{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Embeddings\n", "\n", "获取给定输入的向量表示形式，机器学习模型和算法可以轻松使用该表示形式。" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "ename": "ZeroDivisionError", "evalue": "division by zero", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", "\u001b[1;32me:\\GPTProject\\docs\\source\\examples\\test-Embeddings.ipynb Cell 2\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[39m1\u001b[39;49m\u001b[39m/\u001b[39;49m\u001b[39m0\u001b[39;49m\n", "\u001b[1;31mZeroDivisionError\u001b[0m: division by zero" ] } ], "source": [ "1/0\n", "## 让后面的代码不执行" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Create embeddings\n", " `` https://api.openai.com/v1/embeddings``\n", "\n", "创建表示输入文本的嵌入向量。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "| 参数名称 | 类型 | 是否必须 | 默认值 | 描述 |\n", "| --- | --- | --- | --- | --- |\n", "| model | string | Required |-| 要使用的模型的 ID。您可以使用 List models API 查看所有可用模型，或查看我们的模型概述以获取它们的描述。|\n", "| input | string or array | Required |-| 要获取嵌入的输入文本，编码为字符串或令牌数组。要在单个请求中获取多个输入的嵌入，请传递字符串数组或令牌数组数组。每个输入长度不得超过 8192 个令牌。|\n", "| user | string | Optional |-| 表示您的最终用户的唯一标识符，可帮助 OpenAI 监控和检测滥用。|" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ " JSON: {\n", " \"data\": [\n", " {\n", " \"embedding\": [\n", " 0.002235695719718933,\n", " -0.009273056872189045,\n", " 0.0158150065690279,\n", " -0.007805881090462208,\n", " -0.004738150630146265,\n", " 0.014824187383055687,\n", " -0.00978752039372921,\n", " -0.03828629106283188,\n", " -0.00685316976159811,\n", " -0.02870836667716503,\n", " 0.025291308760643005,\n", " 0.018152326345443726,\n", " -0.003636181354522705,\n", " -0.025532662868499756,\n", " 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"openai.Embedding.create(\n", " model=\"text-embedding-ada-002\",\n", " input=\"The food was delicious and the waiter...\"\n", ")\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3.10.4 64-bit", "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": "3.10.4" }, "vscode": { "interpreter": { "hash": "369f2c481f4da34e4445cda3fffd2e751bd1c4d706f27375911949ba6bb62e1c" } } }, "nbformat": 4, "nbformat_minor": 4 }