# `AshAi.Actions`
[🔗](https://github.com/ash-project/ash_ai/blob/v0.6.1/lib/ash_ai/actions.ex#L5)

Builtin generic action implementations.

## ReqLLM-based Prompt Actions

The `prompt/2` macro accepts ReqLLM-compatible model specifications and uses
ReqLLM for structured output generation.

### Examples

    action :analyze_sentiment, Sentiment do
      argument :text, :string, allow_nil?: false

      run prompt("openai:gpt-4o",
        prompt: [
          %{role: "system", content: "You analyze sentiment."},
          %{role: "user", content: "Analyze: <%= @input.arguments.text %>"}
        ]
      )
    end

### Prompt Formats

The `:prompt` option supports multiple formats:

1. **String (EEx template)**: `"Analyze this: <%= @input.arguments.text %>"`
2. **{System, User} tuple**: `{"You are an expert", "Analyze: <%= @input.arguments.text %>"}`
3. **ReqLLM.Context**: Pass a context directly (canonical format)
4. **List of messages**: Maps, ReqLLM.Message structs, or mixed
5. **Function returning any of the above**: `fn input, context -> ... end`

### Using ReqLLM.Context (Recommended)

    import ReqLLM.Context

    run prompt("openai:gpt-4o",
      prompt: fn input, _ctx ->
        ReqLLM.Context.new([
          system("You are an OCR expert"),
          user([
            ReqLLM.Message.ContentPart.text("Extract text"),
            ReqLLM.Message.ContentPart.image_url(input.arguments.image_url)
          ])
        ])
      end
    )

# `prompt`
*macro* 

---

*Consult [api-reference.md](api-reference.md) for complete listing*