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@@ -7,10 +7,10 @@ RAGStack comes with a set of Python packages that provide the necessary tools to
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. `ragstack-ai-llamaindex`: This package is meant for users who want to use RAGStack with the LlamaIndex framework.
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. `ragstack-ai-colbert`: This package contains the implementation of the ColBERT retrieval.
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== Supported integrations for `ragstack-ai-langchain`
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The `ragstack-ai-langchain` package includes the minimum set of dependencies for using LangChain with {astra_db}.
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LLMs, embeddings, and third-party providers are not included in this package by default, expect for OpenAI and Azure OpenAI.
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LLMs, embeddings, and third-party providers are not included in this package by default, except for OpenAI and Azure OpenAI.
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To use LLMs, embeddings, or third-party providers, you can leverage `ragstack-ai-langchain` extras:
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Additional LangChain packages should work out of the box, although you need to manage the packages and their dependencies yourself.
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== Supported integrations for `ragstack-ai-llamaindex`
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The `ragstack-ai-llamaindex` package includes the minimum set of dependencies for using LlamaIndex with {astra_db}.
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Additional LLamaIndex packages should work out of the box, although you need to manage the packages and their dependencies yourself.
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== ColBERT with `ragstack-ai-langchain` and `ragstack-ai-llamaindex`
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== Colbert with `ragstack-ai-langchain` and `ragstack-ai-llamaindex`
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The `colbert` module provides a vanilla implementation for COLBert retrieval. It is not tied to any specific framework and can be used with any of the RAGStack packages.
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The `colbert` module provides a vanilla implementation for ColBERT retrieval. It is not tied to any specific framework and can be used with any of the RAGStack packages.
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If you want to use COLBert with LangChain or LLamaIndex, you can use the following the extras:
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If you want to use ColBERT with LangChain or LLamaIndex, you can use the following the extras:
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