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46 lines
1.8 KiB
ReStructuredText
46 lines
1.8 KiB
ReStructuredText
LLMs & Prompts
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==============
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The examples here all highlight how to work with LLMs and prompts.
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**LLMs**
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`LLM Functionality <prompts/llm_functionality.ipynb>`_: A walkthrough of all the functionality the standard LLM interface exposes.
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`LLM Serialization <prompts/llm_serialization.ipynb>`_: A walkthrough of how to serialize LLMs to and from disk.
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`LLM Caching <prompts/llm_caching.ipynb>`_: Covers different types of caches, and how to use a cache to save results of LLM calls.
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`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).
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**Specific LLM Integrations**
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`Huggingface Hub <prompts/huggingface_hub.ipynb>`_: Covers how to connect to LLMs hosted on HuggingFace Hub.
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`Azure OpenAI <prompts/azure_openai_example.ipynb>`_: Covers how to connect to Azure-hosted OpenAI Models.
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**Prompts**
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`Prompt Management <prompts/prompt_management.ipynb>`_: A walkthrough of all the functionality LangChain supports for working with prompts.
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`Prompt Serialization <prompts/prompt_serialization.ipynb>`_: A walkthrough of how to serialize prompts to and from disk.
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`Few Shot Examples <prompts/few_shot_examples.ipynb>`_: How to include examples in the prompt.
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`Generate Examples <prompts/generate_examples.ipynb>`_: How to use existing examples to generate more examples.
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`Custom Example Selector <prompts/custom_example_selector.ipynb>`_: How to create and use a custom ExampleSelector (the class responsible for choosing which examples to use in a prompt).
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`Custom Prompt Template <prompts/custom_prompt_template.ipynb>`_: How to create and use a custom PromptTemplate, the logic that decides how input variables get formatted into a prompt.
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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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prompts/*
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