#!/usr/bin/env bash # 07-rag-setup.sh — Create Vertex AI RAG Engine corpus in Serverless mode # Uses REST API directly — no SDK version dependency # RAG_REGION defaults to europe-west4 (Serverless available, no allowlist) # Uploads ALL docs/*.md + corpus-seed/*.md + protocols/sessions/*.md to GCS # Idempotent — safe to run multiple times # Source .env before running: source .env # # VERIFIED WORKING ENDPOINT: # POST /v1beta1/.../ragCorpora/{id}/ragFiles:import # NOTE: Only ONE import operation can run at a time per corpus (FAILED_PRECONDITION otherwise) set -euo pipefail : "${PROJECT_ID:?Set PROJECT_ID}" : "${REGION:?Set REGION}" : "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}" # ── Region Guard ──────────────────────────────────────────────────────── source "$(dirname "$0")/99-region-guard.sh" RAG_REGION=$(validate_rag_region "${RAG_REGION:-${REGION}}") log_region_context "RAG-Engine" "$RAG_REGION" "VALIDATED" REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)" echo "=== 07: Setting up Vertex AI RAG Engine (Serverless mode) ===" echo " Project : ${PROJECT_ID}" echo " Region : ${RAG_REGION} (override with RAG_REGION= if needed)" 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 (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 alle kildedokumenter til GCS ────────────────────────────────── UPLOAD_COUNT=0 SEED_DIR="${REPO_ROOT}/docs/corpus-seed" if [[ -d "${SEED_DIR}" ]] && compgen -G "${SEED_DIR}/*.md" > /dev/null 2>&1; then gsutil -m cp "${SEED_DIR}"/*.md "gs://${CORPUS_BUCKET}/seed/" 2>/dev/null || true COUNT=$(ls "${SEED_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ') echo "✓ corpus-seed/: ${COUNT} filer → gs://${CORPUS_BUCKET}/seed/" UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT)) fi DOCS_DIR="${REPO_ROOT}/docs" if compgen -G "${DOCS_DIR}/*.md" > /dev/null 2>&1; then gsutil -m cp "${DOCS_DIR}"/*.md "gs://${CORPUS_BUCKET}/docs/" 2>/dev/null || true COUNT=$(ls "${DOCS_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ') echo "✓ docs/: ${COUNT} filer → gs://${CORPUS_BUCKET}/docs/" UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT)) fi SESSIONS_DIR="${REPO_ROOT}/protocols/sessions" if [[ -d "${SESSIONS_DIR}" ]] && compgen -G "${SESSIONS_DIR}/*.md" > /dev/null 2>&1; then gsutil -m cp "${SESSIONS_DIR}"/*.md "gs://${CORPUS_BUCKET}/sessions/" 2>/dev/null || true COUNT=$(ls "${SESSIONS_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ') echo "✓ protocols/sessions/: ${COUNT} filer → gs://${CORPUS_BUCKET}/sessions/" UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT)) fi if [[ -f "${REPO_ROOT}/MASTERPLAN.md" ]]; then gsutil cp "${REPO_ROOT}/MASTERPLAN.md" "gs://${CORPUS_BUCKET}/MASTERPLAN.md" 2>/dev/null || true echo "✓ MASTERPLAN.md → gs://${CORPUS_BUCKET}/MASTERPLAN.md" UPLOAD_COUNT=$((UPLOAD_COUNT + 1)) fi echo " Totalt ${UPLOAD_COUNT} filer synkronisert" # ── REST: hent/opprett corpus ─────────────────────────────────────────── TOKEN=$(gcloud auth print-access-token) BASE_URL="https://${RAG_REGION}-aiplatform.googleapis.com/v1beta1" PARENT="projects/${PROJECT_ID}/locations/${RAG_REGION}" echo " Sjekker om corpus finnes..." EXISTING=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \ "${BASE_URL}/${PARENT}/ragCorpora" 2>/dev/null || echo '{}') CORPUS_NAME=$(echo "${EXISTING}" | python3 -c " import sys, json data = json.load(sys.stdin) for c in data.get('ragCorpora', []): if c.get('displayName') == '${RAG_CORPUS_DISPLAY_NAME}': print(c['name']) break " 2>/dev/null || true) if [[ -n "${CORPUS_NAME}" ]]; then echo "✓ RAG corpus finnes allerede: ${CORPUS_NAME}" else echo " Oppretter corpus '${RAG_CORPUS_DISPLAY_NAME}' i ${RAG_REGION}..." RESPONSE=$(curl -sf -X POST \ -H "Authorization: Bearer ${TOKEN}" \ -H "Content-Type: application/json" \ "${BASE_URL}/${PARENT}/ragCorpora" \ -d '{"displayName":"'"${RAG_CORPUS_DISPLAY_NAME}"'","ragEmbeddingModelConfig":{"vertexPredictionEndpoint":{"publisherModel":"publishers/google/models/text-embedding-005"}},"ragVectorDbConfig":{"ragManagedDb":{}}}') OPERATION=$(echo "${RESPONSE}" | python3 -c "import sys,json; print(json.load(sys.stdin).get('name',''))" 2>/dev/null || true) [[ -z "${OPERATION}" ]] && { echo "ERROR: ${RESPONSE}"; exit 1; } echo " Venter på LRO..." for i in $(seq 1 30); do sleep 10 LRO=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \ "${BASE_URL}/${OPERATION}" 2>/dev/null || echo '{}') DONE=$(echo "${LRO}" | python3 -c "import sys,json; print(json.load(sys.stdin).get('done',False))" 2>/dev/null || echo 'False') if [[ "${DONE}" == "True" ]]; then CORPUS_NAME=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \ "${BASE_URL}/${PARENT}/ragCorpora" 2>/dev/null \ | python3 -c " import sys,json data=json.load(sys.stdin) for c in data.get('ragCorpora',[]): if c.get('displayName')=='${RAG_CORPUS_DISPLAY_NAME}': print(c['name']); break " 2>/dev/null || true) echo "✓ Corpus opprettet: ${CORPUS_NAME}" break fi echo " ... venter (${i}/30)" done [[ -z "${CORPUS_NAME}" ]] && { echo "ERROR: timed out"; exit 1; } fi # ── Hjelpefunksjon: trigge import og VENT til den er ferdig før neste ──────── # Vertex AI RAG tillater kun 1 aktiv import-operasjon per corpus om gangen. IMPORT_BASE="${BASE_URL}/${CORPUS_NAME}/ragFiles:import" echo " Import URL: ${IMPORT_BASE}" IMPORT_OK=0 wait_for_op() { local OP="$1" local SHORT="${OP##*/}" for i in $(seq 1 40); do sleep 15 local LRO DONE LRO=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \ "${BASE_URL}/${OP}" 2>/dev/null || echo '{}') DONE=$(echo "${LRO}" | python3 -c "import sys,json; print(json.load(sys.stdin).get('done',False))" 2>/dev/null || echo 'False') if [[ "${DONE}" == "True" ]]; then echo " ✓ Ferdig: ${SHORT}" return 0 fi echo " ... ${SHORT} (${i}/40)" done echo " ADVARSEL: Timed out venter på ${SHORT}" return 1 } for GCS_PATH in "seed/" "docs/" "sessions/" "MASTERPLAN.md"; do GCS_URI="gs://${CORPUS_BUCKET}/${GCS_PATH}" if gsutil ls "${GCS_URI}" &>/dev/null; then RESP=$(curl -s -o /tmp/import_resp.json -w "%{http_code}" -X POST \ -H "Authorization: Bearer ${TOKEN}" \ -H "Content-Type: application/json" \ "${IMPORT_BASE}" \ -d '{"importRagFilesConfig":{"gcsSource":{"uris":["'"${GCS_URI}"'"]},"ragFileChunkingConfig":{"chunkSize":512,"chunkOverlap":50}}}') if [[ "${RESP}" == "200" ]]; then OP_NAME=$(python3 -c "import json; print(json.load(open('/tmp/import_resp.json')).get('name',''))" 2>/dev/null || true) echo "✓ Import trigget: ${GCS_URI} [op: ${OP_NAME##*/}]" IMPORT_OK=$((IMPORT_OK + 1)) # Vent til denne er ferdig før vi starter neste wait_for_op "${OP_NAME}" else echo " ADVARSEL: Import feilet (HTTP ${RESP}): ${GCS_URI}" cat /tmp/import_resp.json 2>/dev/null || true fi fi done echo " ${IMPORT_OK}/4 import-jobber fullført" # ── Verifiser: tell antall indekserte filer ────────────────────────────────── RAG_FILE_COUNT=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \ "${BASE_URL}/${CORPUS_NAME}/ragFiles" 2>/dev/null \ | python3 -c "import sys,json; d=json.load(sys.stdin); print(len(d.get('ragFiles',[])))" 2>/dev/null || echo '?') echo "✓ Indekserte RAG-filer i corpus: ${RAG_FILE_COUNT}" # ── Output ──────────────────────────────────────────────────────────────── echo "${CORPUS_NAME}" > /tmp/rag_corpus_name.txt echo "" echo " Corpus resource name : ${CORPUS_NAME}" echo " Region : ${RAG_REGION}" echo "" echo " ACTION REQUIRED — legg til i .env:" echo " export RAG_CORPUS_NAME=\"${CORPUS_NAME}\"" echo " export RAG_REGION=\"${RAG_REGION}\"" echo "" echo "=== 07: RAG Engine setup COMPLETE ===" echo " View: https://console.cloud.google.com/vertex-ai/rag?project=${PROJECT_ID}" echo ""