From bc028294d0c6563482d512d8a18295f23bb508e0 Mon Sep 17 00:00:00 2001
From: aditya thomas <aditya.thomas@alum.mit.edu>
Date: Sat, 23 Mar 2024 02:32:59 +0530
Subject: [PATCH] docs: delete mistralai embeddings doc from incorrect location
 (#19432)

**Description:** Delete MistralAIEmbeddings usage document from folder
partners/mistralai/docs
**Issue:** The document is present in the folder docs/docs
**Dependencies:** None
---
 libs/partners/mistralai/docs/embeddings.ipynb | 103 ------------------
 1 file changed, 103 deletions(-)
 delete mode 100644 libs/partners/mistralai/docs/embeddings.ipynb

diff --git a/libs/partners/mistralai/docs/embeddings.ipynb b/libs/partners/mistralai/docs/embeddings.ipynb
deleted file mode 100644
index 33ed1137fd..0000000000
--- a/libs/partners/mistralai/docs/embeddings.ipynb
+++ /dev/null
@@ -1,103 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "b14a24db",
-   "metadata": {},
-   "source": [
-    "# MistralAIEmbeddings\n",
-    "\n",
-    "This notebook explains how to use MistralAIEmbeddings, which is included in the langchain_mistralai package, to embed texts in langchain."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "0ab948fc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# pip install -U langchain-mistralai"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "67c637ca",
-   "metadata": {},
-   "source": [
-    "## import the library"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "5709b030",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_mistralai import MistralAIEmbeddings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "1756b1ba",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "embedding = MistralAIEmbeddings(mistral_api_key='your-api-key')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "4a2a098d",
-   "metadata": {},
-   "source": [
-    "# Using the Embedding Model\n",
-    "With `MistralAIEmbeddings`, you can directly use the default model 'mistral-embed', or set a different one if available."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "584b9af5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "embedding.model = 'mistral-embed'  # or your preferred model if available"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "be18b873",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "res_query = embedding.embed_query(\"The test information\")\n",
-    "res_document = embedding.embed_documents([\"test1\", \"another test\"])"
-   ]
-  }
- ],
- "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": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}