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Supporting asyncio in langchain primitives allows for users to run them concurrently and creates more seamless integration with asyncio-supported frameworks (FastAPI, etc.) Summary of changes: **LLM** * Add `agenerate` and `_agenerate` * Implement in OpenAI by leveraging `client.Completions.acreate` **Chain** * Add `arun`, `acall`, `_acall` * Implement them in `LLMChain` and `LLMMathChain` for now **Agent** * Refactor and leverage async chain and llm methods * Add ability for `Tools` to contain async coroutine * Implement async SerpaPI `arun` Create demo notebook. Open questions: * Should all the async stuff go in separate classes? I've seen both patterns (keeping the same class and having async and sync methods vs. having class separation)
26 lines
1.2 KiB
ReStructuredText
26 lines
1.2 KiB
ReStructuredText
How-To Guides
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=============
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A chain is made up of links, which can be either primitives or other chains.
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Primitives can be either `prompts <../prompts.html>`_, `llms <../llms.html>`_, `utils <../utils.html>`_, or other chains.
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The examples here are all end-to-end chains for specific applications.
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They are broken up into three categories:
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1. `Generic Chains <./generic_how_to.html>`_: Generic chains, that are meant to help build other chains rather than serve a particular purpose.
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2. `CombineDocuments Chains <./combine_docs_how_to.html>`_: Chains aimed at making it easy to work with documents (question answering, summarization, etc).
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3. `Utility Chains <./utility_how_to.html>`_: Chains consisting of an LLMChain interacting with a specific util.
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4. `Asynchronous <./async_chain.html>`_: Covering asynchronous functionality.
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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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./generic_how_to.rst
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./combine_docs_how_to.rst
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./utility_how_to.rst
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In addition to different types of chains, we also have the following how-to guides for working with chains in general:
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`Load From Hub <./generic/from_hub.html>`_: This notebook covers how to load chains from `LangChainHub <https://github.com/hwchase17/langchain-hub>`_.
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