45 lines
1.4 KiB
Go
45 lines
1.4 KiB
Go
package ai
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import "context"
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// Coach turns a free-text intent into a validated Proposal.
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type Coach interface {
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Coach(ctx context.Context, intent string) (Proposal, error)
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}
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// Backend is one way to reach an LLM CLI. Adapters differ only in the command
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// and arguments they run; each returns the model's text answer.
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type Backend interface {
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Run(ctx context.Context, prompt string) (string, error)
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Name() string
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}
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// Service implements Coach over any Backend.
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type Service struct {
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backend Backend
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}
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func NewService(b Backend) *Service { return &Service{backend: b} }
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func (s *Service) Coach(ctx context.Context, intent string) (Proposal, error) {
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out, err := s.backend.Run(ctx, buildPrompt(intent))
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if err != nil {
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return Proposal{}, err
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}
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return parseProposal(out)
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}
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func buildPrompt(intent string) string {
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return `You are a focus coach. The user gives a rough intent for a work session. Turn it into ONE concrete, actionable commitment.
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Respond with ONLY a JSON object, no prose and no code fences, exactly this shape:
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{"next_action": "<one concrete action to start now>", "success_condition": "<observable, verifiable done state>", "timebox_minutes": <integer, typically 15-50>}
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Rules:
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- next_action: a single concrete imperative action, doable now.
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- success_condition: observable and verifiable; how you'd know it is done.
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- timebox_minutes: a realistic integer number of minutes for the action.
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User intent: ` + intent
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}
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