From the course: Level up LLM applications development with LangChain and OpenAI

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Load sample data and create the vector store

Load sample data and create the vector store

From the course: Level up LLM applications development with LangChain and OpenAI

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Load sample data and create the vector store

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- [Instructor] MongoDB provides an easy way to load the sample data and index documents. So we're going to find here these documentations to get started easily and quickly with the LangChain integration, and we're going to find the prerequisites, which is already covered. We have also covered the parts, which is to set up the environment, and how to use here the vector store. So we have here made the connections to the Atlas cluster and defined the collection and database name. What's left to do, we're going to do that very soon, is to create a Vector Search index and provide the index name. So what we want to do now is to load the sample data. So we're going to find here code snippets examples. We're going to use the same example, actually. First to load the PDF documents, so we're going to copy these two lines. And what we want to load is this PDF documents from this URL. And this is this documentation that we want to load into our e-learning database that gives instructions about…

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