llama.cpp loads one model per process and the running Qwen3.8-27B chat
model isn't embedding-trained, so this is a second, CPU-only
llama-server instance (bge-small-en-v1.5, 384-dim) rather than adding
--embeddings to the chat one — see docs/research/litellm-knowledgebase.md
#3.
Downloader extended to fetch both GGUFs into the shared models volume.
No host port published — OmniRoute reaches it via the ai-stack network
DNS name (embedding-server:8081).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qx22CV9EUS3hGATucQav13
Cross-checked the deployment against OmniRoute's own docs
(docs/reference/ENVIRONMENT.md, docs/guides/DOCKER_GUIDE.md) and found
three gaps from the original migration:
- OMNIROUTE_WS_BRIDGE_SECRET was entirely missing - ENVIRONMENT.md marks
it REQUIRED (production), for the internal Codex Responses WebSocket
bridge. docker compose config validated fine without it (compose
doesn't know omniroute's own required-var list), so this went
unnoticed until checking the docs directly.
- No mem_limit/OMNIROUTE_MEMORY_MB - the Docker guide is explicit that
the 1024MB default heap is dashboard-only sized; coding-agent workloads
(every client this stack has) need OMNIROUTE_MEMORY_MB=8192 and a
10+ GiB container ceiling. Set both.
- No stop_grace_period - the guide's --stop-timeout 40 equivalent, so
SQLite WAL changes checkpoint back into the main DB file on shutdown
instead of getting killed mid-write.
Redis checked and confirmed correctly absent - OmniRoute uses SQLite
only, no Redis anywhere in its docs.
Still open: whether API_PORT actually isolates /dashboard and /api/*
from the published port, or bridges everything through (see issue #31)
- OmniRoute's own ARCHITECTURE.md doesn't document split-port mode as a
real security boundary, and the live "[API Bridge] ... -> dashboard"
log line is ambiguous. Waiting on a live curl test against
proxy-ai.home before treating that as resolved.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPZ6TogJiYxG8E4EQBB197
Not omniroute's own internal port (API_PORT stays at its default 20129,
unreconfigured) - just the Docker port mapping, so existing NPM/firewall
config pointed at :4000 keeps working without changes on that end. New
OMNIROUTE_PORT env var is the host side of "OMNIROUTE_PORT:API_PORT" in
docker-compose.yml's ports: entry.
Also corrected docs/proxy-key-onboarding.md's dashboard-access
instructions - DASHBOARD_PORT was never published to the host in the
first place, so "http://<host>:20128" was never actually reachable as
written; documented reaching it via the container's own bridge-network IP
or an SSH port-forward instead.
llama-server remains unexposed (no ports: entry, only expose:) -
unaffected by this change, confirming it stays that way.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPZ6TogJiYxG8E4EQBB197
No longer needed - every client is a coding CLI behind the OmniRoute
gateway, not a chat UI. Drops the open-webui and qdrant services,
WEBUI_PORT/OPENWEBUI_OMNIROUTE_KEY env vars, and the openwebui-data/
qdrant-data volumes. Qdrant only ever served Open WebUI's own built-in
memory/RAG (unrelated to the gateway-level knowledgebase removed in
472e3a4), so it goes too rather than sit unused.
Docs updated: README, docs/network-access.md (ai.home/ai.haylan.ch
section was entirely about Open WebUI, rewritten around the gateway),
docs/proxy-key-onboarding.md, docs/proxy-request-priority.md.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPZ6TogJiYxG8E4EQBB197
LiteLLM -> OmniRoute (issue #31, wayfinder map + research tickets #32-37):
replace the litellm/litellm-db services with omniroute, split-port mode
(API_PORT published/reverse-proxied, DASHBOARD_PORT never published -
tighter than litellm's old /ui NPM path-deny rule), 5 new secrets in place
of LITELLM_MASTER_KEY/LITELLM_SALT_KEY, llama-server/searxng registered as
omniroute providers post-boot (no static config.yaml equivalent). No
scripted per-workload key minting yet - omniroute's POST /api/keys needs a
dashboard session, not a static bearer key - so OPENWEBUI_OMNIROUTE_KEY is
a manual step for now (docs/proxy-key-onboarding.md).
Caveat carried into the map and README: OmniRoute's own docs
(docs/security/STEALTH_GUIDE.md, MITM-TPROXY-DECRYPT.md, PUBLIC_CREDS.md
on its release/v3.8.51 branch) describe shipped features for AI-provider
client-detection evasion, system-wide HTTPS interception via a locally
installed root CA, and hiding credentials from secret scanners. Proceeding
anyway was an explicit, informed user decision.
Also drops the gateway-level memory/knowledgebase feature entirely (user:
"I don't need it") - litellm-pgvector, pgvector-db, embedding-server,
scripts/ingest-memory.sh, vendor/litellm-pgvector/, docs/memory-
knowledgebase.md. Open WebUI's own qdrant-backed memory/RAG is unrelated
and untouched. litellm-config.yaml deleted (was kept as a rollback
reference, but there's no rollback path to a feature being deliberately
removed).
Not yet verified against real hardware - see issue #31's open tickets.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPZ6TogJiYxG8E4EQBB197
LLAMA_CTX_SIZE default 65536 -> 131072: real usage was burning through 64K
fast. ~25.6GB VRAM (17.6GB weights + ~8GB KV cache) on the 32GB R9700,
~6GB headroom — see docs/research/qwen3.8-27b-quant.md for the full table.
Also documents LLAMA_GPU_LAYERS as the RAM-offload knob for this dense
model (no separate RAM-offload flag exists in llama.cpp, and --n-cpu-moe/
--cpu-moe/--override-tensor "exps" are MoE-only, no-ops here), and that
there's no explicit SSD offload tier to enable — llama.cpp's default mmap
already falls back to disk implicitly if GPU+RAM run out.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FCAUsjGNSoJTtK8hyLKg5m
This reverts commit abeadc49c8.
Restores vendor/litellm-pgvector/ and the vector_store_registry wiring
(in-band file_search tool-call support) at the user's request, after
re-confirming against docs.litellm.ai/docs/completion/knowledgebase and
litellm-pgvector's own README that pg_vector is still not an in-process
vector_store_registry backend -- it requires this same standalone
connector service either way, so there is no simpler 'native' path that
was missed. Trading back in: 793 lines of vendored code, the untested
Prisma migration, and the git-context build risk noted in VENDORED.md
(all flagged as unverified against real hardware in issue #24), in
exchange for the file_search in-band tool call memory-retrieval did not
support.
Conflicts resolved on top of later commits (Redis, update.sh key-minting
fold-in):
- .env.example / docs/memory-knowledgebase.md: kept the auto-mint-via-
update.sh language, renamed MEMORY_RETRIEVAL_* back to
LITELLM_PGVECTOR_*.
- scripts/generate-secrets.sh: left deleted -- its job was folded into
update.sh in 24d749b, unrelated to this revert.
- scripts/update.sh: renamed the MEMORY_RETRIEVAL_* secret/mint calls to
LITELLM_PGVECTOR_* to match.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018WHfjWrSEcGhCoeu6dQfDa
New redis service (redis:7-alpine, password-protected, no persistence
volume — everything it holds is cache/coordination state). litellm gets
REDIS_HOST/REDIS_PORT/REDIS_PASSWORD, which is all LiteLLM needs to use it
for router state, rate limits/budgets, and cache invalidation — no
litellm-config.yaml block required (docs.litellm.ai/docs/proxy/caching).
REDIS_PASSWORD added to .env.example and update.sh's auto-generated
secrets.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
update.sh now creates .env from .env.example if missing, idempotently fills
in every random secret (same logic generate-secrets.sh had, now removed),
resolves SEARXNG_LAN_IP from search.home via the host's own DNS, and mints
OPENWEBUI_LITELLM_KEY / MEMORY_RETRIEVAL_EMBEDDING_KEY through LiteLLM's own
/key/generate API once litellm is up — no more manual Admin UI step for the
stack's own two workload keys. Docs updated to point at update.sh as the
one command; docs/proxy-key-onboarding.md keeps the manual/API steps as the
fallback and for onboarding other workloads.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Per docs/research/langchain-pgvector-vs-litellm-pgvector.md (issue #25):
the vendored litellm-pgvector connector (793 lines, Prisma migrations, a
fragile git-context build) is replaced by a ~90-line FastAPI service
(services/memory-retrieval/) wrapping langchain_postgres.PGVector directly
against pgvector-db. Same gateway boundary — it still calls litellm for
embeddings, nothing talks to Postgres or the model directly except this
service.
- New services/memory-retrieval/ (main.py, Dockerfile, requirements.txt):
POST /ingest, POST /query, GET /health.
- docker-compose.yml: litellm-pgvector service replaced by memory-retrieval;
pgvector-db and embedding-server untouched.
- litellm-config.yaml: vector_store_registry block removed (no
langchain_postgres provider exists to register against; callers query
memory-retrieval directly instead of an in-band file_search tool call —
that mechanism was never confirmed working per issue #24 anyway).
- scripts/ingest-memory.sh rewritten for the new /ingest endpoint (same
per-line chunking, no dedup).
- .env vars renamed: LITELLM_PGVECTOR_API_KEY/LITELLM_PGVECTOR_EMBEDDING_KEY
-> MEMORY_RETRIEVAL_API_KEY/MEMORY_RETRIEVAL_EMBEDDING_KEY.
- vendor/litellm-pgvector/ removed entirely.
- docs/memory-knowledgebase.md updated for the new setup/query flow.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- search_tools block in litellm-config.yaml (SearXNG as a first-class
search_provider, standalone /v1/search endpoint, not a model tool) plus
extra_hosts on the litellm service so it can resolve search.home.
- New embedding-server (nomic-embed-text-v1.5 on a second llama.cpp
instance), pgvector-db, and litellm-pgvector services — LiteLLM's native
knowledgebase feature has no Qdrant backend, so this is the only
self-hosted path (docs/research/litellm-knowledgebase.md).
- vector_store_registry + local-embedding model entry in
litellm-config.yaml, wiring it together.
- scripts/ingest-memory.sh to load data/memory.md and
data/claude-legacy-memory.md into the knowledgebase.
- docs/memory-knowledgebase.md documenting the whole setup; data/
gitignored (personal memory content, not meant to be committed).
- New .env vars (SEARXNG_LAN_IP, PGVECTOR_DB_PASSWORD,
LITELLM_PGVECTOR_API_KEY, LITELLM_PGVECTOR_EMBEDDING_KEY,
EMBEDDING_MODEL_FILE) and generate-secrets.sh support for the
auto-generatable ones.
Resolves#22 and #23 (wayfinder map #21). Not yet verified on real
hardware — see #24.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Without these, LiteLLM's /ui falls back to username 'admin' and the
master key as the password, forcing the master key to be typed into
a browser. generate-secrets.sh now fills UI_PASSWORD like the other
secrets.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Q2CR8yawSf7pwAVYnjwFea
Open WebUI now points at litellm instead of llama-server directly, using a
provisioned virtual key. llama-server's host port is dropped (internal-only
on the ai-stack network) since the proxy is the only intended entry point
now. docs/coding-cli-setup.md repointed at the proxy's endpoints/ports with
per-CLI virtual keys instead of the old shared dummy key.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Adds litellm + litellm-db to docker-compose.yml, litellm-config.yaml with
custom shadow-cost pricing (Claude Sonnet 5 reference, per #11) and a
priority-scheduling stub (per #16, needs real-hardware smoke test), and
required LITELLM_MASTER_KEY/SALT_KEY/DB_PASSWORD env vars. Untested on real
hardware — that's #17. Open WebUI/coding CLIs still talk to llama.cpp
directly, migration is #15.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Resolves wayfinder ticket #4. Wires up the locked decisions from the map:
- llama.cpp (ghcr.io/ggml-org/llama.cpp:server-rocm, gfx1201) serving
Qwen3.8-27B-UD-Q4_K_XL.gguf, port published for direct Claude Code CLI /
Kimi CLI access alongside Open WebUI.
- Open WebUI with WEBUI_AUTH on, RAG+Memory wired to a standalone Qdrant
service.
- Lazytainer labels on llama-server for a 15 min idle-stop.
- Named Docker volumes only (models, qdrant-data, openwebui-data) — no host
bind-mounts.
- One-off 'downloader' compose profile instead of a host-side script with
its own dependencies, wrapped by scripts/download-model.sh.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
haylanandClaude-Bot