#!/usr/bin/env bash # 07-rag-setup.sh — Create Vertex AI RAG Engine corpus and upload initial documents # Idempotent — safe to run multiple times # Source: Vertex AI RAG Engine SDK (google-cloud-aiplatform >= 1.87) # # REGIONAL AVAILABILITY (OQ-02): # RAG Engine in us-central1 requires allowlist access. # This script auto-falls-back to us-east1 if us-central1 is not accessible. # To bypass: export RAG_REGION=us-east1 before running. # # Source .env before running: source .env set -euo pipefail : "${PROJECT_ID:?Set PROJECT_ID}" : "${REGION:?Set REGION}" : "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}" # RAG region fallback: prefer env override, then REGION, fallback to us-east1 RAG_REGION="${RAG_REGION:-${REGION}}" RAG_FALLBACK_REGION="us-east1" echo "=== 07: Setting up Vertex AI RAG Engine ===" echo " Project : ${PROJECT_ID}" echo " Region : ${RAG_REGION} (fallback: ${RAG_FALLBACK_REGION})" echo " Corpus : ${RAG_CORPUS_DISPLAY_NAME}" echo "" bash "$(dirname "$0")/00-authcheck.sh" gcloud services enable aiplatform.googleapis.com \ storage.googleapis.com \ --project="${PROJECT_ID}" --quiet echo "✓ APIs enabled" # ── GCS bucket for corpus source documents (idempotent) ────────────────── CORPUS_BUCKET="${PROJECT_ID}-agent-corpus" if ! gsutil ls -b "gs://${CORPUS_BUCKET}" &>/dev/null; then gsutil mb -l "${REGION}" -b on "gs://${CORPUS_BUCKET}" echo "✓ GCS corpus bucket created: gs://${CORPUS_BUCKET}" else echo "✓ GCS corpus bucket exists: gs://${CORPUS_BUCKET}" fi # ── Upload seed documents if present ───────────────────────────────────── SEED_DIR="$(dirname "$0")/../docs/corpus-seed" if [[ -d "${SEED_DIR}" ]] && ls "${SEED_DIR}"/*.md &>/dev/null; then gsutil -m cp "${SEED_DIR}"/*.md "gs://${CORPUS_BUCKET}/seed/" 2>/dev/null || true echo "✓ Seed documents uploaded to gs://${CORPUS_BUCKET}/seed/" else echo " No seed documents found in docs/corpus-seed/ — skipping upload" fi # ── Run Python to create/update corpus ─────────────────────────────────── python3 - << PYEOF import os, sys try: import vertexai from vertexai.preview import rag except ImportError: print("ERROR: google-cloud-aiplatform not installed.") print("Run: pip install google-cloud-aiplatform>=1.87.0") sys.exit(1) PROJECT_ID = os.environ["PROJECT_ID"] RAG_REGION = os.environ.get("RAG_REGION", os.environ["REGION"]) FALLBACK_REGION = "us-east1" DISPLAY_NAME = os.environ["RAG_CORPUS_DISPLAY_NAME"] CORPUS_BUCKET = f"{PROJECT_ID}-agent-corpus" def try_init_and_list(region): vertexai.init(project=PROJECT_ID, location=region) try: return list(rag.list_corpora()), region except Exception as e: if "PERMISSION_DENIED" in str(e) or "allowlist" in str(e).lower() or "not found" in str(e).lower(): return None, region raise # Try primary region, fall back if needed corpora, active_region = try_init_and_list(RAG_REGION) if corpora is None and RAG_REGION != FALLBACK_REGION: print(f" RAG Engine not available in {RAG_REGION} — falling back to {FALLBACK_REGION}") corpora, active_region = try_init_and_list(FALLBACK_REGION) if corpora is None: print(f"ERROR: RAG Engine not accessible in {RAG_REGION} or {FALLBACK_REGION}.") print("Apply for allowlist: vertex-ai-rag-engine-support@google.com") print("Or set RAG_REGION=us-east1 in .env") sys.exit(1) print(f"✓ RAG Engine accessible in region: {active_region}") # Find or create corpus corpus = None for c in corpora: if c.display_name == DISPLAY_NAME: corpus = c print(f"✓ RAG corpus already exists: {c.name}") break if corpus is None: embedding_config = rag.EmbeddingModelConfig( publisher_model="publishers/google/models/text-embedding-005" ) corpus = rag.create_corpus( display_name=DISPLAY_NAME, embedding_model_config=embedding_config, ) print(f"✓ RAG corpus created: {corpus.name}") # Import seed documents (non-fatal) gcs_uri = f"gs://{CORPUS_BUCKET}/seed/" try: rag.import_files( corpus_name=corpus.name, paths=[gcs_uri], chunk_size=512, chunk_overlap=50, max_embedding_requests_per_min=900, ) print(f"✓ Documents imported from {gcs_uri}") except Exception as e: print(f" WARNING: Document import skipped or failed: {e}") print(f" Import manually: https://console.cloud.google.com/vertex-ai/rag?project={PROJECT_ID}") # Persist corpus name for 08-memorybank-setup.sh and agent with open("/tmp/rag_corpus_name.txt", "w") as f: f.write(corpus.name) print(f"") print(f" Corpus resource name : {corpus.name}") print(f" Active region : {active_region}") print(f"") print(f" ACTION REQUIRED — add to .env:") print(f" RAG_CORPUS_NAME={corpus.name}") if active_region != os.environ.get("REGION"): print(f" RAG_REGION={active_region}") PYEOF echo "" echo "=== 07: RAG Engine setup COMPLETE ===" echo " View corpus: https://console.cloud.google.com/vertex-ai/rag?project=${PROJECT_ID}" echo ""