Technical requirements

To follow the examples in this chapter, you will need the following prerequisites:

• A MongoDB Atlas cluster. An Atlas M0 free cluster should be sufficient as you will store a small set of documents and create only one vector index.
• An OpenAI account and API key with access to the text-embedding-3-large model.
• A Python 3 working environment.

You will also need to have installed Python libraries for MongoDB, LangChain, and OpenAI. You can install these libraries in your Python 3 environment as follows:

%pip3 install --upgrade --quiet pymongo pythondns langchain langchain-community langchain-mongodb langchain-openai 

To successfully execute the example in this chapter, you will need a MongoDB Atlas Vector Index created on the MongoDB Atlas cluster. The index name must be text_vector_index, created on the embeddings.text collection as follows:

{
  "fields": [
    {
     ...