# 2.9 — Dialect-neutral canonical request (GREEN)

Phase: 2 — LLM surfaces
Stage: GREEN
Depends on: [2.1](2.1-model-registry.md), [2.2](2.2-body-based-dispatch.md)

The gateway serves two permanent protocol dialects: `/v1/*` is OpenAI-compatible and
`/llm/*` is Anthropic Messages. Both translate into one internal shape before anything
else happens to them, and both translate back out of it on the way to the client.

- [ ] A single internal request representation exists that carries at minimum: the
      resolved upstream, the model name as the client sent it, the ordered turns, an
      optional system instruction, a maximum output token count, stop sequences, and a
      streaming flag
- [ ] The representation names no dialect: nothing in it is called openai or anthropic,
      and no field exists solely because one dialect happens to spell it that way
- [ ] Model dispatch, the shared slot controller, per-caller budgets, logging and
      metrics all read the canonical request and never the raw dialect body
- [ ] The surface that received a request is recorded as one field on the canonical
      request, used only to choose the response and error rendering, never to choose an
      upstream or a slot
- [ ] An identical prompt sent to `/v1/chat/completions` and to `/llm/v1/messages`
      produces the same resolved upstream, the same slot accounting and the same log
      fields apart from that one surface label
- [ ] Adding a third dialect requires a new translator only; the slot controller,
      dispatch and budget code are untouched
- [ ] Translation failure is a client error at the surface boundary, and no partially
      populated canonical request ever reaches an upstream

`reasoning` maps to `reasoning-predictor.llm-serving:80`; `ornith:35b` and
`qwen2.5:3b-instruct` both map to `ornith-predictor.llm-serving:80`. Ports are 80.

## Verify

```bash
curl -s -o /dev/null -w '%{http_code}\n' localhost:8080/v1/chat/completions \
  -H 'content-type: application/json' \
  -d '{"model":"reasoning","messages":[{"role":"user","content":"hi"}]}'
# expected: 200, reasoning stub hit once

curl -s -o /dev/null -w '%{http_code}\n' localhost:8080/llm/v1/messages \
  -H 'content-type: application/json' \
  -d '{"model":"reasoning","max_tokens":16,"messages":[{"role":"user","content":"hi"}]}'
# expected: 200, reasoning stub hit once, same upstream and same slot counter as the /v1 call

grep -h 'upstream=' /tmp/gateway.log | tail -2
# expected: both lines show upstream=reasoning-predictor and model=reasoning, differing only in the surface label
```