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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 项目介绍\n",
"ERNIE Bot SDK提供便捷易用的接口，可以调用文心大模型的能力，包含文本创作、通用对话、语义向量、AI作图等。\n",
"\n",
"使用步骤可以大致分为`安装-认证鉴权-模型调用`三个步骤。\n",
"\n",
"在模型调用方面目前主要提供有四类功能：对话补全(Chat Completion)，函数调用(Function Calling)，文本嵌入(Embedding)，文生图(Image Generation)。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 1. 安装\n",
"快速安装Python语言的最新版本ERNIE Bot SDK（要求Python >= 3.8)。"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: erniebot in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (0.4.0)\n",
"Requirement already satisfied: aiohttp in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (3.8.6)\n",
"Requirement already satisfied: bce-python-sdk in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (0.8.92)\n",
"Requirement already satisfied: colorlog in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (6.7.0)\n",
"Requirement already satisfied: jsonschema>=4.19 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (4.19.2)\n",
"Requirement already satisfied: requests>=2.20 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (2.31.0)\n",
"Requirement already satisfied: typing-extensions in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from erniebot) (4.8.0)\n",
"Requirement already satisfied: attrs>=22.2.0 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from jsonschema>=4.19->erniebot) (23.1.0)\n",
"Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from jsonschema>=4.19->erniebot) (2023.7.1)\n",
"Requirement already satisfied: referencing>=0.28.4 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from jsonschema>=4.19->erniebot) (0.30.2)\n",
"Requirement already satisfied: rpds-py>=0.7.1 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from jsonschema>=4.19->erniebot) (0.12.0)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from requests>=2.20->erniebot) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from requests>=2.20->erniebot) (3.4)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from requests>=2.20->erniebot) (2.0.7)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from requests>=2.20->erniebot) (2023.7.22)\n",
"Requirement already satisfied: multidict<7.0,>=4.5 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from aiohttp->erniebot) (6.0.4)\n",
"Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from aiohttp->erniebot) (4.0.3)\n",
"Requirement already satisfied: yarl<2.0,>=1.0 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from aiohttp->erniebot) (1.9.2)\n",
"Requirement already satisfied: frozenlist>=1.1.1 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from aiohttp->erniebot) (1.4.0)\n",
"Requirement already satisfied: aiosignal>=1.1.2 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from aiohttp->erniebot) (1.3.1)\n",
"Requirement already satisfied: pycryptodome>=3.8.0 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from bce-python-sdk->erniebot) (3.19.0)\n",
"Requirement already satisfied: future>=0.6.0 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from bce-python-sdk->erniebot) (0.18.3)\n",
"Requirement already satisfied: six>=1.4.0 in /opt/anaconda3/envs/ernie/lib/python3.10/site-packages (from bce-python-sdk->erniebot) (1.16.0)\n"
]
}
],
"source": [
"!pip install erniebot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 2. 认证鉴权\n",
"\n",
"使用ERNIE Bot SDK之前，请首先申请并设置鉴权参数，详情参考[认证鉴权](../../docs/authentication.md)。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 3. 参数配置\n",
"ERNIE Bot SDK参数配置，主要涉及认证鉴权、后端平台等信息，详情参考[参数配置](../../docs/configuration.md)。\n",
"\n",
"\n",
"**注意事项**：\n",
"* AI Studio每个账户的access token，有100万token的免费额度，可以用于ERNIE Bot SDK调用文心一言大模型。\n",
"* 在[token管理页面](https://aistudio.baidu.com/token/manage)可以查看token获取、消耗明细和过期记录，或者购买更多token。\n",
"* access token是私密信息，切记不要对外公开。"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"1. 如果使用AI Studio（推荐使用），可以在个人中心的[访问令牌页面](https://aistudio.baidu.com/usercenter/token)获取用户凭证access token。"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import erniebot\n",
"\n",
"erniebot.api_type = 'aistudio'\n",
"# 通过使用全局变量设置鉴权信息\n",
"erniebot.access_token = '<eb-access-token>'\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"2. 如果使用qianfan，在完成创建千帆应用后， 在[控制台](https://console.bce.baidu.com/qianfan/ais/console/applicationConsole/application)创建千帆应用，可以获取到API key与secret key。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import erniebot\n",
"\n",
"erniebot.api_type = 'qianfan'\n",
"erniebot.access_token = None # Option\n",
"\n",
"# 通过使用全局变量设置鉴权信息\n",
"erniebot.ak = '<eb-ak>'\n",
"erniebot.sk = '<eb-sk>'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"3. 如果使用yinian（AI绘画功能），先需在智能创作页面中[开通AI绘画服务](https://console.bce.baidu.com/ai/#/ai/intelligentwriting/overview/index),激活AI绘画-高级功能后，进入在智能创作平台 - [应用页面](https://console.bce.baidu.com/ai/#/ai/intelligentwriting/app/list)，创建应用，可以拿到API key和secret key。"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import erniebot\n",
"\n",
"erniebot.api_type = 'yinian'\n",
"erniebot.access_token = None # Option\n",
"\n",
"# 直接使用全局变量设置鉴权信息\n",
"erniebot.ak = '<eb-ak>'\n",
"erniebot.sk = '<eb-sk>'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 4. 模型总览\n",
"\n",
"完成好上述步骤之后，就可以根据需求调用相关模型，ERNIE Bot SDK支持的所有模型如下：\n",
"\n",
"| 模型名称 | 说明 | 功能 | 支持该模型的后端 | 输入token数量上限 |\n",
"|:--- | :--- | :--- | :--- | :--- |\n",
"| ernie-bot | 文心一言模型。具备优秀的知识增强和内容生成能力，在文本创作、问答、推理和代码生成等方面表现出色。 | 对话补全，函数调用 | qianfan，aistudio | 3000 |\n",
"| ernie-bot-turbo | 文心一言模型。相比erniebot模型具备更快的响应速度和学习能力，API调用成本更低。 | 对话补全 | qianfan，aistudio | 3000 |\n",
"| ernie-bot-4 | 文心一言模型。基于文心大模型4.0版本的文心一言，具备目前文心一言系列模型中最优的理解和生成能力。 | 对话补全，函数调用 | qianfan，aistudio | 3000 |\n",
"| ernie-bot-8k | 文心一言模型。在ernie-bot模型的基础上增强了对长对话上下文的支持，输入token数量上限为7000。 | 对话补全，函数调用 | qianfan，aistudio | 7000 |\n",
"| ernie-text-embedding | 文心百中语义模型。支持计算最多384个token的文本的向量表示。 | 语义向量 | qianfan，aistudio | 384*16 |\n",
"| ernie-vilg-v2 | 文心一格模型。 | 文生图 | yinian | 200 |"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"API名称：ernie-bot, 模型名称：文心一言旗舰版\n",
"API名称：ernie-bot-turbo, 模型名称：文心一言轻量版\n",
"API名称：ernie-bot-4, 模型名称：基于文心大模型4.0版本的文心一言\n",
"API名称：ernie-text-embedding, 模型名称：文心百中语义模型\n",
"API名称：ernie-vilg-v2, 模型名称：文心一格模型\n"
]
}
],
"source": [
"import erniebot\n",
"# 您也可以通过命令查找模型\n",
"models = erniebot.Model.list()\n",
"for i in range(len(models)):\n",
" print(f\"API名称：{models[i][0]}, 模型名称：{models[i][1]}\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 5. 快速开始"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5.1 对话补全(Chat Completion)\n",
"文心一言系列对话模型可以理解自然语言，并以文本输出与用户进行对话。将对话上下文与输入文本提供给模型，由模型给出新的回复，即为对话补全。对话补全功能可应用于广泛的实际场景，例如对话沟通、内容创作、分析控制、函数调用等。"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"您好，我是文心一言，英文名是ERNIE Bot。我能够与人对话互动，回答问题，协助创作，高效便捷地帮助人们获取信息、知识和灵感。\n"
]
}
],
"source": [
"import erniebot\n",
"erniebot.api_type = 'aistudio'\n",
"erniebot.access_token = '<eb-access-token>'\n",
"\n",
"chat_message = [\n",
" {'role': 'user', 'content': \"你好，请介绍一下你自己\"}\n",
"]\n",
"response = erniebot.ChatCompletion.create(model='ernie-bot-4', \n",
" messages=chat_message)\n",
"\n",
"# 使用response.get_result()获得模型返回结果\n",
"print(response.get_result())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5.2 文本嵌入(Embedding)\n",
"文本向量，是指将一段文本，转化为一定维度的向量（文心百中语义模型中为384维），其中相近语义、相关主题的文本在向量空间更接近。拥有一个良好的文本嵌入特征，对于文本可视化、检索、聚类、内容审核等下游任务，有着重要的意义，目前API接口可接受的batch_size单次最多支持16个，每段文本最多支持384token。"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"import erniebot\n",
"erniebot.api_type = 'aistudio'\n",
"erniebot.access_token = '<eb-access-token>'\n",
"\n",
"# 将需要向量化的文本转化为list[str]输入\n",
"response = erniebot.Embedding.create(\n",
" model='ernie-text-embedding',\n",
" input=[\n",
" \"我是百度公司开发的人工智能语言模型，我的中文名是文心一言，英文名是ERNIE-Bot，可以协助您完成范围广泛的任务并提供有关各种主题的信息，比如回答问题，提供定义和解释及建议。如果您有任何问题，请随时向我提问。\",\n",
" \"2018年深圳市各区GDP\"\n",
" ])\n",
"\n",
"# 使用response.get_result()获得模型返回结果，维度为(n,384)\n",
"print(response.get_result())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 5.3 文生图(Image Generation)\n",
"\n",
"文生图是指根据文本提示、图像尺寸等信息，使用文心大模型，自动创作图片。\n",
"\n",
"ERNIE Bot SDK提供具备文生图能力的**ernie-vilg-v2**大模型。"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<img src=\"http://aigc-t2p.bj.bcebos.com/artist-long/118470787_0_final.png?authorization=bce-auth-v1%2F174bf5e9a7a84f55a8e85b1cc5d62b1d%2F2023-11-07T08%3A51%3A28Z%2F3600%2Fhost%2F8e4c096243272e66afd4713ef58bdf9e82a8e34635c37133c804ff13a7671b56\"/>"
],
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import erniebot\n",
"from IPython.display import Image\n",
"\n",
"# 注意需api_type与Chat Completion和Embedding不同\n",
"erniebot.api_type = 'yinian'\n",
"erniebot.access_token = None\n",
"erniebot.ak = '<eb-ak>'\n",
"erniebot.sk = '<eb-sk>'\n",
"\n",
"response = erniebot.Image.create(\n",
" model='ernie-vilg-v2',\n",
" prompt=\"雨后的桃花，8k，辛烷值渲染\",\n",
" width=512,\n",
" height=512\n",
")\n",
"\n",
"Image(url=response.get_result()[0])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "ernie",
"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": "3.10.13"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|