.com>
Co-authored-by: rlm <31treehaus@31s-MacBook-Pro.local>

docs/modules/indexes/retrievers/examples/svm_retriever.ipynb

@@ -0,0 +1,128 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "ab66dd43",
+   "metadata": {},
+   "source": [
+    "# SVM Retriever\n",
+    "\n",
+    "This notebook goes over how to use a retriever that under the hood uses an SVM using scikit-learn.\n",
+    "\n",
+    "Largely based on https://github.com/karpathy/randomfun/blob/master/knn_vs_svm.ipynb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "393ac030",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.retrievers import SVMRetriever\n",
+    "from langchain.embeddings import OpenAIEmbeddings"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a801b57c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# !pip install scikit-learn"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aaf80e7f",
+   "metadata": {},
+   "source": [
+    "## Create New Retriever with Texts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "98b1c017",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "retriever = SVMRetriever.from_texts([\"foo\", \"bar\", \"world\", \"hello\", \"foo bar\"], OpenAIEmbeddings())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08437fa2",
+   "metadata": {},
+   "source": [
+    "## Use Retriever\n",
+    "\n",
+    "We can now use the retriever!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c0455218",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = retriever.get_relevant_documents(\"foo\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7dfa5c29",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Document(page_content='foo', metadata={}),\n",
+       " Document(page_content='foo bar', metadata={}),\n",
+       " Document(page_content='hello', metadata={}),\n",
+       " Document(page_content='world', metadata={})]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "74bd9256",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}