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*Introduction:*
Hey, what's up, guys? This is Ronnie, and welcome back to our channel, Total Technology Zone. This is tutorial 9, and today's topic is about using embeddings with Llama Index. It's a simple yet crucial tutorial, especially if you are developing a retrieval-augmented generation (RAG) application or any question-answer related applications. Vector embeddings are essential for efficiently storing and processing your data.
*Overview:*
- We'll be using OpenAI embeddings for this tutorial.
- Understanding vector embeddings is fundamental before diving into application development.
- This video will focus solely on embeddings with the OpenAI model.
*Steps:*
1. *Introduction to Vector Embeddings:*
- Explain the importance of vector embeddings in data processing and storage.
- Emphasize the significance of embeddings for RAG and question-answer applications.
2. *Setting Up:*
- Use OpenAI embeddings as the global configuration.
- Demonstrate how to set parameters for embeddings.
3. *Embedding Configuration:*
- Show how to create a global config for embeddings.
- Illustrate setting the embedding model and parameters.
4. *Practical Implementation:*
- Import necessary modules (Llama Index core, OpenAI embeddings).
- Create a global config for the embedding model.
- Show standalone embedding usage with a simple text example.
- Print the vector representation of the text.
5. *Creating Vector Index:*
- Load documents using `SimpleDirectoryReader`.
- Create a vector index from the documents using the embedding model.
- Demonstrate both global config and variable-based embedding usage.
- Set up a query engine and demonstrate querying with vector embeddings.
*Conclusion:*
- Summarize the steps covered in the tutorial.
- Emphasize the simplicity and importance of embeddings.
- Encourage viewers to explore further by developing applications using these concepts.
*Personal Requests:*
- If you're new to our channel, please subscribe, like, and share this video with your friends and family.
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- Check out our playlist on Llama Index for more detailed tutorials.
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*Thank You:*
- Thank you for watching and supporting our channel.
- Stay tuned for more tutorials and happy learning!
7 сен 2024
