forked from Archives/langchain
985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
20 lines
1.2 KiB
Markdown
20 lines
1.2 KiB
Markdown
# Key Concepts
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## LLMs
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Wrappers around Large Language Models (in particular, the "generate" ability of large language models) are at the core of LangChain functionality.
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The core method that these classes expose is a `generate` method, which takes in a list of strings and returns an LLMResult (which contains outputs for all input strings).
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Read more about LLMResult. This interface operates over a list of strings because often the lists of strings can be batched to the LLM provider,
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providing speed and efficiency gains.
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For convenience, this class also exposes a simpler, more user friendly interface (via `__call__`).
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The interface for this takes in a single string, and returns a single string.
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## Generation
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The output of a single generation. Currently in LangChain this is just the generated text, although could be extended in the future
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to contain log probs or the like.
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## LLMResult
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The full output of a call to the `generate` method of the LLM class.
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Since the `generate` method takes as input a list of strings, this returns a list of results.
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Each result consists of a list of generations (since you can request N generations per input string).
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This also contains a `llm_output` attribute which contains provider-specific information about the call.
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