fix(rpm): explicitly Provides user(name) to satisfy systemd unit Requires

Diagnosing the persistent "Nothing to do" on v0.1.10 surfaced that
removing %attr(,,name) from %files wasn't enough. systemd-rpm-macros
ships its own rpm dep generator (/usr/lib/rpm/systemd.req) that parses
User=/Group= directives from every .service file the package ships
and emits Requires: user(NAME)/group(NAME) accordingly.

Rpmbuild log from v0.1.10 shows these Requires are still emitted even
after the %attr removal. Meanwhile the sysusers provides-generator
emits group(NAME) in both unversioned and versioned forms, but only
a versioned user(NAME) = <base64> when the u-line has GECOS/home/shell
fields. The asymmetry leaves Requires: user(NAME) unresolvable.

Add explicit Provides: user(NAME) back to both specs, with a comment
documenting the actual cause (systemd unit parsing, not file attrs)
so the next person touching these specs doesn't repeat the mistake.

Why monsoon didn't hit this: it creates its user in %pre via
groupadd/useradd (not sysusers.d), so no Provides are generated at
all — matching the Requires: user(monsoon) by luck of the rpm solver
treating unknown symbols as soft-fails for that path. Ours went through
the sysusers Provides code path and hit the asymmetry instead.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

.gitea/workflows/build-prerelease.yml

@@ -1,326 +0,0 @@
-name: build-prerelease
-
-# Manually-dispatched workflow that builds CUDA-flavoured neuron binaries
-# (and a single cortex binary), packages each as a Fedora RPM, signs
-# them, and publishes to the `unstable` channel at rpm.lair.cafe.
-#
-# Trigger from the Gitea UI: Actions → build-prerelease → Run workflow.
-# Optionally provide a `ref` to build from a non-default branch.
-#
-# The published packages are versioned as e.g.
-#   helexa-neuron-blackwell-0.1.16-0.1.20260518gitabcdef0.fc43.x86_64
-# so they sort BELOW the eventual 0.1.16-1 stable release.
-
-on:
-  # Auto-build on every push to main so the unstable channel tracks
-  # head without a manual dispatch step.
-  push:
-    branches: [main]
-  # Manual dispatch still available to build from a non-main ref.
-  workflow_dispatch:
-    inputs:
-      ref:
-        description: "Git ref to build (branch / tag / commit). Defaults to the workflow's branch."
-        required: false
-        default: ""
-
-concurrency:
-  # Coalesce on branch+event so successive pushes don't pile up; the
-  # latest push wins.
-  group: prerelease-build-${{ github.ref }}
-  cancel-in-progress: true
-
-env:
-  CARGO_INCREMENTAL: "0"
-
-jobs:
-  prepare:
-    name: Resolve version stamps
-    runs-on: rust
-    outputs:
-      version: ${{ steps.info.outputs.version }}
-      release: ${{ steps.info.outputs.release }}
-      short_sha: ${{ steps.info.outputs.short_sha }}
-      commit_date: ${{ steps.info.outputs.commit_date }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-          fetch-depth: 0
-
-      - id: info
-        run: |
-          set -eux
-          VERSION=$(awk -F\" '/^version[[:space:]]*=/ { print $2; exit }' Cargo.toml)
-          SHORT_SHA=$(git rev-parse --short=7 HEAD)
-          COMMIT_DATE=$(git log -1 --format=%cd --date=format:%Y%m%d HEAD)
-          # Prerelease release stamp sorts before "1" (the stable release).
-          RELEASE="0.1.${COMMIT_DATE}git${SHORT_SHA}"
-          echo "version=${VERSION}" >> "$GITHUB_OUTPUT"
-          echo "release=${RELEASE}" >> "$GITHUB_OUTPUT"
-          echo "short_sha=${SHORT_SHA}" >> "$GITHUB_OUTPUT"
-          echo "commit_date=${COMMIT_DATE}" >> "$GITHUB_OUTPUT"
-
-  build-cortex:
-    name: Build cortex binary
-    needs: prepare
-    # runner-rust image already provides rust/cargo/clippy/rustfmt via
-    # dnf — no rustup install step needed.
-    runs-on: rust
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-
-      - name: Build cortex (release)
-        run: cargo build --release -p cortex-cli
-
-      - name: Stage binary
-        run: |
-          mkdir --parents artifacts
-          cp target/release/cortex artifacts/cortex
-          ./artifacts/cortex --version || true
-
-      - uses: actions/upload-artifact@v3
-        with:
-          name: cortex-fc43
-          path: artifacts/cortex
-          retention-days: 1
-
-  build-neuron:
-    name: Build neuron-${{ matrix.flavour }}
-    needs: prepare
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-          - flavour: ampere
-            compute_cap: "86"
-            runner: cuda-13.0
-            cuda_home: /usr/local/cuda-13.0
-            build_jobs: 8
-            nvcc_threads: 4
-            cargo_features: "cuda cudnn flash-attn"
-          - flavour: ada
-            compute_cap: "89"
-            runner: cuda-13.0
-            cuda_home: /usr/local/cuda-13.0
-            build_jobs: 8
-            nvcc_threads: 4
-            cargo_features: "cuda cudnn flash-attn"
-          - flavour: blackwell
-            compute_cap: "120"
-            runner: cuda-13.0
-            cuda_home: /usr/local/cuda-13.0
-            build_jobs: 8
-            nvcc_threads: 4
-            cargo_features: "cuda cudnn flash-attn"
-    runs-on: ${{ matrix.runner }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-
-      - name: Build neuron with CUDA (${{ matrix.flavour }})
-        run: |
-          set -eux
-          export PATH="${{ matrix.cuda_home }}/bin:${PATH}"
-          export LD_LIBRARY_PATH="${{ matrix.cuda_home }}/targets/x86_64-linux/lib:${{ matrix.cuda_home }}/lib64:${LD_LIBRARY_PATH:-}"
-          export LIBRARY_PATH="${{ matrix.cuda_home }}/targets/x86_64-linux/lib:${{ matrix.cuda_home }}/lib64:${LIBRARY_PATH:-}"
-          cargo build --release -p neuron --features "${{ matrix.cargo_features }}"
-        env:
-          CUDA_COMPUTE_CAP: ${{ matrix.compute_cap }}
-          CARGO_BUILD_JOBS: ${{ matrix.build_jobs }}
-          NVCC_THREADS: ${{ matrix.nvcc_threads }}
-
-      - name: Stage binary
-        run: |
-          mkdir --parents artifacts
-          cp target/release/neuron artifacts/neuron-${{ matrix.flavour }}
-          file "artifacts/neuron-${{ matrix.flavour }}"
-
-      - uses: actions/upload-artifact@v3
-        with:
-          name: neuron-${{ matrix.flavour }}-fc43
-          path: artifacts/neuron-${{ matrix.flavour }}
-          retention-days: 1
-
-  package-cortex:
-    name: Package cortex RPM
-    needs: [prepare, build-cortex]
-    runs-on: rpm
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-
-      - uses: actions/download-artifact@v3
-        with:
-          name: cortex-fc43
-          path: artifacts/
-
-      - name: Build RPM
-        run: |
-          set -eux
-          rm -f ~/.rpmmacros
-          rpmdev-setuptree
-          cp artifacts/cortex ~/rpmbuild/SOURCES/
-          cp data/cortex.service ~/rpmbuild/SOURCES/
-          cp data/cortex-sysusers.conf ~/rpmbuild/SOURCES/
-          cp data/cortex-firewalld.xml ~/rpmbuild/SOURCES/
-          cp cortex.example.toml ~/rpmbuild/SOURCES/
-          cp models.example.toml ~/rpmbuild/SOURCES/
-          cp LICENSE ~/rpmbuild/SOURCES/
-          rpmbuild -bb rpm/cortex-prerelease.spec \
-            --define "cortex_version ${{ needs.prepare.outputs.version }}" \
-            --define "cortex_prerelease ${{ needs.prepare.outputs.release }}" \
-            --undefine dist \
-            --define "dist .fc43"
-
-      - uses: actions/upload-artifact@v3
-        with:
-          name: rpm-cortex-fc43
-          path: ~/rpmbuild/RPMS/x86_64/*.rpm
-          retention-days: 7
-
-  package-neuron:
-    name: Package helexa-neuron-${{ matrix.flavour }} RPM
-    needs: [prepare, build-neuron]
-    runs-on: rpm
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-          - flavour: ampere
-          - flavour: ada
-          - flavour: blackwell
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-
-      - uses: actions/download-artifact@v3
-        with:
-          name: neuron-${{ matrix.flavour }}-fc43
-          path: artifacts/
-
-      - name: Build RPM
-        run: |
-          set -eux
-          rm -f ~/.rpmmacros
-          rpmdev-setuptree
-          cp artifacts/neuron-${{ matrix.flavour }} ~/rpmbuild/SOURCES/
-          cp data/neuron.service ~/rpmbuild/SOURCES/
-          cp data/neuron-sysusers.conf ~/rpmbuild/SOURCES/
-          cp data/neuron-firewalld.xml ~/rpmbuild/SOURCES/
-          cp neuron.example.toml ~/rpmbuild/SOURCES/
-          cp LICENSE ~/rpmbuild/SOURCES/
-          rpmbuild -bb rpm/helexa-neuron-prerelease.spec \
-            --define "neuron_version ${{ needs.prepare.outputs.version }}" \
-            --define "neuron_flavour ${{ matrix.flavour }}" \
-            --define "neuron_prerelease ${{ needs.prepare.outputs.release }}" \
-            --undefine dist \
-            --define "dist .fc43"
-
-      - uses: actions/upload-artifact@v3
-        with:
-          name: rpm-neuron-${{ matrix.flavour }}-fc43
-          path: ~/rpmbuild/RPMS/x86_64/*.rpm
-          retention-days: 7
-
-  publish:
-    name: Publish to rpm.lair.cafe (unstable)
-    needs: [package-cortex, package-neuron]
-    runs-on: rpm
-    concurrency:
-      group: rpm-publish
-      cancel-in-progress: false
-    env:
-      RPM_REPO_HOST: oolon.kosherinata.internal
-      FEDORA_VERSION: "43"
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          ref: ${{ inputs.ref }}
-
-      - name: Download all built RPMs
-        uses: actions/download-artifact@v3
-        with:
-          path: rpms/
-          pattern: rpm-*-fc43
-
-      - name: Flatten RPM artifacts
-        run: |
-          set -eux
-          find rpms/ -name '*.rpm' -exec mv --target-directory=rpms/ {} +
-          find rpms/ -mindepth 1 -type d -empty -delete
-          ls -la rpms/
-
-      - name: Check for sequoia-sq
-        run: |
-          if ! command -v sq &> /dev/null; then
-            echo "ERROR: sequoia-sq is not installed. Install with: sudo dnf install sequoia-sq"
-            exit 1
-          fi
-
-      - name: Import signing key
-        env:
-          # Pass secrets via env so values stay out of the rendered shell
-          # script (which Gitea includes in step logs). Template
-          # expansion of ${{ secrets.X }} inside `run:` writes the literal
-          # value into the script and depends on Gitea's log masker to
-          # scrub it — fragile for multi-line keys.
-          RPM_SIGNING_KEY: ${{ secrets.RPM_SIGNING_KEY }}
-          RPM_SIGNING_KEY_ID: ${{ secrets.RPM_SIGNING_KEY_ID }}
-        run: |
-          echo "$RPM_SIGNING_KEY" | gpg --batch --import
-          fpr=$(gpg --batch --with-colons --list-keys "$RPM_SIGNING_KEY_ID" | awk -F: '/^fpr:/ { print $10; exit }')
-          echo "${fpr}:6:" | gpg --batch --import-ownertrust
-          sed "s/@GPG_NAME@/$RPM_SIGNING_KEY_ID/" rpm/rpmmacros > ~/.rpmmacros
-
-      - name: Sign RPMs
-        run: |
-          set -eux
-          for rpm in rpms/*.rpm; do
-            echo "signing ${rpm}..."
-            rpm --addsign "${rpm}"
-          done
-
-      - name: Set up SSH for rsync
-        run: |
-          install --directory --mode 700 ~/.ssh
-          echo "${RSYNC_SSH_KEY}" | install --mode 600 /dev/stdin ~/.ssh/id_ed25519
-        env:
-          RSYNC_SSH_KEY: ${{ secrets.RSYNC_SSH_KEY }}
-
-      - name: Test SSH connectivity
-        run: |
-          ssh -o StrictHostKeyChecking=accept-new "gitea_ci@${RPM_REPO_HOST}" exit
-
-      - name: Ensure unstable repo directory exists
-        run: |
-          ssh "gitea_ci@${RPM_REPO_HOST}" \
-            "mkdir --parents /var/www/rpm/fedora/${FEDORA_VERSION}/x86_64/unstable"
-
-      - name: Sync RPMs to unstable repo
-        run: |
-          rsync \
-            --archive \
-            --verbose \
-            --chmod D755,F644 \
-            rpms/*.rpm \
-            "gitea_ci@${RPM_REPO_HOST}:/var/www/rpm/fedora/${FEDORA_VERSION}/x86_64/unstable/"
-
-      - name: Update unstable repo metadata
-        run: |
-          ssh "gitea_ci@${RPM_REPO_HOST}" \
-            "cd /var/www/rpm/fedora/${FEDORA_VERSION}/x86_64/unstable && createrepo_c --update ."
-
-      - name: Generate packages.json manifest
-        run: |
-          scp script/generate-packages-json.py "gitea_ci@${RPM_REPO_HOST}:/tmp/"
-          ssh "gitea_ci@${RPM_REPO_HOST}" \
-            "python3 /tmp/generate-packages-json.py \
-              --repodata-dir /var/www/rpm/fedora/${FEDORA_VERSION}/x86_64/unstable/repodata \
-              --output /var/www/rpm/fedora/${FEDORA_VERSION}/x86_64/unstable/packages.json \
-              --base-url https://rpm.lair.cafe/fedora/${FEDORA_VERSION}/x86_64/unstable"

.gitea/workflows/ci.yml

@@ -16,42 +16,53 @@ env:
   SCCACHE_S3_USE_SSL: "false"
   AWS_ACCESS_KEY_ID: ${{ secrets.SCCACHE_S3_ACCESS_KEY }}
   AWS_SECRET_ACCESS_KEY: ${{ secrets.SCCACHE_S3_SECRET_KEY }}
-  # fmt, clippy, and test all run in parallel on the same `rust` runner
-  # and would otherwise share /root/.cache/act/<hash>/hostexecutor/target/,
-  # racing each other's cargo temp files (.tmpXXXXXX) and failing builds
-  # mid-compile. Give each job its own target directory so the invocations
-  # don't collide. sccache still backs the actual rustc cache, so the
-  # rebuild penalty is small.
-  CARGO_TARGET_DIR: target-${{ github.job }}
 
 jobs:
-  fmt:
+  check:
-    name: Format
+    name: Format, lint, build, test
-    runs-on: rust
+    runs-on: fedora
     steps:
       - uses: actions/checkout@v4
-      - run: cargo fmt --check --all
 
-  clippy:
+      - name: Cache cargo registry and target
-    name: Clippy
+        uses: actions/cache@v4
-    runs-on: rust
+        with:
-    steps:
+          path: |
-      - uses: actions/checkout@v4
+            ~/.cargo/bin
-      - run: cargo clippy --workspace -- -D warnings
+            ~/.cargo/registry/index
-      - run: sccache --show-stats
+            ~/.cargo/registry/cache
+            ~/.cargo/git/db
+            target
+          key: ${{ runner.os }}-cargo-${{ hashFiles('**/Cargo.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-cargo-
 
-  test:
+      - name: Ensure sccache with S3 support
-    name: Test
+        env:
-    runs-on: rust
+          RUSTC_WRAPPER: ""
-    steps:
+        run: |
-      - uses: actions/checkout@v4
+          if sccache --version 2>/dev/null && sccache --show-stats 2>/dev/null; then
-      - run: cargo test --workspace
+            echo "sccache with S3 support already installed"
-      - run: sccache --show-stats
+          else
+            cargo install sccache --features s3 --locked
+          fi
+
+      - name: Check formatting
+        run: cargo fmt --check --all
+
+      - name: Clippy
+        run: cargo clippy --workspace -- -D warnings
+
+      - name: Test
+        run: cargo test --workspace
+
+      - name: Show sccache stats
+        run: sccache --show-stats
 
   srpm-cortex:
     name: Build cortex SRPM
-    runs-on: rpm
+    runs-on: fedora
-    needs: [fmt, clippy, test]
+    needs: check
     if: startsWith(github.ref, 'refs/tags/v')
     steps:
       - uses: actions/checkout@v4
@@ -110,8 +121,8 @@ jobs:
 
   srpm-neuron:
     name: Build neuron SRPM
-    runs-on: rpm
+    runs-on: fedora
-    needs: [fmt, clippy, test]
+    needs: check
     if: startsWith(github.ref, 'refs/tags/v')
     steps:
       - uses: actions/checkout@v4
@@ -128,37 +139,37 @@ jobs:
         run: |
           VERSION="${{ steps.version.outputs.VERSION }}"
           sed -i '/\[workspace\.package\]/,/\[/{ s/^version = ".*"/version = "'"${VERSION}"'"/ }' Cargo.toml
-          sed -i "s/^Version:.*/Version:        ${VERSION}/" helexa-neuron.spec
+          sed -i "s/^Version:.*/Version:        ${VERSION}/" neuron.spec
 
       - name: Generate changelog entry
         uses: https://git.lair.cafe/actions/rpm-changelog@v1
         with:
-          spec: helexa-neuron.spec
+          spec: neuron.spec
           version: ${{ steps.version.outputs.VERSION }}
 
       - name: Generate source tarball
         run: |
           set -ex
           VERSION="${{ steps.version.outputs.VERSION }}"
-          tar czf /tmp/helexa-neuron-${VERSION}.tar.gz \
+          tar czf /tmp/neuron-${VERSION}.tar.gz \
-            --transform "s,^\.,helexa-neuron-${VERSION}," \
+            --transform "s,^\.,neuron-${VERSION}," \
             --exclude='./target' \
             --exclude='./.git' \
             --exclude='*.tar.gz' \
             --exclude='*.src.rpm' \
             .
-          mv /tmp/helexa-neuron-${VERSION}.tar.gz .
+          mv /tmp/neuron-${VERSION}.tar.gz .
 
       - name: Vendor Rust dependencies
         run: |
           VERSION="${{ steps.version.outputs.VERSION }}"
           cargo vendor vendor/
-          tar czf helexa-neuron-${VERSION}-vendor.tar.gz vendor/
+          tar czf neuron-${VERSION}-vendor.tar.gz vendor/
           rm -rf vendor/
 
       - name: Build SRPM
         run: |
-          rpmbuild -bs helexa-neuron.spec \
+          rpmbuild -bs neuron.spec \
             --define "_sourcedir $(pwd)" \
             --define "_srcrpmdir $(pwd)"
 
@@ -170,7 +181,7 @@ jobs:
 
   copr-cortex:
     name: Publish cortex to COPR
-    runs-on: fedora-43
+    runs-on: fedora
     needs: srpm-cortex
     steps:
       - name: Download SRPM
@@ -181,13 +192,13 @@ jobs:
       - name: Publish to COPR
         uses: https://git.lair.cafe/actions/copr-publish@v1
         with:
-          project: helexa/helexa
+          project: helexa/cortex
           srpm: "*.src.rpm"
           copr-config: ${{ secrets.COPR_CONFIG }}
 
   copr-neuron:
     name: Publish neuron to COPR
-    runs-on: fedora-43
+    runs-on: fedora
     needs: srpm-neuron
     steps:
       - name: Download SRPM
@@ -198,53 +209,31 @@ jobs:
       - name: Publish to COPR
         uses: https://git.lair.cafe/actions/copr-publish@v1
         with:
-          project: helexa/helexa
+          project: helexa/neuron
           srpm: "*.src.rpm"
           copr-config: ${{ secrets.COPR_CONFIG }}
 
   bump-version:
     name: Bump version in source
-    runs-on: rust
+    runs-on: fedora
     needs: [copr-cortex, copr-neuron]
     steps:
       - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
 
-      - name: Determine version
+      - name: Stamp version and push
-        id: version
-        run: echo "VERSION=${GITHUB_REF#refs/tags/v}" >> "$GITHUB_OUTPUT"
-
-      - name: Stamp version
-        run: |
-          VERSION="${{ steps.version.outputs.VERSION }}"
-          sed -i '/\[workspace\.package\]/,/\[/{ s/^version = ".*"/version = "'"${VERSION}"'"/ }' Cargo.toml
-          sed -i "s/^Version:.*/Version:        ${VERSION}/" cortex.spec
-          sed -i "s/^Version:.*/Version:        ${VERSION}/" helexa-neuron.spec
-          cargo check --workspace 2>/dev/null || true
-
-      - name: Generate cortex changelog entry
-        uses: https://git.lair.cafe/actions/rpm-changelog@v1
-        with:
-          spec: cortex.spec
-          version: ${{ steps.version.outputs.VERSION }}
-
-      - name: Generate helexa-neuron changelog entry
-        uses: https://git.lair.cafe/actions/rpm-changelog@v1
-        with:
-          spec: helexa-neuron.spec
-          version: ${{ steps.version.outputs.VERSION }}
-
-      - name: Commit and push
         env:
           GITEA_TOKEN: ${{ secrets.GITEA_TOKEN }}
         run: |
-          VERSION="${{ steps.version.outputs.VERSION }}"
+          VERSION="${GITHUB_REF#refs/tags/v}"
+          sed -i '/\[workspace\.package\]/,/\[/{ s/^version = ".*"/version = "'"${VERSION}"'"/ }' Cargo.toml
+          sed -i "s/^Version:.*/Version:        ${VERSION}/" cortex.spec
+          sed -i "s/^Version:.*/Version:        ${VERSION}/" neuron.spec
+          cargo check --workspace 2>/dev/null || true
           git config user.name "Gitea Actions"
           git config user.email "actions@git.lair.cafe"
-          git add Cargo.toml Cargo.lock cortex.spec helexa-neuron.spec
+          git add Cargo.toml Cargo.lock cortex.spec neuron.spec
           if git diff --cached --quiet; then
-            echo "Nothing to commit for ${VERSION}"
+            echo "Version already at ${VERSION}"
           else
             git commit -m "chore: bump version to ${VERSION}"
             git remote set-url origin "https://gitea-actions:${GITEA_TOKEN}@git.lair.cafe/helexa/cortex.git"

CLAUDE.md

@@ -125,8 +125,7 @@ automatically. Clippy warnings must be resolved, not suppressed with
   - One or more GPU nodes running mistral.rs on port 8080
   - Optionally a metrics-only node (no GPU) for Prometheus/Grafana
 - Each node runs `mistralrs serve` on port 8080
-- Gateway listens on port 31313 (API) and 31314 (metrics)
+- Gateway listens on port 8000 (API) and 9100 (metrics)
-- neuron listens on port 13131 on each GPU host
 - TLS terminated at gateway or via nginx; internal traffic is plaintext over WireGuard
 
 ## Conventions
@@ -381,7 +380,7 @@ processes (one process per loaded model, each on its own port).
 
 ## neuron API
 
-neuron exposes an HTTP API on port 13131 that cortex polls and calls.
+neuron exposes an HTTP API on port 9090 that cortex polls and calls.
 
 ```
 GET  /discovery
@@ -425,8 +424,8 @@ endpoint. cortex.toml shrinks to:
 
 ```toml
 [gateway]
-listen = "0.0.0.0:31313"
+listen = "0.0.0.0:8000"
-metrics_listen = "0.0.0.0:31314"
+metrics_listen = "0.0.0.0:9100"
 
 [eviction]
 strategy = "lru"
@@ -434,15 +433,15 @@ defrag_after_cycles = 50
 
 [[neurons]]
 name = "beast"
-endpoint = "http://beast.hanzalova.internal:13131"
+endpoint = "http://beast.hanzalova.internal:9090"
 
 [[neurons]]
 name = "benjy"
-endpoint = "http://benjy.hanzalova.internal:13131"
+endpoint = "http://benjy.kosherinata.internal:9090"
 
 [[neurons]]
 name = "quadbrat"
-endpoint = "http://quadbrat.hanzalova.internal:13131"
+endpoint = "http://quadbrat.hanzalova.internal:9090"
 ```
 
 On startup and periodically, cortex calls `GET /discovery` and
@@ -522,7 +521,7 @@ cortex/
 │   │       └── metrics.rs      # prometheus exporter (unchanged)
 │   ├── neuron/                 # node plane (replaces cortex-agent)
 │   │   └── src/
-│   │       ├── main.rs         # binary entrypoint, axum server on :13131
+│   │       ├── main.rs         # binary entrypoint, axum server on :9090
 │   │       ├── discovery.rs    # nvidia-smi, device enumeration
 │   │       ├── health.rs       # runtime GPU polling
 │   │       ├── api.rs          # HTTP handlers for /discovery, /models, etc.
@@ -596,65 +595,70 @@ placement matching can be added incrementally.
 Completed. Both packages have RPM specs, systemd units, and example configs.
 CI builds parallel SRPMs on tag push and publishes to separate COPR repos.
 
-- `cortex.spec` — installs the `cortex` binary. Package name keeps the
+- `cortex.spec` → `helexa/cortex` COPR: binary, systemd unit, config files
-  short `cortex` because no Fedora package collides with it.
+- `neuron.spec` → `helexa/neuron` COPR: binary, systemd unit, config
-- `helexa-neuron.spec` — installs the `neuron` binary under package name
-  `helexa-neuron`. Renamed from bare `neuron` to avoid collision with
-  Fedora's NEURON neural-simulation package
-  (https://src.fedoraproject.org/rpms/neuron); binary, systemd unit,
-  system user, and config dir all stay named `neuron` since those are
-  project-local contexts.
 - `data/cortex.service`, `data/neuron.service` — systemd units
 - `cortex.example.toml`, `neuron.example.toml`, `models.example.toml`
-- CI: parallel `srpm-cortex` + `srpm-neuron` jobs, then parallel COPR
+- CI: parallel `srpm-cortex` + `srpm-neuron` jobs, then parallel COPR publish
-  publish to a single project `helexa/helexa` hosting both packages.
 
 Install:
 ```sh
-dnf copr enable helexa/helexa
+dnf copr enable helexa/cortex && dnf install cortex    # gateway host
-dnf install cortex                # gateway host
+dnf copr enable helexa/neuron && dnf install neuron    # GPU nodes
-dnf install helexa-neuron         # GPU nodes
 ```
 
-## 2026-05-18 addendum: candle-native pivot
+### Phase 11: llama.cpp harness stub
 
-Phases 11 (llama.cpp harness) and 12 (mistral.rs COPR) below are
+**Goal:** Prove the harness abstraction works with a second engine.
-**superseded**. The project no longer treats mistral.rs or llama.cpp as
-dependencies — both are conceptually out of scope. neuron becomes a
-candle-native inference daemon, with `Harness` retained as an
-internal seam for adding future engines (vision/audio/diffusion) but
-its only implementation being in-process candle.
 
-The full staged plan for this pivot lives at
+**Steps:**
-`~/.claude/plans/create-a-more-aggressive-calm-naur.md`. Summary:
+1. `crates/neuron/src/harness/llamacpp.rs` — implement the `Harness`
+   trait for llama.cpp's `llama-server`.
+   - `start()` — launch `llama-server` with the correct model path,
+     `--port`, `--n-gpu-layers`, `--tensor-split` args. Track the
+     child process.
+   - `stop()` — send SIGTERM to the child process.
+   - `list_models()` — llama-server serves one model per process, so
+     return a single-element list.
+   - `load_model()` — start a new llama-server process for this model.
+   - `unload_model()` — stop the process.
+   - `inference_endpoint()` — return `http://localhost:{assigned_port}`.
+2. Port allocation: neuron assigns ports from a range (e.g. 8100-8199)
+   to llama-server instances.
+3. Register in `HarnessRegistry` when configured:
+   ```toml
+   [[harnesses]]
+   name = "llamacpp"
+   binary = "/usr/local/bin/llama-server"
+   port_range = [8100, 8199]
+   ```
+4. Tests: mock llama-server (simple HTTP server returning canned
+   responses), test load/unload/endpoint lifecycle.
 
-- **Stage 1 (this commit):** delete `mistralrs.rs` and `llamacpp.rs`,
+**Done when:** A model with `harness = "llamacpp"` in `models.toml` can
-  scaffold inert `CandleHarness`, drop `endpoint`/`systemd_unit` from
+be loaded and served through cortex. Tests pass with mock llama-server.
-  `HarnessConfig`, default no-op `start`/`stop` on the `Harness` trait.
-- **Stages 2–4:** wire up candle model load/unload (quantized Qwen3
-  first), add OpenAI-compatible inference endpoint in neuron, then SSE
-  streaming.
-- **Stages 5–6:** load-on-activation (default models in config) and
-  unload-on-deactivation (graceful shutdown).
-- **Stages 7–8:** multi-GPU tensor parallelism and broader model/quant
-  coverage.
 
-Sections of this document that describe mistral.rs HTTP behaviour
+### Phase 12 (lower priority): mistral.rs COPR packaging
-("mistral.rs API gotchas") are retained as historical context for
-Phases 1–10 — they document what was true while the project depended
-on mistral.rs. They do not describe current behaviour.
 
----
+**Goal:** Fedora RPMs for mistral.rs built against specific CUDA versions.
 
-### Phase 11 (superseded): llama.cpp harness stub
+**Steps:**
+1. `mistralrs-cuda.spec` — RPM spec that clones a pinned mistral.rs git
+   tag, builds with `--features cuda`, links against the system CUDA
+   toolkit. Produces `mistralrs-cuda13-server` (CUDA 13.x / sm_120) and
+   `mistralrs-cuda12-server` (CUDA 12.x / sm_89). Install binary to
+   `/usr/local/bin/mistralrs`.
+2. COPR build config: enable the NVIDIA CUDA repo as a build dependency.
+   Pin the CUDA toolkit version in `BuildRequires`.
+3. Gitea Actions or manual workflow: bump the mistral.rs tag in the spec,
+   trigger COPR rebuild.
+4. neuron's mistralrs harness config references which binary/package
+   provides the mistral.rs binary. neuron could warn at startup if the
+   installed mistral.rs CUDA version doesn't match the discovered driver.
 
-~~Originally planned as a second engine to prove the harness
+**Done when:** `dnf install mistralrs-cuda13-server` on beast provides a
-abstraction.~~ Replaced by the candle harness work in the 2026-05-18
+working `mistralrs` binary built for Blackwell GPUs. `dnf install
-addendum above. llama.cpp's any-model/any-hardware breadth is no
+mistralrs-cuda12-server` on benjy provides one built for Ada GPUs.
-longer in scope for helexa.
 
-### Phase 12 (superseded): mistral.rs COPR packaging
+This is a separate repo/spec — not part of the cortex workspace — but
-
+tightly coupled operationally. Track it as a sibling project.
-~~Originally planned to ship CUDA-versioned mistral.rs RPMs.~~ Replaced
-by the candle harness work in the 2026-05-18 addendum above. With
-mistral.rs out of the dependency tree, there is nothing to package.

Cargo.toml

@@ -8,7 +8,7 @@ members = [
 ]
 
 [workspace.package]
-version = "0.1.16"
+version = "0.1.8"
 edition = "2024"
 license = "GPL-3.0-or-later"
 repository = "https://git.lair.cafe/helexa/cortex"
@@ -27,7 +27,7 @@ serde = { version = "1", features = ["derive"] }
 serde_json = "1"
 toml = "0.8"
 
-# http client (for proxying to neuron backends)
+# http client (for proxying to mistralrs backends)
 reqwest = { version = "0.12", features = ["json", "stream"] }
 
 # observability

README.md

@@ -1,23 +1,22 @@
 # cortex
 
-A Rust reverse-proxy and fleet management layer for multi-node GPU inference
+A Rust reverse-proxy and fleet management layer for multi-node
-clusters. Cortex sits in front of one or more `neuron` daemons (each running
+[mistral.rs](https://github.com/EricLBuehler/mistral.rs) inference clusters.
-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
+- Presents a **single `/v1/models` catalogue** merging every model across every
-  served by any neuron in the fleet.
+  node.
-- **Routes requests** to the correct node based on where a model is loaded
+- **Routes requests** to the correct node based on where a model is loaded (or
-  (or can be loaded), handling cold-load and eviction transparently.
+  *can* be loaded).
-- Manages **model lifecycle** — load on demand, unload cold models, pin
+- Manages **model lifecycle** — unload cold models, reload on demand, pin
-  critical ones — by calling each neuron's `/models/{load,unload}` API.
+  critical ones — using the mistral.rs
+  `/v1/models/{unload,reload,status}` HTTP API (PR #1828+).
 - Translates between **OpenAI and Anthropic** request/response envelopes so
-  every client speaks whichever dialect it prefers.
+  every client in the homelab speaks whichever dialect it prefers.
 - Captures **per-request metrics** (tokens, tok/s, TTFT, latency) and exposes
   them as Prometheus counters/histograms.
 
@@ -31,17 +30,18 @@ model affinities) requires a unified API surface that:
        └────────────────┴──────┬───────┴───────────────┘
                                │
                     ┌──────────▼──────────┐
-                    │      cortex         │
+                    │   cortex     │
-                    │  (cortex-gateway)   │
+                    │   (cortex-gateway)      │
                     │                     │
                     │  Router · Metrics   │
                     │  Evictor · Translate│
                     └──┬──────┬────────┬──┘
                        │      │        │
             ┌──────────▼┐  ┌──▼─────┐  ┌▼──────────┐
-            │  neuron   │  │ neuron │  │  neuron   │
+            │ gpu-large │  │gpu-med │  │ gpu-small │
-            │  :13131   │  │ :13131 │  │  :13131   │
+            │ mistralrs │  │mistral │  │ mistralrs │
-            │  candle   │  │ candle │  │  candle   │
+            │ serve     │  │rs serve│  │ serve     │
+            │ :8080     │  │ :8080  │  │  :8080    │
             └───────────┘  └────────┘  └───────────┘
                   private network (.internal)
 ```
@@ -50,48 +50,70 @@ model affinities) requires a unified API surface that:
 
 | Crate | Purpose |
 |---|---|
-| `cortex-core` | Shared types: config, node/model state, metrics, OpenAI/Anthropic envelopes, harness trait, discovery types |
+| `cortex-core` | Shared types: config, node/model state, metrics, OpenAI/Anthropic request/response envelopes |
-| `cortex-gateway` | Axum HTTP server: proxy, router, evictor, poller, metrics exporter |
+| `cortex-gateway` | Axum HTTP server: proxy, router, evictor, metrics exporter |
-| `neuron` | Per-node daemon: GPU discovery, in-process candle inference, model lifecycle API |
+| `cortex-agent` | Per-node sidecar: polls local mistralrs, reports to gateway, handles restart/defrag |
 | `cortex-cli` | CLI entrypoint (`cortex serve`, `cortex status`, etc.) |
 
 ## Node setup
 
-Each GPU node runs `neuron` (listening on `:13131`). Neuron uses
+Each GPU node runs `mistralrs serve` with a multi-model config. Models are
-huggingface/candle for in-process inference — there is no external
+declared but start **unloaded** — mistral.rs lazy-loads on first request and
-inference subprocess to manage.
+the gateway can explicitly unload/reload via the HTTP API.
 
-The neuron RPM (`helexa-neuron`) ships a systemd unit:
+Example node systemd unit:
 
-```sh
+```ini
-dnf copr enable helexa/helexa
+# /etc/systemd/system/mistralrs.service
-dnf install helexa-neuron
+[Unit]
-systemctl enable --now neuron
+Description=mistral.rs inference server
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+ExecStart=/usr/local/bin/mistralrs serve \
+    --from-config /etc/mistralrs/config.toml \
+    --port 8080
+Restart=on-failure
+RestartSec=5
+Environment=CUDA_VISIBLE_DEVICES=0,1
+
+[Install]
+WantedBy=multi-user.target
 ```
 
 ## Gateway config
 
 ```toml
-# /etc/cortex/cortex.toml
+# cortex.toml
 [gateway]
-listen = "0.0.0.0:31313"
+listen = "0.0.0.0:8000"
-metrics_listen = "0.0.0.0:31314"
+metrics_listen = "0.0.0.0:9100"
 
 [eviction]
 strategy = "lru"        # lru | priority
 defrag_after_cycles = 50
 
-[[neurons]]
+[[nodes]]
-name = "beast"
+name = "gpu-large"
-endpoint = "http://beast.internal:13131"
+endpoint = "http://gpu-large.internal:8080"
+vram_mb = 49_152        # e.g. 2x RTX 4090
+pinned = ["your-org/large-model"]
 
-[[neurons]]
+[[nodes]]
-name = "benjy"
+name = "gpu-medium"
-endpoint = "http://benjy.internal:13131"
+endpoint = "http://gpu-medium.internal:8080"
+vram_mb = 24_576        # e.g. RTX 4090
+pinned = ["your-org/medium-model"]
+
+[[nodes]]
+name = "gpu-small"
+endpoint = "http://gpu-small.internal:8080"
+vram_mb = 12_288        # e.g. RTX 3060
+pinned = ["your-org/embedding-model"]
 ```
 
-Model placement profiles live in `models.toml` — see `models.example.toml`.
-
 ## Building
 
 ```sh
@@ -109,20 +131,19 @@ 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
+Tagged releases (`v*`) additionally build an SRPM and publish to COPR.
-`helexa-neuron` and publish to COPR.
 
 ## Running
 
 ```sh
 # start the gateway
-cortex serve --config /etc/cortex/cortex.toml
+cortex serve --config cortex.toml
 
 # check fleet status
 cortex status
 
 # list all models across nodes
-curl http://localhost:31313/v1/models
+curl http://localhost:8000/v1/models
 ```
 
 ## License

asset/manifest.yml

@@ -1,30 +0,0 @@
-# Helexa fleet manifest.
-#
-# Drives rolling deploys via script/deploy.sh and serves as the source
-# of truth for which hosts run cortex vs neuron, and which CUDA
-# compute-capability flavour each neuron host needs.
-#
-# Flavour ↔ NVIDIA generation ↔ compute cap:
-#   ampere    sm_86   (RTX 30 series — e.g. 3060)
-#   ada       sm_89   (RTX 40 series — e.g. 4090)
-#   blackwell sm_120  (RTX 50 series — e.g. 5090)
-#
-# The flavour determines which RPM is installed on a given neuron host:
-# helexa-neuron-<flavour>. Only one flavour may be installed at a time
-# (the packages Conflict: with each other).
-
-cortex:
-  host: hanzalova.internal
-
-neurons:
-  - host: beast.hanzalova.internal
-    flavour: blackwell
-    gpu: "2x RTX 5090"
-
-  - host: benjy.hanzalova.internal
-    flavour: ada
-    gpu: "RTX 4090"
-
-  - host: quadbrat.hanzalova.internal
-    flavour: ampere
-    gpu: "RTX 3060"

cortex.example.toml

@@ -3,22 +3,22 @@
 # Copy to cortex.toml and adjust for your environment.
 #
 # Environment variable overrides use CORTEX_ prefix with __ separators:
-#   CORTEX_GATEWAY__LISTEN=0.0.0.0:31313
+#   CORTEX_GATEWAY__LISTEN=0.0.0.0:9000
 
 [gateway]
-listen = "0.0.0.0:31313"
+listen = "0.0.0.0:8000"
-metrics_listen = "0.0.0.0:31314"
+metrics_listen = "0.0.0.0:9100"
 
 [eviction]
 strategy = "lru"
-# Restart neurons after this many load/unload cycles to defragment VRAM.
+# Restart mistralrs after this many load/unload cycles to defragment VRAM.
 # Set to 0 to disable.
 defrag_after_cycles = 50
 
 # -- Nodes ---------------------------------------------------------------
-# Each [[nodes]] entry declares a neuron daemon in the fleet.
+# Each [[nodes]] entry declares a mistral.rs instance in the fleet.
-# Models are discovered by polling the neuron's /models endpoint.
+# Models are discovered by polling the node's /v1/models endpoint.
-# Pinned models (see models.toml) are never evicted.
+# Pinned models are never evicted.
 
 [[nodes]]
 name = "gpu-large"

cortex.spec

@@ -1,5 +1,5 @@
 Name:           cortex
-Version:        0.1.16
+Version:        0.1.8
 Release:        1%{?dist}
 Summary:        Inference gateway for multi-node GPU clusters
 
@@ -21,7 +21,6 @@ BuildRequires:  systemd-rpm-macros
 
 Requires(pre):  shadow-utils
 Requires:       systemd
-Requires:       firewalld-filesystem
 
 # systemd-rpm-macros ships a unit dep generator that parses User=/Group=
 # from our .service file and emits Requires: user(cortex)/group(cortex).
@@ -57,7 +56,6 @@ cargo build --release -p cortex-cli
 install -Dm755 target/release/cortex %{buildroot}%{_bindir}/cortex
 install -Dm644 data/cortex.service %{buildroot}%{_unitdir}/cortex.service
 install -Dm644 data/cortex-sysusers.conf %{buildroot}%{_sysusersdir}/cortex.conf
-install -Dm644 data/cortex-firewalld.xml %{buildroot}%{_prefix}/lib/firewalld/services/cortex.xml
 install -dm755 %{buildroot}%{_sysconfdir}/cortex
 install -Dm644 cortex.example.toml %{buildroot}%{_sysconfdir}/cortex/cortex.toml
 install -Dm644 models.example.toml %{buildroot}%{_sysconfdir}/cortex/models.toml
@@ -80,21 +78,10 @@ install -Dm644 models.example.toml %{buildroot}%{_sysconfdir}/cortex/models.toml
 %{_bindir}/cortex
 %{_unitdir}/cortex.service
 %{_sysusersdir}/cortex.conf
-%{_prefix}/lib/firewalld/services/cortex.xml
 %dir %{_sysconfdir}/cortex
 %config(noreplace) %{_sysconfdir}/cortex/cortex.toml
 %config(noreplace) %{_sysconfdir}/cortex/models.toml
 
 %changelog
-* Thu Apr 16 2026 Gitea Actions <actions@git.lair.cafe> - 0.1.16-1
-- chore: ignore local deploy script
-- chore: move default ports out of common-collision ranges
-- ci: drop actions/cache for cargo registry and target
-
-* Thu Apr 16 2026 Gitea Actions <actions@git.lair.cafe> - 0.1.14-1
-- ci: publish both packages to a single helexa/helexa COPR project
-- fix(rpm): rename neuron package to helexa-neuron
-- ci: commit generated %changelog entries back to main
-
 * Wed Apr 15 2026 Rob Thijssen <grenade@rob.tn> - 0.1.0-1
 - Initial package

crates/cortex-cli/src/main.rs

@@ -5,7 +5,7 @@ use tracing_subscriber::EnvFilter;
 
 #[derive(Parser)]
 #[command(name = "cortex")]
-#[command(about = "Unified inference gateway for multi-node GPU clusters")]
+#[command(about = "Unified inference gateway for multi-node mistral.rs clusters")]
 #[command(version)]
 struct Cli {
     #[command(subcommand)]
@@ -23,7 +23,7 @@ enum Commands {
     /// Print the fleet status (models, nodes, health).
     Status {
         /// Gateway API endpoint to query.
-        #[arg(short, long, default_value = "http://localhost:31313")]
+        #[arg(short, long, default_value = "http://localhost:8000")]
         endpoint: String,
     },
 }

crates/cortex-core/src/anthropic.rs

@@ -2,7 +2,7 @@
 //!
 //! These mirror the `/v1/messages` format used by the Anthropic API.
 //! The gateway accepts these, translates to OpenAI format, proxies to
-//! the inference backend (neuron), then translates the response back.
+//! mistral.rs, then translates the response back.
 
 use serde::{Deserialize, Serialize};
 use serde_json::Value;

crates/cortex-core/src/config.rs

@@ -22,9 +22,9 @@ fn default_models_path() -> String {
 
 #[derive(Debug, Clone, Serialize, Deserialize)]
 pub struct GatewaySettings {
-    /// Address to listen on for API requests (e.g. "0.0.0.0:31313")
+    /// Address to listen on for API requests (e.g. "0.0.0.0:8000")
     pub listen: String,
-    /// Address to listen on for Prometheus metrics (e.g. "0.0.0.0:31314")
+    /// Address to listen on for Prometheus metrics (e.g. "0.0.0.0:9100")
     pub metrics_listen: String,
 }
 
@@ -50,7 +50,7 @@ pub enum EvictionStrategy {
 pub struct NeuronEndpoint {
     /// Human-readable node name (e.g. "beast")
     pub name: String,
-    /// Base URL of the neuron daemon (e.g. "http://beast.internal:13131")
+    /// Base URL of the neuron daemon (e.g. "http://beast.internal:9090")
     pub endpoint: String,
 }
 
@@ -70,8 +70,8 @@ impl Default for GatewayConfig {
     fn default() -> Self {
         Self {
             gateway: GatewaySettings {
-                listen: "0.0.0.0:31313".into(),
+                listen: "0.0.0.0:8000".into(),
-                metrics_listen: "0.0.0.0:31314".into(),
+                metrics_listen: "0.0.0.0:9100".into(),
             },
             eviction: EvictionSettings {
                 strategy: EvictionStrategy::Lru,

crates/cortex-core/src/harness.rs

@@ -9,13 +9,13 @@ use async_trait::async_trait;
 use serde::{Deserialize, Serialize};
 
 /// Configuration for a harness instance on a neuron.
-///
-/// All current harnesses are in-process (candle); per-harness tuning
-/// (cache paths, device policies, etc.) lives in dedicated config
-/// blocks rather than on this struct.
 #[derive(Debug, Clone, Serialize, Deserialize)]
 pub struct HarnessConfig {
     pub name: String,
+    /// Base URL of the harness (e.g. "http://localhost:8080" for mistral.rs).
+    pub endpoint: Option<String>,
+    /// Systemd unit name, if the harness is managed via systemd.
+    pub systemd_unit: Option<String>,
 }
 
 /// Health status of a harness process.
@@ -47,24 +47,16 @@ pub struct ModelInfo {
 }
 
 /// What an inference harness must do, from neuron's perspective.
-///
-/// All current harnesses are in-process — they share neuron's address
-/// space and lifecycle. `start`/`stop` therefore default to no-ops; a
-/// future process-supervising harness would override them.
 #[async_trait]
 pub trait Harness: Send + Sync {
-    /// Human-readable name (e.g. "candle").
+    /// Human-readable name (e.g. "mistralrs", "llamacpp", "comfyui").
     fn name(&self) -> &str;
 
-    /// Start the harness. Default no-op for in-process harnesses.
+    /// Start the harness process if it is not already running.
-    async fn start(&self, _config: &HarnessConfig) -> Result<()> {
+    async fn start(&self, config: &HarnessConfig) -> Result<()>;
-        Ok(())
-    }
 
-    /// Stop the harness. Default no-op for in-process harnesses.
+    /// Stop the harness process gracefully.
-    async fn stop(&self) -> Result<()> {
+    async fn stop(&self) -> Result<()>;
-        Ok(())
-    }
 
     /// Health check. Returns the harness process status.
     async fn health(&self) -> HarnessHealth;

crates/cortex-core/src/node.rs

@@ -6,7 +6,7 @@ use std::collections::HashMap;
 #[derive(Debug, Clone)]
 pub struct NodeState {
     pub name: String,
-    /// Base URL of the neuron daemon (e.g. "http://beast.internal:13131").
+    /// Base URL of the neuron daemon (e.g. "http://beast.internal:9090").
     pub endpoint: String,
     pub healthy: bool,
     pub models: HashMap<String, ModelEntry>,

crates/cortex-core/src/openai.rs

@@ -3,7 +3,7 @@
 //! These are a subset sufficient for chat completions (streaming + non-streaming).
 //! Fields not relevant to proxying are captured as `serde_json::Value` via
 //! `#[serde(flatten)]` so we forward them without needing to enumerate every
-//! extension field a backend might support.
+//! extension field mistral.rs supports.
 
 use serde::{Deserialize, Serialize};
 use serde_json::Value;
@@ -22,7 +22,7 @@ pub struct ChatCompletionRequest {
     pub max_tokens: Option<u64>,
     #[serde(skip_serializing_if = "Option::is_none")]
     pub stream: Option<bool>,
-    /// All other fields (tools, response_format, backend extensions, etc.)
+    /// All other fields (tools, response_format, mistral.rs extensions, etc.)
     #[serde(flatten)]
     pub extra: Value,
 }

crates/cortex-gateway/src/proxy.rs

@@ -1,4 +1,4 @@
-//! Streaming HTTP reverse proxy to neuron backends.
+//! Streaming HTTP reverse proxy to mistral.rs backends.
 //!
 //! For streaming requests, SSE chunks are forwarded as they arrive.
 //! The proxy captures timing information for metrics but does not

crates/cortex-gateway/tests/common/mod.rs

@@ -22,7 +22,6 @@ use tokio::net::TcpListener;
 /// - GET /models/:id/endpoint (returns the inference URL)
 /// - POST /models/unload (accepts unload requests)
 /// - GET /v1/chat/completions + POST /v1/chat/completions (inference)
-///
 /// Returns the neuron base URL.
 pub async fn spawn_mock_neuron() -> String {
     let listener = TcpListener::bind("127.0.0.1:0").await.unwrap();
@@ -55,7 +54,7 @@ pub async fn spawn_mock_neuron() -> String {
 
 async fn mock_neuron_list_models() -> Json<Value> {
     Json(json!([
-        {"id": "test-model", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": 8000}
+        {"id": "test-model", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": 8000}
     ]))
 }
 

crates/cortex-gateway/tests/poller.rs

@@ -12,8 +12,8 @@ use std::sync::Arc;
 async fn test_poller_discovers_models() {
     // Mock neuron reports 2 models via /models endpoint (neuron format).
     let mock_url = common::spawn_mock_neuron_with_models(json!([
-        {"id": "model-a", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": 8000},
+        {"id": "model-a", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": 8000},
-        {"id": "model-b", "harness": "candle", "status": "unloaded", "devices": [], "vram_used_mb": null}
+        {"id": "model-b", "harness": "mistralrs", "status": "unloaded", "devices": [], "vram_used_mb": null}
     ]))
     .await;
 
@@ -63,8 +63,8 @@ async fn test_poller_discovers_models() {
 #[tokio::test]
 async fn test_poller_updates_gateway_models_endpoint() {
     let mock_url = common::spawn_mock_neuron_with_models(json!([
-        {"id": "model-x", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": null},
+        {"id": "model-x", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": null},
-        {"id": "model-y", "harness": "candle", "status": "loaded", "devices": [1], "vram_used_mb": null}
+        {"id": "model-y", "harness": "mistralrs", "status": "loaded", "devices": [1], "vram_used_mb": null}
     ]))
     .await;
 
@@ -152,8 +152,8 @@ async fn test_poller_marks_unreachable_node_unhealthy() {
 #[tokio::test]
 async fn test_poller_removes_stale_models() {
     let mock_url = common::spawn_mock_neuron_with_models(json!([
-        {"id": "keep-me", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": null},
+        {"id": "keep-me", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": null},
-        {"id": "drop-me", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": null}
+        {"id": "drop-me", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": null}
     ]))
     .await;
 
@@ -183,7 +183,7 @@ async fn test_poller_removes_stale_models() {
 
     // New mock with only one model.
     let new_mock_url = common::spawn_mock_neuron_with_models(json!([
-        {"id": "keep-me", "harness": "candle", "status": "loaded", "devices": [0], "vram_used_mb": null}
+        {"id": "keep-me", "harness": "mistralrs", "status": "loaded", "devices": [0], "vram_used_mb": null}
     ]))
     .await;
 

crates/cortex-gateway/tests/streaming.rs

@@ -51,18 +51,18 @@ async fn test_streaming_sse_passthrough() {
     }
 
     assert!(
-        chunks.len() > chunk_count,
+        chunks.len() >= chunk_count + 1,
-        "expected more than {} chunks (got {}): {:?}",
+        "expected at least {} chunks (got {}): {:?}",
-        chunk_count,
+        chunk_count + 1,
         chunks.len(),
         chunks,
     );
 
     assert_eq!(chunks.last().unwrap(), "[DONE]");
 
-    for (i, chunk) in chunks.iter().enumerate().take(chunk_count) {
+    for i in 0..chunk_count {
         let chunk_json: serde_json::Value =
-            serde_json::from_str(chunk).expect("chunk should be valid JSON");
+            serde_json::from_str(&chunks[i]).expect("chunk should be valid JSON");
         assert_eq!(
             chunk_json["choices"][0]["delta"]["content"],
             format!("token{i}")

crates/neuron/Cargo.toml

@@ -12,30 +12,6 @@ path = "src/lib.rs"
 name = "neuron"
 path = "src/main.rs"
 
-[features]
-default = []
-# Enables CUDA acceleration in candle. Without this feature, candle
-# compiles for CPU only and Device::new_cuda calls fall back to CPU.
-cuda = [
-    "candle-core/cuda",
-    "candle-nn/cuda",
-    "candle-transformers/cuda",
-]
-# Use cuDNN for convolution / attention kernels. Requires CUDA.
-cudnn = [
-    "cuda",
-    "candle-core/cudnn",
-    "candle-nn/cudnn",
-    "candle-transformers/cudnn",
-]
-# FlashAttention kernels. Requires CUDA.
-flash-attn = [
-    "cuda",
-    "candle-transformers/flash-attn",
-]
-# Reserved for GPU-only integration tests in later stages.
-cuda-integration = ["cuda"]
-
 [dependencies]
 cortex-core.workspace = true
 tokio.workspace = true
@@ -48,21 +24,9 @@ tracing-subscriber.workspace = true
 anyhow.workspace = true
 async-trait.workspace = true
 clap.workspace = true
-thiserror.workspace = true
-futures.workspace = true
-tokio-stream.workspace = true
 figment.workspace = true
 toml.workspace = true
 
-# candle for in-process inference. CUDA support is gated behind the
-# crate's `cuda` feature (default off) so the workspace builds on
-# non-CUDA hosts and CI runners.
-candle-core = "0.10.2"
-candle-nn = "0.10.2"
-candle-transformers = "0.10.2"
-tokenizers = { version = "0.22", default-features = false, features = ["onig"] }
-hf-hub = { version = "0.4", features = ["tokio"] }
-
 [dev-dependencies]
 tokio = { workspace = true, features = ["test-util"] }
 reqwest.workspace = true

crates/neuron/src/api.rs

@@ -1,33 +1,23 @@
 //! HTTP API handlers for the neuron daemon.
 
 use crate::harness::HarnessRegistry;
-use crate::harness::candle::{CandleHarness, InferenceError};
 use crate::health::HealthCache;
 use axum::Router;
 use axum::extract::{Path, State};
 use axum::http::StatusCode;
-use axum::response::sse::{Event, KeepAlive, Sse};
 use axum::response::{IntoResponse, Json};
 use axum::routing::{get, post};
 use cortex_core::discovery::{DiscoveryResponse, HealthResponse};
 use cortex_core::harness::ModelSpec;
-use cortex_core::openai::ChatCompletionRequest;
-use futures::stream::{self, StreamExt};
 use serde_json::{Value, json};
-use std::convert::Infallible;
 use std::sync::Arc;
 use tokio::sync::RwLock;
-use tokio_stream::wrappers::ReceiverStream;
 
 /// Shared state for the neuron HTTP server.
 pub struct NeuronState {
     pub discovery: DiscoveryResponse,
     pub health_cache: Arc<HealthCache>,
     pub registry: RwLock<HarnessRegistry>,
-    /// Typed handle to the candle harness for inference routes. Cached at
-    /// startup so `/v1/chat/completions` doesn't have to hold the registry
-    /// read lock or perform dyn-Trait dispatch per request.
-    pub candle: Option<Arc<CandleHarness>>,
 }
 
 /// Build the neuron API router.
@@ -39,7 +29,6 @@ pub fn neuron_routes() -> Router<Arc<NeuronState>> {
         .route("/models/load", post(load_model))
         .route("/models/unload", post(unload_model))
         .route("/models/{model_id}/endpoint", get(model_endpoint))
-        .route("/v1/chat/completions", post(chat_completions))
 }
 
 async fn discovery_handler(State(state): State<Arc<NeuronState>>) -> Json<DiscoveryResponse> {
@@ -56,7 +45,7 @@ async fn list_models(State(state): State<Arc<NeuronState>>) -> impl IntoResponse
         Ok(models) => Json(json!(models)).into_response(),
         Err(e) => (
             StatusCode::INTERNAL_SERVER_ERROR,
-            Json(json!({"error": format!("{e:#}")})),
+            Json(json!({"error": e.to_string()})),
         )
             .into_response(),
     }
@@ -69,22 +58,11 @@ async fn load_model(
     let registry = state.registry.read().await;
     match registry.load_model(&spec).await {
         Ok(()) => Json(json!({"status": "loaded"})).into_response(),
-        Err(e) => {
+        Err(e) => (
-            // Log the full anyhow chain server-side so journalctl shows
+            StatusCode::BAD_REQUEST,
-            // the underlying failure (hf-hub timeout, permission denied,
+            Json(json!({"error": e.to_string()})),
-            // disk full, etc.) without needing to inspect the HTTP
+        )
-            // response body separately.
+            .into_response(),
-            tracing::warn!(
-                model = %spec.model_id,
-                error = %format!("{e:#}"),
-                "load_model failed"
-            );
-            (
-                StatusCode::BAD_REQUEST,
-                Json(json!({"error": format!("{e:#}")})),
-            )
-                .into_response()
-        }
     }
 }
 
@@ -106,11 +84,7 @@ async fn unload_model(
     let registry = state.registry.read().await;
     match registry.unload_model(&model_id).await {
         Ok(()) => Json(json!({"status": "unloaded"})).into_response(),
-        Err(e) => (
+        Err(e) => (StatusCode::NOT_FOUND, Json(json!({"error": e.to_string()}))).into_response(),
-            StatusCode::NOT_FOUND,
-            Json(json!({"error": format!("{e:#}")})),
-        )
-            .into_response(),
     }
 }
 
@@ -128,61 +102,3 @@ async fn model_endpoint(
             .into_response(),
     }
 }
-
-/// OpenAI-compatible chat completions. Dispatches to streaming SSE when
-/// `stream: true` is set on the request; otherwise returns a single
-/// `ChatCompletionResponse`.
-async fn chat_completions(
-    State(state): State<Arc<NeuronState>>,
-    Json(req): Json<ChatCompletionRequest>,
-) -> impl IntoResponse {
-    let Some(candle) = state.candle.as_ref().map(Arc::clone) else {
-        return (
-            StatusCode::SERVICE_UNAVAILABLE,
-            Json(json!({"error": "candle harness not enabled on this neuron"})),
-        )
-            .into_response();
-    };
-
-    if req.stream.unwrap_or(false) {
-        match candle.chat_completion_stream(req).await {
-            Ok(rx) => {
-                // Each chunk → one SSE `data: {json}` line. After the
-                // channel closes, append the OpenAI [DONE] terminator.
-                let body_stream = ReceiverStream::new(rx).map(|chunk| {
-                    let body = serde_json::to_string(&chunk).unwrap_or_default();
-                    Ok::<_, Infallible>(Event::default().data(body))
-                });
-                let done_stream =
-                    stream::once(async { Ok::<_, Infallible>(Event::default().data("[DONE]")) });
-                Sse::new(body_stream.chain(done_stream))
-                    .keep_alive(KeepAlive::default())
-                    .into_response()
-            }
-            Err(InferenceError::ModelNotLoaded(id)) => (
-                StatusCode::NOT_FOUND,
-                Json(json!({"error": format!("model '{id}' not loaded on this neuron")})),
-            )
-                .into_response(),
-            Err(InferenceError::Other(e)) => (
-                StatusCode::INTERNAL_SERVER_ERROR,
-                Json(json!({"error": format!("{e:#}")})),
-            )
-                .into_response(),
-        }
-    } else {
-        match candle.chat_completion(req).await {
-            Ok(resp) => Json(resp).into_response(),
-            Err(InferenceError::ModelNotLoaded(id)) => (
-                StatusCode::NOT_FOUND,
-                Json(json!({"error": format!("model '{id}' not loaded on this neuron")})),
-            )
-                .into_response(),
-            Err(InferenceError::Other(e)) => (
-                StatusCode::INTERNAL_SERVER_ERROR,
-                Json(json!({"error": format!("{e:#}")})),
-            )
-                .into_response(),
-        }
-    }
-}

crates/neuron/src/config.rs

@@ -1,12 +1,12 @@
 //! Neuron configuration loaded from neuron.toml.
 
-use cortex_core::harness::{HarnessConfig, ModelSpec};
+use cortex_core::harness::HarnessConfig;
 use figment::{
     Figment,
     providers::{Env, Format, Toml},
 };
 use serde::{Deserialize, Serialize};
-use std::path::{Path, PathBuf};
+use std::path::Path;
 
 #[derive(Debug, Clone, Serialize, Deserialize)]
 pub struct NeuronConfig {
@@ -14,35 +14,10 @@ pub struct NeuronConfig {
     pub port: u16,
     #[serde(default)]
     pub harnesses: Vec<HarnessConfig>,
-    /// Per-harness configuration. Currently only `candle` is recognised.
-    #[serde(default)]
-    pub harness: HarnessSettings,
-    /// Models to auto-load when the neuron service activates. Each entry
-    /// is loaded sequentially before the HTTP listener binds. A failure
-    /// on any single entry logs a warning and proceeds — broken entries
-    /// don't prevent the rest of the fleet from starting.
-    #[serde(default)]
-    pub default_models: Vec<ModelSpec>,
-}
-
-/// Settings for individual harness implementations. Each harness owns
-/// its own sub-table so users only configure the harnesses they enable.
-#[derive(Debug, Clone, Default, Serialize, Deserialize)]
-pub struct HarnessSettings {
-    #[serde(default)]
-    pub candle: CandleHarnessConfig,
-}
-
-#[derive(Debug, Clone, Default, Serialize, Deserialize)]
-pub struct CandleHarnessConfig {
-    /// HuggingFace cache directory for model weights.
-    /// When unset, defers to hf-hub's default (~/.cache/huggingface).
-    #[serde(default)]
-    pub hf_cache: Option<PathBuf>,
 }
 
 fn default_port() -> u16 {
-    13131
+    9090
 }
 
 impl NeuronConfig {
@@ -58,10 +33,8 @@ impl NeuronConfig {
 impl Default for NeuronConfig {
     fn default() -> Self {
         Self {
-            port: 13131,
+            port: 9090,
             harnesses: vec![],
-            harness: HarnessSettings::default(),
-            default_models: vec![],
         }
     }
 }

crates/neuron/src/harness/candle.rs

@@ -1,687 +0,0 @@
-//! Candle harness — in-process inference using huggingface/candle.
-//!
-//! This is the sole `Harness` implementation. Inference runs inside
-//! the neuron process; there is no external subprocess.
-//!
-//! - Stage 2 wired GGUF (Qwen3 only) load/unload via `quantized_qwen3`.
-//! - Stage 3 (this) adds `chat_completion` — a non-streaming OpenAI
-//!   compatible chat completion routed to the loaded model's forward
-//!   pass on a per-model serialised generation loop.
-
-use anyhow::{Context, Result};
-use async_trait::async_trait;
-use candle_core::quantized::gguf_file;
-use candle_core::{Device, Tensor};
-use candle_transformers::generation::{LogitsProcessor, Sampling};
-use candle_transformers::models::quantized_qwen3::ModelWeights as QuantizedQwen3Weights;
-use cortex_core::harness::{Harness, HarnessHealth, ModelInfo, ModelSpec};
-use cortex_core::openai::{
-    ChatCompletionChoice, ChatCompletionChunk, ChatCompletionRequest, ChatCompletionResponse,
-    ChatMessage, ChunkChoice, MessageContent, Usage,
-};
-use serde_json::json;
-use std::collections::HashMap;
-use std::path::PathBuf;
-use std::sync::Arc;
-use std::time::{SystemTime, UNIX_EPOCH};
-use tokenizers::Tokenizer;
-use tokio::sync::{Mutex, RwLock, mpsc};
-
-/// In-process candle harness. Owns the loaded model registry.
-pub struct CandleHarness {
-    models: Arc<RwLock<HashMap<String, Arc<LoadedModel>>>>,
-    hf_cache: Option<PathBuf>,
-    bind_url: String,
-}
-
-/// A loaded model with its tokenizer, device placement, and architecture-
-/// specific weights. The `arch` is `Arc<Mutex<>>` so the lock guard can be
-/// moved into `spawn_blocking` for synchronous candle forward passes.
-pub struct LoadedModel {
-    pub model_id: String,
-    pub arch: Arc<Mutex<ModelArch>>,
-    pub tokenizer: Tokenizer,
-    pub device: Device,
-    pub quant: Option<String>,
-    pub devices: Vec<u32>,
-}
-
-/// Architecture-specific weights. Stage 3 still supports only Qwen3
-/// quantized; Stage 8 broadens this to additional families and
-/// non-quantized variants.
-pub enum ModelArch {
-    Qwen3Quantized(QuantizedQwen3Weights),
-}
-
-impl CandleHarness {
-    pub fn new(bind_url: String, hf_cache: Option<PathBuf>) -> Self {
-        Self {
-            models: Arc::new(RwLock::new(HashMap::new())),
-            hf_cache,
-            bind_url,
-        }
-    }
-
-    /// Pick a candle `Device` for the requested indices. Without the
-    /// `cuda` feature, or if CUDA initialisation fails, falls back to CPU.
-    fn pick_device(devices: &[u32]) -> Result<Device> {
-        let _idx = devices.first().copied().unwrap_or(0) as usize;
-        #[cfg(feature = "cuda")]
-        {
-            match Device::new_cuda(_idx) {
-                Ok(d) => return Ok(d),
-                Err(e) => tracing::warn!(
-                    device = _idx,
-                    error = %e,
-                    "CUDA device unavailable, falling back to CPU"
-                ),
-            }
-        }
-        Ok(Device::Cpu)
-    }
-
-    /// Resolve a model spec to local GGUF and tokenizer file paths via
-    /// hf-hub. Downloads on first use; subsequent calls are cached.
-    async fn resolve_files(&self, spec: &ModelSpec) -> Result<(PathBuf, PathBuf)> {
-        let mut builder = hf_hub::api::tokio::ApiBuilder::new();
-        if let Some(cache) = &self.hf_cache {
-            builder = builder.with_cache_dir(cache.clone());
-        }
-        let api = builder.build().context("build hf-hub API")?;
-        let repo = api.model(spec.model_id.clone());
-
-        let info = repo
-            .info()
-            .await
-            .with_context(|| format!("fetch HF repo info for {}", spec.model_id))?;
-
-        let quant = spec.quant.as_deref().unwrap_or("");
-        let quant_lc = quant.to_lowercase();
-        let gguf_filename = info
-            .siblings
-            .iter()
-            .map(|s| s.rfilename.as_str())
-            .filter(|name| name.to_lowercase().ends_with(".gguf"))
-            .find(|name| quant_lc.is_empty() || name.to_lowercase().contains(&quant_lc))
-            .ok_or_else(|| {
-                anyhow::anyhow!(
-                    "no GGUF file matching quant {:?} in repo {}",
-                    spec.quant,
-                    spec.model_id
-                )
-            })?
-            .to_string();
-
-        tracing::info!(
-            model = %spec.model_id,
-            file = %gguf_filename,
-            "resolving GGUF (may be cached)"
-        );
-        let gguf_path = repo
-            .get(&gguf_filename)
-            .await
-            .with_context(|| format!("fetch GGUF {gguf_filename}"))?;
-
-        // GGUF-only HF repos (unsloth/Qwen3-*-GGUF, Qwen/Qwen3-*-GGUF,
-        // etc.) ship the .gguf file but not tokenizer.json — the
-        // tokenizer.json lives in the base non-GGUF repo. Derive the
-        // base repo id by stripping a `-GGUF` / `-gguf` suffix; if
-        // there's no such suffix the same repo is used (works for
-        // non-GGUF model_ids).
-        let tokenizer_repo_id = spec
-            .model_id
-            .strip_suffix("-GGUF")
-            .or_else(|| spec.model_id.strip_suffix("-gguf"))
-            .unwrap_or(spec.model_id.as_str())
-            .to_string();
-        let tokenizer_repo = if tokenizer_repo_id == spec.model_id {
-            repo
-        } else {
-            tracing::debug!(
-                from = %spec.model_id,
-                to = %tokenizer_repo_id,
-                "tokenizer.json sourced from base repo (GGUF suffix stripped)"
-            );
-            api.model(tokenizer_repo_id.clone())
-        };
-        let tokenizer_path = tokenizer_repo
-            .get("tokenizer.json")
-            .await
-            .with_context(|| format!("fetch tokenizer.json from {tokenizer_repo_id}"))?;
-        Ok((gguf_path, tokenizer_path))
-    }
-
-    /// Run a non-streaming chat completion against a loaded model.
-    ///
-    /// Returns a typed `InferenceError` when the model isn't loaded so the
-    /// handler can map to an appropriate HTTP status without string-matching.
-    pub async fn chat_completion(
-        &self,
-        request: ChatCompletionRequest,
-    ) -> Result<ChatCompletionResponse, InferenceError> {
-        let loaded = {
-            let models = self.models.read().await;
-            models.get(&request.model).cloned()
-        };
-        let loaded = loaded.ok_or_else(|| InferenceError::ModelNotLoaded(request.model.clone()))?;
-
-        let prompt = format_qwen3_prompt(&request.messages);
-
-        let encoding = loaded
-            .tokenizer
-            .encode(prompt.as_str(), true)
-            .map_err(|e| InferenceError::Other(anyhow::anyhow!("tokenize: {e}")))?;
-        let prompt_tokens: Vec<u32> = encoding.get_ids().to_vec();
-        let prompt_len = prompt_tokens.len();
-
-        let temperature = request.temperature.unwrap_or(0.7);
-        let top_p = request.top_p;
-        let max_new = request.max_tokens.unwrap_or(512) as usize;
-        let seed = unix_subsec_nanos();
-
-        let eos_id = loaded
-            .tokenizer
-            .token_to_id("<|im_end|>")
-            .or_else(|| loaded.tokenizer.token_to_id("<|endoftext|>"));
-
-        let arch_arc = Arc::clone(&loaded.arch);
-        let device = loaded.device.clone();
-        let model_id = request.model.clone();
-
-        let (generated_ids, finish_reason) =
-            tokio::task::spawn_blocking(move || -> Result<(Vec<u32>, String)> {
-                let mut guard = arch_arc.blocking_lock();
-                run_inference(
-                    &mut guard,
-                    &device,
-                    &prompt_tokens,
-                    max_new,
-                    temperature,
-                    top_p,
-                    seed,
-                    eos_id,
-                )
-            })
-            .await
-            .map_err(|e| InferenceError::Other(anyhow::anyhow!("inference task panicked: {e}")))?
-            .map_err(InferenceError::Other)?;
-
-        let completion_text = loaded
-            .tokenizer
-            .decode(&generated_ids, true)
-            .map_err(|e| InferenceError::Other(anyhow::anyhow!("detokenize: {e}")))?;
-
-        let usage = Usage {
-            prompt_tokens: prompt_len as u64,
-            completion_tokens: generated_ids.len() as u64,
-            total_tokens: (prompt_len + generated_ids.len()) as u64,
-        };
-
-        Ok(ChatCompletionResponse {
-            id: format!("chatcmpl-{:x}", unix_subsec_nanos()),
-            object: "chat.completion".into(),
-            created: unix_now_secs(),
-            model: model_id,
-            choices: vec![ChatCompletionChoice {
-                index: 0,
-                message: ChatMessage {
-                    role: "assistant".into(),
-                    content: MessageContent::Text(completion_text),
-                    extra: serde_json::Value::Object(Default::default()),
-                },
-                finish_reason: Some(finish_reason),
-                extra: serde_json::Value::Object(Default::default()),
-            }],
-            usage: Some(usage),
-            extra: serde_json::Value::Object(Default::default()),
-        })
-    }
-
-    /// Run a streaming chat completion against a loaded model.
-    ///
-    /// Returns an `mpsc::Receiver` that yields `ChatCompletionChunk`s in
-    /// OpenAI SSE format. The first chunk carries the assistant role;
-    /// subsequent chunks carry incremental `content` deltas; the final
-    /// chunk carries `finish_reason`. The handler is responsible for
-    /// wrapping these into an SSE response and appending the `[DONE]`
-    /// terminator.
-    ///
-    /// Token-by-token decoding tracks the cumulative decoded prefix so
-    /// BPE byte-fallback boundaries don't split a UTF-8 char across
-    /// chunks.
-    pub async fn chat_completion_stream(
-        &self,
-        request: ChatCompletionRequest,
-    ) -> Result<mpsc::Receiver<ChatCompletionChunk>, InferenceError> {
-        let loaded = {
-            let models = self.models.read().await;
-            models.get(&request.model).cloned()
-        };
-        let loaded = loaded.ok_or_else(|| InferenceError::ModelNotLoaded(request.model.clone()))?;
-
-        let prompt = format_qwen3_prompt(&request.messages);
-        let encoding = loaded
-            .tokenizer
-            .encode(prompt.as_str(), true)
-            .map_err(|e| InferenceError::Other(anyhow::anyhow!("tokenize: {e}")))?;
-        let prompt_tokens: Vec<u32> = encoding.get_ids().to_vec();
-
-        let temperature = request.temperature.unwrap_or(0.7);
-        let top_p = request.top_p;
-        let max_new = request.max_tokens.unwrap_or(512) as usize;
-        let seed = unix_subsec_nanos();
-
-        let eos_id = loaded
-            .tokenizer
-            .token_to_id("<|im_end|>")
-            .or_else(|| loaded.tokenizer.token_to_id("<|endoftext|>"));
-
-        let arch_arc = Arc::clone(&loaded.arch);
-        let device = loaded.device.clone();
-        let tokenizer = loaded.tokenizer.clone();
-        let model_id = request.model.clone();
-        let id = format!("chatcmpl-{:x}", unix_subsec_nanos());
-        let created = unix_now_secs();
-
-        // Bounded channel so the producer (blocking inference) is back-
-        // pressured by the consumer (SSE writer). 32 is generous —
-        // tokens arrive one at a time and the SSE writer is async.
-        let (tx, rx) = mpsc::channel::<ChatCompletionChunk>(32);
-
-        // Lead chunk: announce the assistant role per OpenAI streaming
-        // conventions. Tools that auto-detect a streaming reply expect
-        // this before any content delta.
-        let role_chunk = ChatCompletionChunk {
-            id: id.clone(),
-            object: "chat.completion.chunk".into(),
-            created,
-            model: model_id.clone(),
-            choices: vec![ChunkChoice {
-                index: 0,
-                delta: json!({"role": "assistant"}),
-                finish_reason: None,
-                extra: serde_json::Value::Object(Default::default()),
-            }],
-            usage: None,
-            extra: serde_json::Value::Object(Default::default()),
-        };
-        // If sending the role chunk fails the receiver is already gone;
-        // bail before kicking off the heavy blocking work.
-        tx.send(role_chunk)
-            .await
-            .map_err(|_| InferenceError::Other(anyhow::anyhow!("client disconnected")))?;
-
-        tokio::task::spawn_blocking(move || {
-            let mut guard = arch_arc.blocking_lock();
-            if let Err(e) = run_inference_streaming(
-                &mut guard,
-                &device,
-                &tokenizer,
-                &prompt_tokens,
-                max_new,
-                temperature,
-                top_p,
-                seed,
-                eos_id,
-                &id,
-                created,
-                &model_id,
-                &tx,
-            ) {
-                tracing::warn!(model = %model_id, error = %e, "streaming inference failed");
-            }
-        });
-
-        Ok(rx)
-    }
-}
-
-#[async_trait]
-impl Harness for CandleHarness {
-    fn name(&self) -> &str {
-        "candle"
-    }
-
-    async fn health(&self) -> HarnessHealth {
-        HarnessHealth {
-            name: "candle".into(),
-            running: true,
-            uptime_secs: None,
-        }
-    }
-
-    async fn list_models(&self) -> Result<Vec<ModelInfo>> {
-        let models = self.models.read().await;
-        Ok(models
-            .values()
-            .map(|m| ModelInfo {
-                id: m.model_id.clone(),
-                harness: "candle".into(),
-                status: "loaded".into(),
-                devices: m.devices.clone(),
-                vram_used_mb: None,
-            })
-            .collect())
-    }
-
-    async fn load_model(&self, spec: &ModelSpec) -> Result<()> {
-        if spec.harness != "candle" {
-            anyhow::bail!("expected harness=candle, got harness={}", spec.harness);
-        }
-
-        {
-            let models = self.models.read().await;
-            if models.contains_key(&spec.model_id) {
-                anyhow::bail!("model '{}' already loaded", spec.model_id);
-            }
-        }
-
-        let devices = spec.devices.clone().unwrap_or_else(|| vec![0]);
-        let device = Self::pick_device(&devices)?;
-
-        let (gguf_path, tokenizer_path) = self.resolve_files(spec).await?;
-
-        let tokenizer = Tokenizer::from_file(&tokenizer_path)
-            .map_err(|e| anyhow::anyhow!("load tokenizer: {e}"))?;
-
-        // File I/O + GGUF parsing + tensor materialisation are CPU-bound,
-        // so run them on a blocking task to avoid stalling the runtime.
-        let device_for_load = device.clone();
-        let gguf_path_for_load = gguf_path.clone();
-        let model_id_for_log = spec.model_id.clone();
-        let arch = tokio::task::spawn_blocking(move || -> Result<ModelArch> {
-            tracing::info!(model = %model_id_for_log, path = ?gguf_path_for_load, "loading GGUF");
-            let mut file = std::fs::File::open(&gguf_path_for_load).context("open GGUF file")?;
-            let content = gguf_file::Content::read(&mut file)
-                .map_err(|e| anyhow::anyhow!("parse GGUF: {e}"))?;
-
-            let architecture = content
-                .metadata
-                .get("general.architecture")
-                .and_then(|v| v.to_string().ok().cloned())
-                .unwrap_or_default();
-            tracing::info!(architecture = %architecture, "GGUF architecture");
-
-            match architecture.as_str() {
-                "qwen3" => {
-                    let weights =
-                        QuantizedQwen3Weights::from_gguf(content, &mut file, &device_for_load)
-                            .map_err(|e| anyhow::anyhow!("from_gguf qwen3: {e}"))?;
-                    Ok(ModelArch::Qwen3Quantized(weights))
-                }
-                other => anyhow::bail!(
-                    "unsupported GGUF architecture '{other}'; Stage 3 only supports qwen3"
-                ),
-            }
-        })
-        .await
-        .context("blocking load task panicked")??;
-
-        let loaded = Arc::new(LoadedModel {
-            model_id: spec.model_id.clone(),
-            arch: Arc::new(Mutex::new(arch)),
-            tokenizer,
-            device,
-            quant: spec.quant.clone(),
-            devices,
-        });
-
-        let mut models = self.models.write().await;
-        models.insert(spec.model_id.clone(), loaded);
-        tracing::info!(model = %spec.model_id, "model loaded");
-        Ok(())
-    }
-
-    async fn unload_model(&self, model_id: &str) -> Result<()> {
-        let mut models = self.models.write().await;
-        if models.remove(model_id).is_none() {
-            anyhow::bail!("model '{model_id}' not loaded");
-        }
-        tracing::info!(model = %model_id, "model unloaded");
-        Ok(())
-    }
-
-    async fn inference_endpoint(&self, model_id: &str) -> Option<String> {
-        let models = self.models.read().await;
-        models.contains_key(model_id).then(|| self.bind_url.clone())
-    }
-}
-
-/// Errors returned by `CandleHarness::chat_completion`. The
-/// `ModelNotLoaded` variant lets the HTTP handler map cleanly to 404
-/// without string-matching on anyhow messages.
-#[derive(Debug, thiserror::Error)]
-pub enum InferenceError {
-    #[error("model '{0}' not loaded on this neuron")]
-    ModelNotLoaded(String),
-    #[error(transparent)]
-    Other(#[from] anyhow::Error),
-}
-
-/// Apply the Qwen3 chat template:
-///
-/// ```text
-/// <|im_start|>{role}\n{content}<|im_end|>\n
-/// ...
-/// <|im_start|>assistant\n
-/// ```
-///
-/// The trailing `<|im_start|>assistant\n` cues the model to begin a turn.
-/// Non-text content parts (vision blocks) are joined as text only; full
-/// multimodal handling is out of scope for Stage 3.
-fn format_qwen3_prompt(messages: &[ChatMessage]) -> String {
-    let mut prompt = String::new();
-    for msg in messages {
-        let content = match &msg.content {
-            MessageContent::Text(s) => s.clone(),
-            MessageContent::Parts(parts) => parts
-                .iter()
-                .filter_map(|p| p.get("text").and_then(|v| v.as_str()))
-                .collect::<Vec<_>>()
-                .join(""),
-        };
-        prompt.push_str("<|im_start|>");
-        prompt.push_str(&msg.role);
-        prompt.push('\n');
-        prompt.push_str(&content);
-        prompt.push_str("<|im_end|>\n");
-    }
-    prompt.push_str("<|im_start|>assistant\n");
-    prompt
-}
-
-#[allow(clippy::too_many_arguments)]
-fn run_inference(
-    arch: &mut ModelArch,
-    device: &Device,
-    prompt_tokens: &[u32],
-    max_new: usize,
-    temperature: f64,
-    top_p: Option<f64>,
-    seed: u64,
-    eos_id: Option<u32>,
-) -> Result<(Vec<u32>, String)> {
-    let mut logits_processor = {
-        let sampling = if temperature <= 0.0 {
-            Sampling::ArgMax
-        } else {
-            match top_p {
-                Some(p) => Sampling::TopP { p, temperature },
-                None => Sampling::All { temperature },
-            }
-        };
-        LogitsProcessor::from_sampling(seed, sampling)
-    };
-
-    let mut generated: Vec<u32> = Vec::new();
-
-    let mut next_token = match arch {
-        ModelArch::Qwen3Quantized(model) => {
-            model.clear_kv_cache();
-            let input = Tensor::new(prompt_tokens, device)?.unsqueeze(0)?;
-            let logits = model.forward(&input, 0)?;
-            let logits = logits.squeeze(0)?;
-            logits_processor.sample(&logits)?
-        }
-    };
-
-    if Some(next_token) == eos_id {
-        return Ok((generated, "stop".into()));
-    }
-    generated.push(next_token);
-
-    for index in 0..max_new.saturating_sub(1) {
-        next_token = match arch {
-            ModelArch::Qwen3Quantized(model) => {
-                let input = Tensor::new(&[next_token], device)?.unsqueeze(0)?;
-                let logits = model.forward(&input, prompt_tokens.len() + index)?;
-                let logits = logits.squeeze(0)?;
-                logits_processor.sample(&logits)?
-            }
-        };
-        if Some(next_token) == eos_id {
-            return Ok((generated, "stop".into()));
-        }
-        generated.push(next_token);
-    }
-
-    Ok((generated, "length".into()))
-}
-
-/// Streaming counterpart to `run_inference`. Emits chunks via `tx` as
-/// tokens are generated and exits on EOS, max_new, or receiver drop.
-///
-/// Detokenization tracks the cumulative decoded prefix so each chunk's
-/// `content` delta is the substring appended since the last chunk —
-/// safe across BPE byte-fallback boundaries.
-#[allow(clippy::too_many_arguments)]
-fn run_inference_streaming(
-    arch: &mut ModelArch,
-    device: &Device,
-    tokenizer: &Tokenizer,
-    prompt_tokens: &[u32],
-    max_new: usize,
-    temperature: f64,
-    top_p: Option<f64>,
-    seed: u64,
-    eos_id: Option<u32>,
-    id: &str,
-    created: u64,
-    model_id: &str,
-    tx: &mpsc::Sender<ChatCompletionChunk>,
-) -> Result<()> {
-    let mut logits_processor = {
-        let sampling = if temperature <= 0.0 {
-            Sampling::ArgMax
-        } else {
-            match top_p {
-                Some(p) => Sampling::TopP { p, temperature },
-                None => Sampling::All { temperature },
-            }
-        };
-        LogitsProcessor::from_sampling(seed, sampling)
-    };
-
-    let mut all_tokens: Vec<u32> = Vec::new();
-    let mut decoded_prefix = String::new();
-    let mut finish_reason = "length".to_string();
-
-    let mut next_token = match arch {
-        ModelArch::Qwen3Quantized(model) => {
-            model.clear_kv_cache();
-            let input = Tensor::new(prompt_tokens, device)?.unsqueeze(0)?;
-            let logits = model.forward(&input, 0)?;
-            let logits = logits.squeeze(0)?;
-            logits_processor.sample(&logits)?
-        }
-    };
-
-    let emit_token = |all_tokens: &[u32], decoded_prefix: &mut String| -> Result<bool> {
-        let full = tokenizer
-            .decode(all_tokens, true)
-            .map_err(|e| anyhow::anyhow!("decode: {e}"))?;
-        if full.len() > decoded_prefix.len() {
-            let delta = full[decoded_prefix.len()..].to_string();
-            *decoded_prefix = full;
-            let chunk = ChatCompletionChunk {
-                id: id.into(),
-                object: "chat.completion.chunk".into(),
-                created,
-                model: model_id.into(),
-                choices: vec![ChunkChoice {
-                    index: 0,
-                    delta: json!({ "content": delta }),
-                    finish_reason: None,
-                    extra: serde_json::Value::Object(Default::default()),
-                }],
-                usage: None,
-                extra: serde_json::Value::Object(Default::default()),
-            };
-            // blocking_send returns Err if the consumer hung up — signal
-            // the caller to stop generating.
-            if tx.blocking_send(chunk).is_err() {
-                return Ok(false);
-            }
-        }
-        Ok(true)
-    };
-
-    if Some(next_token) == eos_id {
-        finish_reason = "stop".into();
-    } else {
-        all_tokens.push(next_token);
-        if !emit_token(&all_tokens, &mut decoded_prefix)? {
-            return Ok(());
-        }
-
-        for index in 0..max_new.saturating_sub(1) {
-            next_token = match arch {
-                ModelArch::Qwen3Quantized(model) => {
-                    let input = Tensor::new(&[next_token], device)?.unsqueeze(0)?;
-                    let logits = model.forward(&input, prompt_tokens.len() + index)?;
-                    let logits = logits.squeeze(0)?;
-                    logits_processor.sample(&logits)?
-                }
-            };
-            if Some(next_token) == eos_id {
-                finish_reason = "stop".into();
-                break;
-            }
-            all_tokens.push(next_token);
-            if !emit_token(&all_tokens, &mut decoded_prefix)? {
-                return Ok(());
-            }
-        }
-    }
-
-    let final_chunk = ChatCompletionChunk {
-        id: id.into(),
-        object: "chat.completion.chunk".into(),
-        created,
-        model: model_id.into(),
-        choices: vec![ChunkChoice {
-            index: 0,
-            delta: serde_json::Value::Object(Default::default()),
-            finish_reason: Some(finish_reason),
-            extra: serde_json::Value::Object(Default::default()),
-        }],
-        usage: None,
-        extra: serde_json::Value::Object(Default::default()),
-    };
-    let _ = tx.blocking_send(final_chunk);
-    Ok(())
-}
-
-fn unix_now_secs() -> u64 {
-    SystemTime::now()
-        .duration_since(UNIX_EPOCH)
-        .map(|d| d.as_secs())
-        .unwrap_or(0)
-}
-
-fn unix_subsec_nanos() -> u64 {
-    SystemTime::now()
-        .duration_since(UNIX_EPOCH)
-        .map(|d| d.as_nanos() as u64)
-        .unwrap_or(0)
-}

crates/neuron/src/harness/llamacpp.rs

@@ -0,0 +1 @@
+// llama.cpp harness implementation — Phase 11.

crates/neuron/src/harness/mistralrs.rs

@@ -0,0 +1,163 @@
+//! mistral.rs harness implementation.
+//!
+//! Wraps the mistral.rs HTTP API for model lifecycle management
+//! and optionally manages the process via systemd.
+
+use anyhow::Result;
+use async_trait::async_trait;
+use cortex_core::harness::{Harness, HarnessConfig, HarnessHealth, ModelInfo, ModelSpec};
+use reqwest::Client;
+use serde::Deserialize;
+
+pub struct MistralRsHarness {
+    endpoint: String,
+    systemd_unit: Option<String>,
+    client: Client,
+}
+
+impl MistralRsHarness {
+    pub fn new(endpoint: String, systemd_unit: Option<String>) -> Self {
+        Self {
+            endpoint,
+            systemd_unit,
+            client: Client::builder()
+                .timeout(std::time::Duration::from_secs(30))
+                .build()
+                .expect("failed to build HTTP client"),
+        }
+    }
+}
+
+/// Response from mistral.rs `GET /v1/models`.
+#[derive(Debug, Deserialize)]
+struct ModelsResponse {
+    data: Vec<ModelEntry>,
+}
+
+#[derive(Debug, Deserialize)]
+struct ModelEntry {
+    id: String,
+    #[serde(default)]
+    status: Option<String>,
+}
+
+#[async_trait]
+impl Harness for MistralRsHarness {
+    fn name(&self) -> &str {
+        "mistralrs"
+    }
+
+    async fn start(&self, _config: &HarnessConfig) -> Result<()> {
+        let Some(unit) = &self.systemd_unit else {
+            anyhow::bail!("no systemd unit configured for mistralrs harness");
+        };
+
+        let output = tokio::process::Command::new("systemctl")
+            .args(["start", unit])
+            .output()
+            .await?;
+
+        if !output.status.success() {
+            let stderr = String::from_utf8_lossy(&output.stderr);
+            anyhow::bail!("systemctl start {unit} failed: {stderr}");
+        }
+
+        // Wait for the health endpoint to respond (up to 30s).
+        let url = format!("{}/health", self.endpoint);
+        for _ in 0..30 {
+            tokio::time::sleep(std::time::Duration::from_secs(1)).await;
+            if self.client.get(&url).send().await.is_ok() {
+                tracing::info!(unit, "mistralrs started and healthy");
+                return Ok(());
+            }
+        }
+        anyhow::bail!("mistralrs started but health endpoint did not respond within 30s");
+    }
+
+    async fn stop(&self) -> Result<()> {
+        let Some(unit) = &self.systemd_unit else {
+            anyhow::bail!("no systemd unit configured for mistralrs harness");
+        };
+
+        let output = tokio::process::Command::new("systemctl")
+            .args(["stop", unit])
+            .output()
+            .await?;
+
+        if !output.status.success() {
+            let stderr = String::from_utf8_lossy(&output.stderr);
+            anyhow::bail!("systemctl stop {unit} failed: {stderr}");
+        }
+        Ok(())
+    }
+
+    async fn health(&self) -> HarnessHealth {
+        let url = format!("{}/health", self.endpoint);
+        let running = self.client.get(&url).send().await.is_ok();
+        HarnessHealth {
+            name: "mistralrs".into(),
+            running,
+            uptime_secs: None,
+        }
+    }
+
+    async fn list_models(&self) -> Result<Vec<ModelInfo>> {
+        let url = format!("{}/v1/models", self.endpoint);
+        let resp = self.client.get(&url).send().await?;
+
+        if !resp.status().is_success() {
+            anyhow::bail!("GET /v1/models returned {}", resp.status());
+        }
+
+        let models_resp: ModelsResponse = resp.json().await?;
+        Ok(models_resp
+            .data
+            .into_iter()
+            .map(|m| ModelInfo {
+                id: m.id,
+                harness: "mistralrs".into(),
+                status: m.status.unwrap_or_else(|| "loaded".into()),
+                devices: vec![],
+                vram_used_mb: None,
+            })
+            .collect())
+    }
+
+    async fn load_model(&self, spec: &ModelSpec) -> Result<()> {
+        let url = format!("{}/v1/models/reload", self.endpoint);
+        let resp = self
+            .client
+            .post(&url)
+            .json(&serde_json::json!({ "model_id": spec.model_id }))
+            .send()
+            .await?;
+
+        if !resp.status().is_success() {
+            let body = resp.text().await.unwrap_or_default();
+            anyhow::bail!("POST /v1/models/reload failed: {body}");
+        }
+        Ok(())
+    }
+
+    async fn unload_model(&self, model_id: &str) -> Result<()> {
+        let url = format!("{}/v1/models/unload", self.endpoint);
+        let resp = self
+            .client
+            .post(&url)
+            .json(&serde_json::json!({ "model_id": model_id }))
+            .send()
+            .await?;
+
+        if !resp.status().is_success() {
+            let body = resp.text().await.unwrap_or_default();
+            anyhow::bail!("POST /v1/models/unload failed: {body}");
+        }
+        Ok(())
+    }
+
+    async fn inference_endpoint(&self, _model_id: &str) -> Option<String> {
+        // mistral.rs routes internally by model name in the request body,
+        // so the inference endpoint is always the base URL.
+        Some(self.endpoint.clone())
+    }
+}

crates/neuron/src/harness/mod.rs

@@ -1,22 +1,15 @@
 //! Harness registry — maps harness names to trait implementations.
 
-pub mod candle;
+pub mod llamacpp;
+pub mod mistralrs;
 
 use anyhow::Result;
 use cortex_core::harness::{Harness, HarnessConfig, ModelInfo, ModelSpec};
 use std::collections::HashMap;
-use std::sync::Arc;
 
 /// Registry of available harness implementations.
-///
-/// Holds an `Arc<dyn Harness>` per harness for generic lifecycle dispatch
-/// (load/unload/list_models). When a candle harness is registered, a typed
-/// `Arc<CandleHarness>` is also cached so inference routes can bypass the
-/// dyn-Trait dispatch and reach harness-specific methods (chat completion,
-/// streaming, etc.).
 pub struct HarnessRegistry {
-    harnesses: HashMap<String, Arc<dyn Harness>>,
+    harnesses: HashMap<String, Box<dyn Harness>>,
-    candle: Option<Arc<candle::CandleHarness>>,
 }
 
 impl Default for HarnessRegistry {
@@ -29,11 +22,10 @@ impl HarnessRegistry {
     pub fn new() -> Self {
         Self {
             harnesses: HashMap::new(),
-            candle: None,
         }
     }
 
-    pub fn register(&mut self, harness: Arc<dyn Harness>) {
+    pub fn register(&mut self, harness: Box<dyn Harness>) {
         self.harnesses.insert(harness.name().to_string(), harness);
     }
 
@@ -42,12 +34,6 @@ impl HarnessRegistry {
         self.harnesses.keys().cloned().collect()
     }
 
-    /// Typed handle to the candle harness, if registered. Used by inference
-    /// routes that need methods beyond the `Harness` trait surface.
-    pub fn candle(&self) -> Option<Arc<candle::CandleHarness>> {
-        self.candle.clone()
-    }
-
     /// List models from all registered harnesses.
     pub async fn list_all_models(&self) -> Result<Vec<ModelInfo>> {
         let mut all = Vec::new();
@@ -95,25 +81,19 @@ impl HarnessRegistry {
     }
 
     /// Build a registry from harness configs.
-    ///
+    pub fn from_configs(configs: &[HarnessConfig]) -> Self {
-    /// `bind_url` is the URL where this neuron serves inference (its own
-    /// listen address). In-process harnesses (currently the only kind)
-    /// return this URL from `inference_endpoint`.
-    pub fn from_configs(
-        configs: &[HarnessConfig],
-        bind_url: &str,
-        settings: &crate::config::HarnessSettings,
-    ) -> Self {
         let mut registry = Self::new();
         for config in configs {
             match config.name.as_str() {
-                "candle" => {
+                "mistralrs" => {
-                    let harness = Arc::new(candle::CandleHarness::new(
+                    if let Some(endpoint) = &config.endpoint {
-                        bind_url.to_string(),
+                        registry.register(Box::new(mistralrs::MistralRsHarness::new(
-                        settings.candle.hf_cache.clone(),
+                            endpoint.clone(),
-                    ));
+                            config.systemd_unit.clone(),
-                    registry.candle = Some(Arc::clone(&harness));
+                        )));
-                    registry.harnesses.insert("candle".into(), harness);
+                    } else {
+                        tracing::warn!("mistralrs harness missing endpoint, skipping");
+                    }
                 }
                 other => {
                     tracing::warn!(harness = other, "unknown harness type, skipping");

crates/neuron/src/lib.rs

@@ -3,4 +3,3 @@ pub mod config;
 pub mod discovery;
 pub mod harness;
 pub mod health;
-pub mod startup;

crates/neuron/src/main.rs

@@ -1,6 +1,6 @@
 use anyhow::Result;
 use clap::Parser;
-use neuron::{api, config::NeuronConfig, discovery, harness::HarnessRegistry, health, startup};
+use neuron::{api, config::NeuronConfig, discovery, harness::HarnessRegistry, health};
 use std::sync::Arc;
 use std::time::Instant;
 use tokio::sync::RwLock;
@@ -37,7 +37,6 @@ async fn main() -> Result<()> {
     });
 
     let port = args.port.unwrap_or(cfg.port);
-    let bind_url = format!("http://localhost:{port}");
     let start_time = Instant::now();
 
     tracing::info!("running hardware discovery");
@@ -48,18 +47,9 @@ async fn main() -> Result<()> {
         "discovery complete"
     );
 
-    // Build harness registry from config. In-process harnesses (candle)
+    // Build harness registry from config.
-    // need to know neuron's own bind URL so they can return it from
+    let registry = HarnessRegistry::from_configs(&cfg.harnesses);
-    // inference_endpoint.
-    let registry = HarnessRegistry::from_configs(&cfg.harnesses, &bind_url, &cfg.harness);
     discovery_result.harnesses = registry.names();
-    let candle = registry.candle();
-
-    // Activation: load default models before binding the listener.
-    // Each load may take tens of seconds to several minutes depending
-    // on model size and HF cache state — keep TimeoutStartSec in the
-    // systemd unit generous enough to cover the slowest entry.
-    startup::load_default_models(&registry, &cfg.default_models).await;
 
     let health_cache = Arc::new(health::HealthCache::new());
     health_cache
@@ -75,24 +65,13 @@ async fn main() -> Result<()> {
         discovery: discovery_result,
         health_cache,
         registry: RwLock::new(registry),
-        candle,
     });
 
-    let app = api::neuron_routes().with_state(Arc::clone(&state));
+    let app = api::neuron_routes().with_state(state);
     let addr: std::net::SocketAddr = format!("0.0.0.0:{port}").parse()?;
     tracing::info!("neuron listening on {addr}");
     let listener = tokio::net::TcpListener::bind(addr).await?;
-    axum::serve(listener, app)
+    axum::serve(listener, app).await?;
-        .with_graceful_shutdown(startup::shutdown_signal())
-        .await?;
-
-    // Deactivation: serve has returned (graceful shutdown signal
-    // received and connections drained). Release CUDA contexts / VRAM
-    // by unloading every model before exiting; systemd's TimeoutStopSec
-    // bounds how long this phase may take.
-    let registry = state.registry.read().await;
-    startup::unload_all_models(&registry).await;
-    tracing::info!("shutdown complete");
 
     Ok(())
 }

crates/neuron/src/startup.rs

@@ -1,97 +0,0 @@
-//! Activation- and deactivation-time orchestration.
-//!
-//! Wired from `main.rs` around the HTTP listener — activation runs
-//! before bind, deactivation runs after axum returns from its
-//! graceful-shutdown future. Kept in its own module so the logic is
-//! unit-testable without spinning up a full neuron process.
-
-use crate::harness::HarnessRegistry;
-use cortex_core::harness::ModelSpec;
-use std::time::Instant;
-use tokio::signal;
-
-/// Load each spec sequentially against the registry, treating
-/// individual failures as warnings rather than fatal errors.
-///
-/// VRAM contention makes parallel loads risky; the sequential path is
-/// boring but correct. The function logs elapsed time per load so an
-/// operator can see which model is hogging activation.
-pub async fn load_default_models(registry: &HarnessRegistry, specs: &[ModelSpec]) {
-    if specs.is_empty() {
-        return;
-    }
-    tracing::info!(count = specs.len(), "loading default models");
-    for spec in specs {
-        let start = Instant::now();
-        match registry.load_model(spec).await {
-            Ok(()) => tracing::info!(
-                model = %spec.model_id,
-                elapsed_ms = start.elapsed().as_millis() as u64,
-                "loaded default model"
-            ),
-            Err(e) => tracing::warn!(
-                model = %spec.model_id,
-                error = %e,
-                elapsed_ms = start.elapsed().as_millis() as u64,
-                "failed to load default model, continuing"
-            ),
-        }
-    }
-}
-
-/// Future that resolves on SIGINT (Ctrl-C) or SIGTERM (systemd stop).
-///
-/// Wired into `axum::serve(...).with_graceful_shutdown(shutdown_signal())`
-/// so the HTTP listener stops accepting new connections, lets in-flight
-/// requests drain, and then yields control back to main for cleanup.
-pub async fn shutdown_signal() {
-    let ctrl_c = async {
-        signal::ctrl_c().await.ok();
-    };
-    let terminate = async {
-        signal::unix::signal(signal::unix::SignalKind::terminate())
-            .expect("install SIGTERM handler")
-            .recv()
-            .await;
-    };
-    tokio::select! {
-        _ = ctrl_c => tracing::info!("received SIGINT, shutting down"),
-        _ = terminate => tracing::info!("received SIGTERM, shutting down"),
-    }
-}
-
-/// Unload every model currently registered. Called from `main.rs` after
-/// axum's graceful shutdown future resolves, so CUDA contexts and VRAM
-/// are released before the process exits rather than left to the OS to
-/// reclaim. Per-model failures are logged and skipped — keep cleanup
-/// going even when one harness is unhealthy.
-pub async fn unload_all_models(registry: &HarnessRegistry) {
-    let listed = match registry.list_all_models().await {
-        Ok(m) => m,
-        Err(e) => {
-            tracing::warn!(error = %e, "failed to list models during shutdown");
-            return;
-        }
-    };
-
-    if listed.is_empty() {
-        return;
-    }
-
-    tracing::info!(count = listed.len(), "unloading models for shutdown");
-    for model in listed {
-        let start = Instant::now();
-        match registry.unload_model(&model.id).await {
-            Ok(()) => tracing::info!(
-                model = %model.id,
-                elapsed_ms = start.elapsed().as_millis() as u64,
-                "unloaded"
-            ),
-            Err(e) => tracing::warn!(
-                model = %model.id,
-                error = %e,
-                "unload failed during shutdown"
-            ),
-        }
-    }
-}

crates/neuron/tests/activation.rs

@@ -1,56 +0,0 @@
-//! Activation-time behaviour: load_default_models continues past
-//! individual failures so a single broken catalogue entry doesn't
-//! prevent the rest of the fleet from starting.
-
-use cortex_core::harness::{HarnessConfig, ModelSpec};
-use neuron::config::HarnessSettings;
-use neuron::harness::HarnessRegistry;
-use neuron::startup;
-
-#[tokio::test]
-async fn test_load_default_models_skips_unknown_harness() {
-    let registry = HarnessRegistry::from_configs(
-        &[HarnessConfig {
-            name: "candle".into(),
-        }],
-        "http://localhost:0",
-        &HarnessSettings::default(),
-    );
-
-    // Both entries fail synchronously inside the registry — no network
-    // call escapes (the harness lookup mismatches before hf-hub is
-    // touched). The function should still return cleanly.
-    let specs = vec![
-        ModelSpec {
-            model_id: "model-a".into(),
-            harness: "no-such-harness".into(),
-            quant: None,
-            tensor_parallel: None,
-            devices: None,
-        },
-        ModelSpec {
-            model_id: "model-b".into(),
-            harness: "no-such-harness".into(),
-            quant: None,
-            tensor_parallel: None,
-            devices: None,
-        },
-    ];
-
-    startup::load_default_models(&registry, &specs).await;
-
-    let listed = registry
-        .list_all_models()
-        .await
-        .expect("list_all_models should succeed");
-    assert!(
-        listed.is_empty(),
-        "no models should be loaded after failed entries"
-    );
-}
-
-#[tokio::test]
-async fn test_load_default_models_empty_is_noop() {
-    let registry = HarnessRegistry::new();
-    startup::load_default_models(&registry, &[]).await;
-}

crates/neuron/tests/api.rs

@@ -14,7 +14,6 @@ async fn spawn_neuron(discovery: DiscoveryResponse) -> String {
         discovery,
         health_cache,
         registry: RwLock::new(registry),
-        candle: None,
     });
 
     let app = api::neuron_routes().with_state(state);
@@ -136,30 +135,56 @@ async fn test_models_empty_registry() {
     assert!(body.as_array().unwrap().is_empty());
 }
 
-/// Verify the candle harness registers, list is empty by default, and a
+/// Spawn a mock mistral.rs backend and a neuron with the mistralrs harness
-/// load attempt for an obviously-bogus model id returns a 4xx error
+/// pointing at it, then test the full model lifecycle through neuron's API.
-/// without crashing the daemon. Real load/unload exercising actual GGUF
-/// download is covered by `tests/candle_lifecycle.rs` (cuda-integration).
 #[tokio::test]
-async fn test_candle_harness_registers_and_rejects_bogus_model() {
+async fn test_models_via_mistralrs_harness() {
+    use axum::routing::{get, post};
+    use axum::{Json, Router};
     use cortex_core::harness::HarnessConfig;
-    use neuron::config::HarnessSettings;
+    use serde_json::Value;
 
-    let registry = HarnessRegistry::from_configs(
+    // Mock mistral.rs backend.
-        &[HarnessConfig {
+    let mock_app = Router::new()
-            name: "candle".into(),
+        .route(
-        }],
+            "/v1/models",
-        "http://localhost:13131",
+            get(|| async {
-        &HarnessSettings::default(),
+                Json(json!({
-    );
+                    "data": [
+                        {"id": "test-model", "status": "loaded"},
+                        {"id": "other-model", "status": "unloaded"}
+                    ]
+                }))
+            }),
+        )
+        .route(
+            "/v1/models/unload",
+            post(|Json(_body): Json<Value>| async { Json(json!({"status": "ok"})) }),
+        )
+        .route(
+            "/v1/models/reload",
+            post(|Json(_body): Json<Value>| async { Json(json!({"status": "ok"})) }),
+        );
+
+    let mock_listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
+    let mock_addr = mock_listener.local_addr().unwrap();
+    tokio::spawn(async move {
+        axum::serve(mock_listener, mock_app).await.unwrap();
+    });
+    let mock_url = format!("http://{mock_addr}");
+
+    // Build neuron with mistralrs harness pointing at mock.
+    let registry = HarnessRegistry::from_configs(&[HarnessConfig {
+        name: "mistralrs".into(),
+        endpoint: Some(mock_url.clone()),
+        systemd_unit: None,
+    }]);
 
-    let candle = registry.candle();
     let health_cache = Arc::new(HealthCache::new());
     let state = Arc::new(NeuronState {
         discovery: fake_discovery(),
         health_cache,
         registry: RwLock::new(registry),
-        candle,
     });
 
     let app = api::neuron_routes().with_state(state);
@@ -172,6 +197,7 @@ async fn test_candle_harness_registers_and_rejects_bogus_model() {
 
     let client = reqwest::Client::new();
 
+    // GET /models — should return models from mock mistralrs.
     let resp = client
         .get(format!("{neuron_url}/models"))
         .send()
@@ -179,140 +205,45 @@ async fn test_candle_harness_registers_and_rejects_bogus_model() {
         .unwrap();
     assert_eq!(resp.status(), 200);
     let models: Vec<serde_json::Value> = resp.json().await.unwrap();
-    assert!(models.is_empty());
+    assert_eq!(models.len(), 2);
+    assert_eq!(models[0]["id"], "test-model");
+    assert_eq!(models[0]["harness"], "mistralrs");
+    assert_eq!(models[0]["status"], "loaded");
+    assert_eq!(models[1]["id"], "other-model");
+    assert_eq!(models[1]["status"], "unloaded");
 
-    // Sending a wrong-harness spec should be rejected synchronously
+    // GET /models/test-model/endpoint — should return mock URL.
-    // without touching the network or the model registry.
+    let resp = client
+        .get(format!("{neuron_url}/models/test-model/endpoint"))
+        .send()
+        .await
+        .unwrap();
+    assert_eq!(resp.status(), 200);
+    let body: serde_json::Value = resp.json().await.unwrap();
+    assert_eq!(body["url"], mock_url);
+
+    // POST /models/unload — should succeed.
+    let resp = client
+        .post(format!("{neuron_url}/models/unload"))
+        .json(&json!({"model_id": "test-model"}))
+        .send()
+        .await
+        .unwrap();
+    assert_eq!(resp.status(), 200);
+    let body: serde_json::Value = resp.json().await.unwrap();
+    assert_eq!(body["status"], "unloaded");
+
+    // POST /models/load — should succeed.
     let resp = client
         .post(format!("{neuron_url}/models/load"))
-        .json(&json!({"model_id": "definitely/not-real", "harness": "not-candle"}))
-        .send()
-        .await
-        .unwrap();
-    assert_eq!(resp.status(), 400);
-
-    // Registry still empty.
-    let resp = client
-        .get(format!("{neuron_url}/models"))
-        .send()
-        .await
-        .unwrap();
-    let models: Vec<serde_json::Value> = resp.json().await.unwrap();
-    assert!(models.is_empty());
-}
-
-/// `/v1/chat/completions` returns 503 when no candle harness is registered.
-#[tokio::test]
-async fn test_chat_completions_no_candle_harness() {
-    let registry = HarnessRegistry::new();
-    let health_cache = Arc::new(HealthCache::new());
-    let state = Arc::new(NeuronState {
-        discovery: fake_discovery(),
-        health_cache,
-        registry: RwLock::new(registry),
-        candle: None,
-    });
-    let app = api::neuron_routes().with_state(state);
-    let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
-    let addr = listener.local_addr().unwrap();
-    tokio::spawn(async move {
-        axum::serve(listener, app).await.unwrap();
-    });
-    let url = format!("http://{addr}");
-
-    let resp = reqwest::Client::new()
-        .post(format!("{url}/v1/chat/completions"))
         .json(&json!({
-            "model": "anything",
+            "model_id": "test-model",
-            "messages": [{"role": "user", "content": "hi"}]
+            "harness": "mistralrs"
         }))
         .send()
         .await
         .unwrap();
-    assert_eq!(resp.status(), 503);
+    assert_eq!(resp.status(), 200);
-}
+    let body: serde_json::Value = resp.json().await.unwrap();
-
+    assert_eq!(body["status"], "loaded");
-/// `/v1/chat/completions` returns 404 when the requested model isn't loaded.
-#[tokio::test]
-async fn test_chat_completions_model_not_loaded() {
-    use cortex_core::harness::HarnessConfig;
-    use neuron::config::HarnessSettings;
-
-    let registry = HarnessRegistry::from_configs(
-        &[HarnessConfig {
-            name: "candle".into(),
-        }],
-        "http://localhost:0",
-        &HarnessSettings::default(),
-    );
-    let candle = registry.candle();
-    let health_cache = Arc::new(HealthCache::new());
-    let state = Arc::new(NeuronState {
-        discovery: fake_discovery(),
-        health_cache,
-        registry: RwLock::new(registry),
-        candle,
-    });
-    let app = api::neuron_routes().with_state(state);
-    let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
-    let addr = listener.local_addr().unwrap();
-    tokio::spawn(async move {
-        axum::serve(listener, app).await.unwrap();
-    });
-    let url = format!("http://{addr}");
-
-    let resp = reqwest::Client::new()
-        .post(format!("{url}/v1/chat/completions"))
-        .json(&json!({
-            "model": "definitely/not-loaded",
-            "messages": [{"role": "user", "content": "hi"}]
-        }))
-        .send()
-        .await
-        .unwrap();
-    assert_eq!(resp.status(), 404);
-}
-
-/// `/v1/chat/completions` with `stream: true` returns 404 when the
-/// model isn't loaded — same surface as the non-streaming path. The
-/// streaming code only kicks in once the model lookup succeeds.
-#[tokio::test]
-async fn test_chat_completions_streaming_model_not_loaded() {
-    use cortex_core::harness::HarnessConfig;
-    use neuron::config::HarnessSettings;
-
-    let registry = HarnessRegistry::from_configs(
-        &[HarnessConfig {
-            name: "candle".into(),
-        }],
-        "http://localhost:0",
-        &HarnessSettings::default(),
-    );
-    let candle = registry.candle();
-    let health_cache = Arc::new(HealthCache::new());
-    let state = Arc::new(NeuronState {
-        discovery: fake_discovery(),
-        health_cache,
-        registry: RwLock::new(registry),
-        candle,
-    });
-    let app = api::neuron_routes().with_state(state);
-    let listener = tokio::net::TcpListener::bind("127.0.0.1:0").await.unwrap();
-    let addr = listener.local_addr().unwrap();
-    tokio::spawn(async move {
-        axum::serve(listener, app).await.unwrap();
-    });
-    let url = format!("http://{addr}");
-
-    let resp = reqwest::Client::new()
-        .post(format!("{url}/v1/chat/completions"))
-        .json(&json!({
-            "model": "definitely/not-loaded",
-            "messages": [{"role": "user", "content": "hi"}],
-            "stream": true
-        }))
-        .send()
-        .await
-        .unwrap();
-    assert_eq!(resp.status(), 404);
 }

crates/neuron/tests/candle_lifecycle.rs

@@ -1,87 +0,0 @@
-//! Real model load/unload lifecycle through the candle harness.
-//!
-//! Gated behind the `cuda-integration` feature because it downloads a
-//! real (small) GGUF from HuggingFace and materialises tensors on the
-//! configured device. Run on a host with network access and either a
-//! CUDA GPU (when built with `--features cuda`) or enough CPU RAM to
-//! hold the model.
-//!
-//! Usage:
-//!   cargo test -p neuron --features cuda-integration --test candle_lifecycle
-//!
-//! Optional environment variables:
-//!   NEURON_TEST_MODEL_ID — HuggingFace repo to load (default: a small
-//!     public Qwen3 GGUF repo).
-//!   NEURON_TEST_QUANT    — quant substring matched against GGUF
-//!     filenames (default: "Q4_K_M").
-//!   HF_HOME              — HuggingFace cache directory.
-
-#![cfg(feature = "cuda-integration")]
-
-use cortex_core::harness::{HarnessConfig, ModelSpec};
-use neuron::config::HarnessSettings;
-use neuron::harness::HarnessRegistry;
-use std::path::PathBuf;
-
-#[tokio::test]
-async fn test_candle_qwen3_load_unload_lifecycle() {
-    let _ = tracing_subscriber::fmt()
-        .with_test_writer()
-        .with_env_filter("info,neuron=debug")
-        .try_init();
-
-    let model_id = std::env::var("NEURON_TEST_MODEL_ID")
-        .unwrap_or_else(|_| "Qwen/Qwen3-0.6B-GGUF".to_string());
-    let quant = std::env::var("NEURON_TEST_QUANT").unwrap_or_else(|_| "Q4_K_M".to_string());
-
-    let mut settings = HarnessSettings::default();
-    if let Ok(home) = std::env::var("HF_HOME") {
-        settings.candle.hf_cache = Some(PathBuf::from(home));
-    }
-
-    let registry = HarnessRegistry::from_configs(
-        &[HarnessConfig {
-            name: "candle".into(),
-        }],
-        "http://localhost:13131",
-        &settings,
-    );
-
-    let spec = ModelSpec {
-        model_id: model_id.clone(),
-        harness: "candle".into(),
-        quant: Some(quant),
-        tensor_parallel: None,
-        devices: Some(vec![0]),
-    };
-
-    registry
-        .load_model(&spec)
-        .await
-        .expect("load_model should succeed");
-
-    let models = registry.list_all_models().await.expect("list_all_models");
-    assert_eq!(models.len(), 1, "expected exactly one loaded model");
-    assert_eq!(models[0].id, model_id);
-    assert_eq!(models[0].harness, "candle");
-    assert_eq!(models[0].status, "loaded");
-
-    let url = registry.inference_endpoint(&model_id).await;
-    assert_eq!(url, Some("http://localhost:13131".into()));
-
-    // Re-loading the same model should be rejected.
-    let again = registry.load_model(&spec).await;
-    assert!(again.is_err(), "second load should error");
-
-    registry
-        .unload_model(&model_id)
-        .await
-        .expect("unload_model should succeed");
-
-    let models = registry.list_all_models().await.expect("list_all_models");
-    assert!(models.is_empty(), "registry should be empty after unload");
-
-    // Unloading a model that isn't loaded should error.
-    let err = registry.unload_model(&model_id).await;
-    assert!(err.is_err(), "unload of missing model should error");
-}

crates/neuron/tests/shutdown.rs

@@ -1,32 +0,0 @@
-//! Deactivation behaviour: unload_all_models tolerates an empty
-//! registry and continues past per-model unload failures.
-
-use cortex_core::harness::HarnessConfig;
-use neuron::config::HarnessSettings;
-use neuron::harness::HarnessRegistry;
-use neuron::startup;
-
-#[tokio::test]
-async fn test_unload_all_models_empty_registry_is_noop() {
-    let registry = HarnessRegistry::new();
-    startup::unload_all_models(&registry).await;
-}
-
-#[tokio::test]
-async fn test_unload_all_models_with_no_loaded_models() {
-    let registry = HarnessRegistry::from_configs(
-        &[HarnessConfig {
-            name: "candle".into(),
-        }],
-        "http://localhost:0",
-        &HarnessSettings::default(),
-    );
-
-    startup::unload_all_models(&registry).await;
-
-    let listed = registry
-        .list_all_models()
-        .await
-        .expect("list_all_models should still succeed after shutdown cleanup");
-    assert!(listed.is_empty());
-}

data/cortex-firewalld.xml

@@ -1,7 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<service>
-  <short>cortex</short>
-  <description>Cortex — inference gateway for multi-node GPU clusters</description>
-  <port protocol="tcp" port="31313"/>
-  <port protocol="tcp" port="31314"/>
-</service>

data/neuron-firewalld.xml

@@ -1,6 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<service>
-  <short>helexa-neuron</short>
-  <description>Neuron — per-node GPU discovery and harness daemon for cortex</description>
-  <port protocol="tcp" port="13131"/>
-</service>

data/neuron.service

@@ -10,22 +10,6 @@ Restart=on-failure
 RestartSec=5
 User=neuron
 Group=neuron
-# /var/lib/neuron is the neuron user's $HOME — hf-hub writes its
-# default cache there (~/.cache/huggingface/hub). Without this directive
-# systemd doesn't create the directory and hf-hub downloads fail with
-# "fetch GGUF <file>: failed to create cache dir".
-StateDirectory=neuron
-StateDirectoryMode=0755
-# Loading default_models from neuron.toml happens before the HTTP
-# listener binds; large models can take many minutes to download and
-# materialise on first activation. systemd's default TimeoutStartSec
-# (90s) is far too short; allow 30 minutes.
-TimeoutStartSec=1800s
-# On stop, neuron drains in-flight requests then unloads every model
-# to release CUDA contexts cleanly. Allow generous time for big-model
-# unloads; systemd will SIGKILL after this bound.
-TimeoutStopSec=120s
-KillSignal=SIGTERM
 
 [Install]
 WantedBy=multi-user.target

models.example.toml

@@ -6,7 +6,7 @@
 
 [[models]]
 id = "your-org/large-model"
-harness = "candle"
+harness = "mistralrs"
 quant = "Q4_K_M"
 vram_mb = 19000
 min_devices = 2
@@ -15,7 +15,7 @@ pinned_on = ["gpu-large"]
 
 [[models]]
 id = "your-org/medium-model"
-harness = "candle"
+harness = "mistralrs"
 quant = "Q6_K"
 vram_mb = 12000
 min_devices = 1
@@ -23,7 +23,7 @@ pinned_on = ["gpu-medium"]
 
 [[models]]
 id = "your-org/embedding-model"
-harness = "candle"
+harness = "mistralrs"
 quant = "Q8_0"
 vram_mb = 8000
 min_devices = 1

neuron.example.toml

@@ -3,38 +3,14 @@
 # Copy to /etc/neuron/neuron.toml and adjust for your environment.
 #
 # Environment variable overrides use NEURON_ prefix with __ separators:
-#   NEURON_PORT=13131
+#   NEURON_PORT=9090
 
-port = 13131
+port = 9090
 
 # -- Harnesses ---------------------------------------------------------------
-# Each [[harnesses]] entry enables an inference engine. Currently only
+# Each [[harnesses]] entry declares an inference engine managed by neuron.
-# "candle" is supported — it runs in-process and uses huggingface/candle
-# for inference on local CUDA devices (or CPU when CUDA is unavailable).
 
 [[harnesses]]
-name = "candle"
+name = "mistralrs"
-
+endpoint = "http://localhost:8080"
-# -- Candle harness settings -------------------------------------------------
+systemd_unit = "mistralrs.service"
-# Optional tuning for the candle harness.
-
-[harness.candle]
-# HuggingFace cache directory for model weights. When unset, hf-hub's
-# default (~/.cache/huggingface) is used.
-# hf_cache = "/var/lib/neuron/hf-cache"
-
-# -- Default models ----------------------------------------------------------
-# Models listed here are loaded automatically when the neuron service
-# activates. Loading is sequential — a slow or failing entry doesn't
-# block the rest of the fleet, but it does push out the time before
-# neuron starts serving HTTP, so keep the list short. Operators can
-# load additional models on demand via POST /models/load.
-#
-# Make sure data/neuron.service's TimeoutStartSec is generous enough to
-# cover the slowest entry's first-time download + materialisation.
-
-# [[default_models]]
-# model_id = "Qwen/Qwen3-0.6B-GGUF"
-# harness = "candle"
-# quant = "Q4_K_M"
-# devices = [0]

neuron.spec

@@ -1,10 +1,7 @@
-Name:           helexa-neuron
+Name:           neuron
-Version:        0.1.16
+Version:        0.1.8
 Release:        1%{?dist}
 Summary:        Per-node GPU discovery and harness management daemon for cortex
-# Package name disambiguates from Fedora's existing "neuron" package
-# (NEURON neural simulation environment from Yale). Binary, systemd
-# unit, and system user are still called "neuron" for brevity.
 
 License:        GPL-3.0-or-later
 URL:            https://git.lair.cafe/helexa/cortex
@@ -24,7 +21,6 @@ BuildRequires:  systemd-rpm-macros
 
 Requires(pre):  shadow-utils
 Requires:       systemd
-Requires:       firewalld-filesystem
 
 # systemd-rpm-macros ships a unit dep generator that parses User=/Group=
 # from our .service file and emits Requires: user(neuron)/group(neuron).
@@ -37,9 +33,8 @@ Provides:       user(neuron)
 
 %description
 Neuron is a per-node daemon for cortex inference clusters. It discovers
-local GPU hardware via nvidia-smi, runs in-process inference via
+local GPU hardware via nvidia-smi, manages inference harnesses (mistral.rs,
-huggingface/candle, and exposes an HTTP API for model lifecycle
+llama.cpp), and exposes an HTTP API for model lifecycle management.
-management (load, unload, list, inference endpoint).
 
 %prep
 %autosetup
@@ -60,7 +55,6 @@ cargo build --release -p neuron
 install -Dm755 target/release/neuron %{buildroot}%{_bindir}/neuron
 install -Dm644 data/neuron.service %{buildroot}%{_unitdir}/neuron.service
 install -Dm644 data/neuron-sysusers.conf %{buildroot}%{_sysusersdir}/neuron.conf
-install -Dm644 data/neuron-firewalld.xml %{buildroot}%{_prefix}/lib/firewalld/services/helexa-neuron.xml
 install -dm755 %{buildroot}%{_sysconfdir}/neuron
 install -Dm644 neuron.example.toml %{buildroot}%{_sysconfdir}/neuron/neuron.toml
 
@@ -82,20 +76,9 @@ install -Dm644 neuron.example.toml %{buildroot}%{_sysconfdir}/neuron/neuron.toml
 %{_bindir}/neuron
 %{_unitdir}/neuron.service
 %{_sysusersdir}/neuron.conf
-%{_prefix}/lib/firewalld/services/helexa-neuron.xml
 %dir %{_sysconfdir}/neuron
 %config(noreplace) %{_sysconfdir}/neuron/neuron.toml
 
 %changelog
-* Thu Apr 16 2026 Gitea Actions <actions@git.lair.cafe> - 0.1.16-1
-- chore: ignore local deploy script
-- chore: move default ports out of common-collision ranges
-- ci: drop actions/cache for cargo registry and target
-
-* Thu Apr 16 2026 Gitea Actions <actions@git.lair.cafe> - 0.1.14-1
-- ci: publish both packages to a single helexa/helexa COPR project
-- fix(rpm): rename neuron package to helexa-neuron
-- ci: commit generated %changelog entries back to main
-
 * Wed Apr 15 2026 Rob Thijssen <grenade@rob.tn> - 0.1.0-1
 - Initial package

rpm/cortex-prerelease.spec

@@ -1,102 +0,0 @@
-# Prebuilt-binary spec for cortex.
-#
-# Unlike cortex.spec (which builds from source via cargo), this spec
-# wraps a pre-built `cortex` binary produced by an upstream CI job and
-# packages it for rpm.lair.cafe. The %build phase is a no-op.
-#
-# Required defines at rpmbuild time:
-#   cortex_version    e.g. "0.1.16"
-#   cortex_prerelease e.g. "0.1.20260518gitabcdef0"   (used as Release)
-
-%global _build_id_links none
-%global debug_package %{nil}
-%global __strip /usr/bin/true
-
-%{!?cortex_version: %global cortex_version 0.0.0}
-%if 0%{?cortex_prerelease:1}
-%global cortex_release %{cortex_prerelease}
-%else
-%global cortex_release 1
-%endif
-
-Name:           cortex
-Version:        %{cortex_version}
-Release:        %{cortex_release}%{?dist}
-Summary:        Inference gateway for multi-node GPU clusters (prebuilt)
-
-License:        GPL-3.0-or-later
-URL:            https://git.lair.cafe/helexa/cortex
-
-Source0:        cortex
-Source1:        cortex.service
-Source2:        cortex-sysusers.conf
-Source3:        cortex-firewalld.xml
-Source4:        cortex.example.toml
-Source5:        models.example.toml
-Source6:        LICENSE
-
-ExclusiveArch:  x86_64
-
-Requires(pre):  shadow-utils
-Requires:       systemd
-Requires:       firewalld-filesystem
-
-Provides:       user(cortex)
-
-%description
-Cortex is a Rust reverse-proxy that sits in front of multiple neuron
-inference daemons and presents a unified OpenAI and Anthropic
-compatible API surface.
-
-This package wraps a binary built upstream in CI; the source-build
-spec (cortex.spec) remains available for stable releases.
-
-%prep
-cp %{SOURCE0} ./cortex
-cp %{SOURCE1} .
-cp %{SOURCE2} .
-cp %{SOURCE3} .
-cp %{SOURCE4} .
-cp %{SOURCE5} .
-cp %{SOURCE6} .
-
-%build
-# Already built in the upstream CI build job.
-
-%install
-install -Dm755 cortex %{buildroot}%{_bindir}/cortex
-install -Dm644 cortex.service %{buildroot}%{_unitdir}/cortex.service
-install -Dm644 cortex-sysusers.conf %{buildroot}%{_sysusersdir}/cortex.conf
-install -Dm644 cortex-firewalld.xml %{buildroot}%{_prefix}/lib/firewalld/services/cortex.xml
-install -dm755 %{buildroot}%{_sysconfdir}/cortex
-install -Dm644 cortex.example.toml %{buildroot}%{_sysconfdir}/cortex/cortex.toml
-install -Dm644 models.example.toml %{buildroot}%{_sysconfdir}/cortex/models.toml
-
-%pre
-getent group cortex >/dev/null || groupadd -r cortex
-getent passwd cortex >/dev/null || \
-    useradd -r -g cortex -d /var/lib/cortex -s /sbin/nologin \
-        -c "Cortex inference gateway" cortex
-
-%post
-%systemd_post cortex.service
-
-%preun
-%systemd_preun cortex.service
-
-%postun
-%systemd_postun_with_restart cortex.service
-
-%files
-%license LICENSE
-%{_bindir}/cortex
-%{_unitdir}/cortex.service
-%{_sysusersdir}/cortex.conf
-%{_prefix}/lib/firewalld/services/cortex.xml
-%dir %{_sysconfdir}/cortex
-%config(noreplace) %{_sysconfdir}/cortex/cortex.toml
-%config(noreplace) %{_sysconfdir}/cortex/models.toml
-
-%changelog
-* Mon May 18 2026 Gitea Actions <actions@git.lair.cafe> - %{cortex_version}-%{cortex_release}
-- Prerelease build from upstream CI binary.

rpm/helexa-neuron-prerelease.spec

@@ -1,122 +0,0 @@
-# Prebuilt-binary spec for helexa-neuron flavoured by CUDA compute capability.
-#
-# Unlike helexa-neuron.spec (which builds from source via cargo), this
-# spec wraps a pre-built `neuron-{flavour}` binary produced by an
-# upstream CI job and packages it for rpm.lair.cafe. The %build phase
-# is a no-op.
-#
-# Required defines at rpmbuild time:
-#   neuron_version    e.g. "0.1.16"
-#   neuron_flavour    e.g. "ada", "blackwell"  — matches the CI build
-#                     matrix's compute_cap label.
-#   neuron_prerelease e.g. "0.1.20260518gitabcdef0"   (used as Release)
-#
-# One flavour can be installed at a time on a given host; flavour
-# packages Conflict with each other.
-
-%global _build_id_links none
-%global debug_package %{nil}
-%global __strip /usr/bin/true
-
-%{!?neuron_version: %global neuron_version 0.0.0}
-%{!?neuron_flavour: %global neuron_flavour blackwell}
-%if 0%{?neuron_prerelease:1}
-%global neuron_release %{neuron_prerelease}
-%else
-%global neuron_release 1
-%endif
-
-Name:           helexa-neuron-%{neuron_flavour}
-Version:        %{neuron_version}
-Release:        %{neuron_release}%{?dist}
-Summary:        Per-node GPU inference daemon (candle, %{neuron_flavour} flavour)
-
-License:        GPL-3.0-or-later
-URL:            https://git.lair.cafe/helexa/cortex
-
-Source0:        neuron-%{neuron_flavour}
-Source1:        neuron.service
-Source2:        neuron-sysusers.conf
-Source3:        neuron-firewalld.xml
-Source4:        neuron.example.toml
-Source5:        LICENSE
-
-ExclusiveArch:  x86_64
-
-# Binary links against the CUDA runtime, cuDNN, NCCL, etc. Suppress
-# auto-detected exact soname deps — users may have CUDA from various
-# sources (rpmfusion, nvidia-direct) at different compatible versions;
-# a runtime dlopen failure surfaces a clearer error than rpm dep
-# resolution would.
-%global __requires_exclude ^lib(cuda|cudart|cudnn|cublas|cublasLt|curand|nvrtc|nccl)
-
-Requires(pre):  shadow-utils
-Requires:       systemd
-Requires:       firewalld-filesystem
-
-Provides:       helexa-neuron = %{neuron_version}-%{neuron_release}
-Provides:       user(neuron)
-
-# Mutual exclusion across flavours and the source-build variant.
-Conflicts:      helexa-neuron
-Conflicts:      helexa-neuron-ada
-Conflicts:      helexa-neuron-ampere
-Conflicts:      helexa-neuron-blackwell
-# (The Conflicts: with self is filtered by rpm at install time.)
-
-%description
-Neuron is the per-node daemon for cortex inference clusters. It
-discovers local GPU hardware via nvidia-smi, runs in-process
-inference via huggingface/candle, and exposes an HTTP API for model
-lifecycle management (load, unload, list, inference endpoint).
-
-This is the %{neuron_flavour} flavour, built for that CUDA compute
-capability. Install the flavour matching the GPUs on this host.
-
-%prep
-cp %{SOURCE0} ./neuron
-cp %{SOURCE1} .
-cp %{SOURCE2} .
-cp %{SOURCE3} .
-cp %{SOURCE4} .
-cp %{SOURCE5} .
-
-%build
-# Already built in the upstream CI build job (with --features cuda).
-
-%install
-install -Dm755 neuron %{buildroot}%{_bindir}/neuron
-install -Dm644 neuron.service %{buildroot}%{_unitdir}/neuron.service
-install -Dm644 neuron-sysusers.conf %{buildroot}%{_sysusersdir}/neuron.conf
-install -Dm644 neuron-firewalld.xml %{buildroot}%{_prefix}/lib/firewalld/services/helexa-neuron.xml
-install -dm755 %{buildroot}%{_sysconfdir}/neuron
-install -Dm644 neuron.example.toml %{buildroot}%{_sysconfdir}/neuron/neuron.toml
-
-%pre
-getent group neuron >/dev/null || groupadd -r neuron
-getent passwd neuron >/dev/null || \
-    useradd -r -g neuron -d /var/lib/neuron -s /sbin/nologin \
-        -G video,render \
-        -c "Neuron GPU node daemon" neuron
-
-%post
-%systemd_post neuron.service
-
-%preun
-%systemd_preun neuron.service
-
-%postun
-%systemd_postun_with_restart neuron.service
-
-%files
-%license LICENSE
-%{_bindir}/neuron
-%{_unitdir}/neuron.service
-%{_sysusersdir}/neuron.conf
-%{_prefix}/lib/firewalld/services/helexa-neuron.xml
-%dir %{_sysconfdir}/neuron
-%config(noreplace) %{_sysconfdir}/neuron/neuron.toml
-
-%changelog
-* Mon May 18 2026 Gitea Actions <actions@git.lair.cafe> - %{neuron_version}-%{neuron_release}
-- Prerelease build from upstream CI binary (%{neuron_flavour} flavour).

rpm/rpmmacros

@@ -1 +0,0 @@
-%_openpgp_sign_id @GPG_NAME@

script/deploy.sh

@@ -1,195 +0,0 @@
-#!/bin/env bash
-#
-# Rolling deploy across the helexa fleet, driven by asset/manifest.yml.
-# Installs / upgrades cortex on the gateway host and the appropriate
-# helexa-neuron-<flavour> package on each neuron host, then restarts
-# their services.
-
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-REPO_DIR="$(cd "${SCRIPT_DIR}/.." && pwd)"
-MANIFEST="${REPO_DIR}/asset/manifest.yml"
-
-if [[ ! -f "${MANIFEST}" ]]; then
-    echo "fatal: manifest not found at ${MANIFEST}" >&2
-    exit 1
-fi
-
-# Parse the manifest with yq. NOTE: this expects the pip-installed yq
-# (a jq wrapper using jq syntax) — `pip install yq`. The Fedora rpm
-# `yq` is mikefarah/yq and uses different (yaml-native) syntax; if a
-# host has that one instead these queries will fail.
-cortex_host=$(yq -r '.cortex.host' "${MANIFEST}")
-
-# Emit one TAB-separated 'host\tflavour' line per neuron.
-mapfile -t neuron_entries < <(
-    yq -r '.neurons[] | .host + "\t" + .flavour' "${MANIFEST}"
-)
-
-# Return the installed package's "version-release" string, or
-# "(not installed)" when rpm reports the package as absent. Capture
-# rpm's output into a variable so its "package X is not installed"
-# stdout message (rpm writes that to stdout, not stderr, when -q fails)
-# doesn't leak into the result.
-installed_nvr() {
-    local host="$1" pkg="$2"
-    local nvr
-    if nvr=$(ssh "${host}" "rpm -q --qf '%{version}-%{release}' ${pkg} 2>/dev/null"); then
-        echo "${nvr}"
-    else
-        echo "(not installed)"
-    fi
-}
-
-# Ensure the rpm.lair.cafe unstable repo is configured AND enabled on
-# the remote host.
-#
-# The upstream .repo file at https://rpm.lair.cafe/lair-cafe-unstable.repo
-# ships with `enabled=0` so a host that just fetched it won't start
-# pulling unstable packages by accident. We have to explicitly flip
-# enabled=1 via `dnf config-manager setopt`. Both addrepo and setopt
-# are idempotent.
-#
-# Non-fatal — if either step fails the subsequent `dnf install` will
-# surface a clearer diagnostic on its own.
-ensure_lair_repo() {
-    local host="$1"
-    if ! ssh "${host}" "test -f /etc/yum.repos.d/lair-cafe-unstable.repo" 2>/dev/null; then
-        echo "[${host}] adding rpm.lair.cafe unstable repo"
-        if ! ssh "${host}" sudo dnf config-manager addrepo \
-            --from-repofile=https://rpm.lair.cafe/lair-cafe-unstable.repo \
-            >/dev/null 2>&1; then
-            echo "[${host}] WARNING: failed to add lair.cafe repo file (proceeding anyway)"
-            return 0
-        fi
-    fi
-    # The .repo file ships enabled=0; flip it on. Cheap, idempotent.
-    if ! ssh "${host}" sudo dnf config-manager setopt \
-        lair-cafe-unstable.enabled=1 >/dev/null 2>&1; then
-        echo "[${host}] WARNING: failed to enable lair-cafe-unstable (proceeding anyway)"
-    fi
-}
-
-# True when the named package needs to be installed or upgraded on the
-# remote host — either it's not present, or a newer version exists in
-# the repo. False only when the installed version is current.
-#
-# `dnf check-update <pkg>` returns 0 when the package isn't installed
-# at all (there's nothing to update), so we have to probe with rpm -q
-# first to distinguish "absent" from "current". Other dnf failures
-# collapse into "needs update" so the subsequent install step surfaces
-# the real diagnostic rather than this check swallowing it.
-needs_update() {
-    local host="$1" pkg="$2"
-    # Not installed → needs work.
-    if ! ssh "${host}" "rpm -q ${pkg}" >/dev/null 2>&1; then
-        return 0
-    fi
-    # Installed; ask dnf whether the repo has something newer.
-    if ssh "${host}" sudo dnf check-update --refresh -q "${pkg}" >/dev/null 2>&1; then
-        return 1
-    else
-        return 0
-    fi
-}
-
-# ---------------------------------------------------------------------------
-# cortex (gateway)
-# ---------------------------------------------------------------------------
-
-ensure_lair_repo "${cortex_host}"
-cortex_nvr=$(installed_nvr "${cortex_host}" cortex)
-if needs_update "${cortex_host}" cortex; then
-    echo "[${cortex_host}] cortex update available (current: ${cortex_nvr})"
-    # Stop the service only if the unit file exists — fresh installs
-    # don't have it, and `systemctl stop` on a missing unit returns
-    # non-zero, which would otherwise short-circuit the install branch
-    # under set -e.
-    if ssh "${cortex_host}" "[ ! -f /usr/lib/systemd/system/cortex.service ] || sudo systemctl stop cortex.service"; then
-        echo "[${cortex_host}] stopped cortex service"
-        if dnf_output=$(ssh "${cortex_host}" sudo dnf install --refresh --allowerasing -y cortex 2>&1); then
-            cortex_nvr=$(installed_nvr "${cortex_host}" cortex)
-            echo "[${cortex_host}] installed/upgraded cortex to ${cortex_nvr}"
-        else
-            echo "[${cortex_host}] failed to install/upgrade cortex:"
-            echo "${dnf_output}" | sed "s/^/[${cortex_host}]   /"
-        fi
-    else
-        echo "[${cortex_host}] failed to stop cortex service"
-    fi
-else
-    echo "[${cortex_host}] cortex is up to date (${cortex_nvr})"
-    ssh "${cortex_host}" sudo systemctl stop cortex.service || true
-fi
-
-# Sync cortex.toml whether the package was upgraded or not — the config
-# can change without a package bump.
-if rsync \
-    --archive \
-    --compress \
-    --rsync-path 'sudo rsync' \
-    --chown root:root \
-    --chmod 644 \
-    "${REPO_DIR}/cortex.toml" \
-    "${cortex_host}:/etc/cortex/cortex.toml"; then
-    echo "[${cortex_host}] sync'd cortex.toml"
-else
-    echo "[${cortex_host}] failed to sync cortex.toml"
-fi
-
-ssh "${cortex_host}" sudo systemctl daemon-reload
-if ssh "${cortex_host}" systemctl is-active --quiet cortex.service; then
-    echo "[${cortex_host}] cortex service is active"
-elif ssh "${cortex_host}" sudo systemctl start cortex.service; then
-    echo "[${cortex_host}] started cortex service"
-else
-    echo "[${cortex_host}] failed to start cortex service"
-fi
-
-# ---------------------------------------------------------------------------
-# neuron (per-host, flavour from manifest)
-# ---------------------------------------------------------------------------
-
-for entry in "${neuron_entries[@]}"; do
-    IFS=$'\t' read -r neuron_host neuron_flavour <<< "${entry}"
-    package="helexa-neuron-${neuron_flavour}"
-
-    ensure_lair_repo "${neuron_host}"
-    neuron_nvr=$(installed_nvr "${neuron_host}" "${package}")
-    if needs_update "${neuron_host}" "${package}"; then
-        echo "[${neuron_host}] ${package} update available (current: ${neuron_nvr})"
-        if ssh "${neuron_host}" "[ ! -f /usr/lib/systemd/system/neuron.service ] || sudo systemctl stop neuron.service"; then
-            echo "[${neuron_host}] stopped neuron service"
-            # --allowerasing lets dnf swap out a previously-installed
-            # bare helexa-neuron or a different flavour without manual
-            # intervention. The Conflicts: clauses in the spec ensure
-            # only one flavour is ever resident.
-            if dnf_output=$(ssh "${neuron_host}" sudo dnf install --refresh --allowerasing -y "${package}" 2>&1); then
-                neuron_nvr=$(installed_nvr "${neuron_host}" "${package}")
-                echo "[${neuron_host}] installed/upgraded ${package} to ${neuron_nvr}"
-                # Ensure firewalld allows neuron port
-                ssh "${neuron_host}" "sudo firewall-cmd --query-service=helexa-neuron --quiet 2>/dev/null || sudo firewall-cmd --add-service=helexa-neuron --permanent && sudo firewall-cmd --reload" 2>/dev/null || true
-                if ssh "${neuron_host}" "sudo systemctl daemon-reload && sudo systemctl start neuron.service"; then
-                    echo "[${neuron_host}] started neuron service"
-                else
-                    echo "[${neuron_host}] failed to start neuron service"
-                fi
-            else
-                echo "[${neuron_host}] failed to install ${package}:"
-                echo "${dnf_output}" | sed "s/^/[${neuron_host}]   /"
-            fi
-        else
-            echo "[${neuron_host}] failed to stop neuron service"
-        fi
-    else
-        echo "[${neuron_host}] ${package} is up to date (${neuron_nvr})"
-        if ssh "${neuron_host}" systemctl is-active --quiet neuron.service; then
-            echo "[${neuron_host}] neuron service is active"
-        elif ssh "${neuron_host}" sudo systemctl start neuron.service; then
-            echo "[${neuron_host}] started neuron service"
-        else
-            echo "[${neuron_host}] failed to start neuron service"
-        fi
-    fi
-done

script/generate-packages-json.py

@@ -1,154 +0,0 @@
-#!/usr/bin/env python3
-"""Parse RPM repodata and emit a packages.json manifest for the UI."""
-
-import argparse
-import gzip
-import json
-import os
-import subprocess
-import sys
-import xml.etree.ElementTree as ET
-from datetime import datetime, timezone
-
-RPM_NS = "http://linux.duke.edu/metadata/common"
-OTHER_NS = "http://linux.duke.edu/metadata/other"
-REPO_NS = "http://linux.duke.edu/metadata/repo"
-
-
-def find_repodata_file(repodata_dir, data_type):
-    """Read repomd.xml and return the path to a specific data type's file."""
-    repomd_path = os.path.join(repodata_dir, "repomd.xml")
-    tree = ET.parse(repomd_path)
-    root = tree.getroot()
-
-    for data in root.findall(f"{{{REPO_NS}}}data"):
-        if data.get("type") == data_type:
-            location = data.find(f"{{{REPO_NS}}}location")
-            if location is not None:
-                href = location.get("href", "")
-                return os.path.join(os.path.dirname(repodata_dir), href)
-
-    return None
-
-
-def open_compressed(path):
-    """Open a gzip or zstd compressed file for reading."""
-    if path.endswith(".zst"):
-        result = subprocess.run(
-            ["zstdcat", path], capture_output=True, check=True
-        )
-        import io
-        return io.BytesIO(result.stdout)
-    else:
-        return gzip.open(path, "rb")
-
-
-def parse_primary(repodata_dir):
-    """Parse primary.xml.{gz,zst} and return package metadata."""
-    path = find_repodata_file(repodata_dir, "primary")
-    if not path:
-        print("error: primary metadata not found in repomd.xml", file=sys.stderr)
-        sys.exit(1)
-
-    packages = {}
-    with open_compressed(path) as f:
-        tree = ET.parse(f)
-
-    for pkg in tree.getroot().findall(f"{{{RPM_NS}}}package"):
-        if pkg.get("type") != "rpm":
-            continue
-
-        name = pkg.findtext(f"{{{RPM_NS}}}name", "")
-        version_el = pkg.find(f"{{{RPM_NS}}}version")
-        ver = version_el.get("ver", "") if version_el is not None else ""
-        rel = version_el.get("rel", "") if version_el is not None else ""
-        arch = pkg.findtext(f"{{{RPM_NS}}}arch", "")
-
-        size_el = pkg.find(f"{{{RPM_NS}}}size")
-        size = int(size_el.get("package", "0")) if size_el is not None else 0
-
-        time_el = pkg.find(f"{{{RPM_NS}}}time")
-        build_time = int(time_el.get("build", "0")) if time_el is not None else 0
-
-        location_el = pkg.find(f"{{{RPM_NS}}}location")
-        filename = os.path.basename(location_el.get("href", "")) if location_el is not None else ""
-
-        key = f"{name}-{ver}-{rel}"
-        packages[key] = {
-            "name": name,
-            "version": ver,
-            "release": rel,
-            "arch": arch,
-            "summary": pkg.findtext(f"{{{RPM_NS}}}summary", ""),
-            "size": size,
-            "buildTime": build_time,
-            "rpmFilename": filename,
-            "changelog": [],
-        }
-
-    return packages
-
-
-def parse_other(repodata_dir, packages):
-    """Parse other.xml.gz and attach changelog entries to packages."""
-    path = find_repodata_file(repodata_dir, "other")
-    if not path:
-        return
-
-    with open_compressed(path) as f:
-        tree = ET.parse(f)
-
-    for pkg in tree.getroot().findall(f"{{{OTHER_NS}}}package"):
-        name = pkg.get("name", "")
-        version_el = pkg.find(f"{{{OTHER_NS}}}version")
-        ver = version_el.get("ver", "") if version_el is not None else ""
-        rel = version_el.get("rel", "") if version_el is not None else ""
-        key = f"{name}-{ver}-{rel}"
-
-        if key not in packages:
-            continue
-
-        for entry in pkg.findall(f"{{{OTHER_NS}}}changelog"):
-            packages[key]["changelog"].append({
-                "author": entry.get("author", ""),
-                "date": int(entry.get("date", "0")),
-                "text": (entry.text or "").strip(),
-            })
-
-
-def main():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "--repodata-dir",
-        required=True,
-        help="path to the repodata/ directory",
-    )
-    parser.add_argument(
-        "--output",
-        required=True,
-        help="path to write packages.json",
-    )
-    parser.add_argument(
-        "--base-url",
-        required=True,
-        help="public base URL for the repo (e.g. https://rpm.lair.cafe/fedora/43/x86_64)",
-    )
-    args = parser.parse_args()
-
-    packages = parse_primary(args.repodata_dir)
-    parse_other(args.repodata_dir, packages)
-
-    manifest = {
-        "generated": datetime.now(timezone.utc).isoformat(),
-        "baseUrl": args.base_url,
-        "packages": list(packages.values()),
-    }
-
-    with open(args.output, "w") as f:
-        json.dump(manifest, f, indent=2)
-
-    print(f"wrote {len(packages)} packages to {args.output}")
-
-
-if __name__ == "__main__":
-    main()

script/validate-neuron.sh

@@ -1,141 +0,0 @@
-#!/bin/env bash
-#
-# End-to-end smoke test for a deployed neuron.
-#
-# Confirms the daemon is reachable, loads a small public Qwen3 GGUF,
-# fires a reasoning probe at /v1/chat/completions, and prints the
-# answer. Used to validate the candle harness on a real GPU host
-# before trusting it for production traffic, and as a regression test
-# after pushing new neuron builds.
-#
-# Usage:
-#   script/validate-neuron.sh [host] [model_id] [quant]
-#
-# Defaults:
-#   host     = beast.hanzalova.internal
-#   model_id = unsloth/Qwen3-0.6B-GGUF  (official Qwen3-*-GGUF repos
-#              ship Q8_0 only; unsloth's mirror ships the full Q-spectrum
-#              including Q4_K_M)
-#   quant    = Q4_K_M
-
-set -euo pipefail
-
-HOST="${1:-beast.hanzalova.internal}"
-MODEL_ID="${2:-unsloth/Qwen3-0.6B-GGUF}"
-QUANT="${3:-Q4_K_M}"
-PORT="${NEURON_PORT:-13131}"
-BASE="http://${HOST}:${PORT}"
-
-# Reasoning probe — concrete, low-temperature answer that small models
-# can still get right. "Paris" is a strong signal of basic competence
-# beyond gibberish.
-PROBE_PROMPT='What is the capital of France? Respond with the city name only, no punctuation.'
-EXPECT_SUBSTR='Paris'
-MAX_TOKENS=32
-
-# /models/load is synchronous — neuron blocks the response until the
-# hf-hub download + GGUF parse + tensor materialisation is done. A
-# fresh 0.6B-Q4_K_M is ~400 MB; on a slow link or cold cache that's
-# easily a minute. Pick a generous ceiling.
-LOAD_TIMEOUT=600
-INFER_TIMEOUT=120
-
-say() { printf '[%s] %s\n' "${HOST}" "$*"; }
-die() { say "FAIL: $*"; exit 1; }
-
-probe_health() {
-    curl --silent --fail --max-time 5 "${BASE}/health" >/dev/null \
-        || die "neuron not reachable at ${BASE}/health"
-}
-
-list_loaded_ids() {
-    curl --silent --fail "${BASE}/models" | yq -r '.[].id'
-}
-
-is_loaded() {
-    list_loaded_ids 2>/dev/null | grep -Fxq "${MODEL_ID}"
-}
-
-trigger_load() {
-    say "POST /models/load ${MODEL_ID} (quant=${QUANT}, device=[0])"
-    say "  (synchronous; may take a minute on first run while HF downloads)"
-    local payload
-    payload=$(cat <<EOF
-{
-    "model_id": "${MODEL_ID}",
-    "harness": "candle",
-    "quant": "${QUANT}",
-    "devices": [0]
-}
-EOF
-    )
-    # --write-out captures the response code on a separate line so we
-    # can surface a real diagnostic instead of relying on --fail.
-    local resp http_code body
-    resp=$(curl --silent --show-error --max-time "${LOAD_TIMEOUT}" \
-        --write-out '\n__HTTP__%{http_code}' \
-        -X POST "${BASE}/models/load" \
-        -H 'content-type: application/json' \
-        --data "${payload}") || die "curl /models/load failed: $?"
-    http_code=$(echo "${resp}" | grep -oP '(?<=__HTTP__)\d+$' | tail -1)
-    body=$(echo "${resp}" | sed '$ s/__HTTP__.*$//')
-    if [[ "${http_code}" != "200" ]]; then
-        die "load returned HTTP ${http_code}: ${body}"
-    fi
-    say "load returned ${http_code}: ${body}"
-}
-
-run_probe() {
-    say "POST /v1/chat/completions (probe: ${PROBE_PROMPT})"
-    local payload
-    payload=$(yq -n -c \
-        --arg model "${MODEL_ID}" \
-        --arg content "${PROBE_PROMPT}" \
-        --argjson tokens "${MAX_TOKENS}" \
-        '{
-            model: $model,
-            messages: [{role: "user", content: $content}],
-            temperature: 0.1,
-            max_tokens: $tokens
-        }')
-    local resp http_code body
-    resp=$(curl --silent --show-error --max-time "${INFER_TIMEOUT}" \
-        --write-out '\n__HTTP__%{http_code}' \
-        -X POST "${BASE}/v1/chat/completions" \
-        -H 'content-type: application/json' \
-        --data "${payload}") || die "curl /v1/chat/completions failed: $?"
-    http_code=$(echo "${resp}" | grep -oP '(?<=__HTTP__)\d+$' | tail -1)
-    body=$(echo "${resp}" | sed '$ s/__HTTP__.*$//')
-    if [[ "${http_code}" != "200" ]]; then
-        die "inference returned HTTP ${http_code}: ${body}"
-    fi
-    echo "${body}"
-}
-
-say "validating neuron at ${BASE}"
-probe_health
-say "/health OK"
-
-if is_loaded; then
-    say "${MODEL_ID} already loaded"
-else
-    trigger_load
-fi
-
-raw=$(run_probe)
-echo "---"
-echo "${raw}" | yq -r '.'
-echo "---"
-
-content=$(echo "${raw}" | yq -r '.choices[0].message.content // empty')
-if [[ -z "${content}" ]]; then
-    die "no content in chat completion response"
-fi
-say "assistant said: ${content}"
-
-if echo "${content}" | grep -qiF "${EXPECT_SUBSTR}"; then
-    say "PASS — response contains expected substring '${EXPECT_SUBSTR}'"
-    exit 0
-else
-    die "response did not contain '${EXPECT_SUBSTR}'"
-fi