[Feature]: Expose the Anthropic Messages API (POST /v1/messages) on the PAIR proxy

先阅读 proxy service 以及现有的 Ollama 和 OpenAI 兼容 endpoint handler，然后跟踪请求如何进入 scheduler 并到达所选 node 的 engine。将 ordinary、streaming、tool-use、remote-node 和 count_tokens 检查的要求与现有 validation 进行比较。当 POST /v1/messages 保留 Anthropic 响应，并在 engine 不支持时明确报错，即视为完成。

PAIR pools capacity so that a machine too small to hold a useful model can still use one. Coding agents that speak the Anthropic Messages API are a large and growing class of client that cannot reach PAIR at all today, and the reason is protocol rather than capability: both engines PAIR already routes to serve POST /v1/messages natively, and PAIR re-exposes them as OpenAI only. Adding the endpoint alongside the existing ones would open pooled local capacity to those clients without changing anything for current ones.

Area

API compatibility

User problem

Who is affected: people running an agentic coding client that speaks the Anthropic Messages API against local models, across a mix of machines where no single one is large enough to hold a useful model roster. That is the case PAIR is built for, and it is ours: a team where a few machines have 64 GB or more and most have far less.

What cannot be accomplished today: such a client sends every request to one base URL and speaks only /v1/messages. PAIR presents Ollama-compatible and OpenAI-compatible proxy endpoints, so the client cannot reach PAIR at all.

The gap is narrow rather than architectural, because the destination engines already understand the dialect:

• Ollama's v0.14.0 release notes read "Anthropic API compatibility: support for the /v1/messages API".
• LM Studio's post "Use your LM Studio Models in Claude Code" (2026-01-30) reads "Run Claude Code with any local model using LM Studio's Anthropic-compatible API".

Checked directly rather than taken from the notes: on LM Studio 0.4.20 and Ollama 0.33.2, both return well-formed Anthropic Messages responses, content blocks and stop_reason and usage included.

So a request arrives in a dialect the destination engine already speaks, and the only component in the path that does not is the proxy in the middle.

Desired outcome

POST /v1/messages on the PAIR proxy, alongside the existing endpoints, routed by the same scheduler and answered by the selected node's engine. Observable behavior:

• A client configured with PAIR's endpoint as its Anthropic base URL completes a normal request and receives a well-formed Messages response.
• Streaming returns the Anthropic SSE event grammar rather than a translated approximation.
• tool_use and tool_result content blocks survive intact in both directions. This is the part that matters most for agent clients, because a dropped or reshaped tool block fails silently and looks like a confused model rather than a transport bug.
• /v1/messages/count_tokens behaves predictably. Agent clients call it, and neither engine implements it: at LM Studio 0.4.20 it returns HTTP 200 carrying {"error":"Unexpected endpoint or method."}, and at Ollama 0.33.2 it returns 404. Passing it through where an engine implements it and returning a clear error where none does would improve on both, and PAIR is not the right place to invent a tokenizer.
• Model selection continues to work the way it does on the existing endpoints.

Passthrough rather than translation looks like the smaller and safer change: when the selected node's engine speaks Anthropic Messages, forwarding the body preserves fidelity by construction and needs no per-field mapping to maintain as the API evolves.

Alternatives considered

• Point the client directly at a single node's LM Studio or Ollama. This works, it is what we do today, and it gives up everything PAIR exists to provide: no pooling, no scheduling, no use of idle machines.
• Put a translating gateway in front of PAIR. This reintroduces Anthropic to OpenAI conversion at exactly the point where the destination engine did not need it, and tool-call round trips are the known casualty of that conversion.
• Run a small Anthropic-to-OpenAI shim alongside PAIR. Same fidelity problem, plus another process on every machine.

Each alternative pays a translation cost to reach engines that already speak the dialect.

Compatibility and security implications

Additive. Existing Ollama-compatible and OpenAI-compatible endpoints are unchanged, and clients that do not use /v1/messages see no difference. No change to discovery, pairing, or the trust model is implied.

Routing an unfamiliar path to a node whose engine does not implement it should fail with a clear error rather than a partial or reshaped response, so that a capability gap stays visible instead of silent.

Validation approach

• A three-call check against each supported engine: an ordinary message, a message that must produce a tool_use block with valid arguments, and a streaming request whose SSE event sequence is compared against the Anthropic grammar.
• A count_tokens call that returns either a clear answer or a clear error, never a hang and never an HTTP 200 carrying an error body.
• The same three checks with the request routed to a remote node rather than the local one, confirming the shape survives the hop.

Scope of what I checked

I read the proxy service only, not every service, and I did not locate in source the Ollama-native surface the README describes. The engine behavior above was executed at the pinned versions named; the claim that PAIR has no Anthropic surface today comes from finding no /v1/messages or Anthropic reference in the repository.

This sits next to two open threads rather than pointing in a fresh direction: #9 adds vLLM as a third engine, which serves the same endpoint, and #7 asks for richer placement signals, which is the same question of whether a node can serve a given request rather than merely being idle.

Happy to test on Apple Silicon and report back, and happy to follow up with a pull request if this is a direction you would take.

Confirmations

• I searched existing issues for duplicates.
• I agree to follow the Code of Conduct.