package ai

import "context"

// Coach turns a free-text intent into a validated Proposal.
type Coach interface {
	Coach(ctx context.Context, intent string) (Proposal, error)
}

// Backend is one way to reach an LLM CLI. Adapters differ only in the command
// and arguments they run; each returns the model's text answer.
type Backend interface {
	Run(ctx context.Context, prompt string) (string, error)
	Name() string
}

// Service implements Coach over any Backend.
type Service struct {
	backend Backend
}

func NewService(b Backend) *Service { return &Service{backend: b} }

func (s *Service) Coach(ctx context.Context, intent string) (Proposal, error) {
	out, err := s.backend.Run(ctx, buildPrompt(intent))
	if err != nil {
		return Proposal{}, err
	}
	return parseProposal(out)
}

func buildPrompt(intent string) string {
	return `You are a focus coach. The user gives a rough intent for a work session. Turn it into ONE concrete, actionable commitment.

Respond with ONLY a JSON object, no prose and no code fences, exactly this shape:
{"next_action": "<one concrete action to start now>", "success_condition": "<observable, verifiable done state>", "timebox_minutes": <integer, typically 15-50>}

Rules:
- next_action: a single concrete imperative action, doable now.
- success_condition: observable and verifiable; how you'd know it is done.
- timebox_minutes: a realistic integer number of minutes for the action.

User intent: ` + intent
}