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33 lines
1.6 KiB
ReStructuredText
33 lines
1.6 KiB
ReStructuredText
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Data Augmented Generation
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=========================
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The walkthroughs here are related to data augmented generation.
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They cover either how to work with the components of data augmented generation (documents, embeddings, and vectorstores), or are end-to-end examples for using these components.
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**Components**
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`Text Splitters <data_augmented_generation/textsplitter.ipynb>`_: A walkthrough of how to split large documents up into smaller, more manageable pieces of text.
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`Embeddings & VectorStores <data_augmented_generation/embeddings.ipynb>`_: A walkthrough of the different embedding and vectorstore functionalies that LangChain supports.
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**Examples**
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`Question Answering <data_augmented_generation/question_answering.ipynb>`_: A walkthrough of how to use LangChain for question answering over specific documents.
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`Question Answering with Sources <data_augmented_generation/qa_with_sources.ipynb>`_: A walkthrough of how to use LangChain for question answering (with sources) over specific documents.
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`Summarization <data_augmented_generation/summarize.ipynb>`_: A walkthrough of how to use LangChain for summarization over specific documents.
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`Vector DB Question Answering <data_augmented_generation/vector_db_qa.ipynb>`_: A walkthrough of how to use LangChain for question answering over a vector database.
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`Vector DB Question Answering with Sources <data_augmented_generation/vector_db_qa_with_sources.ipynb>`_: A walkthrough of how to use LangChain for question answering (with sources) over a vector database.
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.. toctree::
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:maxdepth: 1
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:glob:
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:hidden:
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data_augmented_generation/*
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