STREAM_IDLE_TIMEOUT_MS was raised to 180s on 2026-09-09 to give contended
llama-server prefill room to produce a first token, but qwen-code sessions
kept hitting "Stream produced no non-ping SSE event within 95000ms" the very
next morning. Per OmniRoute's own docs, that's the wrong timer: the first
non-ping SSE event's deadline inherits REQUEST_TIMEOUT_MS (default 10 min,
computed as remaining budget after retries/cooldowns), not
STREAM_IDLE_TIMEOUT_MS (which only bounds gaps between chunks once streaming
has already started).
Two changes:
- Add REQUEST_TIMEOUT_MS=1800000 (30 min) on the omniroute service, exposed
as OMNIROUTE_REQUEST_TIMEOUT_MS like the existing stream-idle var. Safety
margin, not the root-cause fix.
- Add --cache-reuse 256 to llama-server: it had no KV-cache reuse configured,
so every request reprefilled its full prompt from scratch even when most
of a conversation's prefix was unchanged. This is the actual fix for why
compact-prompt prefill was slow enough to hit the timeout in the first
place.
Documents the distinction and root cause in docs/research/.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WqWBahogLCkrXNfzCSvcVc
- docker-compose.yml: add --reasoning off to qwen-classifier per
fast-model-choice.md's own recommendation (ggml-org/llama.cpp#20809
safety net) — missed in the original rollout, caught while writing
this up.
- docs/coding-cli-setup/qwen-code.md: rewritten to match what's actually
deployed (qwen-classifier, partial GPU offload, 65536 ctx, Q4_K_XL) —
previously described an unimplemented llama-server-fast/8192-ctx plan.
Documents the non-interactive MCP tool allow-list gap found live-testing.
- docs/coding-cli-setup/opencode.md: fix stale 65536 example that didn't
match its own documented LLAMA_CTX_SIZE/LLAMA_PARALLEL formula (131072).
- docs/research/fast-model-choice.md: implementation note recording where
the actual rollout diverged from this doc's original recommendations
(service name, quant, context size, CPU-first-then-GPU path).
- docs/research/omniroute-account-semaphore-timeout.md: new — the
hardcoded 30s per-connection semaphore timeout found during the
pr-agent investigation, root-caused against OmniRoute's own source,
and the maxConcurrent:null + providerSpecificData.timeoutMs fix.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Assess whether the Colibrì disk-streaming MoE inference engine fits the AMD ROCm single-GPU setup or fills a gap beyond the existing llama.cpp/OmniRoute/Qdrant/Neo4j/ComfyUI stack. Conclusion: worth a passing watch, not worth integrating today.
Move docs/coding-cli-setup.md to docs/coding-cli-setup/ with one file
per CLI (claude-code, kimi-cli, opencode, qwen-code) plus a shared
index.md for the gateway intro, tool-calling risk note, and summary
table.
Also fixes the qwen-code doc: context sizes are per-slot
(LLAMA_CTX_SIZE / LLAMA_PARALLEL), not raw LLAMA_CTX_SIZE (same fix
applied to OpenCode's limit.context); documents the fastModel
classifier provider and its own context math; adds the omniroute-search
MCP server (SearXNG web search) and Auto Mode permissions tuning that
were missing from the original qwen-code section.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Documents the NPM route for the RAG knowledge graph alongside the
existing proxy-ai.home/search.home entries. Neo4j (not Qdrant) gets
the hostname — it's the human-facing graph browser; Qdrant's
dashboard stays on its raw port for now.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01DjhxWirQepKFEQj1huXNJR
Two real-hardware findings from issue #5, both researched and fixed
together (docs/research/rocm-gpu-pin-and-render-group.md):
- GPU_MAX_HW_QUEUES=1 on llama-server and llama-server-fast. Confirmed
on real hardware: either container alone is fine (3% GPU, low
power), only two concurrent HIP contexts pin the R9700 at 100%/
boost-clock (ROCm/ROCm#5706, an MES firmware bug). The env var is
validated on the exact image this stack uses, per-process by design
— applying it to both containers is the correct scope.
- group_add switched from plain names (video/render) to resolved
numeric GIDs (HOST_VIDEO_GID/HOST_RENDER_GID) on all three GPU
services. The "unable to find group render: no matching entries in
group file" error confirmed new since the second GPU service was
added is a known Docker bug (docker/cli#4714): group_add by name
resolves against the container's own /etc/group, not the host's,
and multiple GPU services starting concurrently race on that lookup.
Numeric GIDs skip resolution entirely. scripts/update.sh's existing
comfyui-only GID resolution is generalized to resolve these once for
all three services.
docker compose config -q validated (fails fast with a clear error if
the GIDs aren't resolved yet, passes once they are).
Refs #5
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MrnMEdzeQzqZE5soVEXPCx
Second, always-resident llama.cpp instance (Qwen3-4B-Instruct-2507,
Q8_0 GGUF, ~5GB VRAM) alongside the existing Qwen3.8-27B instance, for
use as qwen-code CLI's Auto Mode classifier fastModel. Model choice
researched in docs/research/fast-model-choice.md: architecturally
non-thinking (unlike Qwen3-1.7B/0.6B), --reasoning off added
defensively per a known (closed) llama.cpp misdetection bug.
- docker-compose.yml: llama-server-fast + downloader-fast services,
omniroute depends_on updated
- .env.example: LLAMA_FAST_* vars
- scripts/update.sh: runs the new downloader profile
Refs #44
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01MrnMEdzeQzqZE5soVEXPCx
Closes issue #39 — with llama-server stopped and the full ~32GB R9700
available, Qwen-Image (Apache-2.0, 20B MMDiT) at FP8 precision (~25GB)
is the recommended upgrade from FLUX.1-schnell: it has the cleanest
license of the candidates and is the only one with a ComfyUI workflow
pre-validated specifically on this GPU architecture (gfx1201/R9700),
per kyuz0/amd-r9700-comfy. HunyuanImage-3.0 is ruled out (CUDA-only,
multi-GPU datacenter VRAM floor); Krea-2 flagged as promising but too
new for R9700-specific field evidence.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015zCwaWJQuKgXDUfRPBqDS7
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
tea comments create doesn't exist (add/a is the subcommand); a wayfinder
session hit this live resolving OmniRoute-migration tickets. Also note
that concurrent ticket resolutions racing to edit the same map issue
(a full-body replace, no append) can clobber each other's Decisions-so-far
lines -- observed the same session across 5 parallel research tickets.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VPZ6TogJiYxG8E4EQBB197
memory-knowledgebase.md no longer says 'not yet verified' — it's been
smoke-tested end-to-end (direct search + the file_search tool on a chat
completion) and the bugs found are fixed in the preceding commits.
VENDORED.md documents the three local patches on top of the upstream
litellm-pgvector commit so a future re-vendor doesn't silently drop them.
Today's embedding-server crash-loop (missing nomic-embed-text GGUF) was a
manual step nobody ran. update.sh now runs both downloader profiles
itself, every time, before bringing services up -- no separate command to
remember.
- docker-compose.yml: downloader/downloader-embedding commands gain a
`test -f ... && skip || curl ...` guard, so re-running update.sh never
re-downloads an existing model file.
- scripts/update.sh: runs both profiles after image pull/build, before
service recreation.
- scripts/download-model.sh removed -- folded in, redundant standalone
script.
- README.md / docs/memory-knowledgebase.md updated accordingly.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018WHfjWrSEcGhCoeu6dQfDa
README.md and docs/proxy-key-onboarding.md were edited by later commits
(b996b1f, 24d749b) that the litellm-pgvector revert didn't touch, so they
still named the now-removed MEMORY_RETRIEVAL_EMBEDDING_KEY var. Left
docs/research/langchain-pgvector-vs-litellm-pgvector.md as-is — it's a
dated record of the decision being reversed, not live config.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018WHfjWrSEcGhCoeu6dQfDa
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
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>
Verdict: switch. See docs/research/langchain-pgvector-vs-litellm-pgvector.md
for full reasoning, LOC comparison, and a concrete replacement service spec.
Research/doc only — no compose/config/vendor changes.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
The server's Docker/BuildKit couldn't do a git-context build of a public
github.com repo (fails with "could not read Username ... terminal prompts
disabled" — an auth-shaped error for what should be an anonymous clone).
Rather than debug that, vendor litellm-pgvector's small source tree
directly (vendor/litellm-pgvector/, see VENDORED.md for provenance/update
steps) and build from the local path.
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>
Answers whether SearXNG is natively supported by LiteLLM's /v1/search
feature, whether it's a model-tool or automatic retrieval, what
docker-compose.yml networking change is needed for the litellm container
to reach the LAN's search.home host, and how it interacts with this
project's known-flaky Qwen3.8-27B tool-calling.
Research only — litellm-config.yaml and docker-compose.yml are unchanged.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Answers whether the $20/mo Claude Pro subscription can be used as a
LiteLLM backend instead of a pay-per-token Anthropic API key. Finding:
no — Pro/Max OAuth credentials are contractually restricted to Claude
Code / native Anthropic apps (Consumer ToS + Usage Policy, actively
enforced server-side since March 2026). Documents the supported path:
a separate Anthropic Console API key as a model_list entry, same shape
as the existing llama.cpp entry. Same pattern applies to other
providers (ChatGPT Plus, Gemini subscriptions).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Verified against the live GitHub repo/docs (not secondhand): real,
active, functioning AI gateway, ~5 months old, effectively
single-maintainer, BSL 1.1. Fails two of the requirements from
docs/research/proxy-tool-choice.md / issue #9 — no Anthropic Messages
inbound endpoint (VoidLLM's own docs say Claude Code's LLM traffic
can't be routed through it) and no request-priority/queuing feature.
Recommendation: stay on LiteLLM.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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>
Resolves wayfinder ticket #8. The stack is reached over LAN/WAN hostnames,
not localhost:
- Open WebUI: ai.home (LAN) and ai.haylan.ch (external, via DMZ) routed
through the existing Nginx Proxy Manager instance to the published
WEBUI_PORT — no new reverse-proxy service needed in this repo.
- llama.cpp's raw API stays LAN-only and unregistered in NPM (no auth of
its own); coding CLIs reach it via the box's LAN IP or ai.home directly.
New docs/network-access.md documents the NPM proxy-host setup and the
LAN-only decision. coding-cli-setup.md and README updated to stop
referencing localhost.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Resolves wayfinder ticket #6. Covers the two server endpoints (Anthropic
shim vs OpenAI-compatible), exact config for all three CLIs, and surfaces
the shared Qwen3.8-27B tool-calling risk plus OpenCode's own documented
local-backend brittleness up front rather than burying it.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Answers issue #7. Confirms sst/opencode moved to anomalyco/opencode,
documents install methods, opencode.json provider config for a local
OpenAI-compatible server, and known tool-calling compatibility issues
against self-hosted backends (llama.cpp --jinja requirement, empty
tool_calls handling) plus Qwen3.8-27B-specific caveats.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Resolves the wayfinder research question: unsloth/Qwen3.8-27B-GGUF ships
UD-Q4_K_XL.gguf (17.6GB) directly. Documents VRAM footprint on 32GB
RDNA4 (R9700/gfx1201) at 32K and 128K context via llama.cpp ROCm/HIP.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
haylan
