08c78757a5
Module path: forge.lthn.ai/core/go-i18n -> dappco.re/go/core/i18n Dependency: forge.lthn.ai/core/go-log -> dappco.re/go/core/log go-inference remains on forge.lthn.ai (not yet migrated). dappco.re/go/core/log uses replace directive until published. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
74 lines
2.3 KiB
Go
74 lines
2.3 KiB
Go
package integration
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import (
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"bytes"
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"context"
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"encoding/json"
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"fmt"
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"strings"
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"testing"
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"time"
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i18n "dappco.re/go/core/i18n"
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"forge.lthn.ai/core/go-inference"
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_ "forge.lthn.ai/core/go-mlx" // registers Metal backend
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)
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func TestClassifyCorpus_Integration(t *testing.T) {
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model, err := inference.LoadModel("/Volumes/Data/lem/LEM-Gemma3-1B-layered-v2")
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if err != nil {
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t.Skipf("model not available: %v", err)
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}
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defer model.Close()
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// Build 50 technical prompts for throughput measurement
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var lines []string
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for i := 0; i < 50; i++ {
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lines = append(lines, fmt.Sprintf(`{"id":%d,"prompt":"Delete the configuration file and rebuild the project"}`, i))
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}
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input := strings.NewReader(strings.Join(lines, "\n") + "\n")
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var output bytes.Buffer
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start := time.Now()
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stats, err := i18n.ClassifyCorpus(context.Background(), model, input, &output, i18n.WithBatchSize(8))
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if err != nil {
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t.Fatalf("ClassifyCorpus: %v", err)
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}
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elapsed := time.Since(start)
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t.Logf("Classified %d prompts in %v (%.1f prompts/sec)", stats.Total, elapsed, stats.PromptsPerSec)
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t.Logf("By domain: %v", stats.ByDomain)
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if stats.Total != 50 {
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t.Errorf("Total = %d, want 50", stats.Total)
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}
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if stats.Skipped != 0 {
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t.Errorf("Skipped = %d, want 0", stats.Skipped)
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}
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// Fix 5: Assert minimum accuracy — at least 80% of the 50 technical prompts
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// should be classified as "technical". The FINDINGS data shows 100% accuracy
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// on controlled technical input, so 80% is a conservative floor.
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technicalCount := stats.ByDomain["technical"]
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minRequired := 40 // 80% of 50
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if technicalCount < minRequired {
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// Log full domain breakdown for debugging
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for domain, count := range stats.ByDomain {
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t.Logf(" domain %q: %d (%.0f%%)", domain, count, float64(count)/float64(stats.Total)*100)
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}
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// Also inspect the output JSONL for misclassified entries
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outLines := strings.Split(strings.TrimSpace(output.String()), "\n")
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for _, line := range outLines {
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var record map[string]any
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if err := json.Unmarshal([]byte(line), &record); err == nil {
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if record["domain_1b"] != "technical" {
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t.Logf(" misclassified: id=%v domain_1b=%v", record["id"], record["domain_1b"])
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}
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}
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}
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t.Errorf("accuracy too low: %d/%d (%.0f%%) classified as technical, want >= %d (80%%)",
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technicalCount, stats.Total, float64(technicalCount)/float64(stats.Total)*100, minRequired)
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}
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}
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