def deps do
  [
    {:beam_weaver, "~> 0.1.0"}
  ]
end

config :beam_weaver,
  openai: [api_key: System.fetch_env!("OPENAI_API_KEY")],
  anthropic: [api_key: System.fetch_env!("ANTHROPIC_API_KEY")],
  google: [api_key: System.fetch_env!("GOOGLE_API_KEY")],
  xai: [api_key: System.fetch_env!("XAI_API_KEY")],
  moonshot: [api_key: System.fetch_env!("MOONSHOT_API_KEY")]

defmodule MyApp.Agents.SupportAgent do
  use BeamWeaver.Agent

  alias BeamWeaver.Agent.Middleware
  alias BeamWeaver.Core.Message

  name "support.reply"
  description "Answer customer support questions with account context."

  model "openai:gpt-5.4-mini", temperature: 0.2, timeout: 30_000
  system_prompt "Answer support questions clearly. Ask for missing details."

  # Agent harness capabilities are regular declarations.
  prompt_caching true
  compact_conversation true
  overflow_recovery true

  middleware do
    use Middleware.TodoList, tool_name: "write_todos"
    use Middleware.ToolCallNormalization
    use Middleware.StructuredOutputRetry, max_retries: 2
    use Middleware.ModelRetry, max_retries: 2, initial_delay: 100, retry_on: :transient
    use Middleware.ToolRetry, max_retries: 1, on_failure: :continue
    use Middleware.ToolCallLimit, run_limit: 8, exit_behavior: :end
    use Middleware.ToolSelection, deny: ["internal_admin_tool"]
    use Middleware.PII, detectors: [:email, :credit_card], strategy: :redact
  end

  def run(question, user) do
    __MODULE__.invoke(%{messages: [Message.user(question)]},
      trace: [
        name: "support.reply",
        user_id: user.id,
        execution_mode: "support_reply",
        fields: %{account_id: user.account_id}
      ]
    )
  end
end

defmodule MyApp.DynamicSupportAgent do
  alias BeamWeaver.Agent
  alias BeamWeaver.Core.Message

  def run(question, user) do
    model =
      BeamWeaver.Models.init_chat_model!("openai:gpt-5.4-mini",
        temperature: 0.2,
        timeout: 30_000
      )

    {:ok, agent} =
      Agent.build(
        name: "support.reply",
        model: model,
        system_prompt: "Answer support questions clearly."
      )

    Agent.invoke(agent, %{messages: [Message.user(question)]},
      trace: [
        name: "support.reply",
        user_id: user.id,
        execution_mode: "support_reply",
        fields: %{account_id: user.account_id}
      ]
    )
  end
end

config :beam_weaver,
  weave_scope: [
    endpoint: "https://app.weavescope.com",
    api_key: System.fetch_env!("WEAVESCOPE_API_KEY")
  ]