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chore: commit modified infra, RAG and session log files

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This commit is contained in:
Chris Christiansen 2026-05-25 12:50:52 +00:00
parent 9cd43572b0
commit e5270e8790
7 changed files with 191 additions and 87 deletions
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232
agents/rag/setup_corpus.py
View File

@ -3,27 +3,20 @@
setup_corpus.py — Create a Vertex AI RAG Engine corpus and import documents. setup_corpus.py — Create a Vertex AI RAG Engine corpus and import documents.
Project: propane-will-491900-m5 Project: propane-will-491900-m5
SDK 1.153.1 has a bug where backend_config crashes when provided. SDK 1.153.1 has bugs in backend_config and RagManagedDbConfig.
We call the REST API directly for corpus creation. We use the REST API (v1beta1) for corpus creation and engine configuration.
v1beta1 REST schema facts (verified from Google docs): Changes implemented:
RagCorpus.backend_config is a union field: - Graceful degradation: If RAG Engine is restricted (Spanner mode), skip and exit cleanly.
vectorDbConfig: RagVectorDbConfig - ensure_serverless_engine_config() sets RAG_ENGINE_AVAILABLE flag.
.ragManagedDb: RagManagedDb <- serverless managed DB, no tier field - get_or_create_corpus() returns None if RAG is unavailable.
.vertexVectorSearch, .pinecone, .weaviate <- alternatives
RagVectorDbConfig has NO 'ragManagedDbConfig' field.
RagManagedDb has NO 'tier' field — empty {} means serverless/basic.
ragEngineConfig (project-level) controls the DEFAULT backend when
vectorDbConfig is omitted. We must verify it is actually in 'basic'
state (not 'spanner') before creating a corpus without an explicit
vectorDbConfig, OR we can pass vectorDbConfig.ragManagedDb explicitly.
""" """
import os import os
import json import json
import time import time
import subprocess import subprocess
import sys
import vertexai import vertexai
from vertexai import rag from vertexai import rag
@ -37,6 +30,9 @@ GCS_SOURCE = os.environ.get(
f"gs://{PROJECT_ID}-agent-staging/rag-docs/", f"gs://{PROJECT_ID}-agent-staging/rag-docs/",
) )
# Global status flag
RAG_ENGINE_AVAILABLE = True
# ragEngineConfig is a project-level control-plane endpoint. # ragEngineConfig is a project-level control-plane endpoint.
# It only exists in us-central1 regardless of where the corpus lives. # It only exists in us-central1 regardless of where the corpus lives.
_ENGINE_CONFIG_LOCATION = "us-central1" _ENGINE_CONFIG_LOCATION = "us-central1"
@ -61,37 +57,61 @@ def get_engine_config() -> dict:
["curl", "-s", "-H", f"Authorization: Bearer {token}", _engine_config_url()], ["curl", "-s", "-H", f"Authorization: Bearer {token}", _engine_config_url()],
capture_output=True, text=True, capture_output=True, text=True,
) )
return json.loads(r.stdout) try:
return json.loads(r.stdout)
except Exception:
print(f"Failed to parse engine config: {r.stdout}")
return {}
def ensure_serverless_engine_config() -> None: def ensure_serverless_engine_config() -> None:
""" """
Set project-level RAG Engine Config to basic (serverless) tier. Set project-level RAG Engine Config to basic (serverless) tier.
Always targets us-central1. Only applicable for us-central1, us-east1, us-east4.
The PATCH is a merge by default. We verify the result with a GET
to confirm 'spanner' is no longer the active mode before proceeding.
""" """
print("Ensuring RAG Engine Config is set to serverless (basic) tier...") global RAG_ENGINE_AVAILABLE
restricted_regions = {"us-central1", "us-east1", "us-east4"}
if LOCATION not in restricted_regions:
print(f"Skipping engine config check for location: {LOCATION} (not restricted)")
return
print(f"Ensuring RAG Engine Config in {_ENGINE_CONFIG_LOCATION} is set to serverless (basic) tier...")
token = get_token() token = get_token()
# Use updateMask=ragManagedDbConfig to target the entire configuration block.
# Set spanner: null to explicitly clear it.
payload = {
"ragManagedDbConfig": {
"basic": {},
"spanner": None
}
}
url = f"{_engine_config_url()}"
result = subprocess.run( result = subprocess.run(
["curl", "-s", "-X", "PATCH", ["curl", "-s", "-X", "PATCH",
"-H", f"Authorization: Bearer {token}", "-H", f"Authorization: Bearer {token}",
"-H", "Content-Type: application/json", "-H", "Content-Type: application/json",
_engine_config_url(), url,
"-d", json.dumps({"ragManagedDbConfig": {"basic": {}}})], "-d", json.dumps(payload)],
capture_output=True, text=True, capture_output=True, text=True,
) )
resp = json.loads(result.stdout)
try:
resp = json.loads(result.stdout)
except Exception:
print(f" \u26a0\ufe0f Failed to parse PATCH response: {result.stdout}")
return
if "error" in resp: if "error" in resp:
err = resp["error"] err = resp["error"]
print(f" \u26a0\ufe0f Engine config PATCH warning ({err.get('code')}): {err.get('message')}") print(f" \u26a0\ufe0f Engine config PATCH error ({err.get('code')}): {err.get('message')}")
op_name = resp.get("name", "") op_name = resp.get("name", "")
if "/operations/" in op_name and not resp.get("done"): if "/operations/" in op_name and not resp.get("done"):
print(f" Polling operation...") print(f" Polling engine config operation...")
op_url = ( op_url = (
f"https://{_ENGINE_CONFIG_LOCATION}-aiplatform.googleapis.com/v1beta1/{op_name}" f"https://{_ENGINE_CONFIG_LOCATION}-aiplatform.googleapis.com/v1beta1/{op_name}"
) )
@ -106,37 +126,32 @@ def ensure_serverless_engine_config() -> None:
if op.get("done"): if op.get("done"):
break break
else: else:
print(" \u26a0\ufe0f Operation timed out.") print(" \u26a0\ufe0f Engine config operation timed out.")
# Verify actual state # Verify actual state
cfg = get_engine_config() cfg = get_engine_config()
db_cfg = cfg.get("ragManagedDbConfig", {}) db_cfg = cfg.get("ragManagedDbConfig", {})
print(f" Current ragManagedDbConfig: {json.dumps(db_cfg)}") print(f" Current ragManagedDbConfig: {json.dumps(db_cfg)}")
if "spanner" in db_cfg and "basic" not in db_cfg:
raise RuntimeError( if "spanner" in db_cfg:
"Engine config is still in Spanner mode. " print(f"\n\u26a0\ufe0f WARN: Engine config in {_ENGINE_CONFIG_LOCATION} is still in Spanner mode.")
"Cannot create a serverless corpus. " print(" RAG Engine appears to be restricted for this project.")
"Run: curl -s -X PATCH -H 'Authorization: Bearer $(gcloud auth print-access-token)' " RAG_ENGINE_AVAILABLE = False
f"-H 'Content-Type: application/json' {_engine_config_url()} " return
"-d '{\"ragManagedDbConfig\":{\"basic\":{}}}'"
)
print(" \u2713 RAG Engine Config verified as basic tier.") print(" \u2713 RAG Engine Config verified as basic tier.")
def create_corpus_rest() -> str: def create_corpus_rest(loc: str) -> str:
""" """
Create corpus via REST API directly, bypassing SDK backend_config bug. Create corpus via REST API directly.
Returns the corpus resource name.
Per v1beta1 docs, RagCorpus.backend_config is a union:
vectorDbConfig.ragManagedDb: {} -> serverless managed DB (no tier field)
This explicitly requests serverless at corpus level regardless of
the project-level engine config default.
""" """
url = ( url = (
f"https://{LOCATION}-aiplatform.googleapis.com/v1beta1" f"https://{loc}-aiplatform.googleapis.com/v1beta1"
f"/projects/{PROJECT_ID}/locations/{LOCATION}/ragCorpora" f"/projects/{PROJECT_ID}/locations/{loc}/ragCorpora"
) )
# vectorDbConfig.ragManagedDb = serverless RAG Managed DB.
# This is the correct v1beta1 field name.
payload = json.dumps({ payload = json.dumps({
"displayName": CORPUS_DISPLAY_NAME, "displayName": CORPUS_DISPLAY_NAME,
"ragEmbeddingModelConfig": { "ragEmbeddingModelConfig": {
@ -144,14 +159,12 @@ def create_corpus_rest() -> str:
"model": "publishers/google/models/text-embedding-004" "model": "publishers/google/models/text-embedding-004"
} }
}, },
# vectorDbConfig.ragManagedDb = serverless RAG Managed DB.
# RagManagedDb has no fields (no tier, no tier enum).
# This is the correct v1beta1 field name — not 'ragManagedDbConfig'.
"vectorDbConfig": { "vectorDbConfig": {
"ragManagedDb": {} "ragManagedDb": {}
} }
}) })
token = get_token() token = get_token()
print(f" Sending POST to {url}...")
result = subprocess.run( result = subprocess.run(
["curl", "-s", "-X", "POST", ["curl", "-s", "-X", "POST",
"-H", f"Authorization: Bearer {token}", "-H", f"Authorization: Bearer {token}",
@ -159,17 +172,22 @@ def create_corpus_rest() -> str:
url, "-d", payload], url, "-d", payload],
capture_output=True, text=True, capture_output=True, text=True,
) )
print(f" API response: {result.stdout[:300]}")
resp = json.loads(result.stdout) try:
resp = json.loads(result.stdout)
except Exception:
raise RuntimeError(f"Failed to parse API response: {result.stdout}")
if "error" in resp: if "error" in resp:
raise RuntimeError(f"Failed to create corpus: {resp['error']}") # Pass the error object up so get_or_create_corpus can inspect it
raise RuntimeError(json.dumps(resp["error"]))
op_name = resp.get("name", "") op_name = resp.get("name", "")
if "/operations/" not in op_name: if "/operations/" not in op_name:
raise RuntimeError(f"Unexpected response (no operation): {resp}") raise RuntimeError(f"Unexpected response (no operation): {resp}")
print(f" Polling corpus creation operation...") print(f" Polling corpus creation operation {op_name}...")
op_url = f"https://{LOCATION}-aiplatform.googleapis.com/v1beta1/{op_name}" op_url = f"https://{loc}-aiplatform.googleapis.com/v1beta1/{op_name}"
for _ in range(40): for _ in range(40):
time.sleep(5) time.sleep(5)
token = get_token() token = get_token()
@ -180,7 +198,7 @@ def create_corpus_rest() -> str:
op = json.loads(r.stdout) op = json.loads(r.stdout)
if op.get("done"): if op.get("done"):
if "error" in op: if "error" in op:
raise RuntimeError(f"Corpus creation failed: {op['error']}") raise RuntimeError(json.dumps(op["error"]))
corpus_name = op["response"]["name"] corpus_name = op["response"]["name"]
return corpus_name return corpus_name
@ -188,16 +206,66 @@ def create_corpus_rest() -> str:
def get_or_create_corpus() -> RagCorpus: def get_or_create_corpus() -> RagCorpus:
"""Return existing corpus by display name, or create a new serverless one.""" """Return existing corpus by display name, or create a new serverless one with fallback."""
for c in rag.list_corpora(): global LOCATION, RAG_ENGINE_AVAILABLE
if c.display_name == CORPUS_DISPLAY_NAME:
print(f"Corpus '{CORPUS_DISPLAY_NAME}' already exists: {c.name}") if not RAG_ENGINE_AVAILABLE:
return c print("\n\u2139 RAG Engine appears to be in restricted Spanner mode for this project. Skipping corpus creation.")
return None
def _find_in_list():
try:
for c in rag.list_corpora():
if c.display_name == CORPUS_DISPLAY_NAME:
return c
except Exception:
pass
return None
# 1. Try finding in current LOCATION
vertexai.init(project=PROJECT_ID, location=LOCATION)
corpus = _find_in_list()
if corpus:
print(f"Corpus '{CORPUS_DISPLAY_NAME}' already exists in {LOCATION}: {corpus.name}")
return corpus
# 2. Try creating in current LOCATION
print(f"Creating corpus '{CORPUS_DISPLAY_NAME}' in {LOCATION} via REST...") print(f"Creating corpus '{CORPUS_DISPLAY_NAME}' in {LOCATION} via REST...")
corpus_name = create_corpus_rest() try:
print(f"\u2713 Corpus created: {corpus_name}") corpus_name = create_corpus_rest(LOCATION)
print(f"\u2713 Corpus created in {LOCATION}: {corpus_name}")
except RuntimeError as e:
err_str = str(e)
# Check for Spanner restriction error message
if "using Spanner mode with RAG Engine in us-central1, us-east1, and us-east4 is restricted" in err_str:
if LOCATION != "europe-west4":
print(f"\u26a0\ufe0f Spanner restriction detected in {LOCATION}. Retrying in europe-west4...")
LOCATION = "europe-west4"
vertexai.init(project=PROJECT_ID, location=LOCATION)
# Check if it already exists in the fallback location
corpus = _find_in_list()
if corpus:
print(f"Corpus '{CORPUS_DISPLAY_NAME}' found in fallback {LOCATION}: {corpus.name}")
return corpus
try:
corpus_name = create_corpus_rest(LOCATION)
print(f"\u2713 Corpus created in fallback {LOCATION}: {corpus_name}")
except RuntimeError as e2:
if "using Spanner mode" in str(e2):
print("\n\u26a0\ufe0f RAG Engine restriction confirmed in fallback region. RAG is effectively unavailable.")
RAG_ENGINE_AVAILABLE = False
return None
raise
else:
print("\n\u26a0\ufe0f RAG Engine restriction confirmed in fallback region. RAG is effectively unavailable.")
RAG_ENGINE_AVAILABLE = False
return None
else:
raise RuntimeError(f"Failed to create corpus in {LOCATION}: {err_str}")
# Final retrieval of the corpus object
for c in rag.list_corpora(): for c in rag.list_corpora():
if c.name == corpus_name: if c.name == corpus_name:
return c return c
@ -206,7 +274,7 @@ def get_or_create_corpus() -> RagCorpus:
def import_documents(corpus: RagCorpus) -> None: def import_documents(corpus: RagCorpus) -> None:
print(f"Importing files from {GCS_SOURCE}...") print(f"Importing files from {GCS_SOURCE} into {corpus.name}...")
rag.import_files( rag.import_files(
corpus.name, corpus.name,
paths=[GCS_SOURCE], paths=[GCS_SOURCE],
@ -217,32 +285,48 @@ def import_documents(corpus: RagCorpus) -> None:
) )
), ),
) )
print("\u2713 Import complete.") print("\u2713 Import job submitted.")
def test_retrieval(corpus: RagCorpus) -> None: def test_retrieval(corpus: RagCorpus) -> None:
print("Running test retrieval query...") print("Running test retrieval query...")
response = rag.retrieval_query( try:
rag_resources=[rag.RagResource(rag_corpus=corpus.name)], response = rag.retrieval_query(
text="test query", rag_resources=[rag.RagResource(rag_corpus=corpus.name)],
rag_retrieval_config=rag.RagRetrievalConfig(top_k=3), text="test query",
) rag_retrieval_config=rag.RagRetrievalConfig(top_k=3),
print(f"\u2713 Test retrieval returned {len(response.contexts.contexts)} chunk(s).") )
print(f"\u2713 Test retrieval returned {len(response.contexts.contexts)} chunk(s).")
except Exception as e:
print(f" \u26a0\ufe0f Retrieval test failed (import might still be processing): {e}")
def main() -> None: def main() -> None:
vertexai.init(project=PROJECT_ID, location=LOCATION) print(f"--- RAG Setup Starting (Target Location: {LOCATION}) ---")
ensure_serverless_engine_config() ensure_serverless_engine_config()
corpus = get_or_create_corpus() corpus = get_or_create_corpus()
if corpus is None:
print("\n--- RAG AVAILABILITY SUMMARY ---")
print(f"Project : {PROJECT_ID}")
print("Status : UNAVAILABLE (Platform restriction: Spanner Mode only)")
print("Action : Skipping RAG integration. Downstream tools will operate without a corpus.")
print("---------------------------------")
sys.exit(0)
import_documents(corpus) import_documents(corpus)
print(f"\nRAG_CORPUS={corpus.name}") print(f"\nSUCCESS")
print("Add this to Secret Manager:") print(f"RAG_LOCATION={LOCATION}")
print(f" gcloud secrets create rag-corpus-name --data-file=- <<<'{corpus.name}'") print(f"RAG_CORPUS={corpus.name}")
print("\nNext steps (set in your environment):")
print(f"export RAG_LOCATION={LOCATION}")
print(f"export RAG_CORPUS_NAME={corpus.name}")
print("\nWaiting 10s before test retrieval...")
time.sleep(10)
test_retrieval(corpus) test_retrieval(corpus)

4
docs/OSVAUCO_OPAX_SESSION_LOG.md
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@ -98,3 +98,7 @@ PHASE 5 — Cloud Run IAM-autentisering på `osvauco-agent`.
## NESTE OPPGAVE ## NESTE OPPGAVE
PHASE 6 — Roter OAuth client secret for `Vauco OS Web App` i [Google Auth Platform](https://console.cloud.google.com/auth/clients?project=propane-will-491900-m5). Deretter: vurder om `jason.vauger@vauco.no` skal beholde `roles/run.invoker` på `osvauco-agent`, eller om tilgang skal innsnevres til kun `@vauco.no`-kontoer via IAP load balancer på sikt. PHASE 6 — Roter OAuth client secret for `Vauco OS Web App` i [Google Auth Platform](https://console.cloud.google.com/auth/clients?project=propane-will-491900-m5). Deretter: vurder om `jason.vauger@vauco.no` skal beholde `roles/run.invoker` på `osvauco-agent`, eller om tilgang skal innsnevres til kun `@vauco.no`-kontoer via IAP load balancer på sikt.
12:44:47 ✔ git pull origin main
12:47:24 ✔ git push origin main
12:48:32 ✔ git push origin main
12:49:53 ✔ git push origin main

4
infrastructure/01-setupenv.sh
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@ -10,6 +10,10 @@ set -euo pipefail
: "${BILLING_ACCOUNT_ID:?Set BILLING_ACCOUNT_ID in .env}" : "${BILLING_ACCOUNT_ID:?Set BILLING_ACCOUNT_ID in .env}"
: "${AGENT_SA:?Set AGENT_SA in .env}" : "${AGENT_SA:?Set AGENT_SA in .env}"
# ── Region Guard ────────────────────────────────────────────────────────
source "$(dirname "$0")/99-region-guard.sh"
log_region_context "Storage-Bucket" "$REGION" "SELECTED"
BUCKET_NAME="gs://${PROJECT_ID}-agent-staging" BUCKET_NAME="gs://${PROJECT_ID}-agent-staging"
BUDGET_PROD_NAME="OSVauco-Agent-Budget-500USD" BUDGET_PROD_NAME="OSVauco-Agent-Budget-500USD"
BUDGET_DEV_NAME="OSVauco-Dev-Budget-75USD" BUDGET_DEV_NAME="OSVauco-Dev-Budget-75USD"

25
infrastructure/05-cloudrun-deploy.sh
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@ -16,12 +16,17 @@ fi
: "${CLOUD_RUN_SERVICE:?Set CLOUD_RUN_SERVICE in .env}" : "${CLOUD_RUN_SERVICE:?Set CLOUD_RUN_SERVICE in .env}"
: "${AGENT_SA:?Set AGENT_SA in .env}" : "${AGENT_SA:?Set AGENT_SA in .env}"
REPO="${REGION}-docker.pkg.dev/${PROJECT_ID}/osvauco-repo" # ── Region Guard ────────────────────────────────────────────────────────
source "$(dirname "$0")/99-region-guard.sh"
DEPLOY_REGION="${DEPLOY_REGION:-${REGION}}"
log_region_context "Cloud-Run" "$DEPLOY_REGION" "SELECTED"
REPO="${DEPLOY_REGION}-docker.pkg.dev/${PROJECT_ID}/osvauco-repo"
IMAGE="${REPO}/osvauco-agent:latest" IMAGE="${REPO}/osvauco-agent:latest"
AGENT_PATH="${SCRIPT_DIR}/../agents/core-logic" AGENT_PATH="${SCRIPT_DIR}/../agents/core-logic"
AGENT_SA_NAME=$(echo "${AGENT_SA}" | cut -d@ -f1) AGENT_SA_NAME=$(echo "${AGENT_SA}" | cut -d@ -f1)
echo "=== 05: Cloud Run Deploy ===" echo "=== 05: Cloud Run Deploy to ${DEPLOY_REGION} ==="
bash "${SCRIPT_DIR}/00-authcheck.sh" bash "${SCRIPT_DIR}/00-authcheck.sh"
@ -67,10 +72,10 @@ echo "✓ iam.serviceAccountUser granted to ${CALLER}"
# Create Artifact Registry repo if it doesn't exist # Create Artifact Registry repo if it doesn't exist
gcloud artifacts repositories describe osvauco-repo \ gcloud artifacts repositories describe osvauco-repo \
--location="${REGION}" --project="${PROJECT_ID}" &>/dev/null || \ --location="${DEPLOY_REGION}" --project="${PROJECT_ID}" &>/dev/null || \
gcloud artifacts repositories create osvauco-repo \ gcloud artifacts repositories create osvauco-repo \
--repository-format=docker \ --repository-format=docker \
--location="${REGION}" \ --location="${DEPLOY_REGION}" \
--project="${PROJECT_ID}" --quiet --project="${PROJECT_ID}" --quiet
echo "✓ Artifact Registry repo ready" echo "✓ Artifact Registry repo ready"
@ -86,24 +91,24 @@ gcloud projects add-iam-policy-binding "${PROJECT_ID}" \
echo "✓ Cloud Build IAM bindings applied" echo "✓ Cloud Build IAM bindings applied"
# Configure Docker for Artifact Registry # Configure Docker for Artifact Registry
gcloud auth configure-docker "${REGION}-docker.pkg.dev" --quiet gcloud auth configure-docker "${DEPLOY_REGION}-docker.pkg.dev" --quiet
# Build image via Cloud Build # Build image via Cloud Build
echo "Building image via Cloud Build..." echo "Building image via Cloud Build..."
gcloud builds submit "${AGENT_PATH}" \ gcloud builds submit "${AGENT_PATH}" \
--tag="${IMAGE}" \ --tag="${IMAGE}" \
--project="${PROJECT_ID}" \ --project="${PROJECT_ID}" \
--region="${REGION}" --region="${DEPLOY_REGION}"
echo "✓ Image built: ${IMAGE}" echo "✓ Image built: ${IMAGE}"
# Deploy to Cloud Run # Deploy to Cloud Run
echo "Deploying to Cloud Run..." echo "Deploying to Cloud Run..."
gcloud run deploy "${CLOUD_RUN_SERVICE}" \ gcloud run deploy "${CLOUD_RUN_SERVICE}" \
--image="${IMAGE}" \ --image="${IMAGE}" \
--region="${REGION}" \ --region="${DEPLOY_REGION}" \
--project="${PROJECT_ID}" \ --project="${PROJECT_ID}" \
--service-account="${AGENT_SA}" \ --service-account="${AGENT_SA}" \
--set-env-vars="GOOGLE_CLOUD_PROJECT=${PROJECT_ID},GOOGLE_CLOUD_LOCATION=${REGION},GOOGLE_GENAI_USE_VERTEXAI=True" \ --set-env-vars="GOOGLE_CLOUD_PROJECT=${PROJECT_ID},GOOGLE_CLOUD_LOCATION=${DEPLOY_REGION},GOOGLE_GENAI_USE_VERTEXAI=True" \
--no-allow-unauthenticated \ --no-allow-unauthenticated \
--port=8080 \ --port=8080 \
--memory=1Gi \ --memory=1Gi \
@ -115,7 +120,7 @@ gcloud run deploy "${CLOUD_RUN_SERVICE}" \
echo "" echo ""
echo "=== 05: Cloud Run Deploy COMPLETE ===" echo "=== 05: Cloud Run Deploy COMPLETE ==="
SERVICE_URL=$(gcloud run services describe "${CLOUD_RUN_SERVICE}" \ SERVICE_URL=$(gcloud run services describe "${CLOUD_RUN_SERVICE}" \
--region="${REGION}" --project="${PROJECT_ID}" \ --region="${DEPLOY_REGION}" --project="${PROJECT_ID}" \
--format="value(status.url)" 2>/dev/null || echo "(pending)") --format="value(status.url)" 2>/dev/null || echo "(pending)")
echo " Service URL: ${SERVICE_URL}" echo " Service URL: ${SERVICE_URL}"
echo "" echo ""
@ -125,4 +130,4 @@ echo " curl -H \"Authorization: Bearer \$TOKEN\" -H 'Content-Type: applicatio
echo " -d '{\"message\": \"Hello\"}' \${SERVICE_URL}/run" echo " -d '{\"message\": \"Hello\"}' \${SERVICE_URL}/run"
echo "" echo ""
echo " COST NOTE: Cloud Run scales to 0. No idle cost." echo " COST NOTE: Cloud Run scales to 0. No idle cost."
echo " Delete with: gcloud run services delete ${CLOUD_RUN_SERVICE} --region=${REGION} --quiet" echo " Delete with: gcloud run services delete ${CLOUD_RUN_SERVICE} --region=${DEPLOY_REGION} --quiet"

6
infrastructure/07-rag-setup.sh
View File

@ -16,7 +16,11 @@ set -euo pipefail
: "${REGION:?Set REGION}" : "${REGION:?Set REGION}"
: "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}" : "${RAG_CORPUS_DISPLAY_NAME:?Set RAG_CORPUS_DISPLAY_NAME}"
RAG_REGION="${RAG_REGION:-europe-west4}" # ── Region Guard ────────────────────────────────────────────────────────
source "$(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 "$0")/.." && pwd)" REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
echo "=== 07: Setting up Vertex AI RAG Engine (Serverless mode) ===" echo "=== 07: Setting up Vertex AI RAG Engine (Serverless mode) ==="

7
infrastructure/08-memorybank-setup.sh
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@ -11,8 +11,11 @@ set -euo pipefail
: "${AGENT_SA:?Set AGENT_SA}" : "${AGENT_SA:?Set AGENT_SA}"
MEMORY_INSTANCE_DISPLAY_NAME="${MEMORY_INSTANCE_DISPLAY_NAME:-${PROJECT_ID}-memory-bank}" MEMORY_INSTANCE_DISPLAY_NAME="${MEMORY_INSTANCE_DISPLAY_NAME:-${PROJECT_ID}-memory-bank}"
# Agent Engine lives in the same region as REGION (us-central1 is fine, eu also works)
MEMORY_REGION="${MEMORY_REGION:-${REGION}}" # ── Region Guard ────────────────────────────────────────────────────────
source "$(dirname "$0")/99-region-guard.sh"
MEMORY_REGION=$(validate_agent_engine_region "${MEMORY_REGION:-${REGION}}")
log_region_context "Agent-Engine" "$MEMORY_REGION" "VALIDATED"
echo "=== 08: Setting up Vertex AI Memory Bank (Agent Engine) ===" echo "=== 08: Setting up Vertex AI Memory Bank (Agent Engine) ==="
echo " Project : ${PROJECT_ID}" echo " Project : ${PROJECT_ID}"

0
scripts/cost-audit.sh Executable file → Normal file
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