import "github.com/happyhackingspace/dit"

// Load classifier. On first call, if no model.json is found in the current
// directory (walked up to the nearest go.mod) or in ~/.dit/, the pretrained
// model is downloaded from Hugging Face to ~/.dit/model.json (~93MB, one-time)
// and reused on subsequent calls.
c, _ := dit.New()

// Or load an explicit file (no network, no search).
c, _ := dit.Load("path/to/model.json")

// Classify page type
page, _ := c.ExtractPageType(htmlString)
fmt.Println(page.Type)  // "login"
fmt.Println(page.Forms) // form classifications included

// Classify forms in HTML
results, _ := c.ExtractForms(htmlString)
for _, r := range results {
    fmt.Println(r.Type)   // "login"
    fmt.Println(r.Fields) // {"username": "username or email", "password": "password"}
}

// With probabilities
pageProba, _ := c.ExtractPageTypeProba(htmlString, 0.05)
formProba, _ := c.ExtractFormsProba(htmlString, 0.05)

// Train a new model
c, _ := dit.Train("data/", &dit.TrainConfig{Verbose: true})
c.Save("model.json")

// Evaluate via cross-validation
result, _ := dit.Evaluate("data/", &dit.EvalConfig{Folds: 10})
fmt.Printf("Form accuracy: %.1f%%\n", result.FormAccuracy*100)
fmt.Printf("Page accuracy: %.1f%%\n", result.PageAccuracy*100)