branch: externals/llm
commit 3b761aca251eea164003743ed02f173f5fab888d
Author: Andrew Hyatt <ahy...@gmail.com>
Commit: Andrew Hyatt <ahy...@gmail.com>
Add README.org
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+#+TITLE: llm package for emacs
+
+This is a library for interfacing with Large Language Models. It allows elisp
code to use LLMs, but gives the user an option to choose which LLM they would
prefer. This is especially useful for LLMs, since there are various
high-quality ones that in which API access costs money, as well as locally
installed ones that are free, but of medium quality. Applications using LLMs
can use this library to make sure their application works regardless of whether
the user has a local LLM or is p [...]
+
+The functionality supported by LLMs is not completely consistent, nor are
their APIs. In this library we attempt to abstract functionality to a higher
level, because sometimes those higher level concepts are supported by an API,
and othertimes they must be put in more low-level concepts. Examples are an
example of this; the GCloud Vertex API has an explicit API for examples, but
for Open AI's API, examples must be specified by modifying the sytem prompt.
And Open AI has the concept of [...]
+
+Some functionality may not be supported by LLMs. Any unsupported
functionality with throw a ='not-implemented= signal.
+
+This package is simple at the moment, but will grow as both LLMs and
functionality is added.
+
+Clients should require the module, =llm=, and code against it. Most functions
are generic, and take a struct representing a provider as the first argument.
The client code, or the user themselves can then require the specific module,
such as =llm-openai=, and create a provider with a function such as
~(make-llm-openai :key user-api-key)~. The client application will use this
provider to call all the generic functions.
+
+A list of all the functions:
+
+- ~llm-chat-response provider prompt~: With user-chosen ~provider~ , and a
~llm-chat-prompt~ structure (containing context, examples, interactions, and
parameters such as temperature and max tokens), send that prompt to the LLM and
wait for the string output.
+- ~llm-embedding provider string~: With the user-chosen ~provider~, send a
string and get an embedding, which is a large vector of floating point values.
The embedding represents the semantic meaning of the string, and the vector can
be compared against other vectors, where smaller distances between the vectors
represent greater semantic similarity.
+
+All of the providers currently implemented.
+
+- =llm-openai=. This is the interface to Open AI's Chat GPT. The user must
set their key, and select their preferred chat and embedding model.
+- =llm-vertex=. This is the interface to Google Cloud's Vertex API. The user
needs to set their project number. In addition, to get authenticated, the user
must have logged in initially, and have a valid path in
~llm-vertex-gcloud-binary~. Users can also configure
~llm-vertex-gcloud-region~ for using a region closer to their location. It
defaults to ="us-central1"= The provider can also contain the user's chosen
embedding and chat model.
+
+If you are interested in creating a provider, please send a pull request, or
open a bug.
+
+This library is not yet part of any package archive.
