Hello there! 👋 Welcome to this fun little Go program that demonstrates how to create embeddings using OpenAI's API. Let's break down what this exciting example does!
This program showcases how to:
- Set up an OpenAI client with specific model options
- Create embeddings for given text inputs
- Print the resulting embeddings
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First, we configure our OpenAI client:
- We use the "gpt-3.5-turbo-0125" model for general language tasks
- We specify "text-embedding-3-large" as our embedding model
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We create a new OpenAI client with these options
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We prepare two simple words for embedding: "ola" and "mundo" (Hello and World in Portuguese)
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We call the
CreateEmbedding
function to generate embeddings for these words -
Finally, we print out the resulting embeddings
Embeddings are super useful! They convert words or phrases into numerical vectors, which can be used for all sorts of neat tricks like:
- Finding similar texts
- Clustering related concepts
- Improving search functionality
- And much more!
This example gives you a starting point to experiment with embeddings in your own projects. Have fun exploring the world of vector representations! 🚀🧠
Make sure you have your OpenAI API key set up properly, and then just run the program. You'll see the embeddings printed out in all their numerical glory!
Happy coding! 😊