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30 lines
1.8 KiB
Markdown
30 lines
1.8 KiB
Markdown
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# Cassandra / Astra DB
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The example notebooks in this directory show how to use the Vector
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Search capabilities available today in **DataStax Astra DB**, a serverless
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Database-as-a-Service built on Apache Cassandra®.
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Moreover, support for vector-oriented workloads is making its way to the
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next major release of Cassandra, so that the code examples in this folder
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are designed to work equally well on it as soon as the vector capabilities
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get released.
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If you want to know more about Astra DB and its Vector Search capabilities,
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head over to [astra.datastax.com](https://docs.datastax.com/en/astra-serverless/docs/vector-search/overview.html) or try out one
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of these hands-on notebooks straight away:
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### Example notebooks
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The following examples show how easily OpenAI and DataStax Astra DB can
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work together to power vector-based AI applications. You can run them either
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with your local Jupyter engine or as Colab notebooks:
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| Use case | Framework | Notebook | Google Colab |
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| -------- | --------- | -------- | ------------ |
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| Search/generate quotes | CassIO | [Notebook](./Philosophical_Quotes_cassIO.ipynb) | [](https://colab.research.google.com/github/openai/openai-cookbook/blob/main/examples/vector_databases/cassandra_astradb/Philosophical_Quotes_cassIO.ipynb) |
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| Search/generate quotes | Plain Cassandra language | [Notebook](./Philosophical_Quotes_CQL.ipynb) | [](https://colab.research.google.com/github/openai/openai-cookbook/blob/main/examples/vector_databases/cassandra_astradb/Philosophical_Quotes_CQL.ipynb) |
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### Vector similarity, visual representation
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