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8
docs/examples/prompts.rst
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@ -14,6 +14,14 @@ The examples here all highlight how to work with LLMs and prompts.
`Custom LLM <prompts/custom_llm.ipynb>`_: How to create and use a custom LLM class, in case you have an LLM not from one of the standard providers (including one that you host yourself).
**Specific LLM Integrations**
`Huggingface Hub <prompts/huggingface_hub.ipynb>`_: Covers how to connect to LLMs hosted on HuggingFace Hub.
`Azure OpenAI <prompts/azure_openai_example.ipynb>`_: Covers how to connect to Azure-hosted OpenAI Models.
**Prompts**
`Prompt Management <prompts/prompt_management.ipynb>`_: A walkthrough of all the functionality LangChain supports for working with prompts.

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pyproject.toml
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@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain"
version = "0.0.43"
version = "0.0.44"
description = "Building applications with LLMs through composability"
authors = []
license = "MIT"