OSVauco/infrastructure/07-rag-setup.sh

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#!/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/projects/{id}/locations/{region}/ragCorpora/{id}/ragFiles:import
set -euo pipefail
: "${PROJECT_ID:?Set PROJECT_ID}"
: "${REGION:?Set REGION}"
: "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}"
RAG_REGION="${RAG_REGION:-europe-west4}"
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 "${CORPUS_NAME}" ]] && { echo "ERROR: timed out"; exit 1; }
fi
# ── Import: riktig endepunkt er /ragFiles:import (bekreftet 2026-05-24) ────────
# IKKE :importRagFiles på corpus-nivå — det gir alltid 404 i europe-west4
IMPORT_BASE="${BASE_URL}/${CORPUS_NAME}/ragFiles:import"
echo " Import URL: ${IMPORT_BASE}"
IMPORT_OK=0
OPS=()
for GCS_PATH in "seed/" "docs/" "sessions/" "MASTERPLAN.md"; do
GCS_URI="gs://${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 sys,json; print(json.load(open('/tmp/import_resp.json')).get('name',''))" 2>/dev/null || true)
echo "✓ Import trigget: ${GCS_URI} [op: ${OP_NAME##*/}]"
OPS+=("${OP_NAME}")
IMPORT_OK=$((IMPORT_OK + 1))
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 trigget (async — indeksering tar noen minutter)"
# ── Vent på at alle LRO-er er ferdig (valgfri polling) ──────────────────────
if [[ ${#OPS[@]} -gt 0 ]]; then
echo " Venter på indeksering..."
for OP in "${OPS[@]}"; do
for i in $(seq 1 20); do
sleep 15
LRO=$(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: ${OP##*/}"
break
fi
echo " ... ${OP##*/} (${i}/20)"
done
done
fi
# ── 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 ""