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https://github.com/hwchase17/langchain
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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)
19 lines
517 B
ReStructuredText
19 lines
517 B
ReStructuredText
How-To Guides
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=============
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The examples here all address certain "how-to" guides for working with LLMs.
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They are split into two categories:
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1. `Generic Functionality <./generic_how_to.html>`_: Covering generic functionality all LLMs should have.
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2. `Integrations <./integrations.html>`_: Covering integrations with various LLM providers.
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3. `Asynchronous <./async_llm.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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./integrations.rst
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