Building a Basic Chatbot with Azure OpenAI
Overview In this turorial, we'll build a simple chatbot that uses Azure OpenAI to generate responses to user queries. To create a basic chatbot, we need to set up a language model resource that enables conversation capabilities. In this tutorial, we will: Set up the Azure OpenAI resource using the Azure AI Foundry portal. Retrieve the API key needed to connect the resource to your chatbot application. Once the API key is configured in your code, you will be able to integrate the language model into your chatbot and enable it to generate responses. By the end of this tutorial, you'll have a working chatbot that can generate responses using the Azure OpenAI model. Signing In and Setting Up Your Azure AI Foundry Workspace Signing In to Azure AI Foundry Open the Azure AI Foundry page in your web browser. Login to your Azure account. If you don't have an account, you can sign up. Setting Up Your Azure AI Foundry Workspace Select + Create project to create a new project. Perform the following tasks: Enter Project name. It must be a unique value. Select Hub you'd like to use (create a new one if needed). Select Create. Setting Up the Azure OpenAI Resource in Azure AI Foundry In this step, you'll learn how to set up the Azure OpenAI resource in Azure AI Foundry. Azure OpenAI is a pre-trained language model that can generate responses to user queries. We'll be using it in our chatbot. Select Models + endpoints from the left side menu. On this page, you can deploy language models and set up Azure AI resources. In this step, we will deploy the Azure OpenAI GPT-4 language model. Select + Deploy model. Select Deploy base model. In this tutorial, we will deploy the GPT-4o model. Select GPT-4o. Select Confirm. Select Deploy. The model will be deployed. Once the deployment is complete, you will see the model listed on the Models + endpoints page. Now that the model is deployed, you can retrieve the API key needed to connect the model to your chatbot application. Select the model you deployed on the Models + endpoints page. ` On the model details page, you can view information about the model, including the API key. We will come back this page later to add the required information into the environment variables. Setting Up the Project and Install the Libraries Now, you will create a folder to work in and set up a virtual environment to develop a program. Creating a Folder to Work Inside It Open a terminal window and type the following command to create a folder named basic-chatbot in the default path. mkdir basic-chatbot Type the following command inside your terminal to navigate to the basic-chatbot folder you created. cd basic-chatbot Creating a Virtual Environment Type the following command inside your terminal to create a virtual environment named .venv. python -m venv .venv Type the following command inside your terminal to activate the virtual environment. .venv\Scripts\activate.bat NOTE If it worked, you should see (.venv) before the command prompt. Installing the Required Packages Type the following commands inside your terminal to install the required packages. openai: A Python library that provides integration with the Azure OpenAI API. python-dotenv: A Python library for managing environment variables stored in an .env file. pip install openai python-dotenv Setting up the Project in Visual Studio Code To create a basic chatbot program, you will need two files: example.py: This file will contain the code to interact with Azure resources. .env: This file will store the Azure credentials and configuration details. NOTE Purpose of the .env File The .env file is essential for storing the Azure information required to connect and use the resources you created. By keeping the Azure credentials in the .env file, you can ensure a secure and organized way to manage sensitive information. Setting Up example.py File Open Visual Studio Code. Select File from the menu bar. Select Open Folder. Select the basic-chatbot folder that you created, which is located at C:\Users\yourUserName\basic-chatbot. In the left pane of Visual Studio Code, right-click and select New File to create a new file named example.py. Add the following code to the example.py file to import the required libraries. from openai import AzureOpenAI from dotenv import load_dotenv import os # Load environment variables from the .env file load_dotenv() # Retrieve environment variables AZURE_OPENAI_ENDPOINT = os.getenv("AZURE_OPENAI_ENDPOINT") AZURE_OPENAI_API_KEY = os.getenv("AZURE_OPENAI_API_KEY") AZURE_OPENAI_MODEL_NAME = os.getenv("AZURE_OPENAI_MODEL_NAME") AZURE_OPENAI_CHAT_DEPLOYMENT_NAME = os.getenv("AZURE_OPENAI_CHAT_DEPLOYMENT_NAME") AZURE_OPENAI_API_VERSION = os.getenv("AZURE_OPENAI_API_VERSION") # Initialize Azure OpenAI client client = AzureOpenAI( api_key=AZURE_OPENAI_API_KEY, api_version=AZURE_OPENAI_API_VERSION, base_url=f"{AZURE_OPENAI_ENDPOINT}/openai/deployments/{AZURE_OPENAI_CHAT_DEPLOYMENT_NAME}" ) print("Chatbot: Hello! How can I assist you today? Type 'exit' to end the conversation.") while True: user_input = input("You: ") if user_input.lower() == "exit": print("Chatbot: Ending the conversation. Have a great day!") break response = client.chat.completions.create( model=AZURE_OPENAI_MODEL_NAME, messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": user_input} ], max_tokens=200 ) print("Chatbot:", response.choices[0].message.content.strip()) Setting Up .env File To set up your development environment, we will create a .env file and store the necessary credentials directly. NOTE Complete folder structure: └── YourUserName . └── basic-chatbot . ├── example.py . └── .env In the left pane of Visual Studio Code, right-click and select New File to create a new file named .env. Add the following code to the .env file to include your Azure information. AZURE_OPENAI_API_KEY=your_azure_openai_api_key AZURE_OPENAI_ENDPOINT=https://your_azure_openai_endpoint AZURE_OPENAI_MODEL_NAME=your_model_name AZURE_OPENAI_CHAT_DEPLOYMENT_NAME=your_deployment_name AZURE_OPENAI_API_VERSION=your_api_version Retrieving Environment Variables from Azure AI Foundry Now, you will retrieve the required information from Azure AI Foundry and update the .env file. Go to the Models + endpoints page and select your deployed model. On the Model Details page, copy the following information in to the .env file.: AZURE_OPENAI_API_KEY AZURE_OPENAI_ENDPOINT AZURE_OPENAI_MODEL_NAME AZURE_OPENAI_CHAT_DEPLOYMENT_NAME Paste this information into the .env file in the respective placeholders. Running the Chatbot Program Type the following command inside your terminal to run the program and see if it can answer questions. python example.py Interact with the chatbot by typing your questions or messages. The chatbot will generate responses based on the Azure OpenAI model you deployed. NOTE You can find the full example of this chatbot, including the code and .env template, in my GitHub repository: GitHub RepositoryStep-by-Step: How to Setup Copilot Chat in VS Code
Copilot Chat is an AI-powered chatbot leveraging OpenAI's GPT-4, designed to enhance your coding workflow. Learn how to set up Copilot Chat step by step in Visual Studio Code (VS Code). Benefit from personalized and flexible coding environments, code analysis, automated unit test generation, and bug fixes. Prerequisites include an active GitHub account and the latest version of VS Code. Elevate your coding efficiency to new heights with Copilot Chat.Build Your Own Chatbot in Minutes with Power Virtual Agents: No Coding Required!
Learn how to build a chatbot without coding using Power Virtual Agent, a platform by Microsoft. Automate tasks, reduce costs, and improve efficiency with AI-powered chatbots. No programming knowledge required! Discover how Power Virtual Agents work, guiding you through information like a digital librarian. Create your first chatbot by signing up on the Power Virtual Agents website and accessing your dashboard. Customize your bot's name, language, and even enable voice capabilities. Add relevant online content to enhance your bot's responses. Test and publish your bot with just a few clicks. Experience the functionality of your chatbot on the demo website. Explore more resources about Power Virtual Agent and reach out for assistance. Start building chatbots effortlessly today!Automatic Grading with Azure OpenAI Services ChatGPT Virtual Assistant
Don’t waste your time grading assignments by hand. Let AI do it for you! Learn how our AI virtual assistant can help students and teachers with their assignments in a fair, effective, and eco-friendly way. Plus, discover the secrets of choosing the best model, parameter, and prompt design for your tasks. ChatGPT 4 is not always the best option!Maximizing Your Academic Potential with Azure OpenAI Services ChatGPT Virtual Assistant
With Azure Open AI Virtual Assistant, schools can easily track how students are utilizing AI to enhance their learning and problem-solving skills. This serverless solution utilizes a wide range of Azure services, providing a cost-effective option for schools to enhance their teaching experience. Don't wait any longer to experience the future of education - try Azure Open AI Virtual Assistant today!Detection of AI-generated plagiarism: mission initiated
Picture this: you are a teacher eagerly checking your inbox, awaiting your students’ homework assignments with anticipation. You’ve assigned a project that you believe will push your students to their limits and unlock their full potential. But as the first submissions start rolling in, you can feel something isn’t quite right. As you begin to grade the assignments, you’re struck by a stark realisation — a number of them are eerily similar, but with unique phrasing and writing styles. It’s not simple cut-and-paste plagiarism but rather the work of advanced AI tools, like ChatGPT, that are able to mimic writing styles and generate undetectable original content. Will you be able to spot the difference and outwit the AI? Think of artificial intelligence as a tidal wave crashing onto the shores of education. Its arrival has transformed the way we learn, including the way students cheat on homework and assignments. For teachers, it’s like trying to navigate a treacherous ocean — they must find new and creative ways to test their students’ knowledge in a world where technology has made cheating a slippery eel. The challenge is real and the stakes are high. Can we rise to the challenge and chart a course towards an honest and fair education system? As American writer Mark Twain famously said, “Education is the path from cocky ignorance to miserable uncertainty.” In the age of AI-assisted cheating, this path is fraught with obstacles. The use of AI to cheat on assignments and online exams undermines the very foundation of education. If grades can be easily manipulated with technology, they cease to be a true measure of a student’s knowledge and understanding. This is a slippery slope that can lead to the devaluation of degrees and the overall purpose of education. In short, AI-assisted cheating threatens to turn the path of growth and enlightenment into a road of “miserable uncertainty.” As the world searches for high-tech solutions to tackle the problem of AI-assisted cheating, sometimes a quick answer is right in front of us. The viva exam is a tried and true method that has stood the test of time. It is a simple yet powerful tool that provides a comprehensive evaluation of a student’s abilities, giving you a window into their true potential. As educators, we hold the power to shape the future of our students and the education system at large. By prioritising the use of viva exams, we can help foster a culture of academic excellence and instil a strong sense of integrity in our students. The investment of time and effort is more than worth it, as we set our students on the path to success and help ensure the validity and credibility of grades. In the words of British author Sir Ken Robinson, “If you had told teachers in the 1960s that every child would have their own computer, they would have thought you were crazy.” But now, teachers would be dubbed absurd if they thought that students could stay strangers to AI tools. So, instead of turning a blind eye to AI, I decided to embrace it in my classroom. I taught my students the ins and outs of AI-powered chatbots, inspiring even the most reluctant learners to dive in and discover new ways to learn. However, with this newfound excitement came the issue of AI-assisted cheating. To tackle this, I included marks for viva exams with every home assignment. This gave me a more well-rounded understanding of my students’ abilities, and helped me cultivate a culture of academic excellence and integrity. By embracing AI and incorporating viva exams, I was able to turn a potential problem into a unique opportunity for growth and learning. Think of the fight against AI-assisted cheating like a battle between Sherlock Holmes and Professor James Moriarty, trying to outsmart each other. Meanwhile, educators are like Dr John Watson, working alongside Holmes, to provide support in solving a crime. So, let’s channel our inner Dr Watson and work together with policymakers to find traditional and innovative solutions to this problem, and ensure academic integrity in the classroom.
