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docs: update better README

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# Vector Database for Python Developers
`any-vector-db` is a simple, user-friendly solution for Python developers looking to create their own vector database with CRUD support. Vector databases are a key component of the stack needed to use LLMs as they allow them to have access to context and memory. Many of the solutions out there require developers and users to use complex solutions that are often not needed. With `any-vector-db`, you can easily create your own vector database solution that can work locally and can still be easily deployed and served with scalability features such as sharding and replication.
`any-vector-db` is a simple, user-friendly solution for Python developers looking to create their own vector database with CRUD support. Vector databases are a key component of the stack needed to use LLMs as they allow them to have access to context and memory. Many of the solutions out there require developers and users to use complex solutions that are often not needed. With `any-vector-db`, you can easily create your own vector database solution that can work locally and still be easily deployed and served with scalability features such as sharding and replication.
`any-vector-db` allows you to start simple and work locally while allowing when needed to deploy and scale in a seamless manner. With the help of [DocArray](https://github.com/docarray/docarray) and [Jina](https://github.com/jina-ai/jina) `any-vector-db` allows developers to focus on the algorithmic part and tweak the core of the vector search with Python as they want while keeping it easy to scale and deploy the solution.
`any-vector-db` allows you to start simple and work locally while allowing when needed to deploy and scale in a seamless manner. With the help of [DocArray](https://github.com/docarray/docarray) and [Jina](https://github.com/jina-ai/jina) `any-vector-db` allows developers to focus on the algorithmic part and tweak the core of the vector search with Python as they want while keeping it easy to scale and deploy the solution.
Stop wondering what exact algorithms do existing solutions apply, how do they apply filtering or how to map your schema to their solutions, with `any-vector-db` you as a Python developer can easily understand and control what is the vector search algorithm doing, giving you the full control if needed while supporting you for local setting and in more advanced and demanding scenarios in the cloud.
## :muscle: Features