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docs: Updating contribution docs to source README.md directly
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
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## Using Retrieval Augmented Generation (RAG)
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## Retrieval Augmented Generation (RAG)
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RAG enables your applications to reference and recall information from previous interactions or external documents.
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RAG enables your applications to reference and recall information from previous interactions or external documents.
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print(f"Unregistering vector database: {vector_db_id.identifier}")
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print(f"Unregistering vector database: {vector_db_id.identifier}")
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client.vector_dbs.unregister(vector_db_id=vector_db_id.identifier)
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client.vector_dbs.unregister(vector_db_id=vector_db_id.identifier)
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```
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```
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### Supported Data Types
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You can ingest data into the vector database using `RAGDocument` objects.
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The supported mime types (https://en.wikipedia.org/wiki/Media_type#mime.types) data types are:
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# Contributing to Llama Stack
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Start with the [Contributing Guide](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md) for some general tips. This section covers a few key topics in more detail.
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```{include} ../../../CONTRIBUTING.md
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```
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See the [Adding a New API Provider](new_api_provider.md) which describes how to add new API providers to the Stack.
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- [Adding a New API Provider](new_api_provider.md) describes adding new API providers to the Stack.
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- [Testing Llama Stack](testing.md) provides details about the testing framework and how to test providers and distributions.
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```{toctree}
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```{toctree}
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:maxdepth: 1
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:maxdepth: 1
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:hidden:
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:hidden:
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new_api_provider
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new_api_provider
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testing
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```
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```
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