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Elixir-native LangChain, LangGraph, and DeepAgents for traceable LLM apps: OTP workflows, tools, memory, human-in-the-loop, streaming, custom clients/adapters, minimal deps, and WeaveScope tracing.

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beam_weaver examples supervised_openai_agent.exs
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examples/supervised_openai_agent.exs 

alias BeamWeaver.Core.ChatModel

alias BeamWeaver.Core.Message

alias BeamWeaver.Runtime.Agent

alias BeamWeaver.Tracing



Tracing.reset()



model =

  BeamWeaver.OpenAI.chat_model(

    api_key: "sk-replay",

    transport: BeamWeaver.Transport.Replay,

    transport_opts: [cassette_path: "priv/openai/cassettes/supervised_openai_agent.yaml"]

  )



{:ok, agent} = Agent.start_child(id: "supervised_openai_agent_example")

:ok = Agent.subscribe(agent)

{:ok, _run} = Tracing.start_run("supervised OpenAI replay example")



{:ok, work} =

  Agent.start_model_call(

    agent,

    [Message.user("agent ping")],

    fn messages -> ChatModel.invoke(model, messages) end,

    timeout: 1_000

  )



receive do

  {:beam_weaver_agent, _agent_id, {:completed, work_id, response}} when work_id == work.id ->

    IO.puts(Message.text(response))



  {:beam_weaver_agent, _agent_id, {:failed, work_id, error}} when work_id == work.id ->

    raise "model call failed: #{inspect(error)}"

after

  1_500 ->

    raise "model call timed out"

end