feat(acb-evolver): add evolve CLI command for LLM-based bot generation
Add the 'evolve' subcommand that ties together the LLM prompt builder and ensemble components: - Load programs from target island - Select parents via tournament selection - Analyze optional replay files for strategic context - Build meta description from current ladder state - Assemble evolution prompt with all context - Run LLM ensemble (fast tier + strong tier refinement) - Output generated bot code Usage: acb-evolver evolve -island alpha -lang go [-replay file.json] [-out file.go] Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
jedarden
parent
f5924e8b15
commit
b191751c2b
1 changed files with 204 additions and 1 deletions
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@ -18,17 +18,25 @@ import (
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"flag"
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"fmt"
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"log"
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"math/rand"
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"os"
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"strings"
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"time"
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_ "github.com/lib/pq"
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evolverdb "github.com/aicodebattle/acb/cmd/acb-evolver/internal/db"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/arena"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/live"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/llm"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/mapelites"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/meta"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/promoter"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/prompt"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/replay"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/selector"
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"github.com/aicodebattle/acb/cmd/acb-evolver/internal/validator"
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"github.com/aicodebattle/acb/engine"
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)
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func main() {
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@ -50,6 +58,9 @@ func main() {
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defer db.Close()
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runLiveExport(ctx, db, os.Args[2:])
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case "evolve":
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runEvolve(ctx, dbURL, os.Args[2:])
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case "evaluate":
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db := mustOpenDB(dbURL)
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defer db.Close()
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@ -112,11 +123,203 @@ func main() {
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default:
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fmt.Fprintf(os.Stderr, "unknown subcommand %q\n", os.Args[1])
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fmt.Fprintln(os.Stderr, "usage: acb-evolver <init-schema|seed|stats|validate|validation-stats|evaluate|retire|live-export>")
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fmt.Fprintln(os.Stderr, "usage: acb-evolver <init-schema|seed|stats|validate|validation-stats|evolve|evaluate|retire|live-export>")
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os.Exit(1)
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}
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}
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// runEvolve generates a new candidate bot using the LLM ensemble.
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//
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// evolve -island alpha -lang go [-replay file.json] [-llm-url URL] [-num-parents 2] [-seed N] [-out file.go]
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func runEvolve(ctx context.Context, dbURL string, args []string) {
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fs := flag.NewFlagSet("evolve", flag.ExitOnError)
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island := fs.String("island", "", "island name (alpha|beta|gamma|delta) [required]")
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lang := fs.String("lang", "", "target language (go|python|rust|typescript|java|php) [required]")
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replayFile := fs.String("replay", "", "optional replay JSON file for analysis (can be specified multiple times as comma-separated)")
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llmURL := fs.String("llm-url", envOrDefault("ACB_LLM_URL", "http://zai-proxy-apexalgo.tail1b1987.ts.net:8080"), "LLM proxy URL")
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numParents := fs.Int("num-parents", 2, "number of parents to select via tournament selection")
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tournamentK := fs.Int("tournament-k", 3, "tournament size for parent selection")
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seed := fs.Int64("seed", 0, "random seed (0 = use time)")
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topBotLimit := fs.Int("top-bots", 10, "number of top bots to include in meta description")
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outFile := fs.String("out", "", "output file for generated code (default: stdout)")
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verbose := fs.Bool("v", false, "verbose output")
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if err := fs.Parse(args); err != nil {
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os.Exit(1)
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}
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if *island == "" {
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fmt.Fprintln(os.Stderr, "evolve: -island is required")
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fs.Usage()
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os.Exit(1)
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}
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if *lang == "" {
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fmt.Fprintln(os.Stderr, "evolve: -lang is required")
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fs.Usage()
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os.Exit(1)
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}
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// Validate island
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validIsland := false
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for _, i := range evolverdb.AllIslands {
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if i == *island {
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validIsland = true
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break
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}
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}
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if !validIsland {
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fmt.Fprintf(os.Stderr, "evolve: invalid island %q (must be one of: alpha, beta, gamma, delta)\n", *island)
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os.Exit(1)
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}
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// Initialize RNG
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rng := rand.New(rand.NewSource(*seed))
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if *seed == 0 {
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rng = rand.New(rand.NewSource(time.Now().UnixNano()))
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}
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// Open database
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db, err := sql.Open("postgres", dbURL)
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if err != nil {
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log.Fatalf("open database: %v", err)
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}
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defer db.Close()
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store := evolverdb.NewStore(db)
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// 1. Load programs from the island
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if *verbose {
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log.Printf("Loading programs from island %s...", *island)
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}
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programs, err := store.ListByIsland(ctx, *island)
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if err != nil {
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log.Fatalf("list programs: %v", err)
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}
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if len(programs) == 0 {
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log.Fatalf("no programs found on island %s - seed the database first", *island)
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}
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if *verbose {
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log.Printf("Found %d programs on island %s", len(programs), *island)
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}
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// 2. Select parents via tournament selection
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if *verbose {
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log.Printf("Selecting %d parents via %d-way tournament selection...", *numParents, *tournamentK)
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}
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parents := selector.SelectParents(programs, *numParents, *tournamentK, rng)
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if *verbose {
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for i, p := range parents {
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log.Printf(" Parent %d: id=%d fitness=%.3f lang=%s", i+1, p.ID, p.Fitness, p.Language)
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}
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}
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// 3. Load and analyze replays (if provided)
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var analyses []*replay.Analysis
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if *replayFile != "" {
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analyzer := replay.NewAnalyzer()
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replayFiles := strings.Split(*replayFile, ",")
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for _, rf := range replayFiles {
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rf = strings.TrimSpace(rf)
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if rf == "" {
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continue
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}
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if *verbose {
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log.Printf("Loading replay: %s", rf)
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}
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rep, err := engine.LoadReplayFile(rf)
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if err != nil {
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log.Printf("warn: failed to load replay %s: %v", rf, err)
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continue
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}
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analysis := analyzer.Analyze(rep)
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if analysis != nil {
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analyses = append(analyses, analysis)
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}
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}
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if *verbose {
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log.Printf("Analyzed %d replays", len(analyses))
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}
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}
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// 4. Build meta description
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if *verbose {
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log.Printf("Building meta description...")
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}
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metaBuilder := meta.NewBuilder(store)
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metaDesc, err := metaBuilder.Build(ctx, *topBotLimit)
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if err != nil {
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log.Printf("warn: failed to build meta description: %v", err)
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// Create a minimal meta description
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metaDesc = &meta.Description{
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TotalBots: len(programs),
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IslandStats: make(map[string]meta.IslandStats),
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}
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}
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// 5. Determine generation number (max generation on island + 1)
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maxGen := 0
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for _, p := range programs {
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if p.Generation > maxGen {
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maxGen = p.Generation
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}
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}
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generation := maxGen + 1
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// 6. Assemble the prompt
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if *verbose {
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log.Printf("Assembling prompt for generation %d...", generation)
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}
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req := prompt.BuildRequest(parents, analyses, metaDesc, *island, *lang, generation)
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fullPrompt := prompt.Assemble(req)
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if *verbose {
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log.Printf("Prompt length: %d bytes", len(fullPrompt))
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}
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// 7. Create LLM client and run ensemble
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if *verbose {
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log.Printf("Connecting to LLM at %s...", *llmURL)
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}
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client := llm.NewClient(*llmURL, "")
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cfg := llm.DefaultEnsembleConfig()
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cfg.NumCandidates = 3
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cfg.RefineTop = true
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if *verbose {
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log.Printf("Running ensemble generation (%d candidates, refinement enabled)...", cfg.NumCandidates)
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}
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result, err := client.Ensemble(ctx, fullPrompt, *lang, cfg)
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if err != nil {
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log.Fatalf("LLM ensemble failed: %v", err)
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}
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if result.Best == nil {
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log.Fatal("No valid candidate generated")
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}
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// 8. Output the result
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if *verbose {
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log.Printf("Generation complete!")
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log.Printf(" Candidates generated: %d", len(result.AllCandidates))
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log.Printf(" Refinement applied: %v", result.RefinementApplied)
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log.Printf(" Best candidate length: %d bytes", len(result.Best.Code))
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if len(result.Errors) > 0 {
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log.Printf(" Errors: %d", len(result.Errors))
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}
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}
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if *outFile != "" {
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if err := os.WriteFile(*outFile, []byte(result.Best.Code), 0644); err != nil {
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log.Fatalf("write output file: %v", err)
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}
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if *verbose {
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log.Printf("Wrote candidate to %s", *outFile)
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}
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} else {
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fmt.Print(result.Best.Code)
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}
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}
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// runEvaluate runs the 10-match mini-tournament and applies the promotion gate.
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//
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// evaluate -lang go -island alpha [-program-id 0] [-promote] [-nash 0.5] [-win-lower 0.4] [-nolog] <file>
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