Welcome to the first lesson of our course on creating a personal tutor with DeepSeek! DeepSeek is an advanced AI platform that offers state-of-the-art language models capable of understanding and generating human-like text. Its unique features include high accuracy in language comprehension, the ability to generate contextually relevant responses, and a robust API that supports seamless integration into various applications. These capabilities make DeepSeek an excellent choice for building AI tutors, as it can provide personalized and insightful interactions with users.

In this lesson, we will explore the basics of interacting with DeepSeek's AI models using C#. Our goal is to send a simple query to DeepSeek's language model and receive a response. This foundational step will set the stage for more complex interactions in future lessons. By understanding how to communicate with DeepSeek, you'll be equipped to harness its full potential in creating a personal tutor that can adapt to individual learning needs.

Before we can send a query to DeepSeek, we need to set up our development environment for C#. This involves installing the necessary tools and libraries. For this course, you will need the System.Net.Http and System.Text.Json libraries, which are included in .NET Core and later versions. These libraries allow us to send HTTP requests and handle JSON data when interacting with DeepSeek's API.

If you are using an older version of .NET, make sure your project targets at least .NET Core 3.1 or later to have access to these libraries.

Once your environment is ready, you can proceed to write and run your C# code to interact with DeepSeek.

In this course, you will be using a coding environment where everything is already set up for you, so you do not need to worry about configuring your API key or environment variables. However, it's useful to understand how this process works in case you want to set it up on your own computer in the future.

To work with DeepSeek models outside of this environment, you need to obtain an API key from their service. This API key is essential for accessing DeepSeek's services and making requests to their API.

To keep your API key secure, you can use environment variables. An environment variable is a way to store important information, such as your DeepSeek API key, outside of your code. This helps keep your key safe and secure.

If you were setting this up on your own system, here's how you would do it:

• On macOS and Linux, open your terminal and use the export command:

• On Windows (Command Prompt):

• On Windows (PowerShell):

In your C# code, you can access these environment variables using the Environment.GetEnvironmentVariable method:

This allows your application to securely retrieve the API key and base URL without hardcoding them.

Once the environment variables are set, you can initialize your API client in C# to communicate with DeepSeek. In this lesson, we will use the HttpClient class to send HTTP requests.

First, retrieve your API key and base URL from the environment variables. Then, create an HttpClient instance and set the necessary headers, including your API key for authentication.

Here is how you can set up the client:

By initializing the client in this way, your script is ready to authenticate requests to DeepSeek's API securely.

Now that your environment is set up and your API client is configured, it's time to send your first query to DeepSeek. We'll start by defining a simple prompt and then use an HTTP POST request to send this query to the AI model.

Here is how you can do this in C#:

In this code, we define a query asking the AI to tell an engineering joke. We then create a POST request to the /v1/chat/completions endpoint, set the necessary headers, and construct the request body in JSON format.

After sending the query to DeepSeek, the next step is to extract the AI's reply from the API response and display it. Here is how you can do that in C#:

Once the request is sent, the response is received as a JSON string. We parse this string and extract the AI's reply from the choices array, then print both the query and the AI's reply to see the interaction.

Let's look at the complete code example for sending a query to DeepSeek. This example includes all the steps we've discussed so far:

In this lesson, we covered the essential steps to send a simple query to DeepSeek's language model using C#. We set up our environment, configured API access, and sent a message to receive a response. This foundational knowledge is crucial as we move forward in building more complex tutoring interactions.

As you proceed to the practice exercises, I encourage you to experiment with different queries and explore the AI's responses. This hands-on practice will reinforce what you've learned and prepare you for the next unit, where we'll delve deeper into handling API parameters. Keep up the great work, and enjoy the journey of creating your personal tutor with DeepSeek!