172 lines
7.6 KiB
Bash
172 lines
7.6 KiB
Bash
#!/usr/bin/env bash
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# 07-rag-setup.sh — Create Vertex AI RAG Engine corpus in Serverless mode
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# Uses REST API directly — no SDK version dependency
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# RAG_REGION defaults to europe-west4 (Serverless available, no allowlist)
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# Uploads ALL docs/*.md + corpus-seed/*.md + protocols/sessions/*.md to GCS
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# Idempotent — safe to run multiple times
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# Source .env before running: source .env
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set -euo pipefail
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: "${PROJECT_ID:?Set PROJECT_ID}"
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: "${REGION:?Set REGION}"
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: "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}"
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RAG_REGION="${RAG_REGION:-europe-west4}"
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REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
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echo "=== 07: Setting up Vertex AI RAG Engine (Serverless mode) ==="
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echo " Project : ${PROJECT_ID}"
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echo " Region : ${RAG_REGION} (override with RAG_REGION= if needed)"
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echo " Corpus : ${RAG_CORPUS_DISPLAY_NAME}"
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echo ""
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bash "$(dirname "$0")/00-authcheck.sh"
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gcloud services enable aiplatform.googleapis.com \
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storage.googleapis.com \
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--project="${PROJECT_ID}" --quiet
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echo "✓ APIs enabled"
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# ── Hent project-number (kræves av importRagFiles-endepunktet) ────────────────
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PROJECT_NUMBER=$(gcloud projects describe "${PROJECT_ID}" \
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--format='value(projectNumber)' 2>/dev/null)
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echo " Project number: ${PROJECT_NUMBER}"
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# ── GCS bucket (idempotent) ─────────────────────────────────────────────
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CORPUS_BUCKET="${PROJECT_ID}-agent-corpus"
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if ! gsutil ls -b "gs://${CORPUS_BUCKET}" &>/dev/null; then
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gsutil mb -l "${REGION}" -b on "gs://${CORPUS_BUCKET}"
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echo "✓ GCS corpus bucket created: gs://${CORPUS_BUCKET}"
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else
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echo "✓ GCS corpus bucket exists: gs://${CORPUS_BUCKET}"
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fi
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# ── Upload alle kildedokumenter til GCS ──────────────────────────────────────
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UPLOAD_COUNT=0
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SEED_DIR="${REPO_ROOT}/docs/corpus-seed"
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if [[ -d "${SEED_DIR}" ]] && compgen -G "${SEED_DIR}/*.md" > /dev/null 2>&1; then
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gsutil -m cp "${SEED_DIR}"/*.md "gs://${CORPUS_BUCKET}/seed/" 2>/dev/null || true
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COUNT=$(ls "${SEED_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ')
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echo "✓ corpus-seed/: ${COUNT} filer → gs://${CORPUS_BUCKET}/seed/"
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UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT))
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fi
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DOCS_DIR="${REPO_ROOT}/docs"
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if compgen -G "${DOCS_DIR}/*.md" > /dev/null 2>&1; then
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gsutil -m cp "${DOCS_DIR}"/*.md "gs://${CORPUS_BUCKET}/docs/" 2>/dev/null || true
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COUNT=$(ls "${DOCS_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ')
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echo "✓ docs/: ${COUNT} filer → gs://${CORPUS_BUCKET}/docs/"
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UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT))
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fi
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SESSIONS_DIR="${REPO_ROOT}/protocols/sessions"
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if [[ -d "${SESSIONS_DIR}" ]] && compgen -G "${SESSIONS_DIR}/*.md" > /dev/null 2>&1; then
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gsutil -m cp "${SESSIONS_DIR}"/*.md "gs://${CORPUS_BUCKET}/sessions/" 2>/dev/null || true
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COUNT=$(ls "${SESSIONS_DIR}"/*.md 2>/dev/null | wc -l | tr -d ' ')
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echo "✓ protocols/sessions/: ${COUNT} filer → gs://${CORPUS_BUCKET}/sessions/"
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UPLOAD_COUNT=$((UPLOAD_COUNT + COUNT))
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fi
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if [[ -f "${REPO_ROOT}/MASTERPLAN.md" ]]; then
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gsutil cp "${REPO_ROOT}/MASTERPLAN.md" "gs://${CORPUS_BUCKET}/MASTERPLAN.md" 2>/dev/null || true
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echo "✓ MASTERPLAN.md → gs://${CORPUS_BUCKET}/MASTERPLAN.md"
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UPLOAD_COUNT=$((UPLOAD_COUNT + 1))
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fi
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echo " Totalt ${UPLOAD_COUNT} filer synkronisert"
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# ── REST: hent/opprett corpus (bruker project-ID for listing/oppretting) ────────
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TOKEN=$(gcloud auth print-access-token)
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BASE_URL="https://${RAG_REGION}-aiplatform.googleapis.com/v1beta1"
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PARENT="projects/${PROJECT_ID}/locations/${RAG_REGION}"
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echo " Sjekker om corpus finnes..."
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EXISTING=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \
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"${BASE_URL}/${PARENT}/ragCorpora" 2>/dev/null || echo '{}')
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CORPUS_NAME=$(echo "${EXISTING}" | python3 -c "
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import sys, json
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data = json.load(sys.stdin)
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for c in data.get('ragCorpora', []):
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if c.get('displayName') == '${RAG_CORPUS_DISPLAY_NAME}':
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print(c['name'])
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break
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" 2>/dev/null || true)
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if [[ -n "${CORPUS_NAME}" ]]; then
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echo "✓ RAG corpus finnes allerede: ${CORPUS_NAME}"
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else
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echo " Oppretter corpus '${RAG_CORPUS_DISPLAY_NAME}' i ${RAG_REGION}..."
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RESPONSE=$(curl -sf -X POST \
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-H "Authorization: Bearer ${TOKEN}" \
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-H "Content-Type: application/json" \
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"${BASE_URL}/${PARENT}/ragCorpora" \
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-d '{"displayName":"'"${RAG_CORPUS_DISPLAY_NAME}"'","ragEmbeddingModelConfig":{"vertexPredictionEndpoint":{"publisherModel":"publishers/google/models/text-embedding-005"}},"ragVectorDbConfig":{"ragManagedDb":{}}}')
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OPERATION=$(echo "${RESPONSE}" | python3 -c "import sys,json; print(json.load(sys.stdin).get('name',''))" 2>/dev/null || true)
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[[ -z "${OPERATION}" ]] && { echo "ERROR: ${RESPONSE}"; exit 1; }
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echo " Venter på LRO..."
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for i in $(seq 1 30); do
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sleep 10
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LRO=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \
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"https://${RAG_REGION}-aiplatform.googleapis.com/v1beta1/${OPERATION}" 2>/dev/null || echo '{}')
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DONE=$(echo "${LRO}" | python3 -c "import sys,json; print(json.load(sys.stdin).get('done',False))" 2>/dev/null || echo 'False')
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if [[ "${DONE}" == "True" ]]; then
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CORPUS_NAME=$(curl -sf -H "Authorization: Bearer ${TOKEN}" \
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"${BASE_URL}/${PARENT}/ragCorpora" 2>/dev/null \
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| python3 -c "
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import sys,json
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data=json.load(sys.stdin)
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for c in data.get('ragCorpora',[]):
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if c.get('displayName')=='${RAG_CORPUS_DISPLAY_NAME}': print(c['name']); break
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" 2>/dev/null || true)
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echo "✓ Corpus opprettet: ${CORPUS_NAME}"
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break
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fi
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echo " ... venter (${i}/30)"
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done
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[[ -z "${CORPUS_NAME}" ]] && { echo "ERROR: timed out"; exit 1; }
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fi
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# Hent corpus-ID (siste del av ressursstien)
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CORPUS_ID=$(echo "${CORPUS_NAME}" | rev | cut -d'/' -f1 | rev)
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# ── Import: bygg URL med project-NUMBER (ikke project-ID) ───────────────────────
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# importRagFiles krever project-number i stien
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IMPORT_URL="https://${RAG_REGION}-aiplatform.googleapis.com/v1beta1/projects/${PROJECT_NUMBER}/locations/${RAG_REGION}/ragCorpora/${CORPUS_ID}:importRagFiles"
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echo " Import URL: ${IMPORT_URL}"
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IMPORT_OK=0
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for GCS_PATH in "seed/" "docs/" "sessions/" "MASTERPLAN.md"; do
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GCS_URI="gs://${CORPUS_BUCKET}/${GCS_PATH}"
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if gsutil ls "${GCS_URI}" &>/dev/null; then
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HTTP_STATUS=$(curl -s -o /tmp/import_response.json -w "%{http_code}" -X POST \
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-H "Authorization: Bearer ${TOKEN}" \
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-H "Content-Type: application/json" \
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"${IMPORT_URL}" \
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-d '{"importRagFilesConfig":{"gcsSource":{"uris":["'"${GCS_URI}"'"]},"ragFileChunkingConfig":{"chunkSize":512,"chunkOverlap":50}}}')
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if [[ "${HTTP_STATUS}" == "200" ]]; then
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echo "✓ Import trigget: ${GCS_URI}"
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IMPORT_OK=$((IMPORT_OK + 1))
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else
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echo " ADVARSEL: Import feilet (HTTP ${HTTP_STATUS}): ${GCS_URI}"
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cat /tmp/import_response.json 2>/dev/null || true
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fi
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fi
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done
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echo " ${IMPORT_OK}/4 import-jobber trigget (async — indeksering tar noen minutter)"
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# ── Output ─────────────────────────────────────────────────────────────────
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echo "${CORPUS_NAME}" > /tmp/rag_corpus_name.txt
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echo ""
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echo " Corpus resource name : ${CORPUS_NAME}"
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echo " Region : ${RAG_REGION}"
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echo ""
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echo " ACTION REQUIRED — legg til i .env:"
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echo " export RAG_CORPUS_NAME=\"${CORPUS_NAME}\""
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echo " export RAG_REGION=\"${RAG_REGION}\""
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echo ""
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echo "=== 07: RAG Engine setup COMPLETE ==="
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echo " View: https://console.cloud.google.com/vertex-ai/rag?project=${PROJECT_ID}"
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echo ""
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