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Fix docs.redisvl.com links
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content/integrate/redisvl/user_guide/getting_started.md

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## Creating `VectorQuery` Objects
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Next we will create a vector query object for our newly populated index. This example will use a simple vector to demonstrate how vector similarity works. Vectors in production will likely be much larger than 3 floats and often require Machine Learning models (i.e. Huggingface sentence transformers) or an embeddings API (Cohere, OpenAI). `redisvl` provides a set of [Vectorizers](https://docs.redisvl.com/en/latest/user_guide/vectorizers_04.html#openai) to assist in vector creation.
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Next we will create a vector query object for our newly populated index. This example will use a simple vector to demonstrate how vector similarity works. Vectors in production will likely be much larger than 3 floats and often require Machine Learning models (i.e. Huggingface sentence transformers) or an embeddings API (Cohere, OpenAI). `redisvl` provides a set of [Vectorizers]({{< relref "vectorizers#openai" >}}) to assist in vector creation.
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```python

content/integrate/redisvl/user_guide/hybrid_queries.md

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## Advanced Query Modifiers
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See all modifier options available on the query API docs: https://docs.redisvl.com/en/latest/api/query.html
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See all modifier options available on the query API docs: https://redis.io/docs/latest/integrate/redisvl/api/query
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```python

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