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125 lines
4.7 KiB
ReStructuredText
How To Guides
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====================================
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Utils
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-----
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There are a lot of different utilities that LangChain provides integrations for
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These guides go over how to use them.
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The utilities here are all utilities that make it easier to work with documents.
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`Text Splitters <./examples/textsplitter.html>`_: A walkthrough of how to split large documents up into smaller, more manageable pieces of text.
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`VectorStores <./examples/vectorstores.html>`_: A walkthrough of the vectorstore abstraction that LangChain supports.
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`Embeddings <./examples/embeddings.html>`_: A walkthrough of embedding functionalities, and different types of embeddings, that LangChain supports.
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`HyDE <./examples/hyde.html>`_: How to use Hypothetical Document Embeddings, a novel way of constructing embeddings for document retrieval systems.
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.. toctree::
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:maxdepth: 1
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:glob:
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:caption: Utils
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:name: utils
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:hidden:
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examples/*
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Vectorstores
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------------
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Vectorstores are one of the most important components of building indexes.
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In the below guides, we cover different types of vectorstores and how to use them.
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`Chroma <./vectorstore_examples/chroma.html>`_: A walkthrough of how to use the Chroma vectorstore wrapper.
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`AtlasDB <./vectorstore_examples/atlas.html>`_: A walkthrough of how to use the AtlasDB vectorstore and visualizer wrapper.
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`DeepLake <./vectorstore_examples/deeplake.html>`_: A walkthrough of how to use the Deep Lake, data lake, wrapper.
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`FAISS <./vectorstore_examples/faiss.html>`_: A walkthrough of how to use the FAISS vectorstore wrapper.
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`Elastic Search <./vectorstore_examples/elasticsearch.html>`_: A walkthrough of how to use the ElasticSearch wrapper.
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`Milvus <./vectorstore_examples/milvus.html>`_: A walkthrough of how to use the Milvus vectorstore wrapper.
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`Open Search <./vectorstore_examples/opensearch.html>`_: A walkthrough of how to use the OpenSearch wrapper.
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`Pinecone <./vectorstore_examples/pinecone.html>`_: A walkthrough of how to use the Pinecone vectorstore wrapper.
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`Qdrant <./vectorstore_examples/qdrant.html>`_: A walkthrough of how to use the Qdrant vectorstore wrapper.
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`Weaviate <./vectorstore_examples/weaviate.html>`_: A walkthrough of how to use the Weaviate vectorstore wrapper.
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`PGVector <./vectorstore_examples/pgvector.html>`_: A walkthrough of how to use the PGVector (Postgres Vector DB) vectorstore wrapper.
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.. toctree::
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:maxdepth: 1
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:glob:
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:caption: Vectorstores
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:name: vectorstores
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:hidden:
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vectorstore_examples/*
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Retrievers
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------------
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The retriever interface is a generic interface that makes it easy to combine documents with
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language models. This interface exposes a `get_relevant_documents` method which takes in a query
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(a string) and returns a list of documents.
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`Vectorstore Retriever <./retriever_examples/vectorstore-retriever.html>`_: A walkthrough of how to use a VectorStore as a Retriever.
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`ChatGPT Plugin Retriever <./retriever_examples/chatgpt-plugin-retriever.html>`_: A walkthrough of how to use the ChatGPT Plugin Retriever within the LangChain framework.
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.. toctree::
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:maxdepth: 1
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:glob:
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:caption: Retrievers
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:name: retrievers
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:hidden:
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retriever_examples/*
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Chains
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------
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The examples here are all end-to-end chains that use indexes or utils covered above.
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`Question Answering <./chain_examples/question_answering.html>`_: A walkthrough of how to use LangChain for question answering over specific documents.
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`Question Answering with Sources <./chain_examples/qa_with_sources.html>`_: A walkthrough of how to use LangChain for question answering (with sources) over specific documents.
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`Summarization <./chain_examples/summarize.html>`_: A walkthrough of how to use LangChain for summarization over specific documents.
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`Vector DB Text Generation <./chain_examples/vector_db_text_generation.html>`_: A walkthrough of how to use LangChain for text generation over a vector database.
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`Vector DB Question Answering <./chain_examples/vector_db_qa.html>`_: A walkthrough of how to use LangChain for question answering over a vector database.
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`Vector DB Question Answering with Sources <./chain_examples/vector_db_qa_with_sources.html>`_: A walkthrough of how to use LangChain for question answering (with sources) over a vector database.
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`Graph Question Answering <./chain_examples/graph_qa.html>`_: A walkthrough of how to use LangChain for question answering (with sources) over a graph database.
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`Chat Vector DB <./chain_examples/chat_vector_db.html>`_: A walkthrough of how to use LangChain as a chatbot over a vector database.
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`Analyze Document <./chain_examples/analyze_document.html>`_: A walkthrough of how to use LangChain to analyze long documents.
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.. toctree::
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:maxdepth: 1
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:glob:
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:caption: With Chains
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:name: chains
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:hidden:
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./chain_examples/*
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