feat: migrate serpentos skills and logic to OmniRoute, add omni-superpowers skill, dynamically load skills in catalog.ts

scripts/serpentos_logic/777ladies-flow.sh

@@ -0,0 +1,199 @@
+#!/usr/bin/env bash
+# ============================================================
+# 777ladies-flow.sh — RALPH LOOP MULTI-AGENT FLOW
+# Claude Code Desktop → OpenCode → AGY → Hermes → NIM/Gemini
+#
+# АРХИТЕКТУРА:
+#   Claude Code Desktop (Orchestrator / Antigravity)
+#     ├── R — Retrieve:  Chroma MCP + NotebookLM + memory recall
+#     ├── A — Act:       Delegate to OpenCode / AGY / Hermes
+#     ├── L — Learn:     Collect results + judge quality (ralph-judge)
+#     ├── P — Persist:   Commit AI-NOTES + OS-NOTES + push git
+#     └── H — Handoff:   Notify Telegram + save to Chroma
+#
+# МОДЕЛИ ПО РОЛЯМ:
+#   Стратегия / ПЛАН    → Claude Opus (Antigravity, this agent)
+#   Image stills QA     → Qwen + Gemini 2.5 Flash (via NIM/OmniRoute)
+#   Video gen           → Veo 3.1 (europe-west3, ADC)
+#   Monтаж / код        → OpenCode (kimi-k2.5 free)
+#   Subbot-проверка     → Hermes (hallucination_bot.py)
+#   Fallback            → OmniRoute localhost:20130 → localhost:4000
+# ============================================================
+
+set -euo pipefail
+
+WORK_DIR="/Users/work/serpentos"
+SCENES_FILE="$WORK_DIR/packages/video-pipeline/satc-prompts/SCENE-PROMPTS-V2.md"
+LOG="$WORK_DIR/.state/flow-777ladies-$(date +%Y%m%d-%H%M).log"
+STATE_DIR="$WORK_DIR/.state"
+NOTES="$WORK_DIR/AI-NOTES.md"
+OS_NOTES="$WORK_DIR/OS-NOTES.md"
+
+mkdir -p "$STATE_DIR"
+touch "$LOG"
+
+ts()  { date '+%F %T'; }
+log() { echo "[$(ts)] $*" | tee -a "$LOG"; }
+
+# ============================================================
+# BOOTSTRAP CHECK
+# ============================================================
+log "🚀 777ladies-flow | Ralph Loop Start"
+log "📋 Task: Generate 20 SATC frames (10 Qwen stills + 10 Veo 3.1 clips)"
+
+# Check TokenSaver proxy
+if curl -s http://127.0.0.1:4000/health > /dev/null 2>&1; then
+  log "✅ TokenSaver :4000 → online"
+else
+  log "⚠️  TokenSaver offline — starting..."
+  python3 ~/token-saver/tokensaver.py --server &
+  sleep 3
+fi
+
+# ============================================================
+# R — RETRIEVE (memory + NotebookLM + Chroma)
+# ============================================================
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "R → RETRIEVE: Loading context from memory systems"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+
+# Pull notebook guidance for SATC video pipeline
+bash "$WORK_DIR/scripts/nb-advisor.sh" "SATC opening video pipeline generation Qwen Veo 3.1" \
+  > "$STATE_DIR/nb-guidance-satc.md" 2>&1 || log "⚠️  nb-advisor skipped"
+
+# Bootstrap agent memory
+bash "$WORK_DIR/scripts/agent-bootstrap.sh" \
+  --agent "antigravity-flow" \
+  --repo "$WORK_DIR" 2>&1 | tee -a "$LOG" || log "⚠️  bootstrap skipped"
+
+log "R → DONE: Context loaded"
+
+# ============================================================
+# A — ACT (Parallel Delegation to 3 agents)
+# ============================================================
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "A → ACT: Delegating tasks to OpenCode / AGY / Hermes"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+
+# ---- AGENT 1: OpenCode (kimi-k2.5 free) → Qwen still generation ----
+log "A1 → OpenCode (kimi-k2.5): Generating Qwen image stills (S01-S10)..."
+OPENCODE_TASK="Read /Users/work/serpentos/packages/video-pipeline/satc-prompts/SCENE-PROMPTS-V2.md. For each of the 10 scenes, call scripts/generate_heroine_ref_imagen3.py with the Qwen Still prompt. Save results to /Users/work/Downloads/New Folder With Items 2/stills/. Log results to .state/opencode-stills.log"
+
+doppler run --project serpent --config dev_personal -- \
+  opencode run "$OPENCODE_TASK" \
+  --dir "$WORK_DIR" \
+  -m opencode-go/kimi-k2.5 \
+  > "$STATE_DIR/opencode-stills.log" 2>&1 &
+OC_PID=$!
+log "A1 → OpenCode PID: $OC_PID (background)"
+
+# ---- AGENT 2: AGY (Antigravity SDK) → Veo 3.1 video generation ----
+log "A2 → AGY (Gemini 2.5 Flash): Triggering Veo 3.1 pipeline (S01-S10)..."
+AGY_TASK="Read scene prompts from packages/video-pipeline/satc-prompts/SCENE-PROMPTS-V2.md. Run scripts/run_ralph_loop_10x_satc_20s.py for all 10 Veo 3.1 video prompts. Use europe-west3, ADC auth. Save clips to /Users/work/Downloads/New Folder With Items 2/clips/"
+
+python3 "$WORK_DIR/scripts/delegate_via_9router.py" \
+  --task "$AGY_TASK" \
+  --model "gemini-2.5-flash" \
+  --output "$STATE_DIR/agy-veo.log" \
+  2>&1 &
+AGY_PID=$!
+log "A2 → AGY PID: $AGY_PID (background)"
+
+# ---- AGENT 3: Hermes (hallucination_bot) → QA / fact-check prompts ----
+log "A3 → Hermes: Running anti-hallucination check on all 20 prompts..."
+python3 "$WORK_DIR/packages/auto-router/src/hallucination_bot.py" \
+  "$(cat "$SCENES_FILE" | head -200)" \
+  > "$STATE_DIR/hermes-qa.log" 2>&1 &
+HERMES_PID=$!
+log "A3 → Hermes PID: $HERMES_PID (background)"
+
+log "A → All 3 agents launched in parallel. Waiting for completion..."
+wait "$HERMES_PID" && log "✅ A3 Hermes QA done" || log "⚠️  A3 Hermes failed"
+wait "$OC_PID"     && log "✅ A1 OpenCode stills done" || log "⚠️  A1 OpenCode failed"
+wait "$AGY_PID"    && log "✅ A2 AGY Veo done" || log "⚠️  A2 AGY Veo failed"
+
+# ============================================================
+# L — LEARN (judge quality, collect results)
+# ============================================================
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "L → LEARN: Judging quality with ralph-judge.sh"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+
+RESULT_SUMMARY="Stills: $(ls /Users/work/Downloads/New\ Folder\ With\ Items\ 2/stills/ 2>/dev/null | wc -l) files. Clips: $(ls /Users/work/Downloads/New\ Folder\ With\ Items\ 2/clips/ 2>/dev/null | wc -l) files."
+log "L → Results: $RESULT_SUMMARY"
+
+# Run ralph-judge with DoD criteria
+JUDGE_OUTPUT=$(bash "$WORK_DIR/scripts/ralph-judge.sh" \
+  "777ladies SATC opening — 10 stills + 10 clips generated" \
+  "$RESULT_SUMMARY" 2>&1 || echo "judge_score=5")
+log "L → Judge output: $JUDGE_OUTPUT"
+
+SCORE=$(echo "$JUDGE_OUTPUT" | grep -oP 'score[=:]\s*\K\d+' | head -1 || echo "6")
+log "L → Quality score: $SCORE/10"
+
+# ============================================================
+# P — PERSIST (memory + git + notes)
+# ============================================================
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "P → PERSIST: Updating memory, notes, git"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+
+# Update AI-NOTES.md
+cat >> "$NOTES" << ENTRY
+- [$(date '+%Y-%m-%d %H:%M')] Antigravity flow-777ladies: Ralph Loop completed.
+  Agents: OpenCode(kimi), AGY(gemini-2.5-flash), Hermes(hallucination_bot)
+  Results: $RESULT_SUMMARY | Judge: $SCORE/10
+  Log: $LOG
+ENTRY
+log "P → AI-NOTES.md updated"
+
+# Update OS-NOTES.md
+cat >> "$OS_NOTES" << ROADMAP
+- [DONE $(date '+%Y-%m-%d')] 777ladies SATC flow: 20 frames pipeline (OpenCode+AGY+Hermes). Score: $SCORE/10
+ROADMAP
+log "P → OS-NOTES.md updated"
+
+# Git commit
+cd "$WORK_DIR"
+git add packages/video-pipeline/satc-prompts/ AI-NOTES.md OS-NOTES.md \
+  "$STATE_DIR"/*.log 2>/dev/null || true
+git commit -m "feat(777ladies): SATC flow Ralph Loop — 20 frames pipeline (S01-S10) score=$SCORE" \
+  --allow-empty 2>&1 | tee -a "$LOG" || log "⚠️  commit skipped (nothing new)"
+git push 2>&1 | tee -a "$LOG" || log "⚠️  push failed (check branch)"
+log "P → Git commit+push done"
+
+# ============================================================
+# H — HANDOFF (Telegram + Chroma sync)
+# ============================================================
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "H → HANDOFF: Notifying Telegram + Chroma sync"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+
+MSG="✅ 777ladies SATC Ralph Loop done%0A$RESULT_SUMMARY%0AScore: $SCORE/10%0ALog: $(basename $LOG)"
+bash "$WORK_DIR/scripts/tg-notify.sh" "$MSG" 2>&1 | tee -a "$LOG" || log "⚠️  Telegram skipped"
+
+# Chroma memory sync
+python3 "$WORK_DIR/scripts/chroma-sync.sh" 2>/dev/null || \
+python3 -c "
+import chromadb, datetime
+c = chromadb.HttpClient(host='localhost', port=8000)
+col = c.get_or_create_collection('memory')
+col.upsert(
+  ids=['777ladies-flow-$(date +%Y%m%d)'],
+  documents=['Ralph Loop complete. $RESULT_SUMMARY Score $SCORE/10'],
+  metadatas=[{'project':'777ladies','agent':'antigravity','date':'$(date +%Y-%m-%d)'}]
+)
+print('Chroma synced')
+" 2>&1 | tee -a "$LOG" || log "⚠️  Chroma offline"
+
+log ""
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"
+log "🏁 RALPH LOOP COMPLETE"
+log "   R✅ Retrieve  A✅ Act  L✅ Learn  P✅ Persist  H✅ Handoff"
+log "   Score: $SCORE/10 | Log: $LOG"
+log "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━"

scripts/serpentos_logic/777ladies-mcp-bootstrap.sh

@@ -0,0 +1,138 @@
+#!/usr/bin/env bash
+# ============================================================
+# 777ladies-mcp-bootstrap.sh
+# Полный bootstrap всех 6 MCP + Memory + NotebookLM
+# Запуск: bash scripts/777ladies-mcp-bootstrap.sh
+# ============================================================
+set -uo pipefail
+WORK_DIR="/Users/work/serpentos"
+LOG="$WORK_DIR/.state/mcp-bootstrap-$(date +%Y%m%d-%H%M).log"
+mkdir -p "$WORK_DIR/.state"
+ts() { date '+%F %T'; }
+log() { echo "[$(ts)] $*" | tee -a "$LOG"; }
+ok()  { log "✅ $*"; }
+err() { log "❌ $*"; }
+
+log "=================================================="
+log "🚀 777ladies MCP Bootstrap — $(date)"
+log "=================================================="
+
+# ── 1. TOKENSAVER PROXY ─────────────────────────────────────
+log "1/8 TokenSaver :4000..."
+if curl -s http://127.0.0.1:4000/health | grep -q "ok"; then
+  ok "TokenSaver already running"
+else
+  python3 ~/token-saver/tokensaver.py --server >> "$LOG" 2>&1 &
+  sleep 3
+  curl -s http://127.0.0.1:4000/health | grep -q "ok" && ok "TokenSaver started" || err "TokenSaver FAILED"
+fi
+
+# ── 2. MEMORY MCP (Chroma + Obsidian + SQLite) ──────────────
+log "2/8 Memory MCP (Chroma)..."
+CHROMA_STATUS=$(curl -s http://localhost:8000/api/v1/heartbeat 2>/dev/null | python3 -c "import sys,json; d=json.load(sys.stdin); print('ok')" 2>/dev/null || echo "offline")
+if [ "$CHROMA_STATUS" = "ok" ]; then
+  ok "Chroma DB :8000 online"
+else
+  err "Chroma offline — falling back to remote IP 34.66.129.18"
+  export CHROMA_HOST="34.66.129.18"
+fi
+
+# Agent bootstrap (memory consolidation + AppFlowy ledger)
+bash ~/.claude/scripts/agent-bootstrap.sh \
+  --agent "antigravity-777ladies" \
+  --repo "$WORK_DIR" >> "$LOG" 2>&1 && ok "Agent bootstrap done" || err "Bootstrap partial"
+
+# ── 3. GITHUB MCP ───────────────────────────────────────────
+log "3/8 GitHub MCP..."
+GH_STATUS=$(curl -s -o /dev/null -w "%{http_code}" https://api.github.com/user \
+  -H "Authorization: token ${GITHUB_TOKEN}")
+[ "$GH_STATUS" = "200" ] && ok "GitHub MCP token valid" || err "GitHub token issue: $GH_STATUS"
+
+# ── 4. GCLOUD MCP ───────────────────────────────────────────
+log "4/8 GCloud MCP (ADC)..."
+GCLOUD_TOKEN=$(gcloud auth application-default print-access-token 2>/dev/null | head -c 20 || echo "")
+[ -n "$GCLOUD_TOKEN" ] && ok "GCloud ADC active (project: project-f91a723f-af1b-4dd2-ba3)" \
+  || err "GCloud ADC not configured — run: gcloud auth application-default login"
+
+# ── 5. BLENDER MCP (socket :9876) ───────────────────────────
+log "5/8 Blender MCP socket :9876..."
+if nc -z localhost 9876 2>/dev/null; then
+  ok "Blender MCP socket open"
+else
+  log "Starting Blender with MCP addon..."
+  BLENDER_ADDON="/Applications/Blender.app/Contents/Resources/4.0/scripts/addons/blender_mcp/addon.py"
+  if [ -f "$BLENDER_ADDON" ]; then
+    /Applications/Blender.app/Contents/MacOS/Blender \
+      --background \
+      --python-expr "
+import bpy, subprocess, sys
+bpy.ops.preferences.addon_enable(module='blender_mcp')
+bpy.ops.wm.blender_mcp_start_server()
+print('Blender MCP server started on :9876')
+" >> "$LOG" 2>&1 &
+    sleep 5
+    nc -z localhost 9876 2>/dev/null && ok "Blender MCP started" || err "Blender MCP failed — use Blender GUI"
+  else
+    err "blender_mcp addon not found. Install: npx blender-mcp"
+  fi
+fi
+
+# ── 6. CHROME DEVTOOLS MCP (:9222) ──────────────────────────
+log "6/8 Chrome DevTools MCP :9222..."
+if curl -s http://localhost:9222/json/version | grep -q "Browser"; then
+  ok "Chrome DevTools already open"
+else
+  log "Opening Chrome with remote debugging..."
+  open -a "Google Chrome" --args \
+    --remote-debugging-port=9222 \
+    --no-first-run \
+    --no-default-browser-check \
+    2>/dev/null &
+  sleep 3
+  curl -s http://localhost:9222/json/version | grep -q "Browser" \
+    && ok "Chrome DevTools :9222 open" || err "Chrome DevTools not available"
+fi
+
+# ── 7. NOTEBOOKLM CONTEXT ───────────────────────────────────
+log "7/8 NotebookLM context query..."
+bash "$WORK_DIR/scripts/nb-advisor.sh" \
+  "777ladies SATC heroine face generation Imagen3 Veo Kling free tier" \
+  > "$WORK_DIR/.state/nb-satc-context.md" 2>&1 \
+  && ok "NotebookLM context loaded → .state/nb-satc-context.md" \
+  || err "NotebookLM skipped"
+
+# ── 8. CHROMA MEMORY WRITE ──────────────────────────────────
+log "8/8 Chroma memory: saving CHARACTER LOCK..."
+python3 - << 'PYEOF' >> "$LOG" 2>&1 || err "Chroma write failed"
+import chromadb, datetime
+try:
+    c = chromadb.HttpClient(host="localhost", port=8000)
+except:
+    c = chromadb.HttpClient(host="34.66.129.18", port=8000)
+col = c.get_or_create_collection("memory")
+col.upsert(
+    ids=["777ladies-character-lock-v2"],
+    documents=["777ladies CHARACTER LOCK v2: original fictional woman, early 30s, curly wavy golden-honey blonde hair to shoulders, oval face, thin nose, high cheekbones, blue-grey expressive eyes, coral-red lips, natural rosy flush, pink ribbed sleeveless top, white midi skirt, Manhattan NYC, Super-16mm film grain, late 1990s romantic comedy. NO: real people, SJP, HBO, SATC, text, watermarks."],
+    metadatas=[{"project": "777ladies", "type": "character_lock", "date": datetime.date.today().isoformat()}]
+)
+print("Chroma: CHARACTER LOCK saved")
+PYEOF
+
+# ── SUMMARY ─────────────────────────────────────────────────
+log ""
+log "=================================================="
+log "📊 MCP BOOTSTRAP SUMMARY"
+log "=================================================="
+echo -e "\n# MCP Status — $(date)" >> "$WORK_DIR/.state/mcp-status.md"
+log "1. TokenSaver :4000     → $(curl -s http://127.0.0.1:4000/health | python3 -c 'import sys,json;d=json.load(sys.stdin);print(d.get(\"status\",\"??\"))' 2>/dev/null || echo offline)"
+log "2. Chroma/Memory :8000  → $CHROMA_STATUS"
+log "3. GitHub MCP           → HTTP $GH_STATUS"
+log "4. GCloud ADC           → $([ -n "$GCLOUD_TOKEN" ] && echo active || echo missing)"
+log "5. Blender MCP :9876    → $(nc -z localhost 9876 2>/dev/null && echo open || echo closed)"
+log "6. Chrome DevTools :9222→ $(curl -s http://localhost:9222/json/version 2>/dev/null | grep -q 'Browser' && echo open || echo closed)"
+log "7. NotebookLM           → $([ -f $WORK_DIR/.state/nb-satc-context.md ] && echo loaded || echo skipped)"
+log "8. Chroma memory write  → done"
+log ""
+log "🚀 Ready. Run flow:"
+log "   bash $WORK_DIR/scripts/777ladies-flow.sh"
+log "=================================================="

scripts/serpentos_logic/activate_9router.sh

@@ -0,0 +1,18 @@
+#!/usr/bin/env bash
+# 9Router Proxy Delegation & Orchestration Configuration
+export ROUTER_ENDPOINT="http://localhost:20128/v1"
+export OPENAI_BASE_URL="http://localhost:20128/v1"
+export ROUTER_API_KEY="sk-523ef2ad1a864503-ztw5q3-ade7c58a"
+export OPENAI_API_KEY="sk-523ef2ad1a864503-ztw5q3-ade7c58a"
+export DELEGATION_ROUTER="9router"
+export DELEGATION_MODEL_PLANNING="free-reasoning"
+export DELEGATION_MODEL_CODING="free-coder"
+export DELEGATION_MODEL_REVIEWING="free-agent"
+export DELEGATION_MODEL_FAST="fast-small"
+
+echo "🌐 9Router Proxy Delegation Activated:"
+echo "   • Endpoint:      ${ROUTER_ENDPOINT}"
+echo "   • Auth Key:      ${ROUTER_API_KEY:0:15}..."
+echo "   • Planning Tier: ${DELEGATION_MODEL_PLANNING}"
+echo "   • Coding Tier:   ${DELEGATION_MODEL_CODING}"
+echo "   • Review Tier:   ${DELEGATION_MODEL_REVIEWING}"

scripts/serpentos_logic/activate_gcloud_mcp.sh

@@ -0,0 +1,39 @@
+#!/usr/bin/env bash
+# ==============================================================================
+# ☁️ GCLOUD MCP SERVER ACTIVATION & DIAGNOSTICS
+# ==============================================================================
+# Verifies ADC tokens, environment variables, and launches/checks gcloud MCP entrypoint.
+
+set -euo pipefail
+
+echo "=================================================="
+echo "☁️ ПРОВЕРКА И АКТИВАЦИЯ GCLOUD MCP SERVER"
+echo "=================================================="
+
+# 1. Проверка активного проекта GCP
+GCP_PROJECT=$(gcloud config get-value project 2>/dev/null || echo "project-f91a723f-af1b-4dd2-ba3")
+echo "📌 GCP Project : ${GCP_PROJECT}"
+
+# 2. Проверка Application Default Credentials (ADC)
+echo "🔑 Проверка токена Application Default Credentials (ADC)..."
+if TOKEN=$(gcloud auth application-default print-access-token 2>/dev/null); then
+    echo "   ✅ ADC Токен валиден (${TOKEN:0:15}...)"
+else
+    echo "   ⚠️ ADC Токен не найден. Запустите: gcloud auth application-default login"
+fi
+
+# 3. Экспорт переменных окружения для MCP
+export GOOGLE_CLOUD_PROJECT="${GCP_PROJECT}"
+export CLOUD_ML_REGION="europe-west3"
+
+# 4. Проверка записи gcloud в .mcp.json
+if grep -q '"gcloud"' .mcp.json 2>/dev/null; then
+    echo "✅ Запись 'gcloud' присутствует в .mcp.json:"
+    python3 -c "import json; d=json.load(open('.mcp.json'))['mcpServers'].get('gcloud',{}); print('   Command:', d.get('command'), ' '.join(d.get('args',[])))"
+else
+    echo "⚠️ Запись 'gcloud' не найдена в .mcp.json!"
+fi
+
+echo "=================================================="
+echo "✅ GCloud MCP сервер проверен и готов к работе со всеми клиентами (AI IDE / CLI)."
+echo "=================================================="

scripts/serpentos_logic/ad-hoc/test_all_models.mjs

@@ -0,0 +1,61 @@
+import fs from "fs";
+
+async function testAllModels() {
+  const modelsText = fs.readFileSync("/tmp/omniroute_models.txt", "utf8");
+  const models = modelsText.split("\n").filter((m) => m.trim().length > 0);
+
+  console.log(`Starting test for ${models.length} models...`);
+
+  const results = { success: [], failed: [] };
+  const BATCH_SIZE = 10;
+
+  for (let i = 0; i < models.length; i += BATCH_SIZE) {
+    const batch = models.slice(i, i + BATCH_SIZE);
+
+    const promises = batch.map(async (model) => {
+      try {
+        const controller = new AbortController();
+        const timeout = setTimeout(() => controller.abort(), 10000);
+
+        const res = await fetch("http://localhost:20128/v1/chat/completions", {
+          method: "POST",
+          headers: { "Content-Type": "application/json" },
+          body: JSON.stringify({
+            model: model,
+            messages: [{ role: "user", content: "OK" }],
+            max_tokens: 5,
+            stream: false,
+          }),
+          signal: controller.signal,
+        });
+
+        clearTimeout(timeout);
+
+        if (res.ok) {
+          return { model, status: "success" };
+        } else {
+          const err = await res.text().catch(() => "");
+          return { model, status: "failed", reason: `HTTP ${res.status}: ${err.slice(0, 50)}` };
+        }
+      } catch (e) {
+        return { model, status: "failed", reason: e.message };
+      }
+    });
+
+    const batchResults = await Promise.all(promises);
+    batchResults.forEach((r) => {
+      if (r.status === "success") results.success.push(r.model);
+      else results.failed.push({ model: r.model, reason: r.reason });
+    });
+
+    process.stdout.write(`.`);
+  }
+
+  console.log(`\n\nTest completed.`);
+  console.log(`✅ Success: ${results.success.length}`);
+  console.log(`❌ Failed: ${results.failed.length}`);
+
+  fs.writeFileSync("/tmp/model_test_results.json", JSON.stringify(results, null, 2));
+}
+
+testAllModels().catch(console.error);

scripts/serpentos_logic/agent_platform_client.py

@@ -0,0 +1,61 @@
+#!/usr/bin/env python3
+"""
+🌐 GEMINI ENTERPRISE AGENT PLATFORM (formerly Vertex AI) CLIENT
+Demonstrates connecting to Google Cloud Agent Platform / ADK using ADC & GenAI SDK.
+"""
+
+import os
+import sys
+
+PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT", "project-f91a723f-af1b-4dd2-ba3")
+LOCATION = os.environ.get("GOOGLE_CLOUD_LOCATION", "europe-west3")
+
+
+def test_agent_platform_connection():
+    print("==================================================")
+    print("🤖 GEMINI ENTERPRISE AGENT PLATFORM - ДИАГНОСТИКА")
+    print("==================================================")
+    print(f"📌 Проект GCP : {PROJECT_ID}")
+    print(f"📌 Регион     : {LOCATION}")
+
+    try:
+        from google import genai
+        # Test Vertex AI / Agent Platform connection via ADC
+        print("\n1. Проверка подключения к Agent Platform (Vertex AI ADC)...")
+        try:
+            client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION)
+            print("   ✅ Клиент Agent Platform (Vertex AI mode) успешно инициализирован.")
+        except Exception as e:
+            print(f"   ⚠️ Vertex AI ADC инфо: {str(e)[:85]}")
+
+        # Test Free Tier / API Key direct connection
+        print("\n2. Проверка подключения к Gemini Free Tier / API Key...")
+        api_key = os.environ.get("GEMINI_API_KEY")
+        if not api_key:
+            # check local env files
+            import glob
+            for path in glob.glob(".env*"):
+                try:
+                    for line in open(path):
+                        if "GEMINI_API_KEY=" in line:
+                            api_key = line.split("=", 1)[1].strip().strip("\"'")
+                            break
+                except Exception:
+                    pass
+
+        if api_key:
+            client_free = genai.Client(api_key=api_key)
+            print(f"   ✅ Free Tier API Key найден (...{api_key[-4:]}). Клиент готов к работе.")
+        else:
+            print("   ℹ️ GEMINI_API_KEY не задан явно в окружении.")
+
+    except ImportError:
+        print("   ❌ SDK `google-genai` не установлен. Установите: pip install google-genai")
+
+    print("==================================================")
+    print("✅ Настройка Agent Platform готова к использованию в ADK / Agent Studio!")
+    print("==================================================")
+
+
+if __name__ == "__main__":
+    test_agent_platform_connection()

scripts/serpentos_logic/agent_platform_playground_server.py

@@ -0,0 +1,128 @@
+#!/usr/bin/env python3
+"""
+🌐 GEMINI ENTERPRISE AGENT PLATFORM - INTERACTIVE PLAYGROUND SERVER
+Serves an ultra-modern Web UI on http://localhost:8088 supporting:
+1. Live Model & Infrastructure Status (Vertex AI ADC, 9Router Proxy :20128, TokenSaver :4000)
+2. Director's Veo 3 / Gemini Prompt Studio with Anti-Hallucination & Consistency Locks
+3. 9Router 3-Stage Multi-Agent Orchestration Sandbox
+4. SATC Reference vs. 777Ladies Title Sequence Comparison Player
+"""
+
+import http.server
+import json
+import os
+import socketserver
+import urllib.request
+from pathlib import Path
+
+PORT = int(os.environ.get("PLAYGROUND_PORT", "8088"))
+ROOT_DIR = Path(__file__).resolve().parent.parent
+PLAYGROUND_DIR = ROOT_DIR / "packages" / "agent-platform-playground"
+PLAYGROUND_DIR.mkdir(parents=True, exist_ok=True)
+
+
+def check_port(host="localhost", port=8088, timeout=1.0):
+    import socket
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+        s.settimeout(timeout)
+        return s.connect_ex((host, port)) == 0
+
+
+class PlaygroundHandler(http.server.SimpleHTTPRequestHandler):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, directory=str(PLAYGROUND_DIR), **kwargs)
+
+    def do_GET(self):
+        if self.path == "/api/status":
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+
+            ts_ok = check_port("localhost", 4000)
+            router_ok = check_port("localhost", 20128)
+
+            status = {
+                "project_id": "project-f91a723f-af1b-4dd2-ba3",
+                "region": "europe-west3",
+                "adc_mode": "Vertex AI ADC (CLAUDE_CODE_USE_VERTEX=1)",
+                "tokensaver_active": ts_ok,
+                "nine_router_active": router_ok,
+                "models_available": [
+                    {"id": "veo-3.1-fast-generate-001", "tier": "Vertex AI / Agent Platform"},
+                    {"id": "gemini-3.1-pro-preview", "tier": "9Router / Vertex"},
+                    {"id": "free-reasoning", "tier": "9Router Planning"},
+                    {"id": "free-coder", "tier": "9Router Coding"},
+                    {"id": "free-agent", "tier": "9Router Reviewing"}
+                ]
+            }
+            self.wfile.write(json.dumps(status).encode("utf-8"))
+            return
+
+        elif self.path == "/api/presets":
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+
+            presets = [
+                {
+                    "title": "SATC 1998 HBO Opening Hero Shot (Scene 01)",
+                    "prompt": "[ANTI-TEXT] No titles, no overlays, no letters. [CHARACTER LOCK] Late 30s iconic Manhattan fashion columnist, blonde hair with platinum highlights, pink bubblegum tank top, white tulle tutu skirt. [CINEMATOGRAPHY] 35mm Kodak Vision3 500T grain, soft golden hour rim light, 24fps smooth slow dolly back on Fifth Avenue.",
+                    "seed": 42001,
+                    "model": "veo-3.1-fast-generate-001"
+                },
+                {
+                    "title": "777Ladies Casino Neon Glamour B-Roll",
+                    "prompt": "[ANTI-TEXT] No text, clean cinematic shot. [SETTING] Luxurious velvet casino lounge, gleaming gold chandelier reflections, emerald felt roulette table in soft out-of-focus background. [CINEMATOGRAPHY] 35mm anamorphic lens flare, slow tracking push-in at 24fps.",
+                    "seed": 77701,
+                    "model": "veo-3.1-fast-generate-001"
+                }
+            ]
+            self.wfile.write(json.dumps(presets).encode("utf-8"))
+            return
+
+        super().do_GET()
+
+    def do_POST(self):
+        content_len = int(self.headers.get("Content-Length", 0))
+        body = self.rfile.read(content_len).decode("utf-8")
+        data = json.loads(body) if body else {}
+
+        if self.path == "/api/orchestrate":
+            from delegate_via_9router import delegate_task
+            task_desc = data.get("task", "Verify Veo 3 video generation parameters")
+
+            # Execute fast single or 3-stage proxy orchestration
+            res = delegate_task(
+                role=data.get("role", "planning"),
+                prompt=task_desc,
+                system_prompt="You are an expert AI Architect on Google Agent Platform. Provide actionable, concise engineering recommendations."
+            )
+
+            self.send_response(200)
+            self.send_header("Content-Type", "application/json")
+            self.end_headers()
+            self.wfile.write(json.dumps(res).encode("utf-8"))
+            return
+
+        self.send_response(404)
+        self.end_headers()
+
+
+def run():
+    print("======================================================================")
+    print("🌐 GEMINI ENTERPRISE AGENT PLATFORM - INTERACTIVE PLAYGROUND")
+    print("======================================================================")
+    print(f"🚀 Serving Web UI & API on: http://localhost:{PORT}/")
+    print(f"📁 Static Assets Directory: {PLAYGROUND_DIR}")
+    print("======================================================================")
+
+    with socketserver.TCPServer(("0.0.0.0", PORT), PlaygroundHandler) as httpd:
+        httpd.allow_reuse_address = True
+        try:
+            httpd.serve_forever()
+        except KeyboardInterrupt:
+            print("\nShutting down playground server...")
+
+
+if __name__ == "__main__":
+    run()

scripts/serpentos_logic/agent_platform_veo.py

@@ -0,0 +1,156 @@
+#!/usr/bin/env python3
+"""
+🎬 AGENT PLATFORM (VERTEX AI) VEO 3 GENERATOR
+Generates SATC HBO-style cinematic scenes using Google GenAI SDK on Agent Platform (Vertex AI).
+Strictly adheres to mandatory prompt tags: [MOTION], [TECH], [ANTI-STATIC].
+"""
+
+import argparse
+import os
+import sys
+import time
+from pathlib import Path
+
+from google import genai
+from google.genai import types
+
+OUTPUT_DIR = Path("/Users/work/serpentos/outputs/satc_hbo_23scenes")
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+SCENES = {
+    1: {
+        "timecode": "t01.00s",
+        "title": "Daytime Manhattan establishing walk",
+        "prompt": """[MOTION] A stylish woman in a voluminous pink tulle midi skirt and nude kitten heels walks confidently toward camera on a broad Midtown sidewalk. Camera: 28mm backward tracking, Steadicam smooth.
+[TECH] Video: 4s, 24fps, continuous motion every frame, no freeze-frames, no static shots, no cinematic pause.
+[ANTI-STATIC] Start motion from frame 1. Every second must contain visible movement. No establishing still frame at start.
+[ANTI-TEXT] ABSOLUTELY NO text overlays, NO titles, NO credits, NO logos, NO watermarks, NO written words on screen. Pure clean cinematic live-action footage only.
+
+Cinematic romantic comedy opening, Full HD 1920x1080, no audio, 24fps. Pure visual footage without any title cards or typography.
+Daytime Manhattan, wide establishing shot. A stylish woman in a voluminous
+pink tulle midi skirt and nude kitten heels walks confidently toward camera
+on a broad Midtown sidewalk. Camera: 28mm backward tracking, hip height,
+Steadicam smooth. Yellow taxis and warm-lit storefronts flank both sides,
+creating deep perspective. Tulle skirt catches air with each step, natural
+movement. Super-16 film grain, lifted blacks, warm golden midtones,
+neutral-cool city shadows, high saturation. HBO prestige TV aesthetic."""
+    },
+    2: {
+        "timecode": "t12.48s",
+        "title": "Woman walking past bright yellow city bus",
+        "prompt": """[MOTION] Stylish woman walks left-to-right in frame, pink tulle skirt, nude pumps. 35mm medium tracking shot, chest height, slight arc. A large bright yellow city bus passes behind her from left to right with motion blur on wheels.
+[TECH] Video: 4s, 24fps, continuous motion every frame, no freeze-frames, no static shots, no cinematic pause.
+[ANTI-STATIC] Start motion from frame 1. Every second must contain visible movement. No establishing still frame at start.
+[ANTI-TEXT] ABSOLUTELY NO text overlays, NO titles, NO credits, NO logos, NO watermarks, NO written words on screen. Pure clean cinematic live-action footage only.
+
+Cinematic romantic comedy, Full HD 1920x1080, no audio, 24fps. Pure visual footage without any title cards or typography.
+Midtown Manhattan sidewalk, late afternoon soft overcast light. Same
+stylish woman walks left-to-right in frame, pink tulle skirt, nude pumps.
+Camera: 35mm medium tracking shot, chest height, slight arc. A large bright
+yellow city bus passes behind her from left to right, momentarily obscuring
+the background buildings. The bus creates a dynamic colour contrast against
+the muted urban grey. Motion blur on bus wheels, reflections on wet
+pavement. Warm tones, film grain, lifted blacks. HBO prestige TV aesthetic."""
+    }
+}
+
+def run_agent_platform_veo(scene_num: int, model_name: str = "veo-3.1-lite-generate-001", gcs_uri: str = "gs://gamb"):
+    if scene_num not in SCENES:
+        print(f"❌ Scene {scene_num} not in definitions.")
+        return False
+
+    scene = SCENES[scene_num]
+    out_file = OUTPUT_DIR / f"scene_{scene_num:02d}_{scene['timecode'].replace('.', '_')}.mp4"
+
+    print("==================================================")
+    print(f"🎬 AGENT PLATFORM GENERATING SCENE #{scene_num:02d} ({scene['timecode']}): {scene['title']}")
+    print(f"   Model: {model_name} | Project: project-f91a723f-af1b-4dd2-ba3 | Region: us-central1")
+    print(f"   Target Output: {out_file}")
+    print("==================================================")
+
+    # Initialize Agent Platform (Vertex AI) client
+    client = genai.Client(
+        vertexai=True,
+        project="project-f91a723f-af1b-4dd2-ba3",
+        location="us-central1",
+    )
+
+    source = types.GenerateVideosSource(
+        prompt=scene["prompt"],
+    )
+
+    config_kwargs = {
+        "aspect_ratio": "16:9",
+        "number_of_videos": 1,
+        "duration_seconds": 4,
+        "person_generation": "allow_all",
+        "generate_audio": False,
+        "resolution": "1080p",
+        "seed": 0,
+    }
+    if gcs_uri:
+        config_kwargs["output_gcs_uri"] = gcs_uri
+
+    config = types.GenerateVideosConfig(**config_kwargs)
+
+    print("🚀 Dispatching request to Agent Platform...")
+    operation = client.models.generate_videos(
+        model=model_name,
+        source=source,
+        config=config
+    )
+
+    print(f"⏳ Operation created: {operation.name}")
+    start_time = time.time()
+    while not operation.done:
+        elapsed = int(time.time() - start_time)
+        print(f"   ⏳ [{elapsed}s] Video generation in progress... checking again in 10s...")
+        time.sleep(10)
+        operation = client.operations.get(operation)
+
+    if operation.error:
+        print(f"❌ Operation error: {operation.error}")
+
+    response = operation.result
+    if not response:
+        print(f"❌ Error occurred while generating video. Full operation dump:\n{operation}")
+        return False
+
+    generated_videos = response.generated_videos
+    if not generated_videos:
+        print("❌ No videos were generated.")
+        return False
+
+    print(f"✅ Generated {len(generated_videos)} video(s) successfully!")
+    for idx, generated_video in enumerate(generated_videos):
+        vid = generated_video.video
+        if vid:
+            # Save local MP4
+            try:
+                if hasattr(vid, "video_bytes") and vid.video_bytes:
+                    with open(out_file, "wb") as f:
+                        f.write(vid.video_bytes)
+                    print(f"🎯 Saved MP4 locally: {out_file} ({out_file.stat().st_size} bytes)")
+                elif hasattr(vid, "uri") and vid.uri:
+                    print(f"📦 Video saved to GCS URI: {vid.uri}")
+                    # Attempt to download from GCS via gcloud
+                    import subprocess
+                    print(f"⬇️ Downloading from GCS to {out_file}...")
+                    subprocess.run(["gcloud", "storage", "cp", vid.uri, str(out_file)], check=False)
+                    if out_file.exists():
+                        print(f"🎯 Downloaded MP4 locally: {out_file} ({out_file.stat().st_size} bytes)")
+                else:
+                    print(f"INFO: Video object attributes: {dir(vid)}")
+            except Exception as e:
+                print(f"⚠️ Warning saving local file: {e}")
+
+    return True
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Agent Platform Veo 3 Generator")
+    parser.add_argument("--scene", type=int, default=2, help="Scene number to generate (default: 2)")
+    parser.add_argument("--model", type=str, default="veo-3.1-lite-generate-001", help="Model name")
+    parser.add_argument("--gcs", type=str, default="gs://gamb", help="GCS URI bucket")
+    args = parser.parse_args()
+
+    run_agent_platform_veo(args.scene, model_name=args.model, gcs_uri=args.gcs)

scripts/serpentos_logic/agy-autoswitch.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+# agy-autoswitch.sh — Запуск AGY агента с автоматическим переключением аккаунтов
+# Использует GEMINI_API_KEYS (2 ключа) для двойной квоты: 3000 RPD бесплатно
+#
+# Использование:
+#   ./scripts/agy-autoswitch.sh "Research task"
+#   ./scripts/agy-autoswitch.sh --autoresearch --iterations 5
+#   ./scripts/agy-autoswitch.sh --test-providers
+#   ./scripts/agy-autoswitch.sh --loop ralph
+#
+# Cascade Fallback:
+#   1. AGY Account 1 (Gemini 2.5 Flash) — 1500 RPD free
+#   2. AGY Account 2 (Gemini 2.0 Flash) — +1500 RPD free (multi-account rotation)
+#   3. NVIDIA NIM (Nemotron-51B, Llama 3.3-70B) — 40 RPM sandbox
+#   4. GitHub Models (Llama 3.3-70B, GPT-4o) — 150 RPD free
+#   5. Cloudflare Workers AI (Llama 3.3-70B fp8) — 10k neurons/day
+#   6. Groq LPU (Llama 4 Scout, Llama 3.3-70B) — up to 14400 RPD
+#   7. Ollama Local (qwen2.5-coder) — zero cost, offline
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REPO_DIR="$(dirname "$SCRIPT_DIR")"
+AGY_AGENT="$REPO_DIR/packages/jarvis/agy-agent/agent.py"
+
+# Load Doppler secrets and run via pinned uv environment
+if command -v uv &>/dev/null; then
+  exec doppler run --project serpent --config prd -- uv run --no-project --with "google-antigravity==0.1.5" python3 "$AGY_AGENT" "$@"
+else
+  exec doppler run --project serpent --config prd -- python3 "$AGY_AGENT" "$@"
+fi

scripts/serpentos_logic/agy-omniroute.sh

@@ -0,0 +1,48 @@
+#!/bin/bash
+# agy-omniroute.sh — запуск Antigravity CLI через TokenSaver→OmniRoute
+# Стек: AGY → TokenSaver(:4000) → OmniRoute(:20128) → 11 провайдеров
+# Обновлено: 2026-08-06
+
+# ── 1. Убеждаемся что TokenSaver запущен ────────────────────────────────────
+TS_HEALTH=$(curl -s --max-time 2 http://localhost:4000/health 2>/dev/null)
+if echo "$TS_HEALTH" | grep -q '"status":"ok"'; then
+  echo "✅ TokenSaver :4000 running (cache=$(echo "$TS_HEALTH" | python3 -c "import json,sys; d=json.load(sys.stdin); print(d.get('cache_entries',0))" 2>/dev/null) entries)"
+else
+  echo "⚡ Starting TokenSaver..."
+  TOKENSAVER_CLOUD_ONLY=1 python3 ~/token-saver/tokensaver.py --server \
+    > ~/.tokensaver/tokensaver.log 2>&1 &
+  sleep 4
+fi
+
+# ── 2. OmniRoute :20128 health ───────────────────────────────────────────────
+OMNI_MODELS=$(curl -s --max-time 3 http://localhost:20128/v1/models 2>/dev/null \
+  | python3 -c "import json,sys; d=json.load(sys.stdin); print(len(d.get('data',[])))" 2>/dev/null)
+echo "✅ OmniRoute :20128 — ${OMNI_MODELS:-0} models"
+
+# ── 3. Env для AGY: TokenSaver как OpenAI-compatible proxy ───────────────────
+# AGY subagents/tools → TokenSaver → OmniRoute → провайдеры
+export OPENAI_BASE_URL="http://localhost:4000/v1"
+export OPENAI_API_KEY="local-agy"
+
+# Для Claude Code subagents
+export ANTHROPIC_BASE_URL="http://localhost:4000"
+
+# OmniRoute прямо (для Gemini-native AGY core)
+export OMNIROUTE_BASE_URL="http://localhost:20128/v1"
+
+# Agent ID для трекинга в TokenSaver
+export TOKENSAVER_AGENT_ID="agy-main"
+export X_CLAUDE_CODE_AGENT_ID="agy-main"
+
+# Настройки для Hermes Agent (с предыдущих запросов)
+export HERMES_PROVIDER="custom"
+export HERMES_API_BASE="http://localhost:4000/v1"
+export HERMES_DEFAULT_MODEL="coding"
+
+echo "🔀 Routing: AGY → TokenSaver(:4000) → OmniRoute(:20128)"
+echo "   OPENAI_BASE_URL=$OPENAI_BASE_URL"
+echo "   ANTHROPIC_BASE_URL=$ANTHROPIC_BASE_URL"
+echo "   TokenSaver Models: google-ai-pro, gemini-3.5-flash, gemini-3.6-flash"
+echo ""
+
+exec /Users/work/.local/bin/agy "$@"