esh-pfi-infrastructure/stacks/litellm/README.md

litellm

OpenAI-compatible gateway in front of the vLLM services on ana-ml2, standing in the request path so every request + response is logged and inspectable in a browser. This is the thing vLLM does not give us: Dozzle shows vLLM's stdout (connection/request metadata) but not the full prompt/completion bodies. LiteLLM captures both, per call, with a Logs UI.

Server: ana-docker (10.250.50.70) Port: 4000 (proxy API + admin/Logs UI at /ui) — configurable in .env Backs: the vllm stack on ana-ml2 (10.250.50.54)

Why it exists

phi4-mini is becoming a production summarizer + "dreaming" agent. Being able to read exactly what it was asked and what it answered is the difference between debuggable and opaque. See docs/roadmap.md → "Observability for the vLLM stack". This is the lean first cut of that roadmap item — see Langfuse-ready below for the upgrade path.

What routes through it

Consumers point their OpenAI base_url at http://10.250.50.70:4000 and pick a model by name; the gateway forwards to the right vLLM port and logs the round-trip.

model name (here)	upstream	vLLM port	logged
phi4-mini	generative chat	:8004	full prompt + completion
qwen3-embedding	/v1/embeddings	:8001	input + vector metadata
qwen3-reranker	/rerank	:8002	query + docs + scores

Not routed: the vllm-reward Skywork classifier (:8003) is a pooling /classify endpoint with no first-class LiteLLM route — callers hit it directly for now. The generative model is the high-value target for req/resp visibility and it routes cleanly here. (If reward logging is wanted later, LiteLLM pass_through_endpoints can cover it.)

The log switch

Full prompt/response text shows in the Logs UI because of store_prompts_in_spend_logs: true in conf/config.yaml. Without it you'd get metadata only (tokens, latency, model name) — not the text. The Postgres sidecar (litellm-db) is the store.

Langfuse-ready

This deliberately does not stand up Langfuse's heavy v3 stack (ClickHouse + Redis + MinIO + Postgres + app containers). To graduate to full Langfuse traces later:

1. Stand up (or point at) a Langfuse instance.
2. Set LANGFUSE_PUBLIC_KEY / LANGFUSE_SECRET_KEY / LANGFUSE_HOST in .env.
3. Uncomment success_callback / failure_callback in conf/config.yaml.
4. docker compose up -d to restart.

No re-architecture: the gateway and every consumer stay pointed here.

⚠ reasoning_effort is not a universal vocabulary

gen-reasoning accepts only xhigh (its default), medium and low, and returns HTTP 400 on anything else:

Unexpected reasoning effort high. Supported types are xhigh (default),
medium, and low.

That is the default value of several clients, so the seat presents as broken rather than as one enum value out of step. conf/reasoning_effort_map.py is a pre-call hook that maps high and max onto xhigh for that model group only.

Measured 2026-09-02 across every local seat before scoping it:

model	reasoning_effort: high
gen-reasoning	rejected → mapped
gen, sec, char-rp-reasoning, summarizer	accepted → untouched

Paid passthroughs (gen-frontier*, glm*, kimi*) were deliberately not probed — they spend vendor credits — and are not mapped. Add a model to EFFORT_MAP only after measuring that it actually rejects the value.

⚠ A hook file needs a compose change, not just a conf push. Callbacks are bind-mounted per-file beside config.yaml, so a new hook requires a new volume line and docker compose up -d litellm (a restart will not pick it up — the volume only attaches at container creation). Target the service by name; a bare up -d bounces the DB too.

Deploy

# 1. Sync canonical → ana-docker (compose + conf/config.yaml)
scripts/deploy-stack.sh ana-docker litellm

# 2. On the server: create .env from the template and fill secrets
ssh ana-docker 'cd /opt/docker/compose/litellm && cp -n .env.example .env'
#   generate the keys:
#     openssl rand -hex 24 | sed 's/^/sk-/'   # LITELLM_MASTER_KEY
#     openssl rand -hex 32                     # LITELLM_SALT_KEY
#     openssl rand -hex 24                     # POSTGRES_PASSWORD
$EDITOR  # fill .env on the server

# 3. Sanity-parse then launch
ssh ana-docker 'cd /opt/docker/compose/litellm && docker compose config >/dev/null && docker compose up -d && docker compose ps'

.env.example is the only env file in git. The real .env (master key, salt, Postgres password) lives on the server and is gitignored.

Smoke test

# liveness (no auth)
curl -fsS http://10.250.50.70:4000/health/liveliness   # -> "I'm alive!"

# a chat round-trip (uses the master key), then look for it in the Logs UI
curl -s http://10.250.50.70:4000/v1/chat/completions \
  -H "Authorization: Bearer $LITELLM_MASTER_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"phi4-mini","messages":[{"role":"user","content":"say hi"}]}'

# embeddings
curl -s http://10.250.50.70:4000/v1/embeddings \
  -H "Authorization: Bearer $LITELLM_MASTER_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen3-embedding","input":"hello"}'

Then open http://10.250.50.70:4000/ui (log in with the master key) → Logs tab → the calls appear with full request + response.

Notes

• Both boxes are Anaheim (10.250.0.0/16) so the ana-docker → ana-ml2 hop is LAN-local; negligible added latency.
• VLLM_API_KEY is blank by default because the vllm stack ships API_KEY= empty. Set it here only if you set it there.
• LITELLM_SALT_KEY must be set once and never changed — rotating it makes any keys stored in Postgres undecryptable.
• Empty tools: [] stripping — conf/strip_empty_tools.py is a pre-call hook (registered via litellm_settings.callbacks) that drops an empty/None tools field (and any orphaned tool_choice) before forwarding. vLLM 400s on tools: [] ("tools must not be an empty array"); drop_params doesn't catch empty values, only unsupported params. It runs on every request, so all vLLM-backed models are covered, and only fires when tools is present-and-empty (real tools pass through untouched). The file mounts at /app/strip_empty_tools.py beside config.yaml because LiteLLM resolves callbacks relative to the config dir. Note: real tool-calls additionally need the upstream vLLM server launched with --enable-auto-tool-choice — a vLLM-side flag, separate from this gateway.