rob thijssen 7733eecba5
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feat(neuron): strip reasoning from chat completions by default
Closes #8.

Reasoning-capable models (Qwen3, DeepSeek-R1, gpt-oss, Mistral
Magistral, …) emit `<think>...</think>` blocks inline in their
content stream. The chat-completions wire format has no slot for
reasoning, so until this change every consumer either parsed the
markers themselves (helexa-acp) or wrote the raw scratchpad
content into their UI (Zed's commit-message generator — visible
as the leaked reasoning block on every generated commit message
against benjy's Qwen3-8B).

## Implementation, model-agnostic by design

The neuron side now does token-level routing without any
hardcoded model knowledge:

1. **At load time** (`detect_reasoning_token_pair` in
   `wire::event`), probe the tokenizer's vocabulary for a known
   reasoning-marker pair: `<think>` / `</think>` (Qwen3,
   DeepSeek-R1, gpt-oss), `[THINK]` / `[/THINK]` (Mistral
   Magistral), and a couple of derivatives. Each marker must
   resolve to a single token id; if both open and close resolve,
   stash on `LoadedModel.reasoning_tokens` (similarly
   `TpLoadedModel`). Non-reasoning models get `None` and pass
   through unchanged.

2. **At inference time**, the three streaming paths
   (`run_inference_streaming` CPU, `stream_inference_via_worker`
   CUDA single-GPU, `chat_completion_tp_stream` CUDA TP) now
   check each sampled token against the pair via the new
   `handle_reasoning_marker` helper before feeding it to the
   detokeniser. Open marker → set `in_reasoning = true`, drop
   the marker. Close marker → unset, drop. Other tokens go
   through `emit_delta(_blocking)` which now picks
   `ReasoningDelta` or `TextDelta` based on state. Markers
   never appear in the streamed output.

3. **In `wire::openai_chat`**, the projector splits into:
   - `project_chat_stream` (unchanged signature; default
     behaviour — drops `ReasoningDelta`)
   - `project_chat_stream_with(rx, …, ChatProjectionConfig)` —
     when `include_thinking: true` and `reasoning_markers:
     Some(_)`, re-wraps reasoning content with the literal
     open/close marker text and emits as content deltas.
     Preserves the on-the-wire shape that helexa-acp's
     `ThinkParser` expects.

4. **HTTP handler** reads `x-include-thinking: true` (case-
   insensitive `1`/`true`/`yes`) from the request headers and
   threads it into the projection config. cortex-gateway already
   forwards arbitrary headers verbatim, so the opt-in works
   end-to-end without gateway changes.

5. **helexa-acp's `openai_chat` provider** sets
   `x-include-thinking: true` on every request so its existing
   `ThinkParser` keeps receiving the marked content stream.
   `ThinkParser` itself is unchanged — needed for endpoints that
   aren't reasoning-aware (OpenRouter, OpenAI directly, etc.).

## Acceptance

- Zed's commit-message generator (vanilla chat-completions
  client, no `x-include-thinking`) gets clean commit messages
  with no `<think>` block.
- helexa-acp sessions continue to render thinking in Zed's
  thought UI via the opt-in path.
- Models without reasoning tokens declared in their tokenizer
  pass through unchanged.
- Implementation contains zero references to "qwen3" or any
  specific model — entirely driven by tokenizer metadata.

## Tests

9 new tests in `wire::event` (token-pair detection across 4
marker conventions, edge cases) and `wire::openai_chat` (default
drop, opt-in re-wrap with multi-chunk reasoning, close-marker on
Finish, fallback when markers absent, off-switch with markers
present). All 213 workspace tests pass; fmt + clippy clean.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-31 17:55:04 +03:00

cortex

A Rust reverse-proxy and fleet management layer for multi-node GPU inference clusters. Cortex sits in front of one or more neuron daemons (each running candle-based inference on a local GPU host) and presents a unified OpenAI + Anthropic compatible API surface.

Problem

Running local LLMs across multiple GPU nodes (different VRAM tiers, different model affinities) requires a unified API surface that:

  • Presents a single /v1/models catalogue merging every model that can be served by any neuron in the fleet.
  • Routes requests to the correct node based on where a model is loaded (or can be loaded), handling cold-load and eviction transparently.
  • Manages model lifecycle — load on demand, unload cold models, pin critical ones — by calling each neuron's /models/{load,unload} API.
  • Translates between OpenAI and Anthropic request/response envelopes so every client speaks whichever dialect it prefers.
  • Captures per-request metrics (tokens, tok/s, TTFT, latency) and exposes them as Prometheus counters/histograms.

Architecture

┌──────────────┐  ┌──────────┐  ┌────────────┐  ┌────────────┐
│ Claude Code  │  │ Zed/IDE  │  │ Tidal / mm │  │ curl / etc │
└──────┬───────┘  └─────┬────┘  └──────┬─────┘  └──────┬─────┘
       │                │              │               │
       └────────────────┴──────┬───────┴───────────────┘
                               │
                    ┌──────────▼──────────┐
                    │      cortex         │
                    │  (cortex-gateway)   │
                    │                     │
                    │  Router · Metrics   │
                    │  Evictor · Translate│
                    └──┬──────┬────────┬──┘
                       │      │        │
            ┌──────────▼┐  ┌──▼─────┐  ┌▼──────────┐
            │  neuron   │  │ neuron │  │  neuron   │
            │  :13131   │  │ :13131 │  │  :13131   │
            │  candle   │  │ candle │  │  candle   │
            └───────────┘  └────────┘  └───────────┘
                  private network (.internal)

Crates

Crate Purpose
cortex-core Shared types: config, node/model state, metrics, OpenAI/Anthropic envelopes, harness trait, discovery types
cortex-gateway Axum HTTP server: proxy, router, evictor, poller, metrics exporter
neuron Per-node daemon: GPU discovery, in-process candle inference, model lifecycle API
cortex-cli CLI entrypoint (cortex serve, cortex status, etc.)

Node setup

Each GPU node runs neuron (listening on :13131). Neuron uses huggingface/candle for in-process inference — there is no external inference subprocess to manage.

Inside the daemon, every CUDA device gets one dedicated OS thread (named cuda-dev-N) that owns the device's CUDA context for the daemon's lifetime. Model loads, forward passes, KV-cache resets, NCCL collectives, VRAM queries, and unloads all route through that thread via a job channel; tensors never escape it alive. This pins context binding to a known thread, makes the CUDA Drop contract structurally safe, and isolates driver-error poisoning to one worker rather than the whole process. See CLAUDE.md for the design rationale and crates/neuron/src/harness/device_worker/ for the code.

The neuron RPM (helexa-neuron) ships a systemd unit:

dnf copr enable helexa/helexa
dnf install helexa-neuron
systemctl enable --now neuron

Gateway config

# /etc/cortex/cortex.toml
[gateway]
listen = "0.0.0.0:31313"
metrics_listen = "0.0.0.0:31314"

[eviction]
strategy = "lru"        # lru | priority
defrag_after_cycles = 50

[[neurons]]
name = "beast"
endpoint = "http://beast.internal:13131"

[[neurons]]
name = "benjy"
endpoint = "http://benjy.internal:13131"

Model placement profiles live in models.toml — see models.example.toml.

Building

cargo build --release

CI

Every push triggers format, lint, and test checks. Ensure these pass locally before pushing:

cargo fmt --check --all                    # must be clean
cargo clippy --workspace -- -D warnings   # warnings are errors
cargo test --workspace                     # all tests must pass

Tagged releases (v*) additionally build SRPMs for both cortex and helexa-neuron and publish to COPR.

Running

# start the gateway
cortex serve --config /etc/cortex/cortex.toml

# check fleet status
cortex status

# list all models across nodes
curl http://localhost:31313/v1/models

License

GPL-3.0

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