LEM/main.go
Claude 08363ee1af
feat: add lem worker command for distributed inference network
Go client for the LEM distributed inference API (BugSETI/Agentic).
Workers register via Forgejo PAT auth, pull prompt batches, run local
inference (MLX/vLLM/llama.cpp), submit results. Credits tracked as
Phase 1 stub for Phase 2 blockchain LEM token.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-15 18:10:59 +00:00

292 lines
8 KiB
Go

package main
import (
"flag"
"fmt"
"log"
"os"
"time"
"forge.lthn.ai/lthn/lem/pkg/lem"
)
const usage = `Usage: lem <command> [flags]
Scoring:
score Score existing response files
probe Generate responses and score them
compare Compare two score files
tier-score Score expansion responses (heuristic/judge tiers)
agent ROCm scoring daemon (polls M3, scores checkpoints)
Generation:
expand Generate expansion responses via trained LEM model
conv Generate conversational training data (calm phase)
Data Management:
import-all Import ALL LEM data into DuckDB from M3
consolidate Pull worker JSONLs from M3, merge, deduplicate
normalize Normalize seeds → deduplicated expansion_prompts
approve Filter scored expansions → training JSONL
Export & Publish:
export Export golden set to training-format JSONL splits
parquet Export JSONL training splits to Parquet
publish Push Parquet files to HuggingFace dataset repo
convert Convert MLX LoRA adapter to PEFT format
Monitoring:
status Show training and generation progress (InfluxDB)
expand-status Show expansion pipeline status (DuckDB)
inventory Show DuckDB table inventory
coverage Analyze seed coverage gaps
metrics Push DuckDB golden set stats to InfluxDB
Distributed:
worker Run as distributed inference worker node
Infrastructure:
ingest Ingest benchmark data into InfluxDB
seed-influx Seed InfluxDB golden_gen from DuckDB
query Run ad-hoc SQL against DuckDB
`
func main() {
if len(os.Args) < 2 {
fmt.Fprint(os.Stderr, usage)
os.Exit(1)
}
switch os.Args[1] {
case "score":
runScore(os.Args[2:])
case "probe":
runProbe(os.Args[2:])
case "compare":
runCompare(os.Args[2:])
case "status":
lem.RunStatus(os.Args[2:])
case "expand":
lem.RunExpand(os.Args[2:])
case "export":
lem.RunExport(os.Args[2:])
case "conv":
lem.RunConv(os.Args[2:])
case "ingest":
lem.RunIngest(os.Args[2:])
case "parquet":
lem.RunParquet(os.Args[2:])
case "publish":
lem.RunPublish(os.Args[2:])
case "metrics":
lem.RunMetrics(os.Args[2:])
case "convert":
lem.RunConvert(os.Args[2:])
case "import-all":
lem.RunImport(os.Args[2:])
case "consolidate":
lem.RunConsolidate(os.Args[2:])
case "normalize":
lem.RunNormalize(os.Args[2:])
case "approve":
lem.RunApprove(os.Args[2:])
case "tier-score":
lem.RunTierScore(os.Args[2:])
case "expand-status":
lem.RunExpandStatus(os.Args[2:])
case "inventory":
lem.RunInventory(os.Args[2:])
case "coverage":
lem.RunCoverage(os.Args[2:])
case "seed-influx":
lem.RunSeedInflux(os.Args[2:])
case "query":
lem.RunQuery(os.Args[2:])
case "agent":
lem.RunAgent(os.Args[2:])
case "worker":
lem.RunWorker(os.Args[2:])
default:
fmt.Fprintf(os.Stderr, "unknown command: %s\n\n%s", os.Args[1], usage)
os.Exit(1)
}
}
func runScore(args []string) {
fs := flag.NewFlagSet("score", flag.ExitOnError)
input := fs.String("input", "", "Input JSONL response file (required)")
suites := fs.String("suites", "all", "Comma-separated suites or 'all'")
judgeModel := fs.String("judge-model", "mlx-community/gemma-3-27b-it-qat-4bit", "Judge model name")
judgeURL := fs.String("judge-url", "http://10.69.69.108:8090", "Judge API URL")
concurrency := fs.Int("concurrency", 4, "Max concurrent judge calls")
output := fs.String("output", "scores.json", "Output score file path")
resume := fs.Bool("resume", false, "Resume from existing output, skipping scored IDs")
if err := fs.Parse(args); err != nil {
log.Fatalf("parse flags: %v", err)
}
if *input == "" {
fmt.Fprintln(os.Stderr, "error: --input is required")
fs.Usage()
os.Exit(1)
}
responses, err := lem.ReadResponses(*input)
if err != nil {
log.Fatalf("read responses: %v", err)
}
log.Printf("loaded %d responses from %s", len(responses), *input)
if *resume {
if _, statErr := os.Stat(*output); statErr == nil {
existing, readErr := lem.ReadScorerOutput(*output)
if readErr != nil {
log.Fatalf("read existing scores for resume: %v", readErr)
}
scored := make(map[string]bool)
for _, scores := range existing.PerPrompt {
for _, ps := range scores {
scored[ps.ID] = true
}
}
var filtered []lem.Response
for _, r := range responses {
if !scored[r.ID] {
filtered = append(filtered, r)
}
}
log.Printf("resume: skipping %d already-scored, %d remaining",
len(responses)-len(filtered), len(filtered))
responses = filtered
if len(responses) == 0 {
log.Println("all responses already scored, nothing to do")
return
}
}
}
client := lem.NewClient(*judgeURL, *judgeModel)
client.MaxTokens = 512
judge := lem.NewJudge(client)
engine := lem.NewEngine(judge, *concurrency, *suites)
log.Printf("scoring with %s", engine)
perPrompt := engine.ScoreAll(responses)
if *resume {
if _, statErr := os.Stat(*output); statErr == nil {
existing, _ := lem.ReadScorerOutput(*output)
for model, scores := range existing.PerPrompt {
perPrompt[model] = append(scores, perPrompt[model]...)
}
}
}
averages := lem.ComputeAverages(perPrompt)
scorerOutput := &lem.ScorerOutput{
Metadata: lem.Metadata{
JudgeModel: *judgeModel,
JudgeURL: *judgeURL,
ScoredAt: time.Now().UTC(),
ScorerVersion: "1.0.0",
Suites: engine.SuiteNames(),
},
ModelAverages: averages,
PerPrompt: perPrompt,
}
if err := lem.WriteScores(*output, scorerOutput); err != nil {
log.Fatalf("write scores: %v", err)
}
log.Printf("wrote scores to %s", *output)
}
func runProbe(args []string) {
fs := flag.NewFlagSet("probe", flag.ExitOnError)
model := fs.String("model", "", "Target model name (required)")
targetURL := fs.String("target-url", "", "Target model API URL (defaults to judge-url)")
probesFile := fs.String("probes", "", "Custom probes JSONL file (uses built-in content probes if not specified)")
suites := fs.String("suites", "all", "Comma-separated suites or 'all'")
judgeModel := fs.String("judge-model", "mlx-community/gemma-3-27b-it-qat-4bit", "Judge model name")
judgeURL := fs.String("judge-url", "http://10.69.69.108:8090", "Judge API URL")
concurrency := fs.Int("concurrency", 4, "Max concurrent judge calls")
output := fs.String("output", "scores.json", "Output score file path")
if err := fs.Parse(args); err != nil {
log.Fatalf("parse flags: %v", err)
}
if *model == "" {
fmt.Fprintln(os.Stderr, "error: --model is required")
fs.Usage()
os.Exit(1)
}
if *targetURL == "" {
*targetURL = *judgeURL
}
targetClient := lem.NewClient(*targetURL, *model)
targetClient.MaxTokens = 1024
judgeClient := lem.NewClient(*judgeURL, *judgeModel)
judgeClient.MaxTokens = 512
judge := lem.NewJudge(judgeClient)
engine := lem.NewEngine(judge, *concurrency, *suites)
prober := lem.NewProber(targetClient, engine)
var scorerOutput *lem.ScorerOutput
var err error
if *probesFile != "" {
probes, readErr := lem.ReadResponses(*probesFile)
if readErr != nil {
log.Fatalf("read probes: %v", readErr)
}
log.Printf("loaded %d custom probes from %s", len(probes), *probesFile)
scorerOutput, err = prober.ProbeModel(probes, *model)
} else {
log.Printf("using %d built-in content probes", len(lem.ContentProbes))
scorerOutput, err = prober.ProbeContent(*model)
}
if err != nil {
log.Fatalf("probe: %v", err)
}
if writeErr := lem.WriteScores(*output, scorerOutput); writeErr != nil {
log.Fatalf("write scores: %v", writeErr)
}
log.Printf("wrote scores to %s", *output)
}
func runCompare(args []string) {
fs := flag.NewFlagSet("compare", flag.ExitOnError)
oldFile := fs.String("old", "", "Old score file (required)")
newFile := fs.String("new", "", "New score file (required)")
if err := fs.Parse(args); err != nil {
log.Fatalf("parse flags: %v", err)
}
if *oldFile == "" || *newFile == "" {
fmt.Fprintln(os.Stderr, "error: --old and --new are required")
fs.Usage()
os.Exit(1)
}
if err := lem.RunCompare(*oldFile, *newFile); err != nil {
log.Fatalf("compare: %v", err)
}
}