erlangchain

Minimal building blocks for talking to LLMs from Erlang, with zero third-party dependencies (only OTP inets + ssl).

Module	Role
`llm`	one-call chat client for OpenAI (Responses API) and Anthropic, with tool-use and multimodal support
`json_util`	dependency-free JSON encode/decode

Install

%% rebar.config
{deps, [
    {erlangchain, {git, "https://github.com/abhavk/erlangchain.git", {tag, "0.1.0"}}}
]}.

Set OPENAI_API_KEY and/or ANTHROPIC_API_KEY in the environment (a .env file in the working directory is loaded automatically if present).

llm

%% Simple completion (defaults to openai/small):
{ok, #{content := Text}} = llm:chat([#{role => user, content => <<"hello">>}]),

%% Pick provider + size:
{ok, Resp} = llm:chat(openai, big, Messages),

%% Tool use — pass tool specs, get back tool_calls to run and feed back:
{ok, #{tool_calls := Calls}} = llm:chat(openai, big, Messages, Tools).

Messages are maps like #{role => system|user|assistant, content => binary()}, plus #{role => tool_result, tool_use_id => Id, content => Bin} to return tool output. See the header of src/llm.erl for the full message/response shapes.

json_util

<<"{\"a\":1}">> = json_util:encode(#{<<"a">> => 1}),
#{<<"a">> := 1} = json_util:decode(<<"{\"a\":1}">>).

License

MIT — see LICENSE.