Files
homelab/cluster/platform/openviking/values.yaml
Maria Hill e301770adc openviking: repoint embedding+vlm api_base :8002->:8001
astro-orbiter llama-server-router retired :8002 on 2026-08-18
(llama-swap now serves the OpenAI-compatible API on :8001).
OpenViking still pointed at the dead :8002, so every search/find
call failed: dense embedding -> Connection error -> 500 INTERNAL
server error on /api/v1/search/search and /api/v1/search/find.

Verified from the pod: :8002 = connection refused,
:8001/v1/embeddings (nomic-embed-text-v1.5) = 200 with vectors.
Repoints embedding.dense.api_base and vlm.api_base to :8001.

t_abc05db5
2026-08-20 13:46:41 -05:00

241 lines
9.3 KiB
YAML

# ============================================================================
# OpenViking Helm Chart Values
# Cluster: fastpass (Talos Kubernetes)
# Wave: 8 (after Harbor at Wave 7)
# Pilot scope: Two corpora (hermes/ skills, personal/homelab/)
# ============================================================================
#
# KEY CONSTRAINT: Vault (~/friday) is the CANONICAL source of truth.
# OpenViking's index is a derived cache, rebuilt from vault source files.
# If index and vault ever diverge, vault wins and re-index runs.
# See inbox/ryan/2026-08-13-openviking-pilot-deployment-plan.md for full context.
#
replicaCount: 1
image:
repository: ghcr.io/volcengine/openviking
# Pin to a stable release tag (not "latest" for production-ish pilot)
tag: v0.3.17
pullPolicy: IfNotPresent
imagePullSecrets: []
nameOverride: ""
fullnameOverride: ""
serviceAccount:
create: false
annotations: {}
name: ""
podAnnotations: {}
podLabels:
app: openviking
wave: "8"
# Security context: run as non-root if the image supports it
podSecurityContext: {}
securityContext: {}
# Service: ClusterIP (no direct external exposure; MCP proxy handles agent access)
service:
type: ClusterIP
port: 1933
# ============================================================================
# Ingress: enabled, INTERNAL-ONLY
# Constraint from Phase 0 (Ryan's decision, 2026-08-13):
# Standard nginx-ingress fronting the service (consistent with Harbor pattern),
# but internal DNS only — no external/public DNS entry, no public-facing cert-manager issuer.
# Use internal CA / self-signed cert to get ingress consistency without expanding public attack surface.
# ============================================================================
ingress:
enabled: true
className: nginx
annotations:
# Internal cert-manager cluster issuer (DNS-01 via Cloudflare)
cert-manager.io/cluster-issuer: "letsencrypt-prod"
# Block external DNS registration (internal only)
external-dns.alpha.kubernetes.io/enabled: "false"
hosts:
- host: openviking.local.mk-labs.cloud
paths:
- path: /
pathType: Prefix
tls:
- secretName: openviking-tls
hosts:
- openviking.local.mk-labs.cloud
# ============================================================================
# Resources: start conservative, tune after pilot
# ============================================================================
resources:
limits:
cpu: "2"
memory: 4Gi
requests:
cpu: 500m
memory: 1Gi
# ============================================================================
# Persistence: RocksDB index + workspace
# Storage class: px-fa-direct-access (Portworx direct access to Pure FlashArray)
# Rationale (from Phase 0 / t_77b3ff79): 40+ days of proven production history on fastpass,
# RocksDB-optimized (direct block access, not NFS), RAID 6 durability via FlashArray.
# Access mode: ReadWriteOnce (single replica only — RocksDB does not support concurrent access)
# Update strategy: Recreate (no rolling updates; single-replica RocksDB workload)
# ============================================================================
persistence:
enabled: true
storageClass: px-fa-direct-access
accessMode: ReadWriteOnce
size: 30Gi # 30Gi provides headroom for ~6 months of pilot corpus growth (~2GB actual use at launch)
existingClaim: ""
mountPath: /app/.openviking
# Pod disruption budget: single replica, no HA
# Explicit Recreate strategy (handled via Deployment patch in ArgoCD Application)
podDisruptionBudget: {}
# ============================================================================
# Bot feature: disabled (scope out vikingbot for this phase)
# ============================================================================
bot:
enabled: false
# ============================================================================
# OpenViking server configuration (ov.conf)
# Rendered into a ConfigMap mounted at ${persistence.mountPath}/ov.conf
# ============================================================================
config:
storage:
workspace: "" # Defaults to /app/.openviking/openviking_workspace
vectordb:
name: context
backend: local
project: default
agfs:
backend: local
timeout: 10
log:
level: INFO
output: stdout
server:
host: "0.0.0.0"
port: 1933
workers: 1
# root_api_key injected via environment variable + ExternalSecret
root_api_key: "${OPENVIKING_ROOT_API_KEY}"
cors_origins:
- "*"
# ============================================================================
# Embedding configuration (dense)
# Provider: openai-compatible endpoint (local llama-server router)
# Model: nomic-embed-text-v1.5-Q4_K_M (137M params, 768-dim, local inference)
# Endpoint: http://astro-orbiter:8002/v1 (folded into existing astro-orbiter router per t_eb36eb2e)
# No cloud key needed; internal unauthenticated endpoint
# ============================================================================
embedding:
dense:
provider: "openai"
api_base: "http://astro-orbiter:8001/v1"
api_key: "${OPENVIKING_EMBEDDING_API_KEY}" # Placeholder: "local-nomic" or similar
model: "nomic-embed-text-v1.5"
dimension: 768
input: "text"
max_concurrent: 5
# max_input_tokens caps the raw text tokens OpenViking sends per chunk to the
# embedding model. astro-orbiter's llama.cpp router hard-caps nomic-embed-text-v1.5's
# effective context at 2048 tokens regardless of ctx-size config (known llama.cpp
# nomic-bert limitation, not fixable via server flags). OpenViking's chunker was
# observed producing 2000-3400 token chunks, well over that ceiling, causing
# `400 exceed_context_size_error, n_ctx: 2048` and endless circuit-breaker re-enqueues.
# Set well under 2048 (1536) to leave headroom: OpenViking's chunk-time token
# estimator is not the same tokenizer llama.cpp uses to count context, so token
# counts won't match 1:1 between the two. Approved by Ryan as lowest-risk fix
# (option 1 of 3) vs. touching the astro-orbiter serving stack further.
#
# ROOT CAUSE (2026-08-15 incident): 1536 was still not low enough. Observed
# llama.cpp actual n_prompt_tokens vs. OpenViking's own max_input_tokens=1536
# estimate ratio ranged 1.35x-1.86x across real ingested chunks (see homelab
# re-ingest circuit-breaker errors, e.g. estimate 1536 -> actual 2860 tokens,
# 2124, 2088, 2066... all > 2048 n_ctx ceiling). OpenViking's estimator
# (likely a chars/4 or similar heuristic) undercounts vs. llama.cpp's real
# BPE/wordpiece tokenizer for this corpus's content (dense code/config
# snippets tokenize denser than the estimator assumes). Lowering to 1536 alone
# does not hold for all chunks; using worst-observed ratio (1.86x) with margin,
# 2048 / 1.86 ~= 1100, rounded down further for safety across untested
# corpora -> 1024.
max_input_tokens: 1024
# ============================================================================
# VLM / Summarization configuration (L0/L1/L2 generation)
# Provider: openai-compatible endpoint (local llama-server router)
# Model: Llama-3.1-8B (already resident on astro-orbiter per Phase 0 analysis)
# Endpoint: http://astro-orbiter:8002/v1 (same router as embedding)
# No cloud key needed; internal unauthenticated endpoint
# max_concurrent: 4 (recommend capping background indexing load on shared VLM)
# ============================================================================
vlm:
api_base: "http://astro-orbiter:8001/v1"
api_key: "${OPENVIKING_VLM_API_KEY}" # Placeholder: "local-llama" or similar
# Fixed 2026-08-15: "llama3.1-8b" does not exist on astro-orbiter's /v1/models
# (caused every summarization call to fail with 400 model not found, endless
# circuit-breaker retries). Actual served model id/alias confirmed via
# /home/hermes/git/homelab/ansible/playbooks/day2_add_nomic_embed.yml and
# day2_per_model_ctx_size.yml: "Meta-Llama-3.1-8B-Instruct-Q4_K_M".
model: "Meta-Llama-3.1-8B-Instruct-Q4_K_M"
provider: "openai"
temperature: 0.0
max_retries: 2
thinking: false
max_concurrent: 4 # Cap background indexing pressure on shared VLM
# ============================================================================
# Extra environment variables: secrets from ExternalSecret
# Injected by ArgoCD Application via kustomize or helm hook
# ============================================================================
extraEnv:
- name: OPENVIKING_ROOT_API_KEY
valueFrom:
secretKeyRef:
name: openviking-credentials
key: root_api_key
- name: OPENVIKING_EMBEDDING_API_KEY
valueFrom:
secretKeyRef:
name: openviking-credentials
key: embedding_api_key
- name: OPENVIKING_VLM_API_KEY
valueFrom:
secretKeyRef:
name: openviking-credentials
key: vlm_api_key
# ============================================================================
# Probes
# ============================================================================
livenessProbe:
httpGet:
path: /health
port: http
initialDelaySeconds: 30
periodSeconds: 30
timeoutSeconds: 5
failureThreshold: 3
readinessProbe:
httpGet:
path: /ready
port: http
initialDelaySeconds: 15
periodSeconds: 10
timeoutSeconds: 5
failureThreshold: 3
nodeSelector: {}
tolerations: []
affinity: {}