Django AI 聊天机器人项目:基于 ChatGPT 的 Django REST API
本文档将介绍如何使用 Django 和 Django REST Framework 构建一个 AI 聊天机器人项目,并结合 OpenAI 的 GPT 模型提供代码解释服务。步骤包括创建 Django 项目、配置 API、与 OpenAI 集成,并最终提供一个可通过 REST API 调用的服务。
项目结构
drf_chatgpt/ # Django 项目目录
├── api/ # API 应用目录
├── src/ # Django 配置文件目录
├── manage.py # Django 管理工具
├── .env # 环境变量文件
├── requirements.txt # 项目依赖
步骤 1:创建虚拟环境
首先,创建一个虚拟环境来隔离项目的依赖:
python -m venv venv
激活虚拟环境:
- Windows:
venv\Scripts\activate - Linux / MacOS:
source venv/bin/activate
步骤 2:安装依赖
安装 Django、Django REST Framework 和 OpenAI SDK:
pip install django djangorestframework openai
生成
requirements.txt
以便日后使用:
pip freeze > requirements.txt
步骤 3:创建 Django 项目
使用
django-admin
命令创建一个名为
src
的 Django 项目:
django-admin startproject src .
修改
src/settings.py
在
INSTALLED_APPS
中添加所需的应用:
INSTALLED_APPS =[# external apps'rest_framework','rest_framework.authtoken',# internal apps'api',# default apps'django.contrib.admin','django.contrib.auth','django.contrib.contenttypes','django.contrib.sessions','django.contrib.messages','django.contrib.staticfiles',]
步骤 4:创建数据库并运行开发服务器
- 创建数据库迁移并应用:
python manage.py migrate - 创建超级用户以便访问 Django 管理后台:
python manage.py createsuperuser - 启动开发服务器:
python manage.py runserver
步骤 5:获取 OpenAI API Key
使用环境变量来存储 OpenAI API 密钥。首先,创建一个
.env
文件并将 API 密钥添加到其中:
# .env 文件
OPENAI_APIKEY="sk-Wxxxxxxxx"
在
settings.py
中加载该变量:
import os
from dotenv import load_dotenv
load_dotenv()
APIKEY = os.getenv("OPENAI_APIKEY")
步骤 6:创建 API 应用
创建一个新的 Django 应用
api
:
python manage.py startapp api
设置 API 请求到 OpenAI 的工具函数
在
api/utils.py
中创建与 OpenAI API 的集成函数:
import openai
from django.conf import settings
openai.api_key = settings.APIKEY
defsend_code_to_api(code):try:
res = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[{"role":"user","content":f"Tell me what language is this code written? {code}"},{"role":"system","content":"You are a helpful assistant that provides code explanations."},{"role":"assistant","content":"Sure! Please provide the code you want me to explain."}],)return res["choices"][0]["message"]["content"]except openai.error.APIError as e:raise ValueError(f"OpenAI API returned an API Error: {e}")except openai.error.APIConnectionError as e:raise ValueError(f"Failed to connect to OpenAI API: {e}")except openai.error.RateLimitError as e:raise ValueError(f"OpenAI API request exceeded rate limit: {e}")
步骤 7:创建模型
在
api/models.py
中定义一个用于存储代码及其解释的模型:
from django.db import models
classCodeExplainer(models.Model):
_input = models.TextField()
_output = models.TextField()classMeta:
db_table ="t_code_explainer"
创建并迁移模型:
python manage.py makemigrations api
python manage.py migrate api
步骤 8:配置 URL 和视图
- 在项目的
urls.py中包含api.urls:
# src/urls.pyfrom django.contrib import admin
from django.urls import path, include
urlpatterns =[
path('admin/', admin.site.urls),
path('api/v1/', include('api.urls'))]
- 在
api/urls.py中定义 API 路由:
# api/urls.pyfrom django.urls import path
from api.views import UserView, TokenView, CodeExplainView
urlpatterns =[
path('users/', UserView.as_view(), name='users'),
path('tokens/', TokenView.as_view(), name='tokens'),
path('code-explain/', CodeExplainView.as_view(), name='code-explain')]
- 在
api/views.py中实现视图逻辑:
# api/views.pyfrom rest_framework import views, status
from rest_framework.response import Response
from rest_framework.authentication import TokenAuthentication
from rest_framework.permissions import AllowAny
from api.serializers import CodeExplainSerializer, UserSerializer, TokenSerializer
from api.models import CodeExplainer
classCodeExplainView(views.APIView):
serializer_class = CodeExplainSerializer
authentication_classes =[TokenAuthentication]defget(self, request,format=None):
qs = CodeExplainer.objects.all()
serializer = self.serializer_class(qs, many=True)return Response(serializer.data)defpost(self, request,format=None):
serializer = self.serializer_class(data=request.data)if serializer.is_valid():
serializer.save()return Response(serializer.data, status=status.HTTP_201_CREATED)return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)# 用户和 token 视图 (稍后定义)classUserView(views.APIView):
serializer_class = UserSerializer
permission_classes =[AllowAny]classTokenView(ObtainAuthToken):
serializer_class = TokenSerializer
步骤 9:实现序列化器
在
api/serializers.py
中编写模型序列化器:
# api/serializers.pyfrom rest_framework import serializers
from django.contrib.auth.models import User
from rest_framework.authtoken.models import Token
from api.models import CodeExplainer
from api.utils import send_code_to_api
classCodeExplainSerializer(serializers.ModelSerializer):classMeta:
model = CodeExplainer
fields =("id","_input","_output")
extra_kwargs ={"_output":{"read_only":True}}defcreate(self, validated_data):
code_explainer = CodeExplainer(**validated_data)
_output = send_code_to_api(validated_data["_input"])
code_explainer._output = _output
code_explainer.save()return code_explainer
classUserSerializer(serializers.ModelSerializer):classMeta:
model = User
fields =("id","username","email","password")
extra_kwargs ={"password":{"write_only":True}}defcreate(self, validated_data):
password = validated_data.pop("password")
user = User.objects.create(**validated_data)
user.set_password(password)
user.save()
Token.objects.create(user=user)return user
classTokenSerializer(serializers.Serializer):
username = serializers.CharField()
password = serializers.CharField(style={"input_type":"password"}, trim_whitespace=False)defvalidate(self, attrs):
username = attrs.get("username")
password = attrs.get("password")
user = authenticate(request=self.context.get("request"), username=username, password=password)ifnot user:
msg ="Credentials are not provided correctly..."raise serializers.ValidationError(msg, code="authentication")
attrs["user"]= user
return attrs
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