LOT 1 - Optimizare script build -Instalare mono comanda

ai_platform/local_gpu_stack/seed/seed_brain.sh

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+#!/usr/bin/env bash
+# Brain stack helpers: render env, align postgres password, create atomic token,
+# seed the canonical taxonomy. Idempotent. Requires lib.sh sourced + master .env
+# loaded ($POSTGRES_PASSWORD, $ATOMIC_TOKEN, $HOST_IP, $ENV_FILE, $BRAIN_DIR).
+
+# Write didi_brain/.env (read by brain-api/scheduler) + infra/.env (compose interpolation)
+brain_write_env() {
+  local pw=$1 tok=$2
+  cp "${BRAIN_DIR}/.env.example" "${BRAIN_DIR}/.env"
+  sed -i \
+    -e "s#^LLM_ROUTER_URL=.*#LLM_ROUTER_URL=http://didiAI-llm-api:14011#" \
+    -e "s#^LLM_VLLM_URL=.*#LLM_VLLM_URL=http://didiAI-vllm-qwen3.5:14001#" \
+    -e "s#^EMBEDDING_URL=.*#EMBEDDING_URL=http://didiAI-embeddings-api:14100#" \
+    -e "s#^RERANKER_URL=.*#RERANKER_URL=http://didiAI-rerank-api:14200#" \
+    -e "s#^MODEL_FAST_ENABLED=.*#MODEL_FAST_ENABLED=true#" \
+    -e "s#^POSTGRES_PASSWORD=.*#POSTGRES_PASSWORD=${pw}#" \
+    "${BRAIN_DIR}/.env"
+  if grep -q '^ATOMIC_TOKEN=' "${BRAIN_DIR}/.env"; then
+    sed -i "s#^ATOMIC_TOKEN=.*#ATOMIC_TOKEN=${tok}#" "${BRAIN_DIR}/.env"
+  else
+    echo "ATOMIC_TOKEN=${tok}" >> "${BRAIN_DIR}/.env"
+  fi
+  printf 'POSTGRES_USER=atomic\nPOSTGRES_PASSWORD=%s\nPOSTGRES_DB=atomic\n' "$pw" > "${BRAIN_DIR}/infra/.env"
+}
+
+# Force the postgres role password to match (volume may have been initialized with a different one)
+brain_align_pg() {
+  local pw=$1
+  docker exec didibrain-postgres psql -U atomic -d atomic \
+    -c "ALTER USER atomic WITH PASSWORD '${pw}';" >/dev/null 2>&1 || true
+}
+
+# Create an atomic API token if the master .env doesn't have one yet. Echos the token.
+brain_ensure_token() {
+  local pw=$1 cur=$2
+  if [ -n "$cur" ]; then printf '%s' "$cur"; return 0; fi
+  local out tok
+  out=$(docker exec didibrain-atomic atomic-server token create --name didibrain \
+          --storage postgres --database-url "postgres://atomic:${pw}@postgres:5432/atomic" 2>&1)
+  tok=$(printf '%s' "$out" | grep -oE 'at_[A-Za-z0-9_.-]{20,}' | head -1)
+  printf '%s' "$tok"
+}
+
+# Seed canonical taxonomy into atomic (idempotent; tags created if missing).
+brain_seed_taxonomy() {
+  docker cp "${BRAIN_DIR}/scripts" didibrain-api:/app/scripts >/dev/null 2>&1 || true
+  # local _tag_ids.json write is read-only in the image — harmless, atomic gets the tags
+  docker exec -e PYTHONPATH=/app didibrain-api python /app/scripts/04_seed_taxonomy.py >/dev/null 2>&1 || true
+}

ai_platform/local_gpu_stack/seed/seed_catalog.sh

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+#!/usr/bin/env bash
+# Idempotent seed of the dashboard DB-backed Model & Extractor catalog.
+# Defines seed_catalog(); requires lib.sh sourced + $HOST_IP set.
+
+seed_catalog() {
+  local base="http://${HOST_IP}:51300/api/catalog"
+  # existing names (idempotency)
+  local existing
+  existing=$(curl -s -m10 "$base" | python3 -c 'import sys,json
+try:
+ d=json.load(sys.stdin); items=d if isinstance(d,list) else d.get("items",d.get("data",[]))
+ print("\n".join(x.get("name","") for x in items))
+except Exception: pass' 2>/dev/null)
+
+  local entries=(
+'{"kind":"model","name":"qwen3.5","display_name":"Qwen3.5-35B-A3B","service":"llm","capabilities":["chat","completion","reasoning"],"context_length":32000,"supports_gpu":true,"endpoint":"http://HOST:14011","notes":"vLLM MoE, GPU 0"}'
+'{"kind":"model","name":"bge-m3","display_name":"BGE-M3 Embeddings","service":"embeddings","capabilities":["embeddings"],"context_length":8192,"supports_gpu":true,"endpoint":"http://HOST:14100","notes":"1024-dim, vLLM GPU 1"}'
+'{"kind":"model","name":"bge-reranker-v2-m3","display_name":"BGE Reranker v2-m3","service":"rerank","capabilities":["rerank"],"context_length":8192,"supports_gpu":true,"endpoint":"http://HOST:14200","notes":"cross-encoder, vLLM GPU 1"}'
+'{"kind":"model","name":"busterx","display_name":"BusterX++ (deepfake)","service":"video","capabilities":["deepfake-detection","video-vlm"],"context_length":32768,"supports_gpu":true,"endpoint":"http://HOST:54600","notes":"Qwen2.5-VL based, vLLM GPU 1"}'
+'{"kind":"model","name":"whisper-large-v3-turbo","display_name":"Whisper large-v3-turbo","service":"audio","capabilities":["transcription","stt"],"supports_gpu":true,"endpoint":"http://HOST:54300","notes":"faster-whisper, GPU 0"}'
+'{"kind":"extractor","name":"gliner-multi-v2.1","display_name":"GLiNER NER (multilingual)","service":"extractors","capabilities":["ner"],"supports_gpu":true,"endpoint":"http://HOST:54400/v1/ner","notes":"validat RO"}'
+'{"kind":"extractor","name":"yolov8n","display_name":"YOLOv8 Object Detection","service":"extractors","capabilities":["object-detection"],"supports_gpu":true,"endpoint":"http://HOST:54400/v1/detect"}'
+'{"kind":"extractor","name":"metadata","display_name":"Media Metadata (EXIF/ELA/ffprobe/C2PA)","service":"extractors","capabilities":["exif","ela","spectrogram","integrity"],"supports_cpu":true,"endpoint":"http://HOST:54400/v1/metadata"}'
+'{"kind":"extractor","name":"forensic-suite","display_name":"Forensic detectors (rPPG/lip-sync/forgery/lighting)","service":"forensic","capabilities":["rppg","lip-sync","forgery-heatmap","lighting"],"supports_gpu":true,"endpoint":"http://HOST:8085/api/forensic-evidence"}'
+  )
+  local added=0 skipped=0 e name
+  for e in "${entries[@]}"; do
+    name=$(printf '%s' "$e" | python3 -c 'import sys,json;print(json.load(sys.stdin)["name"])')
+    if printf '%s\n' "$existing" | grep -qx "$name"; then skipped=$((skipped+1)); continue; fi
+    e=${e//HOST/$HOST_IP}
+    if [ "$(curl -s -m10 -o /dev/null -w '%{http_code}' -X POST "$base" -H 'Content-Type: application/json' -d "$e")" = "200" ]; then
+      added=$((added+1))
+    fi
+  done
+  echo "catalog: +$added adaugate, $skipped existau deja"
+}