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Ettore Di Giacinto 40c325c7d0 docs: add RKLLM Rockchip NPU integration
Document how to connect LocalAI to the upstream RKLLM OpenAI-compatible server through cloud-proxy, including supported SoCs and current limitations.

Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-08-10 10:10:23 +00:00
671 changed files with 6789 additions and 50503 deletions

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-34
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@@ -49,40 +49,6 @@ AI agents MUST NOT add `Co-Authored-By` trailers for themselves either.
A human reviewer owns the contribution; the AI's involvement is recorded
via `Assisted-by` (see below).
### Exception: automation operated by a maintainer
The rule above addresses the common case, an AI assistant helping a human
contributor who then signs off. It does not fit automation that a
maintainer runs themselves, which opens pull requests with no human
submitter to sign. Applied literally there, nothing ever signs and the
DCO check blocks the pull request permanently.
A maintainer-operated bot MUST therefore add a `Signed-off-by` trailer
naming **the maintainer who operates it**, not the bot and not the model:
```
Assisted-by: Codex:gpt-5
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
```
This is not the AI certifying the DCO. The maintainer is, exactly as they
do for a commit they typed by hand: they configured the automation, they
own its output, and they take responsibility for it when they merge it.
The `Assisted-by` trailer still records that a model produced the code, so
the provenance trail is unchanged.
The exception is narrow and does not widen the rule for anyone else:
- It applies only to automation a LocalAI maintainer operates and whose
output that maintainer reviews before merge.
- The sign-off names a real person who accepts DCO responsibility.
- An AI assistant helping an outside contributor still MUST NOT sign off.
That contributor adds their own trailer.
- A bot MUST NOT sign off on behalf of anyone other than its operator, and
MUST NOT add a trailer for a contributor whose branch it pushes to. If
automation contributes to someone else's branch, it leaves the sign-off
to that contributor.
## Attribution
When AI tools contribute to LocalAI development, proper attribution helps
-52
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@@ -236,58 +236,6 @@ Use these HTTP status codes:
If your endpoint should be tracked for usage (token counts, request counts), add the `usageMiddleware` to its middleware chain. See `core/http/middleware/usage.go` and how it's applied in `routes/openai.go`.
## Control-plane database health metrics
In distributed mode the frontend registers three OpenTelemetry gauges over the
PostgreSQL control-plane database (`core/services/monitoring/control_plane_db.go`,
wired in `core/application/distributed.go`). They reach `/metrics` through the
same Prometheus exporter as the rest of the API metrics.
| Metric | Meaning | Page when |
|--------|---------|-----------|
| `localai_control_plane_oldest_xmin_age` | Transactions elapsed since the oldest snapshot any backend still holds | above a few million, and rising |
| `localai_control_plane_longest_transaction_seconds` | Age of the longest open transaction | above 3600 |
| `localai_control_plane_dead_tuple_ratio` | Dead tuples per live tuple, labelled by `table`, on `backend_nodes`, `node_models` and `gallery_operations` | sustained above ~10 on a small table |
A sustained high `localai_control_plane_oldest_xmin_age` is the one to page on.
While it grows, autovacuum can reclaim nothing anywhere in the database no
matter how often it runs, so the dead tuple ratio keeps climbing and a six-row
registry table can reach hundreds of megabytes. Tuning autovacuum does not help.
The fix is to find the transaction holding the horizon open and clear it:
```sql
SELECT pid, state, age(backend_xmin) AS xmin_age, now() - xact_start AS xact_age, query
FROM pg_stat_activity
WHERE backend_xmin IS NOT NULL
ORDER BY age(backend_xmin) DESC;
```
Then `pg_terminate_backend(pid)` on the offenders, and `VACUUM (VERBOSE)` the
bloated tables once the horizon has moved.
**A healthy-looking xmin age does not on its own prove the horizon is free.**
The gauge reads `pg_stat_activity`, which only sees live backends. Two other
things pin the very same horizon and are invisible there, so either one can hold
vacuum back while the gauge reads 0:
```sql
SELECT gid, prepared, database, transaction FROM pg_prepared_xacts;
SELECT slot_name, active, xmin, catalog_xmin FROM pg_replication_slots;
```
An orphaned prepared transaction is cleared with `ROLLBACK PREPARED '<gid>'`,
and a stale slot with `pg_drop_replication_slot('<slot_name>')`. Check both
before concluding that a bloated table has some other cause.
Sampling is scrape-driven behind a 30 second cache, so scrape frequency does not
translate into database load. Failed and timed-out samples cost the same interval
as successful ones, so a database that is already struggling is not retried on
every scrape. A failed sample reports the last good values rather than failing the
scrape, because these gauges matter most when the database is struggling. Before
the first successful sample the gauges are absent rather than zero, since a zero
xmin age would read as a healthy horizon: alert on `absent()` too if you need to
distinguish "healthy" from "never sampled".
## Advertising surfaces — where to register a new capability
Beyond routing and auth, LocalAI publishes its capability surface in **four independent places**. When you add an endpoint — especially one introducing a net-new capability like a new media type or a new auth-gated feature — you must update every relevant surface. These aren't optional: missing them means the endpoint works but is invisible to clients, admins, and the UI.
-50
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@@ -77,56 +77,6 @@ spectrum. **Metal (Darwin) only** - it is a no-op on CUDA/CPU. Enable with
budget). Gallery entries built on this: `deepseek-v4-flash-q4-ssd` (153 GB Flash
on a 128 GB Mac) and `deepseek-v4-pro-q2-ssd` (433 GB Pro, experimental).
## CUDA architecture (do not build without one)
`backend/cpp/ds4/Makefile` drives upstream's **object targets** directly
(`$(MAKE) -C ds4 ds4.o ds4_cuda.o ...`), which bypasses upstream's own guard:
its `cuda` target refuses to build unless `CUDA_ARCH` is set, and offers
`cuda-spark` (sm_121, DGX Spark / GB10) and `cuda-generic` (native) instead.
Built with no `-arch`, nvcc targets its default architecture and the kernels run
as JIT'd PTX. On GB10 that silently corrupted every prefill batch of >=128
tokens - the model emitted text unrelated to the prompt and never closed its
thinking block, so `content` came back empty - and cost close to two orders of
magnitude of prefill throughput (4.21 t/s vs 325.70 t/s, same box, same model).
Short prompts stayed correct, which is why it went unnoticed.
The Makefile therefore picks a gencode list from `CUDA_MAJOR_VERSION` (a build
arg the backend matrix already declares, forwarded by `Dockerfile.ds4`) and
`uname -m`, and passes it as `NVCC_ARCH_FLAGS` to the sub-make. Upstream's
`CUDA_ARCH` accepts a single value, so it cannot express the fat binary the
shipped images need; a command-line assignment beats its `:=`. An empty
`CUDA_MAJOR_VERSION` falls back to upstream's `native` for local developer
builds, and an unrecognised one is a hard error - no CI runner has a GPU, so a
silent `native` there is exactly the failure mode this guards against.
`DS4_CUDA_HAVE_MXF4` is deliberately unset: upstream defines it only for
single-arch sm_120/sm_121 builds and guards it with a plain `#ifdef` rather than
`__CUDA_ARCH__`, so it cannot be combined with older archs. It gates an optional
MXFP4 indexer fast path whose `#ifndef` branch returns 0, so omitting it costs
speed, not correctness.
### Verifying a build
Check which flags a configuration resolves to, without compiling anything:
```
make -C backend/cpp/ds4 BUILD_TYPE=cublas CUDA_MAJOR_VERSION=13 NATIVE=false \
--eval='show: ; @echo [$(DS4_ARCH_MAKEVARS)]' show
```
Do not use `make -n` for this: the recipe is `+$(MAKE) ...`, and the `+` prefix
makes it run even under `-n`.
Then exercise the failure mode itself against a built backend. It only appears
above one prefill batch, so the ordinary `predict` spec cannot catch it:
```
BACKEND_BINARY=$(pwd)/backend/cpp/ds4/package/run.sh \
BACKEND_TEST_MODEL_FILE=/path/to/ds4flash.gguf \
BACKEND_TEST_CAPS=health,load,predict,long_prefill \
go test -count=1 -timeout=30m -v ./tests/e2e-backends/...
```
## Build matrix
| Build | Where | Notes |
-2
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@@ -59,9 +59,7 @@ backend/rust/*/target
backend-images
local-backends
local-ai
.claude
.crush
.tools
protoc
tests
+1 -1
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@@ -5,7 +5,7 @@ This PR fixes #
**Notes for Reviewers**
**[Signed commits](../CONTRIBUTING.md#commit-messages)**
**[Signed commits](../CONTRIBUTING.md#signing-off-on-commits-developer-certificate-of-origin)**
- [ ] Yes, I signed my commits.
- [ ] Documentation updated (docs/content/) for user-facing changes, or not applicable
-13
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@@ -3754,19 +3754,6 @@ include:
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'hipblas'
cuda-major-version: ""
cuda-minor-version: ""
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-rocm-hipblas-stablediffusion-ggml'
runs-on: 'ubuntu-latest'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
skip-drivers: 'false'
backend: "stablediffusion-ggml"
dockerfile: "./backend/Dockerfile.golang"
context: "./"
ubuntu-version: '2404'
- build-type: 'sycl_f16'
cuda-major-version: ""
cuda-minor-version: ""
+10 -15
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@@ -3,9 +3,9 @@
# darwin (Apple Silicon) install path. The macOS/Metal build
# (backend/python/vllm/install.sh, Darwin branch) installs vllm-metal, which is
# version-locked to a specific vLLM source release. install.sh derives that vLLM
# version, and the wheel asset name, at build time from the pinned tag, so there
# is only ONE value to bump here -- mirroring bump_vllm_wheel.sh, which bumps the
# Linux cu130 wheel pin.
# version at build time from vllm-metal's own installer (`vllm_v=`) at the pinned
# tag, so there is only ONE value to bump here -- mirroring bump_vllm_wheel.sh,
# which bumps the Linux cu130 wheel pin.
#
# This deliberately tracks vllm-project/vllm-metal, NOT vllm-project/vllm: the
# darwin build can only use the exact vLLM version vllm-metal supports, so it may
@@ -23,24 +23,19 @@ if [ -z "$FILE" ] || [ -z "$REPO" ] || [ -z "$VAR" ]; then
exit 1
fi
# vllm-metal ships frequent .dev releases, flagged as prereleases, alongside the
# stable ones. /releases/latest skips the prereleases and returns the newest
# stable tag, which is what darwin should pin: upstream deletes and re-cuts .dev
# tags, and a pin to a deleted tag 404s the whole build.
# vllm-metal ships frequent dev releases, all flagged as non-prerelease, so
# /releases/latest returns the newest one (with its cp312 wheel asset).
LATEST_TAG=$(gh_curl -H "Accept: application/vnd.github+json" \
"https://api.github.com/repos/$REPO/releases/latest" \
| python3 -c "import json,sys; print(json.load(sys.stdin)['tag_name'])")
# The coupled vLLM release lives in .github/vllm-release-tag.commit at that tag
# (since vllm-metal 0.28); releases predating that file pinned it inline in their
# own install.sh. The extractor reads both forms.
NEW_VLLM_VERSION=$( { gh_curl \
"https://raw.githubusercontent.com/$REPO/$LATEST_TAG/.github/vllm-release-tag.commit" \
|| gh_curl "https://raw.githubusercontent.com/$REPO/$LATEST_TAG/install.sh"; } \
| "$(dirname "${BASH_SOURCE[0]}")/../scripts/lib/extract-vllm-metal-version.sh")
# The coupled vLLM source version lives in vllm-metal's installer at that tag.
NEW_VLLM_VERSION=$(gh_curl \
"https://raw.githubusercontent.com/$REPO/$LATEST_TAG/install.sh" \
| grep -oE 'vllm_v="[0-9]+\.[0-9]+\.[0-9]+"' | head -1 | cut -d'"' -f2)
if [ -z "$LATEST_TAG" ] || [ -z "$NEW_VLLM_VERSION" ]; then
echo "Could not resolve vllm-metal tag ($LATEST_TAG) or its vLLM version ($NEW_VLLM_VERSION)." >&2
echo "Could not resolve vllm-metal tag ($LATEST_TAG) or its vllm_v ($NEW_VLLM_VERSION)." >&2
exit 1
fi
-44
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@@ -1,44 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
python3 - <<'PY'
from pathlib import Path
home = Path("website/layouts/index.html").read_text()
css = Path("website/static/css/site.css").read_text()
install = Path("docs/content/getting-started/install.md").read_text()
containers = Path("docs/content/getting-started/containers.md").read_text()
def require(condition, message):
if not condition:
raise SystemExit(f"FAIL: {message}")
require("Drop-in replacement for most upstream APIs." in home,
"homepage must use the requested drop-in API heading")
require("Everything else plugs into LocalAI." not in home,
"old runtime heading must be removed")
require("When the engine we need" not in home,
"hero must describe user outcomes instead of team implementation")
require('href="mailto:contact@localai.io"' in home and "business" in home.lower(),
"homepage must provide a direct business contact action")
require(home.index('id="localai"') < home.index('id="proof-quotes"') < home.index('id="mission"'),
"headline testimonials must directly follow the runtime section")
require(home.count('id="proof-quotes"') == 1,
"headline testimonials must appear exactly once")
require('id="engines"' not in home and "Engines we build" not in home,
"homepage engine showcase must be removed")
require('href="/docs/installation/index.html"' in home,
"installation guide action must use the direct installation URL")
require('<iframe' in install and "youtube.com/embed/cMVNnlqwfw4" in install,
"installation page must embed the walkthrough video")
require("## Quick Start" not in install,
"installation landing page must not duplicate Quick Start")
for text in ("CUDA 12", "CUDA 13", "ROCm", "Intel", "Jetson", "Vulkan", "fallback"):
require(text.lower() in containers.lower(), f"GPU chooser must explain {text}")
require('class="sn__e"><a href="https://github.com/mudler/parakeet.cpp">parakeet.cpp</a>' in home,
"capability engine names must link to their repositories")
require(".pane{min-height:" in css.replace(" ", ""),
"all installation panes must have a fixed minimum height")
print("website review 143 source checks passed")
PY
+65 -1
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@@ -29,6 +29,10 @@ updates:
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/bark"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/common/template"
schedule:
@@ -51,10 +55,30 @@ updates:
ignore:
- dependency-name: "torch"
- dependency-name: "transformers"
- package-ecosystem: "pip"
directory: "/backend/python/exllama"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/exllama2"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/mamba"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/openvoice"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/rerankers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/sentencetransformers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/transformers"
schedule:
@@ -62,4 +86,44 @@ updates:
- package-ecosystem: "pip"
directory: "/backend/python/vllm"
schedule:
interval: "weekly"
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/chainlit"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/functions"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/langchain/langchainpy-localai-example"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/langchain-chroma"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/examples/streamlit-bot"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/k8sgpt"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/kubernetes"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/langchain"
schedule:
interval: "weekly"
- package-ecosystem: "gomod"
directory: "/examples/semantic-todo"
schedule:
interval: "weekly"
- package-ecosystem: "docker"
directory: "/examples/telegram-bot"
schedule:
interval: "weekly"
+3 -3
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@@ -166,7 +166,7 @@ jobs:
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update ${{ matrix.repository }}'
title: 'chore: :arrow_up: Update ${{ matrix.repository }} to `${{ steps.bump.outputs.commit }}`'
branch: "bump/${{ matrix.variable }}"
branch: "update/${{ matrix.variable }}"
body: ${{ steps.bump.outputs.message }}
signoff: true
@@ -203,7 +203,7 @@ jobs:
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update vllm-project/vllm cu130 wheel'
title: 'chore: :arrow_up: Update vllm-project/vllm cu130 wheel to `${{ steps.bump.outputs.commit }}`'
branch: "bump/VLLM_VERSION"
branch: "update/VLLM_VERSION"
body: ${{ steps.bump.outputs.message }}
signoff: true
@@ -241,6 +241,6 @@ jobs:
push-to-fork: ci-forks/LocalAI
commit-message: ':arrow_up: Update vllm-project/vllm-metal (darwin)'
title: 'chore: :arrow_up: Update vllm-metal (darwin) to `${{ steps.bump.outputs.commit }}`'
branch: "bump/VLLM_METAL_VERSION"
branch: "update/VLLM_METAL_VERSION"
body: ${{ steps.bump.outputs.message }}
signoff: true
+3 -4
View File
@@ -31,14 +31,13 @@ jobs:
messages: [
{
role: "system",
content: "Write a Discord message with a bullet point summary of the release notes. Keep the complete message under 1800 characters."
content: "Write a discord message with a bullet point summary of the release notes."
},
{
role: "user",
content: $input
}
],
max_tokens: 450
]
}')
# Send the request to LocalAI API
@@ -47,7 +46,7 @@ jobs:
-d "$json_payload")
# Extract the summary from the response
summary=$(printf '%s' "$response" | jq -er '.choices[0].message.content | strings | .[0:1800]')
summary=$(echo $response | jq -r '.choices[0].message.content')
# Print the summary
# -H "Authorization: Bearer $API_KEY" \
+9 -20
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@@ -14,7 +14,6 @@ on:
permissions:
contents: write
pull-requests: write
concurrency:
group: refresh-site-counters
@@ -31,25 +30,15 @@ jobs:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: ./.github/ci/refresh-site-counters.sh
- name: Show changes
- name: Commit only if something moved
run: |
if git diff --quiet -- website/data/stats.yaml; then
echo "counters unchanged"
else
git diff --unified=0 -- website/data/stats.yaml
echo "counters unchanged, nothing to commit"
exit 0
fi
- name: Create pull request when counters moved
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: "chore(website): refresh the counters"
title: "chore(website): refresh the counters"
body: |
Weekly refresh of the landing-page counters from the GitHub API.
This PR was created automatically by the `refresh-site-counters` workflow.
branch: update/site-counters
delete-branch: true
labels: automated
git diff --unified=0 -- website/data/stats.yaml
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
git add website/data/stats.yaml
git commit -m "chore(website): refresh the counters"
git push
-1
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@@ -526,7 +526,6 @@ jobs:
- name: Build llama-cpp backend image and run gRPC e2e tests
run: |
make test-extra-backend-llama-cpp
make test-extra-backend-llama-cpp-embeddings
tests-llama-cpp-grpc-transcription:
needs: detect-changes
if: needs.detect-changes.outputs.llama-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
+2 -18
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@@ -65,12 +65,6 @@ jobs:
- name: Test (with coverage gate)
run: |
PATH="$PATH:/root/go/bin" make --jobs 5 --output-sync=target test-coverage-check
# tests/integration is outside the coverage roots because its store specs
# need a live backend. test-stores builds and installs local-store before
# running the complete suite, so new local-store specs are collected
# automatically without adding another workflow entry.
- name: Test local-store integration
run: PATH="$PATH:$HOME/go/bin" make test-stores
- name: Upload coverage report
if: ${{ always() }}
uses: actions/upload-artifact@v4
@@ -80,13 +74,8 @@ jobs:
coverage/coverage.out
coverage/coverage.html
if-no-files-found: ignore
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
@@ -130,13 +119,8 @@ jobs:
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$PATH"
PATH="$PATH:$HOME/go/bin" make protogen-go
PATH="$PATH:$HOME/go/bin" BUILD_TYPE="GITHUB_CI_HAS_BROKEN_METAL" CMAKE_ARGS="-DGGML_F16C=OFF -DGGML_AVX512=OFF -DGGML_AVX2=OFF -DGGML_FMA=OFF" make --jobs 4 --output-sync=target test
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
+1 -6
View File
@@ -77,13 +77,8 @@ jobs:
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-e2e e2e-aio
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
+1 -6
View File
@@ -63,13 +63,8 @@ jobs:
- name: Test Backend E2E
run: |
PATH="$PATH:$HOME/go/bin" make build-mock-backend test-e2e
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
+1 -6
View File
@@ -88,13 +88,8 @@ jobs:
# CPU and runs the token_classify capability spec (byte-offset contract).
- name: Run live PII NER backend E2E
run: PATH="$PATH:$HOME/go/bin" make test-extra-backend-privacy-filter
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
+1 -8
View File
@@ -52,8 +52,6 @@ jobs:
run: |
sudo apt-get update
sudo apt-get install -y build-essential libopus-dev
- name: Run stale chunk recovery tests
run: PATH="$PATH:$HOME/go/bin" make test-ui-stale-chunk
# Builds an instrumented UI bundle, runs the Playwright specs, and fails
# if line coverage regressed beyond the jitter tolerance (the gate is
# in `make test-ui-coverage-check`). PLAYWRIGHT_CHROMIUM_PATH is unset
@@ -75,13 +73,8 @@ jobs:
path: core/http/react-ui/coverage/
if-no-files-found: ignore
retention-days: 7
# tmate keeps the runner busy until the 6 hour job limit, so a single
# failure costs a whole runner slot. Only open a session when someone
# asked for one by labelling the pull request `ci-debug`, and cap the
# session so a forgotten label cannot idle a runner either.
- name: Setup tmate session if tests fail
if: ${{ failure() && contains(github.event.pull_request.labels.*.name, 'ci-debug') }}
timeout-minutes: 30
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
-21
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@@ -1,21 +0,0 @@
## Design Context
### Users
LocalAI serves both single-host users who want to install and try models quickly and experienced developers, ML engineers, system administrators, and DevOps operators who manage production hosts or distributed clusters. The interface must support first-time discovery without hiding the runtime state, configuration, and control that returning operators need.
### Brand Personality
Capable, easy to use, and trustworthy. The interface should make sophisticated local-AI infrastructure feel understandable and under control. It should be direct and calm rather than playful, ornamental, or intimidating.
### Aesthetic Direction
Use LocalAI's established technical, editorial design language: Geist typography, compact information density, sharp geometry, deep blue-black surfaces, action blue, mint for healthy/local/live state, and amber only for decisions requiring attention. Support both dark and light themes. Avoid generic card dashboards, decorative gradients, glass effects, and visual noise.
### Design Principles
1. Use progressive disclosure to serve newcomers and operators in the same workflow: make the common path obvious, then reveal operational depth in context.
2. Organize navigation around user intent and lifecycle state, not implementation concepts or nested containers.
3. Give each resource one canonical home; expose discovery, installed state, and runtime state as clear views of that resource instead of duplicating management surfaces.
4. Keep operational status visible and trustworthy through precise labels, explicit scope, and actionable state—not decoration.
5. Preserve information density for expert use while flattening navigation and reducing repeated summaries, tabs, rails, and panels.
-1
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@@ -27,7 +27,6 @@ To be removed, open a pull request deleting your row, or email
| Organisation | What they use it for | Status |
|---|---|---|
| [walcz.de](https://walcz.de) | Self-hosted appliance for a German B2B consultancy: local-only inference on AMD Strix Halo (gfx1151/ROCm), agents with MCP tools, RAG over an internal knowledge base, and a document/bookkeeping pipeline. | Production |
| _Your organisation here_ | | |
## What this list is not
+1 -2
View File
@@ -8,7 +8,7 @@ Human contributors: see [CONTRIBUTING.md](CONTRIBUTING.md) for the development w
LocalAI follows the Linux kernel project's [guidelines for AI coding assistants](https://docs.kernel.org/process/coding-assistants.html). Before submitting AI-assisted code, read [.agents/ai-coding-assistants.md](.agents/ai-coding-assistants.md). Key rules:
- **No `Signed-off-by` from AI.** Only the human submitter may sign off on the Developer Certificate of Origin. One exception: automation a maintainer operates signs off with *that maintainer's* identity, since no other human submitter exists to certify it. See [.agents/ai-coding-assistants.md](.agents/ai-coding-assistants.md).
- **No `Signed-off-by` from AI.** Only the human submitter may sign off on the Developer Certificate of Origin.
- **No `Co-Authored-By: <AI>` trailers.** The human contributor owns the change.
- **Use an `Assisted-by:` trailer** to attribute AI involvement. Format: `Assisted-by: AGENT_NAME:MODEL_VERSION [TOOL1] [TOOL2]`.
- **The human submitter is responsible** for reviewing, testing, and understanding every line of generated code.
@@ -33,7 +33,6 @@ LocalAI follows the Linux kernel project's [guidelines for AI coding assistants]
| [.agents/localai-assistant-mcp.md](.agents/localai-assistant-mcp.md) | LocalAI Assistant chat modality — adding admin tools to the in-process MCP server, editing skill prompts, keeping REST + MCP + skills in sync |
| [.agents/backend-signing.md](.agents/backend-signing.md) | Backend OCI image signing (keyless cosign + sigstore-go) — producer-side CI setup, consumer-side gallery `verification:` block, strict mode (`LOCALAI_REQUIRE_BACKEND_INTEGRITY`), revocation via `not_before` |
| [.agents/preparing-a-release.md](.agents/preparing-a-release.md) | Cutting a release: PR labels, `RELEASE_NOTES_vX.Y.Z.md`, the blog post under `website/content/blog/`, and the demo clips under `website/static/media/` |
| [.impeccable.md](.impeccable.md) | Design context for UI/UX work — users, brand personality, aesthetic direction, and design principles |
## Quick Reference
+1 -1
View File
@@ -218,7 +218,7 @@ LocalAI follows the **same guidelines as the Linux kernel project** for AI-assis
The full policy for this repository lives in [`.agents/ai-coding-assistants.md`](.agents/ai-coding-assistants.md). Summary:
- **AI agents MUST NOT add `Signed-off-by` tags.** Only humans can certify the Developer Certificate of Origin. Automation operated by a maintainer is the one exception: it signs off with that maintainer's identity, because there is no other human submitter to certify it.
- **AI agents MUST NOT add `Signed-off-by` tags.** Only humans can certify the Developer Certificate of Origin.
- **AI agents MUST NOT add `Co-Authored-By` trailers** attributing themselves as co-authors.
- **Attribute AI involvement with an `Assisted-by` trailer** in the commit message:
+6 -38
View File
@@ -34,11 +34,6 @@ TEST_FLAKES?=5
RANDOM := $(shell bash -c 'echo $$RANDOM')
VERSION?=$(shell git describe --always --tags || echo "dev" )
# fyne package only accepts numeric x[.y[.z]] app versions, so reduce git
# describe output (v4.9.0, v4.9.0-14-gabc1234, or a bare sha on untagged
# checkouts) to its numeric core; anything non-numeric falls back to 0.0.0.
# Without this the packaged launcher reports itself as version 0.0.0 (#11673).
LAUNCHER_APP_VERSION?=$(shell v=$$(echo "$(VERSION)" | sed -E 's/^v//; s/[+-].*$$//'); echo "$$v" | grep -qE '^[0-9]+(\.[0-9]+){0,2}$$' && echo "$$v" || echo "0.0.0")
# go tool nm ./local-ai | grep Commit
LD_FLAGS?=-s -w
override LD_FLAGS += -X "github.com/mudler/LocalAI/internal.Version=$(VERSION)"
@@ -108,7 +103,7 @@ COVERAGE_E2E_LABELS?=!real-models
COVERAGE_EXCLUDE_RE?=grpc/proto/.*[.]pb[.]go
.PHONY: all test test-coverage test-coverage-baseline test-coverage-check test-backend-cpp test-build-scripts test-ui test-ui-stale-chunk test-ui-coverage-baseline test-ui-coverage-check build vendor lint lint-all
.PHONY: all test test-coverage test-coverage-baseline test-coverage-check test-backend-cpp test-build-scripts test-ui test-ui-coverage-baseline test-ui-coverage-check build vendor lint lint-all
all: help
@@ -240,7 +235,7 @@ test-ci-scripts:
## pure stdlib on purpose so they run without any backend venv; the list is
## explicit because their siblings (model_identity_test) import grpc and the
## generated protobufs, which only exist inside a built backend.
PYTHON_HELPER_TESTS?=python_utils_test vllm_utils_test model_utils_test mlx_utils_test parent_watch_test temp_utils_test
PYTHON_HELPER_TESTS?=python_utils_test vllm_utils_test model_utils_test mlx_utils_test parent_watch_test
test-python-helpers:
cd backend/python/common && python3 -m unittest $(PYTHON_HELPER_TESTS)
@@ -393,17 +388,9 @@ test-e2e: build-mock-backend build-cloud-proxy-backend prepare-e2e run-e2e-image
$(MAKE) teardown-e2e
docker rmi localai-tests
# `docker stop` returns as soon as the container exits, but Docker reaps a
# `--rm` container asynchronously after that. The `docker rmi localai-tests` in
# test-e2e then loses the race against the reaper and fails on a still
# referenced image, turning a green suite red. Removing the container ourselves
# is synchronous, so the image reference is gone before we return. It also
# covers the case where nothing is running, which `docker stop` could not
# because it rejects an empty argument list.
teardown-e2e:
rm -rf $(TEST_DIR) || true
@CONTAINERS=$$(docker ps -aq --filter ancestor=localai-tests 2>/dev/null); \
if [ -n "$$CONTAINERS" ]; then docker rm -f $$CONTAINERS || true; fi
docker stop $$(docker ps -q --filter ancestor=localai-tests)
########################################################
## Integration and unit tests
@@ -689,7 +676,6 @@ test-extra: prepare-test-extra
## BACKEND_TEST_PROMPT Override the prompt used in predict/stream specs.
## BACKEND_TEST_OPTIONS Comma-separated Options[] entries forwarded to LoadModel,
## e.g. "tool_parser:hermes,reasoning_parser:qwen3".
## BACKEND_TEST_EMBEDDING_LAYOUT Expected EmbeddingResult layout: "final" or "per_token".
##
## Direct usage (image already built, no docker-build-* dependency):
##
@@ -719,7 +705,6 @@ test-extra-backend: protogen-go
BACKEND_TEST_CAPS="$$BACKEND_TEST_CAPS" \
BACKEND_TEST_PROMPT="$$BACKEND_TEST_PROMPT" \
BACKEND_TEST_OPTIONS="$$BACKEND_TEST_OPTIONS" \
BACKEND_TEST_EMBEDDING_LAYOUT="$$BACKEND_TEST_EMBEDDING_LAYOUT" \
BACKEND_TEST_TOOL_PROMPT="$$BACKEND_TEST_TOOL_PROMPT" \
BACKEND_TEST_TOOL_NAME="$$BACKEND_TEST_TOOL_NAME" \
BACKEND_TEST_CACHE_TYPE_K="$$BACKEND_TEST_CACHE_TYPE_K" \
@@ -739,15 +724,6 @@ test-extra-backend-llama-cpp: docker-build-llama-cpp
BACKEND_TEST_CAPS=health,load,predict,stream,logprobs,logit_bias \
$(MAKE) test-extra-backend
## Raw llama.cpp embeddings are required by Go-side pooling. This exercises the
## real C++ backend and verifies that it marks the flattened matrix per-token.
test-extra-backend-llama-cpp-embeddings: docker-build-llama-cpp
BACKEND_IMAGE=local-ai-backend:llama-cpp \
BACKEND_TEST_CAPS=health,load,embeddings \
BACKEND_TEST_OPTIONS=pooling:none \
BACKEND_TEST_EMBEDDING_LAYOUT=per_token \
$(MAKE) test-extra-backend
test-extra-backend-ik-llama-cpp: docker-build-ik-llama-cpp
BACKEND_IMAGE=local-ai-backend:ik-llama-cpp $(MAKE) test-extra-backend
@@ -837,7 +813,6 @@ test-extra-backend-tinygrad-embeddings: docker-build-tinygrad
BACKEND_IMAGE=local-ai-backend:tinygrad \
BACKEND_TEST_MODEL_NAME=Qwen/Qwen3-0.6B \
BACKEND_TEST_CAPS=health,load,embeddings \
BACKEND_TEST_EMBEDDING_LAYOUT=final \
$(MAKE) test-extra-backend
## tinygrad — Stable Diffusion 1.5. The original CompVis/runwayml repos have
@@ -1530,13 +1505,6 @@ test-ui: build-mock-backend protogen-go
$(GOCMD) build -o tests/e2e-ui/ui-test-server ./tests/e2e-ui
cd core/http/react-ui && sh $(CURDIR)/scripts/ensure-playwright-browser.sh && bunx playwright test $(PLAYWRIGHT_WORKERS_FLAG)
## The stale-chunk specs need the production code-split bundle. The V8 coverage
## bundle below inlines dynamic imports to keep every page in its denominator.
test-ui-stale-chunk: build-mock-backend protogen-go
cd core/http/react-ui && bun install && bun run build
$(GOCMD) build -o tests/e2e-ui/ui-test-server ./tests/e2e-ui
cd core/http/react-ui && sh $(CURDIR)/scripts/ensure-playwright-browser.sh && bunx playwright test --grep @production-chunks --workers=1
## React UI code coverage from the Playwright e2e suite. Builds a
## NON-instrumented bundle with source maps (COVERAGE_V8=true), re-embeds it
## into the ui-test-server (the dist is //go:embed'ed at compile time), runs the
@@ -1552,7 +1520,7 @@ test-ui-coverage: build-mock-backend protogen-go
$(GOCMD) build -o tests/e2e-ui/ui-test-server ./tests/e2e-ui && \
( cd core/http/react-ui && rm -rf .nyc_output coverage && \
sh $(CURDIR)/scripts/ensure-playwright-browser.sh && \
PW_V8_COVERAGE=1 bunx playwright test --grep-invert @production-chunks $(PLAYWRIGHT_WORKERS_FLAG) && bun run coverage:report )
PW_V8_COVERAGE=1 bunx playwright test $(PLAYWRIGHT_WORKERS_FLAG) && bun run coverage:report )
## UI coverage baseline (committed) and the strict gate that compares against
## it — the React mirror of test-coverage-baseline / test-coverage-check.
@@ -1635,7 +1603,7 @@ site-serve: site
build-launcher-darwin:
rm -rf dist/LocalAI.app cmd/launcher/LocalAI.app
mkdir -p dist
cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os darwin -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME) --app-version $(LAUNCHER_APP_VERSION)
cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os darwin -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME)
mv cmd/launcher/LocalAI.app dist/LocalAI.app
bash contrib/macos/sign-and-notarize.sh sign dist/LocalAI.app
@@ -1662,4 +1630,4 @@ release-launcher-darwin: notarize-launcher-darwin
@echo "dist/LocalAI.dmg is ready"
build-launcher-linux:
cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os linux -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME)-linux --app-version $(LAUNCHER_APP_VERSION) && mv LocalAI.tar.xz ../../$(LAUNCHER_BINARY_NAME)-linux.tar.xz
cd cmd/launcher && go run fyne.io/tools/cmd/fyne@latest package -os linux -icon ../../core/http/static/logo.png --executable $(LAUNCHER_BINARY_NAME)-linux && mv LocalAI.tar.xz ../../$(LAUNCHER_BINARY_NAME)-linux.tar.xz
+7
View File
@@ -5,6 +5,9 @@
</h1>
<p align="center">
<a href="https://github.com/go-skynet/LocalAI/stargazers" target="blank">
<img src="https://img.shields.io/github/stars/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI stars"/>
</a>
<a href='https://github.com/go-skynet/LocalAI/releases'>
<img src='https://img.shields.io/github/release/go-skynet/LocalAI?&label=Latest&style=for-the-badge'>
</a>
@@ -315,6 +318,10 @@ Past sponsors
A special thanks to individual sponsors, a full list is on [GitHub](https://github.com/sponsors/mudler) and [buymeacoffee](https://buymeacoffee.com/mudler). Special shout out to [drikster80](https://github.com/drikster80) for being generous. Thank you everyone!
## Star history
[![LocalAI Star history Chart](https://api.star-history.com/svg?repos=go-skynet/LocalAI&type=Date)](https://star-history.com/#go-skynet/LocalAI&Date)
## License
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/) and maintained by the [LocalAI team](#team).
+1 -3
View File
@@ -10,7 +10,6 @@ FROM ${BASE_IMAGE} AS builder
ARG BUILD_TYPE
ARG TARGETARCH
ARG TARGETVARIANT
ARG CUDA_MAJOR_VERSION
ENV BUILD_TYPE=${BUILD_TYPE} \
DEBIAN_FRONTEND=noninteractive \
@@ -36,8 +35,7 @@ RUN apt-get update && \
COPY . /LocalAI
RUN --mount=type=cache,target=/root/.ccache,id=ds4-ccache-${TARGETARCH}-${BUILD_TYPE},sharing=locked \
make -C /LocalAI/backend/cpp/ds4 BUILD_TYPE=${BUILD_TYPE} \
CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION} NATIVE=false grpc-server package
make -C /LocalAI/backend/cpp/ds4 BUILD_TYPE=${BUILD_TYPE} NATIVE=false grpc-server package
FROM scratch
COPY --from=builder /LocalAI/backend/cpp/ds4/package/. ./
-20
View File
@@ -536,28 +536,8 @@ message Result {
bool success = 2;
}
// EmbeddingLayout describes whether embeddings contains one final vector or
// a matrix of per-token vectors. Go-side pooling must never infer this from
// tokens/dim alone: a one-token raw matrix and a final vector have the same
// shape.
enum EmbeddingLayout {
EMBEDDING_LAYOUT_UNSPECIFIED = 0;
EMBEDDING_LAYOUT_FINAL = 1;
EMBEDDING_LAYOUT_PER_TOKEN = 2;
}
message EmbeddingResult {
repeated float embeddings = 1;
// Shape of the payload above: dim is the embedding width, tokens is the
// number of vectors packed into `embeddings` (1 when the backend pooled
// server-side, N with pooling:none; total across prompts if a request
// carried several). tokens=0/dim=0 means the backend predates shape
// reporting. prompt_tokens is the number of prompt tokens evaluated, for
// usage accounting.
int32 tokens = 2;
int32 dim = 3;
int32 prompt_tokens = 4;
EmbeddingLayout layout = 5;
}
message TranscriptRequest {
+1 -1
View File
@@ -9,7 +9,7 @@
# recipe is a make target (not a prepare.sh) so 'make purge && make' is a clean
# rebuild and so the bump bot can see the pin.
AUDIO_CPP_VERSION?=fa5aaac9266a98c68f8a5c9fcd1ba6ff65875416
AUDIO_CPP_VERSION?=748c5e28f6a7228b8f38ad7142ca97d29584544b
AUDIO_CPP_REPO?=https://github.com/0xShug0/audio.cpp
CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
@@ -29,7 +29,6 @@ const NamedTask kTaskNames[] = {
{Task::VoiceDesign, "vdes"},
{Task::SpeakerRecognition, "spk"},
{Task::Svc, "svc"},
{Task::Midi, "midi"},
};
// Accepted on input but never emitted. "spkrec" was this backend's own earlier
@@ -25,7 +25,6 @@ enum class Task {
VoiceDesign,
SpeakerRecognition,
Svc,
Midi,
};
// Mirrors engine::runtime::RunMode.
@@ -361,7 +361,7 @@ static void test_names_round_trip() {
Task::SourceSeparation, Task::AudioGeneration, Task::Tts,
Task::VoiceCloning, Task::VoiceConversion,
Task::SpeechToSpeech, Task::Alignment, Task::VoiceDesign,
Task::SpeakerRecognition, Task::Svc, Task::Midi};
Task::SpeakerRecognition, Task::Svc};
for (const Task t : all) {
Task parsed = Task::Vad;
const bool ok = parse_task_name(task_name(t), parsed);
+1 -5
View File
@@ -69,8 +69,7 @@ static_assert(kEngine(engine::runtime::VoiceTaskKind::VoiceDesign) == 10, "Voice
static_assert(kEngine(engine::runtime::VoiceTaskKind::SpeakerRecognition) == 11, "VoiceTaskKind drifted");
// The last member. Pinning it pins the member count too, as long as the
// enumerators stay contiguous and unassigned, which upstream's declaration is.
static_assert(kEngine(engine::runtime::VoiceTaskKind::Svc) == 12, "VoiceTaskKind drifted");
static_assert(kEngine(engine::runtime::VoiceTaskKind::Midi) == 13,
static_assert(kEngine(engine::runtime::VoiceTaskKind::Svc) == 12,
"engine::runtime::VoiceTaskKind gained, lost or reordered a member. "
"audiocpp_backend::Task mirrors it positionally: update capability_routing.h, "
"to_engine_task and from_engine_task together, then move this pin.");
@@ -88,7 +87,6 @@ static_assert(kMirror(Task::Alignment) == 9, "Task drifted from VoiceTaskKind");
static_assert(kMirror(Task::VoiceDesign) == 10, "Task drifted from VoiceTaskKind");
static_assert(kMirror(Task::SpeakerRecognition) == 11, "Task drifted from VoiceTaskKind");
static_assert(kMirror(Task::Svc) == 12, "Task drifted from VoiceTaskKind");
static_assert(kMirror(Task::Midi) == 13, "Task drifted from VoiceTaskKind");
static_assert(static_cast<int>(engine::runtime::RunMode::Offline) == 0, "RunMode drifted");
static_assert(static_cast<int>(engine::runtime::RunMode::Streaming) == 1,
@@ -243,7 +241,6 @@ engine::runtime::VoiceTaskKind to_engine_task(Task task) {
case Task::VoiceDesign: return K::VoiceDesign;
case Task::SpeakerRecognition: return K::SpeakerRecognition;
case Task::Svc: return K::Svc;
case Task::Midi: return K::Midi;
}
// Unreachable for any valid enumerator. No `default:` label, so -Wswitch
// still reports a member this switch stops covering.
@@ -266,7 +263,6 @@ Task from_engine_task(engine::runtime::VoiceTaskKind kind) {
case K::VoiceDesign: return Task::VoiceDesign;
case K::SpeakerRecognition: return Task::SpeakerRecognition;
case K::Svc: return Task::Svc;
case K::Midi: return Task::Midi;
}
return Task::Vad;
}
+1 -3
View File
@@ -1,7 +1,7 @@
# Pinned to the HEAD of the `prism` branch on https://github.com/PrismML-Eng/llama.cpp.
# Auto-bumped nightly by .github/workflows/bump_deps.yaml.
BONSAI_VERSION?=312bb2a93ea2bf798333fa859614fbf913ecb9e2
BONSAI_VERSION?=9ca265a57f85f2117942490f421f64a226dd9847
LLAMA_REPO?=https://github.com/PrismML-Eng/llama.cpp
CMAKE_ARGS?=
@@ -41,7 +41,6 @@ define bonsai-build
# and are applied by apply-patches.sh below.
rm -rf $(CURRENT_MAKEFILE_DIR)/../bonsai-$(1)-build/patches
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../bonsai-$(1)-build purge
bash $(CURRENT_MAKEFILE_DIR)/patch-grpc-server.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-$(1)-build/grpc-server.cpp
bash $(LLAMA_CPP_DIR)/disable-score-task.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-$(1)-build/grpc-server.cpp
bash $(LLAMA_CPP_DIR)/disable-tts-task.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-$(1)-build/grpc-server.cpp
$(info $(GREEN)I bonsai build info:$(1)$(RESET))
@@ -80,7 +79,6 @@ bonsai-cpu-all:
# and are applied by apply-patches.sh below.
rm -rf $(CURRENT_MAKEFILE_DIR)/../bonsai-cpu-all-build/patches
$(MAKE) -C $(CURRENT_MAKEFILE_DIR)/../bonsai-cpu-all-build purge
bash $(CURRENT_MAKEFILE_DIR)/patch-grpc-server.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-cpu-all-build/grpc-server.cpp
bash $(LLAMA_CPP_DIR)/disable-score-task.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-cpu-all-build/grpc-server.cpp
bash $(LLAMA_CPP_DIR)/disable-tts-task.sh $(CURRENT_MAKEFILE_DIR)/../bonsai-cpu-all-build/grpc-server.cpp
$(info $(GREEN)I bonsai build info:cpu-all-variants$(RESET))
-24
View File
@@ -1,24 +0,0 @@
#!/bin/bash
# Adapt the shared llama.cpp gRPC source to the older JSON API in Bonsai.
set -euo pipefail
if [[ $# -ne 1 ]]; then
echo "usage: $0 <grpc-server.cpp>" >&2
exit 2
fi
SRC=$1
if [[ ! -f "$SRC" ]]; then
echo "grpc-server.cpp not found at $SRC" >&2
exit 2
fi
if grep -q 'common_json_error' "$SRC"; then
echo "==> patching $SRC to use the Bonsai JSON exception type"
awk '{ gsub(/common_json_error/, "json::parse_error"); print }' "$SRC" > "$SRC.tmp"
mv "$SRC.tmp" "$SRC"
echo "==> Bonsai JSON exception patch OK"
else
echo "==> $SRC already uses a Bonsai-compatible JSON exception type, skipping"
fi
+3 -4
View File
@@ -84,10 +84,9 @@ elseif(DS4_GPU STREQUAL "cpu")
set(DS4_OBJS "${DS4_DIR}/ds4_cpu.o")
endif()
# Upstream splits image preprocessing, distributed inference, tensor-parallel
# transport, the SSD expert cache, and layer placement into GPU-agnostic
# translation units. Link them regardless of DS4_GPU.
list(APPEND DS4_OBJS "${DS4_DIR}/ds4_image.o")
# Upstream splits distributed inference, tensor-parallel transport, the SSD
# expert cache, and layer placement into GPU-agnostic translation units. Link
# them regardless of DS4_GPU.
list(APPEND DS4_OBJS "${DS4_DIR}/ds4_distributed.o")
list(APPEND DS4_OBJS "${DS4_DIR}/ds4_tp.o")
list(APPEND DS4_OBJS "${DS4_DIR}/ds4_ssd.o")
+11 -73
View File
@@ -1,10 +1,10 @@
# ds4 backend Makefile.
#
# Upstream pin lives below as DS4_VERSION?=6289c516273979173abbc062209a81dd3706b804
# Upstream pin lives below as DS4_VERSION?=84cc882352757baf628a1776badf7cc54d584e28
# (.github/bump_deps.sh) can find and update it - matches the
# llama-cpp / ik-llama-cpp / turboquant convention.
DS4_VERSION?=6289c516273979173abbc062209a81dd3706b804
DS4_VERSION?=84cc882352757baf628a1776badf7cc54d584e28
DS4_REPO?=https://github.com/antirez/ds4
CURRENT_MAKEFILE_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
@@ -18,83 +18,21 @@ UNAME_S := $(shell uname -s)
CMAKE_ARGS ?= -DCMAKE_BUILD_TYPE=Release
# nvcc must be told the target architecture explicitly for a cublas build, and
# this is not a tuning knob. Upstream's Makefile leaves CUDA_ARCH empty and its
# `cuda` target REFUSES to build without one, offering `cuda-spark`
# (CUDA_ARCH=sm_121) and `cuda-generic` (CUDA_ARCH=native) instead. We drive its
# object targets directly, which bypasses that guard: nvcc then compiles with no
# -arch at all, and the kernels run as JIT'd PTX for its default architecture.
# On GB10 (sm_121) that silently produced corrupt inference output above a
# ~128-token prefill batch and ~77x slower prefill (4.21 t/s vs 325.70 t/s,
# measured on the same box with the same model). No CI runner has a GPU, so
# `native` has nothing to enumerate there.
#
# Upstream's CUDA_ARCH takes a SINGLE value (see its sm_120/sm_121 special cases
# and the `-arch=$(CUDA_ARCH)` fallback), so it cannot express the fat binary
# these images need. NVCC_ARCH_FLAGS is overridden instead: a command-line
# assignment wins over the `:=` in upstream's Makefile, and its NVCCFLAGS
# expands whatever we pass.
#
# The architecture lists are copied from backend/go/vllm-cpp/Makefile rather
# than invented, so the two CUDA images cover the same GPUs: amd64 datacenter +
# consumer, and l4t/arm64 covering Orin (87), Thor (110) and GB10 (121a).
#
# -DDS4_CUDA_HAVE_MXF4=1 is deliberately NOT set. Upstream only defines it for
# single-arch sm_120/sm_121 builds and guards the code with a plain #ifdef
# rather than __CUDA_ARCH__, so it cannot be combined with older archs in one
# fat binary. It gates an optional MXFP4 indexer fast path whose #ifndef branch
# returns 0 and falls back to the generic path, so omitting it costs some speed
# on GB10, not correctness. Revisit if upstream adds __CUDA_ARCH__ guards.
#
# An EMPTY CUDA_MAJOR_VERSION means a local developer build, not CI: fall back
# to upstream's own `native` handling, which needs a GPU present but is what a
# developer building on their own machine wants. Both variables are `?=` so an
# explicit value on the command line always wins.
UNAME_M := $(shell uname -m)
CUDA_MAJOR_VERSION ?=
ifeq ($(BUILD_TYPE),cublas)
ifeq ($(CUDA_MAJOR_VERSION),13)
ifeq ($(UNAME_M),aarch64)
DS4_NVCC_ARCH_FLAGS ?= -gencode arch=compute_87,code=sm_87 \
-gencode arch=compute_90a,code=sm_90a \
-gencode arch=compute_100a,code=sm_100a \
-gencode arch=compute_110,code=sm_110 \
-gencode arch=compute_121a,code=sm_121a
else
DS4_NVCC_ARCH_FLAGS ?= -gencode arch=compute_80,code=sm_80 \
-gencode arch=compute_86,code=sm_86 \
-gencode arch=compute_89,code=sm_89 \
-gencode arch=compute_90a,code=sm_90a \
-gencode arch=compute_100a,code=sm_100a \
-gencode arch=compute_103a,code=sm_103a \
-gencode arch=compute_120a,code=sm_120a \
-gencode arch=compute_121a,code=sm_121a
endif
DS4_ARCH_MAKEVARS := NVCC_ARCH_FLAGS="$(DS4_NVCC_ARCH_FLAGS)"
else ifeq ($(CUDA_MAJOR_VERSION),)
# Local build: let upstream resolve the host GPU.
DS4_ARCH_MAKEVARS := CUDA_ARCH=native
else
$(error CUDA_MAJOR_VERSION=$(CUDA_MAJOR_VERSION) has no architecture list here (13 does). Leave it empty for a native build, or pass DS4_NVCC_ARCH_FLAGS explicitly.)
endif
endif
# Upstream splits image preprocessing, distributed inference, tensor-parallel
# transport, the SSD expert cache, and layer placement into GPU-agnostic
# translation units. They are shared by every GPU mode, so append them
# unconditionally below.
# Upstream splits distributed inference, tensor-parallel transport, the SSD
# expert cache, and layer placement into GPU-agnostic translation units. They
# are shared by every GPU mode, so append them unconditionally below.
ifeq ($(BUILD_TYPE),cublas)
CMAKE_ARGS += -DDS4_GPU=cuda
DS4_OBJ_TARGET := ds4.o ds4_image.o ds4_cuda.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o \
DS4_OBJ_TARGET := ds4.o ds4_cuda.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o \
cuda/mmq/ds4_ggml_stubs.o cuda/mmq/ds4_mmq.o cuda/mmq/ds4_mmq_d2r.o \
cuda/mmq/quantize.o cuda/mmq/mmid.o cuda/mmq/mmvq.o cuda/mmq/ds4_repack.o
else ifeq ($(UNAME_S),Darwin)
CMAKE_ARGS += -DDS4_GPU=metal
DS4_OBJ_TARGET := ds4.o ds4_image.o ds4_metal.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
DS4_OBJ_TARGET := ds4.o ds4_metal.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
else
# CPU reference path (Linux only - macOS CPU path is broken by VM bug per ds4 README).
CMAKE_ARGS += -DDS4_GPU=cpu
DS4_OBJ_TARGET := ds4_cpu.o ds4_image.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
DS4_OBJ_TARGET := ds4_cpu.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
endif
ifneq ($(NATIVE),true)
@@ -119,11 +57,11 @@ ds4:
# the right per-platform compile flags (Objective-C/Metal on Darwin, nvcc on Linux+CUDA).
ds4/ds4.o: ds4
ifeq ($(BUILD_TYPE),cublas)
+$(MAKE) -C ds4 $(DS4_ARCH_MAKEVARS) $(DS4_OBJ_TARGET)
+$(MAKE) -C ds4 $(DS4_OBJ_TARGET)
else ifeq ($(UNAME_S),Darwin)
+$(MAKE) -C ds4 ds4.o ds4_image.o ds4_metal.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
+$(MAKE) -C ds4 ds4.o ds4_metal.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
else
+$(MAKE) -C ds4 ds4_cpu.o ds4_image.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
+$(MAKE) -C ds4 ds4_cpu.o ds4_distributed.o ds4_tp.o ds4_ssd.o ds4_layer_pack.o
endif
grpc-server: ds4/ds4.o
+1 -2
View File
@@ -92,8 +92,7 @@ std::string json_escape(const std::string &in) {
} // namespace
DsmlParser::DsmlParser(bool starts_in_thinking)
: state_(starts_in_thinking ? State::THINK : State::TEXT) {}
DsmlParser::DsmlParser() = default;
bool DsmlParser::IsInDsmlStructural() const {
switch (state_) {
+2 -4
View File
@@ -17,9 +17,7 @@ struct ParserEvent {
// Streaming parser. Stateless across instances; one per Predict call.
class DsmlParser {
public:
// The chat prompt may already contain the opening thinking marker, so the
// generated text can begin directly with reasoning bytes.
explicit DsmlParser(bool starts_in_thinking = false);
DsmlParser();
// Feed a chunk of raw model-emitted text. Appends classified events to
// `out`. May buffer the tail of `chunk` internally if it looks like a
@@ -45,7 +43,7 @@ public:
private:
enum class State { TEXT, THINK, TOOL_CALLS, INVOKE, PARAM_VALUE };
State state_;
State state_ = State::TEXT;
std::string buf_;
std::string current_tool_name_;
int tool_index_ = -1;
-133
View File
@@ -1,133 +0,0 @@
// SPDX-License-Identifier: MIT
// Standalone regression tests for the DSML streaming parser.
//
// The repository's backend/cpp/run-unit-tests.sh harness compiles each
// *_test.cpp as a single translation unit, so include the implementation here.
#include "dsml_parser.cpp"
#include <cstdio>
#include <string>
#include <type_traits>
#include <vector>
namespace {
struct ParsedText {
std::string content;
std::string reasoning;
};
int failures = 0;
void check_equal(const std::string &got, const std::string &want,
const char *name) {
if (got == want) return;
std::fprintf(stderr, "FAIL %s: got \"%s\", want \"%s\"\n",
name, got.c_str(), want.c_str());
failures++;
}
void collect_text(const std::vector<ds4cpp::ParserEvent> &events,
ParsedText *parsed) {
for (const auto &event : events) {
if (event.type == ds4cpp::ParserEvent::CONTENT) {
parsed->content += event.text;
} else if (event.type == ds4cpp::ParserEvent::REASONING) {
parsed->reasoning += event.text;
}
}
}
ParsedText parse_chunks(ds4cpp::DsmlParser *parser,
const std::vector<std::string> &chunks) {
ParsedText parsed;
for (const auto &chunk : chunks) {
std::vector<ds4cpp::ParserEvent> events;
parser->Feed(chunk, events);
collect_text(events, &parsed);
}
std::vector<ds4cpp::ParserEvent> events;
parser->Flush(events);
collect_text(events, &parsed);
return parsed;
}
template <typename Parser>
void test_reasoning_opened_by_prompt() {
if constexpr (!std::is_constructible_v<Parser, bool>) {
std::fprintf(stderr,
"FAIL reasoning_opened_by_prompt: parser cannot start in thinking state\n");
failures++;
} else {
Parser parser(true);
ParsedText parsed = parse_chunks(
&parser,
{"We need to calculate factorial recursively.</think>Here is the answer."});
check_equal(parsed.reasoning,
"We need to calculate factorial recursively.",
"reasoning_opened_by_prompt:reasoning");
check_equal(parsed.content, "Here is the answer.",
"reasoning_opened_by_prompt:content");
}
}
template <typename Parser>
Parser text_parser() {
if constexpr (std::is_constructible_v<Parser, bool>) {
return Parser(false);
} else {
return Parser();
}
}
void test_reasoning_disabled() {
auto parser = text_parser<ds4cpp::DsmlParser>();
ParsedText parsed = parse_chunks(&parser, {"Here is the answer."});
check_equal(parsed.reasoning, "", "reasoning_disabled:reasoning");
check_equal(parsed.content, "Here is the answer.",
"reasoning_disabled:content");
}
void test_explicit_think_tag() {
auto parser = text_parser<ds4cpp::DsmlParser>();
ParsedText parsed = parse_chunks(
&parser, {"<think>reasoning</think>answer"});
check_equal(parsed.reasoning, "reasoning", "explicit_think_tag:reasoning");
check_equal(parsed.content, "answer", "explicit_think_tag:content");
}
template <typename Parser>
void test_split_think_close_marker() {
if constexpr (!std::is_constructible_v<Parser, bool>) {
std::fprintf(stderr,
"FAIL split_think_close_marker: parser cannot start in thinking state\n");
failures++;
} else {
Parser parser(true);
ParsedText parsed = parse_chunks(
&parser,
{"We need ", "to calculate ", "factorial", "</thi", "nk>",
"Here is ", "the answer."});
check_equal(parsed.reasoning, "We need to calculate factorial",
"split_think_close_marker:reasoning");
check_equal(parsed.content, "Here is the answer.",
"split_think_close_marker:content");
}
}
} // namespace
int main() {
test_reasoning_opened_by_prompt<ds4cpp::DsmlParser>();
test_reasoning_disabled();
test_explicit_think_tag();
test_split_think_close_marker<ds4cpp::DsmlParser>();
if (failures == 0) {
std::fprintf(stderr, "all dsml_parser checks passed\n");
return 0;
}
std::fprintf(stderr, "%d check(s) failed\n", failures);
return 1;
}
-27
View File
@@ -1,27 +0,0 @@
// SPDX-License-Identifier: MIT
#pragma once
#include <algorithm>
namespace ds4cpp {
inline int EffectiveGenerationLimit(int requested, int context_size,
int session_position) {
const int limit = requested > 0 ? requested : 256;
const int room = context_size - session_position;
if (room <= 1) return 0;
return std::min(limit, room - 1);
}
inline int RemainingGenerationBudget(int effective_limit, int produced) {
if (effective_limit <= produced) return 0;
return effective_limit - produced;
}
inline int SpeculativeAcceptedCapacity(int remaining, int draft_allowance,
int buffer_capacity) {
if (remaining <= 0 || draft_allowance < 0 || buffer_capacity <= 0) return 0;
return std::min({remaining, draft_allowance + 1, buffer_capacity});
}
} // namespace ds4cpp
@@ -1,92 +0,0 @@
// SPDX-License-Identifier: MIT
#include "generation_limits.h"
#include <cstdio>
namespace {
int failures = 0;
void check_equal(int got, int want, const char *name) {
if (got == want) return;
std::fprintf(stderr, "FAIL %s: got %d, want %d\n", name, got, want);
failures++;
}
// Mutation caught: treating omitted or negative max_tokens as unlimited instead
// of preserving DS4's legacy 256-token default.
void test_nonpositive_uses_legacy_default_when_space_permits() {
check_equal(ds4cpp::EffectiveGenerationLimit(0, 4096, 100), 256,
"zero max_tokens uses legacy default");
check_equal(ds4cpp::EffectiveGenerationLimit(-1, 4096, 100), 256,
"negative max_tokens uses legacy default");
}
// Mutation caught: applying the legacy default without clamping it to the
// post-prefill context room and reserved slot.
void test_legacy_default_is_clamped_by_context() {
check_equal(ds4cpp::EffectiveGenerationLimit(0, 300, 100), 199,
"legacy default is context-clamped");
}
// Mutation caught: allowing an explicitly large request to overrun the
// post-prefill context boundary.
void test_large_positive_limit_is_clamped_to_context() {
check_equal(ds4cpp::EffectiveGenerationLimit(32768, 32768, 100), 32667,
"large positive is context-clamped");
}
// Mutation caught: replacing every positive request with the legacy default
// rather than preserving a smaller configured limit.
void test_smaller_positive_limit_is_preserved() {
check_equal(ds4cpp::EffectiveGenerationLimit(64, 4096, 100), 64,
"smaller positive is preserved");
}
// Mutation caught: consuming the final context slot instead of reserving it as
// required by DS4's generation loop.
void test_no_usable_room_returns_zero() {
check_equal(ds4cpp::EffectiveGenerationLimit(32, 100, 99), 0,
"one remaining context slot is not usable");
}
// Mutation caught: sending the original generation limit to a later
// speculative cycle instead of subtracting tokens already produced.
void test_remaining_budget_accounts_for_produced_tokens() {
check_equal(ds4cpp::RemainingGenerationBudget(10, 4), 6,
"remaining budget subtracts produced tokens");
check_equal(ds4cpp::RemainingGenerationBudget(10, 12), 0,
"remaining budget never becomes negative");
}
// Mutation caught: giving speculative evaluation capacity beyond either the
// output budget, the draft allowance plus its first target token, or the fixed
// accepted-token buffer.
void test_speculative_capacity_obeys_all_bounds() {
check_equal(ds4cpp::SpeculativeAcceptedCapacity(3, 8, 8), 3,
"capacity respects remaining output budget");
check_equal(ds4cpp::SpeculativeAcceptedCapacity(20, 4, 8), 5,
"capacity includes one target token beyond draft allowance");
check_equal(ds4cpp::SpeculativeAcceptedCapacity(20, 8, 6), 6,
"capacity respects fixed buffer");
}
} // namespace
int main() {
test_nonpositive_uses_legacy_default_when_space_permits();
test_legacy_default_is_clamped_by_context();
test_large_positive_limit_is_clamped_to_context();
test_smaller_positive_limit_is_preserved();
test_no_usable_room_returns_zero();
test_remaining_budget_accounts_for_produced_tokens();
test_speculative_capacity_obeys_all_bounds();
if (failures == 0) {
std::fprintf(stderr, "all generation limit checks passed\n");
return 0;
}
std::fprintf(stderr, "%d check(s) failed\n", failures);
return 1;
}
+57 -186
View File
@@ -10,9 +10,7 @@
#include "dsml_parser.h" // populated in Task 12
#include "dsml_renderer.h" // populated in Task 16
#include "generation_limits.h"
#include "kv_cache.h" // populated in Task 17
#include "request_lifecycle.h"
extern "C" {
#include "ds4.h"
@@ -37,7 +35,6 @@ extern "C" {
#include <mutex>
#include <string>
#include <thread>
#include <utility>
#include <vector>
using grpc::Server;
@@ -72,21 +69,6 @@ int g_route_timeout_sec = 60;
std::atomic<Server *> g_server{nullptr};
static bool server_context_cancelled(void *ud) {
return static_cast<ServerContext *>(ud)->IsCancelled();
}
static void set_session_cancel(void *target, ds4cpp::CancelCallback callback,
void *userdata) noexcept {
ds4_session_set_cancel(static_cast<ds4_session *>(target), callback, userdata);
}
static bool request_should_continue(ds4cpp::RequestLifecycle *request,
ServerContext *context) {
request->ObserveContextCancellation(context->IsCancelled());
return request->ShouldContinue();
}
// Parse a "key:value" option string. Returns empty when no colon.
static std::pair<std::string, std::string> split_option(const std::string &opt) {
auto colon = opt.find(':');
@@ -256,58 +238,37 @@ static bool apply_engine_option(ds4_engine_options *opt, const std::string &key,
// When acting as a distributed coordinator, block until the worker route
// covers all layers (ds4_session_distributed_route_ready == 1) or the timeout
// elapses. No-op when not distributed.
// elapses. Returns an empty string on success, or an error message to return
// to the client. No-op when not distributed.
//
// Takes the g_engine_mu lock by reference and RELEASES it during each poll
// sleep. The wait can span up to g_route_timeout_sec seconds while workers
// connect; holding g_engine_mu the whole time would block the Status/Health
// readiness probes (they also lock g_engine_mu), making LocalAI's loader treat
// a still-starting worker as hung.
struct RouteWaitResult {
ds4cpp::RouteWaitDecision decision;
std::string error;
};
static RouteWaitResult wait_route_ready(std::unique_lock<std::mutex> &lock,
ServerContext *context) {
if (!g_distributed) return {ds4cpp::RouteWaitDecision::Ready, ""};
static std::string wait_route_ready(std::unique_lock<std::mutex> &lock) {
if (!g_distributed) return "";
char err[256] = {0};
const int deadline_polls = g_route_timeout_sec * 10; // 100ms per poll
for (int i = 0; i <= deadline_polls; ++i) {
int ready = ds4_session_distributed_route_ready(g_session, err, sizeof(err));
switch (ds4cpp::DecideRouteWait(ready, context->IsCancelled())) {
case ds4cpp::RouteWaitDecision::Ready:
return {ds4cpp::RouteWaitDecision::Ready, ""};
case ds4cpp::RouteWaitDecision::Error:
return {ds4cpp::RouteWaitDecision::Error,
std::string("ds4 distributed route error: ") +
(err[0] ? err : "unknown")};
case ds4cpp::RouteWaitDecision::Cancelled:
return {ds4cpp::RouteWaitDecision::Cancelled, ""};
case ds4cpp::RouteWaitDecision::Pending:
break;
if (ready == 1) return "";
if (ready < 0) {
return std::string("ds4 distributed route error: ") +
(err[0] ? err : "unknown");
}
if (i == deadline_polls) break;
// Release the lock while sleeping so Status/Health and other RPCs can
// interleave during worker startup.
lock.unlock();
struct timespec ts = {0, 100L * 1000L * 1000L}; // 100ms
nanosleep(&ts, nullptr);
lock.lock();
if (context->IsCancelled()) {
return {ds4cpp::RouteWaitDecision::Cancelled, ""};
}
// A concurrent Free() may have torn down the engine while we slept.
if (!g_engine || !g_session) {
return {ds4cpp::RouteWaitDecision::Error,
"ds4: model unloaded while waiting for distributed route"};
return "ds4: model unloaded while waiting for distributed route";
}
}
if (context->IsCancelled()) {
return {ds4cpp::RouteWaitDecision::Cancelled, ""};
}
return {ds4cpp::RouteWaitDecision::Error,
"ds4 distributed route incomplete: workers not connected (layers uncovered)"};
return "ds4 distributed route incomplete: workers not connected (layers uncovered)";
}
static void append_token_text(ds4_engine *engine, int token, std::string &out) {
@@ -380,9 +341,9 @@ static void collect_done(void *) {}
struct StreamCtx {
ds4_engine *engine;
ServerWriter<backend::Reply> *writer;
ds4cpp::RequestLifecycle *request;
ds4cpp::DsmlParser parser;
int tokens;
bool aborted;
// Track which tool indices we've seen TOOL_START for, so subsequent
// ARGS deltas can elide the redundant id/name fields.
std::vector<bool> tool_started;
@@ -390,7 +351,7 @@ struct StreamCtx {
static void stream_emit(void *ud, int token) {
auto *s = static_cast<StreamCtx *>(ud);
if (!s->request->ShouldContinue()) return;
if (s->aborted) return;
if (token == ds4_token_eos(s->engine)) return;
size_t len = 0;
const char *text = ds4_token_text(s->engine, token, &len);
@@ -440,7 +401,7 @@ static void stream_emit(void *ud, int token) {
reply.set_message(chunk);
reply.set_tokens(1);
if (any_field) {
s->request->ObserveStreamWrite(s->writer->Write(reply));
if (!s->writer->Write(reply)) s->aborted = true;
}
s->tokens++;
}
@@ -796,30 +757,21 @@ public:
return GStatus::OK;
}
GStatus Predict(ServerContext *context, const backend::PredictOptions *request,
GStatus Predict(ServerContext *, const backend::PredictOptions *request,
backend::Reply *reply) override {
std::unique_lock<std::mutex> lock(g_engine_mu);
if (!g_engine || !g_session) {
return GStatus(StatusCode::FAILED_PRECONDITION, "ds4: model not loaded");
}
if (GStatus id = check_model_identity(request); !id.ok()) return id;
RouteWaitResult route = wait_route_ready(lock, context);
if (route.decision == ds4cpp::RouteWaitDecision::Cancelled) {
return GStatus(StatusCode::CANCELLED, "ds4 request cancelled");
}
if (route.decision == ds4cpp::RouteWaitDecision::Error) {
return GStatus(StatusCode::UNAVAILABLE, route.error);
if (std::string route_err = wait_route_ready(lock); !route_err.empty()) {
return GStatus(StatusCode::UNAVAILABLE, route_err);
}
ds4_tokens prompt = {};
build_prompt(g_engine, request, &prompt);
int n_predict = request->tokens() > 0 ? request->tokens() : 256;
const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
const bool starts_in_thinking = think_enabled &&
request->usetokenizertemplate() && request->messages_size() > 0;
CollectCtx collect = {
g_engine, "", ds4cpp::DsmlParser(starts_in_thinking),
reply, 0, {}, "", ""};
ds4cpp::RequestLifecycle lifecycle;
CollectCtx collect = {g_engine, "", {}, reply, 0, {}, "", ""};
std::string cache_key = render_prompt_text(request);
size_t cache_hit = maybe_load_cache(cache_key);
(void)cache_hit; // future: skip prompt prefix if hit covers full prompt
@@ -831,27 +783,15 @@ public:
// Either way g_session advances so the disk KV cache picks up a
// real checkpoint after the call (see maybe_save_cache below).
char err[256] = {0};
int rc;
{
ds4cpp::CancelCallbackScope cancel_scope(
g_session, set_session_cancel, server_context_cancelled, context);
rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
}
int rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
int prompt_len = prompt.len;
ds4_tokens_free(&prompt);
if (rc == DS4_SESSION_SYNC_INTERRUPTED) {
lifecycle.ObserveContextCancellation(true);
}
const bool generation_started = rc == 0;
if (generation_started) {
const int n_predict = ds4cpp::EffectiveGenerationLimit(
request->tokens(), ds4_session_ctx(g_session),
ds4_session_pos(g_session));
if (rc == 0) {
const int eos = ds4_token_eos(g_engine);
const int draft_max = ds4_engine_mtp_draft_tokens(g_engine);
const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
int produced = 0;
while (produced < n_predict) {
if (!request_should_continue(&lifecycle, context)) break;
SampleParams sp = compute_sample_params(request, collect.parser, think_enabled);
int first;
if (sp.temperature <= 0.0f) {
@@ -866,20 +806,13 @@ public:
if (draft_max > 0 && sp.temperature <= 0.0f) {
constexpr int kAcceptedMax = 8;
int accepted[kAcceptedMax];
const int remaining = ds4cpp::RemainingGenerationBudget(
n_predict, produced);
const int cap = ds4cpp::SpeculativeAcceptedCapacity(
remaining, draft_max, kAcceptedMax);
int cap = std::min(kAcceptedMax, draft_max + 1);
int n = ds4_session_eval_speculative_argmax(
g_session, first, remaining, eos,
g_session, first, draft_max, eos,
accepted, cap, err, sizeof(err));
if (n < 0) { rc = -1; break; }
bool stop = false;
for (int j = 0; j < n; ++j) {
if (!request_should_continue(&lifecycle, context)) {
stop = true;
break;
}
if (accepted[j] == eos) { stop = true; break; }
collect_emit(&collect, accepted[j]);
if (++produced >= n_predict) { stop = true; break; }
@@ -888,26 +821,12 @@ public:
} else {
collect_emit(&collect, first);
if (++produced >= n_predict) break;
if (!request_should_continue(&lifecycle, context)) break;
rc = ds4_session_eval(g_session, first, err, sizeof(err));
if (rc != 0) break;
}
}
collect_done(&collect);
}
request_should_continue(&lifecycle, context);
ds4cpp::TerminalDecision terminal = ds4cpp::ResolveTerminalDecision(
rc == DS4_SESSION_SYNC_INTERRUPTED, rc != 0,
!lifecycle.ShouldFinalize());
if (!terminal.should_finalize) {
if (terminal.cause == ds4cpp::TerminalCause::EngineError) {
return GStatus(StatusCode::INTERNAL,
std::string("ds4 generation failed: ") + err);
}
return GStatus(StatusCode::CANCELLED,
"ds4 request cancelled");
}
if (generation_started) collect_done(&collect);
maybe_save_cache(cache_key);
// Flush any buffered parser state.
@@ -915,7 +834,7 @@ public:
collect.parser.Flush(events);
apply_events(&collect, events);
if (terminal.cause == ds4cpp::TerminalCause::EngineError) {
if (rc != 0) {
return GStatus(StatusCode::INTERNAL,
std::string("ds4 generation failed: ") + err);
}
@@ -938,30 +857,21 @@ public:
return GStatus::OK;
}
GStatus PredictStream(ServerContext *context, const backend::PredictOptions *request,
GStatus PredictStream(ServerContext *, const backend::PredictOptions *request,
ServerWriter<backend::Reply> *writer) override {
std::unique_lock<std::mutex> lock(g_engine_mu);
if (!g_engine || !g_session) {
return GStatus(StatusCode::FAILED_PRECONDITION, "ds4: model not loaded");
}
if (GStatus id = check_model_identity(request); !id.ok()) return id;
RouteWaitResult route = wait_route_ready(lock, context);
if (route.decision == ds4cpp::RouteWaitDecision::Cancelled) {
return GStatus(StatusCode::CANCELLED, "ds4 request cancelled");
}
if (route.decision == ds4cpp::RouteWaitDecision::Error) {
return GStatus(StatusCode::UNAVAILABLE, route.error);
if (std::string route_err = wait_route_ready(lock); !route_err.empty()) {
return GStatus(StatusCode::UNAVAILABLE, route_err);
}
ds4_tokens prompt = {};
build_prompt(g_engine, request, &prompt);
int n_predict = request->tokens() > 0 ? request->tokens() : 256;
const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
const bool starts_in_thinking = think_enabled &&
request->usetokenizertemplate() && request->messages_size() > 0;
ds4cpp::RequestLifecycle lifecycle;
StreamCtx s = {
g_engine, writer, &lifecycle,
ds4cpp::DsmlParser(starts_in_thinking), 0, {}};
StreamCtx s = {g_engine, writer, {}, 0, false, {}};
std::string cache_key = render_prompt_text(request);
size_t cache_hit = maybe_load_cache(cache_key);
(void)cache_hit;
@@ -969,26 +879,14 @@ public:
// Manual loop on g_session - see Predict() above for the rationale.
// MTP speculative path used when ds4_engine_mtp_draft_tokens > 0.
char err[256] = {0};
int rc;
{
ds4cpp::CancelCallbackScope cancel_scope(
g_session, set_session_cancel, server_context_cancelled, context);
rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
}
int rc = ds4_session_sync(g_session, &prompt, err, sizeof(err));
ds4_tokens_free(&prompt);
if (rc == DS4_SESSION_SYNC_INTERRUPTED) {
lifecycle.ObserveContextCancellation(true);
}
const bool generation_started = rc == 0;
if (generation_started) {
const int n_predict = ds4cpp::EffectiveGenerationLimit(
request->tokens(), ds4_session_ctx(g_session),
ds4_session_pos(g_session));
if (rc == 0) {
const int eos = ds4_token_eos(g_engine);
const int draft_max = ds4_engine_mtp_draft_tokens(g_engine);
const bool think_enabled = ds4_think_mode_enabled(parse_think_mode(request));
int produced = 0;
while (produced < n_predict) {
if (!request_should_continue(&lifecycle, context)) break;
while (produced < n_predict && !s.aborted) {
SampleParams sp = compute_sample_params(request, s.parser, think_enabled);
int first;
if (sp.temperature <= 0.0f) {
@@ -1002,77 +900,50 @@ public:
if (draft_max > 0 && sp.temperature <= 0.0f) {
constexpr int kAcceptedMax = 8;
int accepted[kAcceptedMax];
const int remaining = ds4cpp::RemainingGenerationBudget(
n_predict, produced);
const int cap = ds4cpp::SpeculativeAcceptedCapacity(
remaining, draft_max, kAcceptedMax);
int cap = std::min(kAcceptedMax, draft_max + 1);
int n = ds4_session_eval_speculative_argmax(
g_session, first, remaining, eos,
g_session, first, draft_max, eos,
accepted, cap, err, sizeof(err));
if (n < 0) { rc = -1; break; }
bool stop = false;
for (int j = 0; j < n; ++j) {
if (!request_should_continue(&lifecycle, context)) {
stop = true;
break;
}
if (accepted[j] == eos) { stop = true; break; }
stream_emit(&s, accepted[j]);
if (!lifecycle.ShouldContinue()) { stop = true; break; }
if (s.aborted) { stop = true; break; }
if (++produced >= n_predict) { stop = true; break; }
}
if (stop) break;
} else {
stream_emit(&s, first);
if (!lifecycle.ShouldContinue() || ++produced >= n_predict) break;
if (!request_should_continue(&lifecycle, context)) break;
if (s.aborted || ++produced >= n_predict) break;
rc = ds4_session_eval(g_session, first, err, sizeof(err));
if (rc != 0) break;
}
}
stream_done(&s);
}
maybe_save_cache(cache_key);
// Flush parser state.
std::vector<ds4cpp::ParserEvent> events;
s.parser.Flush(events);
if (!events.empty() && !s.aborted) {
backend::Reply reply;
auto *delta = reply.add_chat_deltas();
for (const auto &e : events) {
if (e.type == ds4cpp::ParserEvent::CONTENT) {
delta->set_content(delta->content() + e.text);
} else if (e.type == ds4cpp::ParserEvent::REASONING) {
delta->set_reasoning_content(delta->reasoning_content() + e.text);
}
}
s.writer->Write(reply);
}
request_should_continue(&lifecycle, context);
ds4cpp::TerminalDecision terminal = ds4cpp::ResolveTerminalDecision(
rc == DS4_SESSION_SYNC_INTERRUPTED, rc != 0,
!lifecycle.ShouldFinalize());
terminal = ds4cpp::RunPostlude(
terminal,
[&]() {
ds4cpp::DsmlParser staged_parser = s.parser;
std::vector<ds4cpp::ParserEvent> events;
staged_parser.Flush(events);
bool write_succeeded = true;
if (!events.empty()) {
backend::Reply reply;
auto *delta = reply.add_chat_deltas();
for (const auto &e : events) {
if (e.type == ds4cpp::ParserEvent::CONTENT) {
delta->set_content(delta->content() + e.text);
} else if (e.type == ds4cpp::ParserEvent::REASONING) {
delta->set_reasoning_content(
delta->reasoning_content() + e.text);
}
}
write_succeeded = s.writer->Write(reply);
}
lifecycle.ObserveStreamWrite(write_succeeded);
request_should_continue(&lifecycle, context);
if (!lifecycle.ShouldFinalize()) return false;
s.parser = std::move(staged_parser);
if (generation_started) stream_done(&s);
return true;
},
[&]() { maybe_save_cache(cache_key); });
if (terminal.cause == ds4cpp::TerminalCause::EngineError) {
if (rc != 0 && !s.aborted) {
return GStatus(StatusCode::INTERNAL,
std::string("ds4 generation failed: ") + err);
}
if (terminal.cause == ds4cpp::TerminalCause::Cancelled) {
return GStatus(StatusCode::CANCELLED,
"ds4 request cancelled");
}
return GStatus::OK;
}
-111
View File
@@ -1,111 +0,0 @@
// SPDX-License-Identifier: MIT
#pragma once
namespace ds4cpp {
using CancelCallback = bool (*)(void *);
using CancelSetter = void (*)(void *, CancelCallback, void *) noexcept;
class CancelCallbackScope {
public:
CancelCallbackScope(void *target, CancelSetter setter,
CancelCallback callback, void *userdata) noexcept
: target_(target), setter_(setter) {
setter_(target_, callback, userdata);
}
~CancelCallbackScope() noexcept {
setter_(target_, nullptr, nullptr);
}
CancelCallbackScope(const CancelCallbackScope &) = delete;
CancelCallbackScope &operator=(const CancelCallbackScope &) = delete;
private:
void *target_;
CancelSetter setter_;
};
enum class RouteWaitDecision {
Pending,
Ready,
Error,
Cancelled,
};
inline RouteWaitDecision DecideRouteWait(int route_status, bool cancelled) {
if (cancelled) return RouteWaitDecision::Cancelled;
if (route_status > 0) return RouteWaitDecision::Ready;
if (route_status < 0) return RouteWaitDecision::Error;
return RouteWaitDecision::Pending;
}
enum class TerminalCause {
Success,
Cancelled,
EngineError,
};
inline TerminalCause DecideTerminalCause(bool sync_interrupted,
bool engine_error,
bool abandoned) {
if (sync_interrupted) return TerminalCause::Cancelled;
if (engine_error) return TerminalCause::EngineError;
if (abandoned) return TerminalCause::Cancelled;
return TerminalCause::Success;
}
struct TerminalDecision {
TerminalCause cause;
bool should_finalize;
};
inline TerminalDecision ResolveTerminalDecision(bool sync_interrupted,
bool engine_error,
bool abandoned) {
return {
DecideTerminalCause(sync_interrupted, engine_error, abandoned),
!sync_interrupted && !abandoned,
};
}
template <typename Finalize, typename Persist>
TerminalDecision RunPostlude(TerminalDecision terminal,
Finalize transactional_finalize,
Persist persist) {
if (!terminal.should_finalize) return terminal;
if (!transactional_finalize()) {
terminal.should_finalize = false;
if (terminal.cause != TerminalCause::EngineError) {
terminal.cause = TerminalCause::Cancelled;
}
return terminal;
}
persist();
return terminal;
}
class RequestLifecycle {
public:
void ObserveContextCancellation(bool cancelled) {
context_cancelled_ = context_cancelled_ || cancelled;
}
void ObserveStreamWrite(bool succeeded) {
stream_write_aborted_ = stream_write_aborted_ || !succeeded;
}
bool ShouldContinue() const {
return !context_cancelled_ && !stream_write_aborted_;
}
bool ShouldFinalize() const {
return ShouldContinue();
}
private:
bool context_cancelled_ = false;
bool stream_write_aborted_ = false;
};
} // namespace ds4cpp
-414
View File
@@ -1,414 +0,0 @@
// SPDX-License-Identifier: MIT
// Standalone regression tests for DS4 request cancellation policy.
#include "request_lifecycle.h"
#include <cstdio>
namespace {
int failures = 0;
struct FakeCancelTarget {
ds4cpp::CancelCallback callback = nullptr;
void *userdata = nullptr;
int installs = 0;
int clears = 0;
};
struct PostludeCounts {
int finalize_attempts = 0;
int finalize_commits = 0;
int cache_persists = 0;
bool cache_followed_commit = true;
};
ds4cpp::TerminalDecision run_fake_postlude(
ds4cpp::TerminalDecision terminal, bool finalize_succeeds,
PostludeCounts *counts) {
return ds4cpp::RunPostlude(
terminal,
[=]() {
counts->finalize_attempts++;
if (!finalize_succeeds) return false;
counts->finalize_commits++;
return true;
},
[=]() {
counts->cache_followed_commit = counts->finalize_commits == 1;
counts->cache_persists++;
});
}
bool fake_cancel(void *) {
return false;
}
void fake_set_cancel(void *target, ds4cpp::CancelCallback callback,
void *userdata) noexcept {
auto *fake = static_cast<FakeCancelTarget *>(target);
fake->callback = callback;
fake->userdata = userdata;
if (callback) {
fake->installs++;
} else {
fake->clears++;
}
}
void check(bool condition, const char *name) {
if (condition) return;
std::fprintf(stderr, "FAIL %s\n", name);
failures++;
}
// Production mutation caught: treating an active request as abandoned would
// skip its parser finalization and cache save.
void test_active_request_continues_and_finalizes() {
ds4cpp::RequestLifecycle request;
check(request.ShouldContinue(), "active:continue");
check(request.ShouldFinalize(), "active:finalize");
}
// Production mutation caught: omitting the ServerContext cancellation branch
// would continue decoding and finalize a partial response.
void test_context_cancellation_stops_without_finalizing() {
ds4cpp::RequestLifecycle request;
request.ObserveContextCancellation(true);
check(!request.ShouldContinue(), "context_cancelled:stop");
check(!request.ShouldFinalize(), "context_cancelled:no_finalize");
}
// Production mutation caught: ignoring ServerWriter::Write failure would keep
// streaming and finalize a response whose client has gone away.
void test_stream_write_abort_stops_without_finalizing() {
ds4cpp::RequestLifecycle request;
request.ObserveStreamWrite(false);
check(!request.ShouldContinue(), "write_abort:stop");
check(!request.ShouldFinalize(), "write_abort:no_finalize");
}
// Production mutation caught: combining cancellation and write failure with
// AND would fail to stop when either signal occurs on its own.
void test_cancellation_and_write_abort_are_independent_or_conditions() {
ds4cpp::RequestLifecycle cancelled;
cancelled.ObserveContextCancellation(true);
cancelled.ObserveStreamWrite(true);
ds4cpp::RequestLifecycle write_aborted;
write_aborted.ObserveContextCancellation(false);
write_aborted.ObserveStreamWrite(false);
check(!cancelled.ShouldContinue(), "or:context_only");
check(!write_aborted.ShouldContinue(), "or:write_only");
}
// Production mutation caught: treating an incomplete distributed route as an
// error would return before workers have time to connect.
void test_route_wait_pending() {
check(ds4cpp::DecideRouteWait(0, false) ==
ds4cpp::RouteWaitDecision::Pending,
"route_wait:pending");
}
// Production mutation caught: failing to recognize a complete route would
// keep a ready inference request in the polling loop.
void test_route_wait_ready() {
check(ds4cpp::DecideRouteWait(1, false) ==
ds4cpp::RouteWaitDecision::Ready,
"route_wait:ready");
}
// Production mutation caught: ignoring a route probe error would poll until a
// misleading timeout instead of returning UNAVAILABLE promptly.
void test_route_wait_error() {
check(ds4cpp::DecideRouteWait(-1, false) ==
ds4cpp::RouteWaitDecision::Error,
"route_wait:error");
}
// Production mutation caught: omitting cancellation from route waiting would
// leave an abandoned request blocked until the distributed timeout.
void test_route_wait_cancellation() {
check(ds4cpp::DecideRouteWait(0, true) ==
ds4cpp::RouteWaitDecision::Cancelled,
"route_wait:cancelled");
}
// Production mutation caught: checking route errors before cancellation would
// report UNAVAILABLE for a request the client already abandoned.
void test_route_wait_cancellation_precedes_error() {
check(ds4cpp::DecideRouteWait(-1, true) ==
ds4cpp::RouteWaitDecision::Cancelled,
"route_wait:cancellation_precedence");
}
// Production mutation caught: classifying a successful active request as a
// terminal failure would suppress its normal response finalization.
void test_terminal_success() {
check(ds4cpp::DecideTerminalCause(false, false, false) ==
ds4cpp::TerminalCause::Success,
"terminal:success");
}
// Production mutation caught: treating DS4's cooperative sync interruption
// as an ordinary engine error would return INTERNAL instead of CANCELLED.
void test_terminal_sync_interruption_is_cancelled() {
check(ds4cpp::DecideTerminalCause(true, true, true) ==
ds4cpp::TerminalCause::Cancelled,
"terminal:sync_interrupted");
}
// Production mutation caught: treating every nonzero engine result as client
// abandonment would hide genuine DS4 failures behind CANCELLED.
void test_terminal_engine_error() {
check(ds4cpp::DecideTerminalCause(false, true, false) ==
ds4cpp::TerminalCause::EngineError,
"terminal:engine_error");
}
// Production mutation caught: ignoring an rc==0 context cancellation would
// finalize and cache an abandoned request.
void test_terminal_context_abandonment() {
ds4cpp::RequestLifecycle request;
request.ObserveContextCancellation(true);
check(ds4cpp::DecideTerminalCause(
false, false, !request.ShouldFinalize()) ==
ds4cpp::TerminalCause::Cancelled,
"terminal:context_abandonment");
}
// Production mutation caught: ignoring an rc==0 stream write failure would
// finalize and cache an abandoned streaming request.
void test_terminal_write_abandonment() {
ds4cpp::RequestLifecycle request;
request.ObserveStreamWrite(false);
check(ds4cpp::DecideTerminalCause(
false, false, !request.ShouldFinalize()) ==
ds4cpp::TerminalCause::Cancelled,
"terminal:write_abandonment");
}
// Production mutation caught: checking late cancellation or write failure
// before a determined ordinary DS4 error would replace INTERNAL with CANCELLED.
void test_terminal_engine_error_precedes_late_abandonment() {
ds4cpp::RequestLifecycle cancelled;
cancelled.ObserveContextCancellation(true);
ds4cpp::RequestLifecycle write_aborted;
write_aborted.ObserveStreamWrite(false);
check(ds4cpp::DecideTerminalCause(
false, true, !cancelled.ShouldFinalize()) ==
ds4cpp::TerminalCause::EngineError,
"terminal:engine_error_precedes_cancellation");
check(ds4cpp::DecideTerminalCause(
false, true, !write_aborted.ShouldFinalize()) ==
ds4cpp::TerminalCause::EngineError,
"terminal:engine_error_precedes_write_abort");
}
// Production mutation caught: using status precedence alone to gate side
// effects would finalize and persist an engine-error request abandoned later.
void test_abandoned_engine_error_keeps_internal_without_finalizing() {
ds4cpp::RequestLifecycle request;
request.ObserveContextCancellation(true);
ds4cpp::TerminalDecision terminal = ds4cpp::ResolveTerminalDecision(
false, true, !request.ShouldFinalize());
check(terminal.cause == ds4cpp::TerminalCause::EngineError,
"terminal_decision:abandoned_engine_error_status");
check(!terminal.should_finalize,
"terminal_decision:abandoned_engine_error_no_finalize");
}
// Production mutation caught: suppressing side effects for every engine error
// would change the existing finalization and cache behavior of active failures.
void test_active_engine_error_still_finalizes() {
ds4cpp::RequestLifecycle request;
ds4cpp::TerminalDecision terminal = ds4cpp::ResolveTerminalDecision(
false, true, !request.ShouldFinalize());
check(terminal.cause == ds4cpp::TerminalCause::EngineError,
"terminal_decision:active_engine_error_status");
check(terminal.should_finalize,
"terminal_decision:active_engine_error_finalize");
}
// Production mutation caught: persisting before committed finalization would
// cache a state whose final buffered stream reply was never completed.
void test_postlude_active_success_commits_then_persists() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::Success, true}, true, &counts);
check(terminal.cause == ds4cpp::TerminalCause::Success,
"postlude:success_outcome");
check(terminal.should_finalize, "postlude:success_committed");
check(counts.finalize_attempts == 1, "postlude:success_attempts");
check(counts.finalize_commits == 1, "postlude:success_commits");
check(counts.cache_persists == 1, "postlude:success_cache");
check(counts.cache_followed_commit, "postlude:success_cache_order");
}
// Production mutation caught: starting the postlude for an already-cancelled
// request would flush buffered parser state or persist an abandoned session.
void test_postlude_cancellation_skips_all_side_effects() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::Cancelled, false}, true, &counts);
check(terminal.cause == ds4cpp::TerminalCause::Cancelled,
"postlude:cancelled_outcome");
check(counts.finalize_attempts == 0, "postlude:cancelled_attempts");
check(counts.finalize_commits == 0, "postlude:cancelled_commits");
check(counts.cache_persists == 0, "postlude:cancelled_cache");
}
// Production mutation caught: committing the live parser or cache after a
// failed final Write would publish an abandoned streaming postlude.
void test_postlude_finalize_failure_cancels_without_commit_or_cache() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::Success, true}, false, &counts);
check(terminal.cause == ds4cpp::TerminalCause::Cancelled,
"postlude:write_failure_outcome");
check(!terminal.should_finalize, "postlude:write_failure_not_committed");
check(counts.finalize_attempts == 1, "postlude:write_failure_attempts");
check(counts.finalize_commits == 0, "postlude:write_failure_commits");
check(counts.cache_persists == 0, "postlude:write_failure_cache");
}
// Production mutation caught: skipping the postlude for every engine error
// would change active internal-error finalization and cache behavior.
void test_postlude_active_engine_error_finalizes_and_persists() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::EngineError, true}, true, &counts);
check(terminal.cause == ds4cpp::TerminalCause::EngineError,
"postlude:engine_error_outcome");
check(counts.finalize_attempts == 1, "postlude:engine_error_attempts");
check(counts.finalize_commits == 1, "postlude:engine_error_commits");
check(counts.cache_persists == 1, "postlude:engine_error_cache");
check(counts.cache_followed_commit, "postlude:engine_error_cache_order");
}
// Production mutation caught: replacing every failed transactional finalize
// with cancellation would hide an already-determined engine error.
void test_postlude_engine_error_finalize_failure_preserves_internal() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::EngineError, true}, false, &counts);
check(terminal.cause == ds4cpp::TerminalCause::EngineError,
"postlude:engine_error_write_failure_outcome");
check(!terminal.should_finalize,
"postlude:engine_error_write_failure_not_committed");
check(counts.finalize_attempts == 1,
"postlude:engine_error_write_failure_attempts");
check(counts.finalize_commits == 0,
"postlude:engine_error_write_failure_commits");
check(counts.cache_persists == 0,
"postlude:engine_error_write_failure_cache");
}
// Production mutation caught: status precedence must not grant side-effect
// permission to an engine-error request that was also abandoned.
void test_postlude_abandoned_engine_error_skips_all_side_effects() {
PostludeCounts counts;
ds4cpp::TerminalDecision terminal = run_fake_postlude(
{ds4cpp::TerminalCause::EngineError, false}, true, &counts);
check(terminal.cause == ds4cpp::TerminalCause::EngineError,
"postlude:abandoned_engine_error_outcome");
check(counts.finalize_attempts == 0,
"postlude:abandoned_engine_error_attempts");
check(counts.finalize_commits == 0,
"postlude:abandoned_engine_error_commits");
check(counts.cache_persists == 0,
"postlude:abandoned_engine_error_cache");
}
// Production mutation caught: failing to install the request callback would
// make DS4 prompt synchronization unable to observe client cancellation.
void test_cancel_callback_scope_installs_callback() {
FakeCancelTarget target;
int request_context = 42;
{
ds4cpp::CancelCallbackScope scope(
&target, fake_set_cancel, fake_cancel, &request_context);
check(target.callback == fake_cancel, "cancel_scope:callback_installed");
check(target.userdata == &request_context, "cancel_scope:userdata_installed");
check(target.installs == 1, "cancel_scope:installed_once");
}
}
// Production mutation caught: failing to clear the callback at every scope
// exit would leave DS4 pointing at a destroyed stack-owned ServerContext.
void test_cancel_callback_scope_clears_callback() {
FakeCancelTarget target;
int request_context = 42;
{
ds4cpp::CancelCallbackScope scope(
&target, fake_set_cancel, fake_cancel, &request_context);
}
check(target.callback == nullptr, "cancel_scope:callback_cleared");
check(target.userdata == nullptr, "cancel_scope:userdata_cleared");
check(target.clears == 1, "cancel_scope:cleared_once");
}
} // namespace
int main() {
test_active_request_continues_and_finalizes();
test_context_cancellation_stops_without_finalizing();
test_stream_write_abort_stops_without_finalizing();
test_cancellation_and_write_abort_are_independent_or_conditions();
test_route_wait_pending();
test_route_wait_ready();
test_route_wait_error();
test_route_wait_cancellation();
test_route_wait_cancellation_precedes_error();
test_terminal_success();
test_terminal_sync_interruption_is_cancelled();
test_terminal_engine_error();
test_terminal_context_abandonment();
test_terminal_write_abandonment();
test_terminal_engine_error_precedes_late_abandonment();
test_abandoned_engine_error_keeps_internal_without_finalizing();
test_active_engine_error_still_finalizes();
test_postlude_active_success_commits_then_persists();
test_postlude_cancellation_skips_all_side_effects();
test_postlude_finalize_failure_cancels_without_commit_or_cache();
test_postlude_active_engine_error_finalizes_and_persists();
test_postlude_engine_error_finalize_failure_preserves_internal();
test_postlude_abandoned_engine_error_skips_all_side_effects();
test_cancel_callback_scope_installs_callback();
test_cancel_callback_scope_clears_callback();
if (failures == 0) {
std::fprintf(stderr, "all request_lifecycle checks passed\n");
return 0;
}
std::fprintf(stderr, "%d check(s) failed\n", failures);
return 1;
}
+1 -1
View File
@@ -1,5 +1,5 @@
IK_LLAMA_VERSION?=3e416d7f5a9d4cc3195e8171dbf891541ca59c6a
IK_LLAMA_VERSION?=a7c81affa48c6800d63111bdb33469a01d062daa
LLAMA_REPO?=https://github.com/ikawrakow/ik_llama.cpp
CMAKE_ARGS?=
-1
View File
@@ -2565,7 +2565,6 @@ public:
grpc::Status Embedding(ServerContext* context, const backend::PredictOptions* request, backend::EmbeddingResult* embeddingResult) {
auto identity = checkModelIdentity(request);
if (!identity.ok()) return identity;
embeddingResult->set_layout(backend::EMBEDDING_LAYOUT_FINAL);
json data = parse_options(false, request, llama);
const int task_id = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(task_id);
-5
View File
@@ -120,9 +120,4 @@ if(LLAMA_GRPC_BUILD_TESTS)
target_include_directories(tts_request_options_test PRIVATE ${CMAKE_CURRENT_SOURCE_DIR})
target_compile_features(tts_request_options_test PRIVATE cxx_std_17)
add_test(NAME tts_request_options_test COMMAND tts_request_options_test)
add_executable(thread_params_test thread_params_test.cpp thread_params.h)
target_include_directories(thread_params_test PRIVATE ${CMAKE_CURRENT_SOURCE_DIR})
target_compile_features(thread_params_test PRIVATE cxx_std_17)
add_test(NAME thread_params_test COMMAND thread_params_test)
endif()
+1 -1
View File
@@ -1,5 +1,5 @@
LLAMA_VERSION?=434ddbbc0e30522e897670681e503b797c12b7c1
LLAMA_VERSION?=9de0fcf2b3e587a43f293d9a2b6ec0a32991f768
LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
CMAKE_ARGS?=
+70 -88
View File
@@ -53,7 +53,6 @@
#include "arg.h"
#include "chat-auto-parser.h"
#include "llama_compat.h" // fork-skew switches, generated by prepare.sh
#include "thread_params.h"
#include "message_content.h"
#include "passthrough_options.h"
#include "tts_request_options.h"
@@ -88,12 +87,6 @@ using grpc::ServerBuilder;
using grpc::ServerContext;
using grpc::Status;
#if LOCALAI_HAS_MTMD_INIT_OPT
#define LOCALAI_MTMD_INIT_OPT_ARG(value) , value
#else
#define LOCALAI_MTMD_INIT_OPT_ARG(value)
#endif
// gRPC bearer token auth for distributed mode.
// Reads LOCALAI_GRPC_AUTH_TOKEN from the environment. When set, rejects
// requests without a matching "authorization: Bearer <token>" metadata header.
@@ -300,7 +293,7 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, const
} else {
SRV_WRN("[TOOLS DEBUG] parse_options: Parsed tools JSON is not an array: %s\n", tools_json.dump().c_str());
}
} catch (const common_json_error& e) {
} catch (const json::parse_error& e) {
SRV_WRN("Failed to parse tools JSON from proto: %s\n", e.what());
SRV_WRN("[TOOLS DEBUG] parse_options: Tools string that failed to parse: %s\n", predict->tools().c_str());
}
@@ -330,7 +323,7 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, const
SRV_DBG("[TOOLS DEBUG] Received tool_choice object from Go layer: %s\n", tool_choice_json.dump().c_str());
}
SRV_INF("Extracted tool_choice from proto: %s\n", predict->toolchoice().c_str());
} catch (const common_json_error& e) {
} catch (const json::parse_error& e) {
// If parsing fails, treat as string
data["tool_choice"] = predict->toolchoice();
SRV_INF("Extracted tool_choice as string: %s\n", predict->toolchoice().c_str());
@@ -359,7 +352,7 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, const
// Add to data - llama.cpp server expects it as an object (map)
data["logit_bias"] = logit_bias_json;
SRV_INF("Using logit_bias: %s\n", predict->logitbias().c_str());
} catch (const common_json_error& e) {
} catch (const json::parse_error& e) {
SRV_ERR("Failed to parse logit_bias JSON from proto: %s\n", e.what());
}
}
@@ -404,10 +397,7 @@ json parse_options(bool streaming, const backend::PredictOptions* predict, const
});
}
data["stop"] = json::array();
for (const auto & stop : predict->stopprompts()) {
data["stop"].push_back(stop);
}
data["stop"] = predict->stopprompts();
// data["n_probs"] = predict->nprobs();
//TODO: images,
@@ -1125,16 +1115,14 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
try {
int n = std::stoi(optval_str);
if (n < 0) n = 0;
#if LOCALAI_HAS_N_CPU_FFN_HELPER
llm_add_n_cpu_ffn_overrides(n, LLM_FFN_EXPS_REGEX, params.speculative.draft.tensor_buft_overrides);
#else
// Keep override-name storage alive for the lifetime of the params struct
// (mirrors upstream arg.cpp behavior with a function-local static).
static std::list<std::string> buft_overrides_draft;
for (int i = 0; i < n; ++i) {
buft_overrides_draft.push_back(llm_ffn_exps_block_regex(i));
params.speculative.draft.tensor_buft_overrides.push_back(
{buft_overrides_draft.back().c_str(), ggml_backend_cpu_buffer_type()});
}
#endif
} catch (...) {}
}
@@ -1152,16 +1140,14 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
try {
int n = std::stoi(optval_str);
if (n < 0) n = 0;
#if LOCALAI_HAS_N_CPU_FFN_HELPER
llm_add_n_cpu_ffn_overrides(n, LLM_FFN_EXPS_REGEX, params.tensor_buft_overrides);
#else
// Keep override-name storage alive for the lifetime of the
// params struct (mirrors upstream arg.cpp's function-local static).
static std::list<std::string> buft_overrides_main;
for (int i = 0; i < n; ++i) {
buft_overrides_main.push_back(llm_ffn_exps_block_regex(i));
params.tensor_buft_overrides.push_back(
{buft_overrides_main.back().c_str(), ggml_backend_cpu_buffer_type()});
}
#endif
} catch (...) {}
}
@@ -1426,12 +1412,6 @@ static void params_parse(server_context& /*ctx_server*/, const backend::ModelOpt
passthrough_draft_gpu_layers);
}
// The library initializer now creates both threadpools before the server
// can apply llama_context's fallback for the -1 batch-thread sentinel.
params.cpuparams_batch.n_threads = llama_grpc::resolve_batch_threads(
params.cpuparams_batch.n_threads,
params.cpuparams.n_threads);
#ifndef LOCALAI_LLAMA_CPP_NO_SCORE_TASK
// Score-task suffix forking: reserve seq ids (and recurrent-state cells)
// beyond the slots so one scoring call decodes all candidate tails in a
@@ -1808,7 +1788,7 @@ public:
for (int j = 0; j < request->audios_size(); j++) rin.audios.push_back(request->audios(j));
for (int j = 0; j < request->videos_size(); j++) rin.videos.push_back(request->videos(j));
}
messages_json.push_back(json::parse(llama_grpc::build_reconstructed_message(rin).dump()));
messages_json.push_back(llama_grpc::build_reconstructed_message(rin));
}
// Final safety check: Ensure no message has null content (Jinja templates require strings)
@@ -2001,7 +1981,7 @@ public:
if (!body_json.contains("chat_template_kwargs")) {
body_json["chat_template_kwargs"] = json::object();
}
for (auto el : ctk.items()) {
for (auto& el : ctk.items()) {
body_json["chat_template_kwargs"][el.key()] = el.value();
}
}
@@ -2087,27 +2067,30 @@ public:
// If not using chat templates, extract files from image_data/audio_data fields
// (If using chat templates, files were already extracted by oaicompat_chat_params_parse)
if (!request->usetokenizertemplate() || request->messages_size() == 0 || ctx_server.impl->chat_params.tmpls == nullptr) {
if (data.contains("image_data") && data.at("image_data").is_array())
const auto &images_data = data.find("image_data");
if (images_data != data.end() && images_data->is_array())
{
for (const auto &img : data.at("image_data"))
for (const auto &img : *images_data)
{
auto decoded_data = base64_decode(img["data"].get<std::string>());
files.push_back(decoded_data);
}
}
if (data.contains("audio_data") && data.at("audio_data").is_array())
const auto &audio_data = data.find("audio_data");
if (audio_data != data.end() && audio_data->is_array())
{
for (const auto &audio : data.at("audio_data"))
for (const auto &audio : *audio_data)
{
auto decoded_data = base64_decode(audio["data"].get<std::string>());
files.push_back(decoded_data);
}
}
if (data.contains("video_data") && data.at("video_data").is_array())
const auto &video_data = data.find("video_data");
if (video_data != data.end() && video_data->is_array())
{
for (const auto &video : data.at("video_data"))
for (const auto &video : *video_data)
{
auto decoded_data = base64_decode(video["data"].get<std::string>());
files.push_back(decoded_data);
@@ -2121,10 +2104,10 @@ public:
std::vector<server_tokens> inputs;
if (has_mtmd) {
// multimodal
inputs.push_back(process_mtmd_prompt(ctx_server.impl->mctx, prompt_str, files LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt)));
inputs.push_back(process_mtmd_prompt(ctx_server.impl->mctx, prompt_str, files));
} else {
// Everything else, including multimodal completions.
inputs = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt_str, true, true LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt));
inputs = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt_str, true, true);
}
tasks.reserve(inputs.size());
@@ -2380,7 +2363,7 @@ public:
for (int j = 0; j < request->audios_size(); j++) rin.audios.push_back(request->audios(j));
for (int j = 0; j < request->videos_size(); j++) rin.videos.push_back(request->videos(j));
}
messages_json.push_back(json::parse(llama_grpc::build_reconstructed_message(rin).dump()));
messages_json.push_back(llama_grpc::build_reconstructed_message(rin));
}
// Final safety check: Ensure no message has null content (Jinja templates require strings)
@@ -2573,7 +2556,7 @@ public:
if (!body_json.contains("chat_template_kwargs")) {
body_json["chat_template_kwargs"] = json::object();
}
for (auto el : ctk.items()) {
for (auto& el : ctk.items()) {
body_json["chat_template_kwargs"][el.key()] = el.value();
}
}
@@ -2659,10 +2642,11 @@ public:
// If not using chat templates, extract files from image_data/audio_data fields
// (If using chat templates, files were already extracted by oaicompat_chat_params_parse)
if (!request->usetokenizertemplate() || request->messages_size() == 0 || ctx_server.impl->chat_params.tmpls == nullptr) {
if (data.contains("image_data") && data.at("image_data").is_array())
const auto &images_data = data.find("image_data");
if (images_data != data.end() && images_data->is_array())
{
std::cout << "[PREDICT] Processing " << data.at("image_data").size() << " images" << std::endl;
for (const auto &img : data.at("image_data"))
std::cout << "[PREDICT] Processing " << images_data->size() << " images" << std::endl;
for (const auto &img : *images_data)
{
std::cout << "[PREDICT] Processing image" << std::endl;
auto decoded_data = base64_decode(img["data"].get<std::string>());
@@ -2670,18 +2654,20 @@ public:
}
}
if (data.contains("audio_data") && data.at("audio_data").is_array())
const auto &audio_data = data.find("audio_data");
if (audio_data != data.end() && audio_data->is_array())
{
for (const auto &audio : data.at("audio_data"))
for (const auto &audio : *audio_data)
{
auto decoded_data = base64_decode(audio["data"].get<std::string>());
files.push_back(decoded_data);
}
}
if (data.contains("video_data") && data.at("video_data").is_array())
const auto &video_data = data.find("video_data");
if (video_data != data.end() && video_data->is_array())
{
for (const auto &video : data.at("video_data"))
for (const auto &video : *video_data)
{
auto decoded_data = base64_decode(video["data"].get<std::string>());
files.push_back(decoded_data);
@@ -2696,10 +2682,10 @@ public:
std::vector<server_tokens> inputs;
if (has_mtmd) {
// multimodal
inputs.push_back(process_mtmd_prompt(ctx_server.impl->mctx, prompt_str, files LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt)));
inputs.push_back(process_mtmd_prompt(ctx_server.impl->mctx, prompt_str, files));
} else {
// Everything else, including multimodal completions.
inputs = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt_str, true, true LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt));
inputs = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt_str, true, true);
}
tasks.reserve(inputs.size());
@@ -2886,7 +2872,7 @@ public:
json prompt = body.at("embeddings");
auto tokenized_prompts = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt, true, true LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt));
auto tokenized_prompts = tokenize_input_prompts(ctx_server.impl->vocab, ctx_server.impl->mctx, prompt, true, true);
for (const auto & tokens : tokenized_prompts) {
// this check is necessary for models that do not add BOS token to the input
if (tokens.empty()) {
@@ -2925,40 +2911,42 @@ public:
return grpc::Status(grpc::StatusCode::INTERNAL, all_results.error->to_json().value("message", "Error in receiving results"));
}
// Extract the embeddings typed, straight from the task results (no
// JSON round-trip), and report the payload shape alongside the same
// flat float array as before: dim is the embedding width, tokens the
// number of vectors packed into `embeddings` (1 per prompt when the
// server pooled, one per token with pooling:none; summed across
// prompts if the request carried several), prompt_tokens the prompt
// tokens evaluated, for usage accounting. Consumers seeing 0/0 know
// the backend predates shape reporting.
int32_t n_vectors = 0;
int32_t dim = 0;
int32_t prompt_tokens = 0;
// Collect responses
json responses = json::array();
for (auto & res : all_results.results) {
auto * embd_res = dynamic_cast<server_task_result_embd*>(res.get());
GGML_ASSERT(embd_res != nullptr);
prompt_tokens += embd_res->n_tokens;
for (const auto & vec : embd_res->embedding) {
for (const float value : vec) {
embeddingResult->add_embeddings(value);
GGML_ASSERT(dynamic_cast<server_task_result_embd*>(res.get()) != nullptr);
responses.push_back(res->to_json());
}
std::cout << "[DEBUG] Responses size: " << responses.size() << std::endl;
// Process the responses and extract embeddings
for (const auto & response_elem : responses) {
// Check if the response has an "embedding" field
if (response_elem.contains("embedding")) {
json embedding_data = json_value(response_elem, "embedding", json::array());
if (embedding_data.is_array() && !embedding_data.empty()) {
for (const auto & embedding_vector : embedding_data) {
if (embedding_vector.is_array()) {
for (const auto & embedding_value : embedding_vector) {
embeddingResult->add_embeddings(embedding_value.get<float>());
}
}
}
}
if (!vec.empty()) {
n_vectors++;
dim = (int32_t) vec.size();
} else {
// Check if the response itself contains the embedding data directly
if (response_elem.is_array()) {
for (const auto & embedding_value : response_elem) {
embeddingResult->add_embeddings(embedding_value.get<float>());
}
}
}
}
embeddingResult->set_tokens(n_vectors);
embeddingResult->set_dim(dim);
embeddingResult->set_prompt_tokens(prompt_tokens);
embeddingResult->set_layout(
llama_pooling_type(ctx_server.get_llama_context()) == LLAMA_POOLING_TYPE_NONE
? backend::EMBEDDING_LAYOUT_PER_TOKEN
: backend::EMBEDDING_LAYOUT_FINAL);
std::cout << "[DEBUG] Embedding vectors: " << n_vectors << " x " << dim << std::endl;
return grpc::Status::OK;
}
@@ -2991,7 +2979,7 @@ public:
tasks.reserve(documents.size());
for (size_t i = 0; i < documents.size(); i++) {
auto tmp = format_prompt_rerank(ctx_server.impl->model_tgt, ctx_server.impl->vocab, ctx_server.impl->mctx, request->query(), documents[i] LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt));
auto tmp = format_prompt_rerank(ctx_server.impl->model_tgt, ctx_server.impl->vocab, ctx_server.impl->mctx, request->query(), documents[i]);
server_task task = server_task(SERVER_TASK_TYPE_RERANK);
task.id = rd.queue_tasks.get_new_id();
task.index = i;
@@ -3012,7 +3000,7 @@ public:
}
// Collect responses
std::vector<json> responses;
json responses = json::array();
for (auto & res : all_results.results) {
GGML_ASSERT(dynamic_cast<server_task_result_rerank*>(res.get()) != nullptr);
responses.push_back(res->to_json());
@@ -3025,7 +3013,7 @@ public:
// Crop results by request.top_n if specified
int top_n = request->top_n();
if (top_n > 0 && top_n < static_cast<int>(responses.size())) {
responses.resize(top_n);
responses = json(responses.begin(), responses.begin() + top_n);
}
// Set usage information
backend::Usage* usage = rerankResult->mutable_usage();
@@ -3072,7 +3060,7 @@ public:
return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT, opts.error);
}
auto wrapper = mtmd_helper_bitmap_init_from_file(ctx_server.impl->mctx, opts.voice_path.c_str(), false LOCALAI_MTMD_INIT_OPT_ARG(ctx_server.impl->init_opt));
auto wrapper = mtmd_helper_bitmap_init_from_file(ctx_server.impl->mctx, opts.voice_path.c_str(), false);
if (!wrapper.bitmap) {
return grpc::Status(grpc::StatusCode::INVALID_ARGUMENT,
"failed to read speaker reference audio: " + opts.voice_path);
@@ -3609,15 +3597,9 @@ public:
// Populate the response with metrics
response->set_slot_id(0);
response->set_prompt_json_for_slot("");
#if LOCALAI_HAS_SERVER_METRICS
response->set_tokens_per_second(res_metrics->metrics.prompt_bucket.n_per_second());
response->set_tokens_generated(res_metrics->metrics.predict.count);
response->set_prompt_tokens_processed(res_metrics->metrics.prompt.count);
#else
response->set_tokens_per_second(res_metrics->n_prompt_tokens_processed ? 1.e3 / res_metrics->t_prompt_processing * res_metrics->n_prompt_tokens_processed : 0.);
response->set_tokens_generated(res_metrics->n_tokens_predicted_total);
response->set_prompt_tokens_processed(res_metrics->n_prompt_tokens_processed_total);
#endif
return grpc::Status::OK;
+3 -4
View File
@@ -52,15 +52,14 @@ inline nlohmann::ordered_json normalize_message_content(const std::string& role,
// (#7528). A multimodal user message legitimately carries a typed-part array
// ({type:text}, {type:image_url}, ...), which must be left intact. Shared by the
// streaming and non-streaming paths so this invariant cannot drift between them.
template <typename Json>
inline void normalize_template_message(Json& msg) {
inline void normalize_template_message(nlohmann::ordered_json& msg) {
if (!msg.contains("content")) {
msg["content"] = ""; // templates expect the field to exist
return;
}
auto& content = msg["content"];
nlohmann::ordered_json& content = msg["content"];
const std::string role = (msg.contains("role") && msg["role"].is_string())
? msg["role"].template get<std::string>()
? msg["role"].get<std::string>()
: std::string();
if (content.is_null()) {
content = ""; // #7324: null would crash content[:N] slicing
@@ -1,20 +1,8 @@
From 75220a0d74892e3315f4042274b1efa6195868d8 Mon Sep 17 00:00:00 2001
From: Codex <codex@local>
Date: Mon, 10 Aug 2026 23:05:52 +0000
Subject: [PATCH 1/2] score-patch
---
common/common.cpp | 6 +-
common/common.h | 3 +
tools/server/server-context.cpp | 358 +++++++++++++++++++++++++++++++-
tools/server/server-task.h | 47 +++++
4 files changed, 405 insertions(+), 9 deletions(-)
diff --git a/common/common.cpp b/common/common.cpp
index 2e3f14c..0cec0dc 100644
index 8f13217..fc584e1 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -1636,8 +1636,10 @@ struct llama_context_params common_context_params_to_llama(const common_params &
@@ -1591,8 +1591,10 @@ struct llama_context_params common_context_params_to_llama(const common_params &
auto cparams = llama_context_default_params();
cparams.n_ctx = params.n_ctx;
@@ -25,13 +13,13 @@ index 2e3f14c..0cec0dc 100644
+ cparams.n_seq_max = params.n_parallel + params.n_seq_score_forks;
+ cparams.n_rs_seq = std::max(params.speculative.need_n_rs_seq(), (uint32_t) std::max(0, params.n_rs_seq));
cparams.n_outputs_max = std::max(params.n_outputs_max, 0);
cparams.n_outputs_max_per_seq = std::max(params.n_outputs_max_per_seq, 0);
cparams.n_batch = params.n_batch;
cparams.n_ubatch = params.n_ubatch;
diff --git a/common/common.h b/common/common.h
index 878534d..4001df2 100644
index bffc176..e313bd6 100644
--- a/common/common.h
+++ b/common/common.h
@@ -445,6 +445,9 @@ struct common_params {
@@ -455,6 +455,9 @@ struct common_params {
int32_t n_keep = 0; // number of tokens to keep from initial prompt
int32_t n_chunks = -1; // max number of chunks to process (-1 = unlimited)
int32_t n_parallel = 1; // number of parallel sequences to decode
@@ -40,26 +28,39 @@ index 878534d..4001df2 100644
+ bool score_enabled = false; // reserve server resources for the Score task type
int32_t n_sequences = 1; // number of sequences to decode
int32_t n_outputs_max = 0; // max outputs in a batch (0 = n_batch)
int32_t n_outputs_max_per_seq = 1; // max outputs per sequence
int32_t grp_attn_n = 1; // group-attention factor
diff --git a/tools/CMakeLists.txt b/tools/CMakeLists.txt
index 780df32..1d2fe8f 100644
--- a/tools/CMakeLists.txt
+++ b/tools/CMakeLists.txt
@@ -41,3 +41,4 @@ else()
add_subdirectory(fit-params)
add_subdirectory(results)
endif()
+add_subdirectory(grpc-server)
diff --git a/tools/server/server-context.cpp b/tools/server/server-context.cpp
index 3b5f6a1..d0e18e6 100644
index 715477e..de5bed8 100644
--- a/tools/server/server-context.cpp
+++ b/tools/server/server-context.cpp
@@ -48,6 +48,13 @@ static common_speculative_output_limits server_output_limits(const common_params
auto result = common_speculative_get_output_limits(
params.n_batch, params.n_parallel, common_speculative_n_max(&params.speculative));
@@ -49,7 +49,16 @@ static uint32_t server_n_outputs_max(const common_params & params) {
+ // Score tasks output logits for every candidate token, so reserve room
+ // for a bounded candidate tail per parallel slot.
+ if (params.score_enabled) {
+ result.per_seq = std::max<int32_t>(result.per_seq, 1 + SERVER_SCORE_MAX_CAND_TOKENS);
+ result.total = std::min<int32_t>(params.n_batch, params.n_parallel * result.per_seq);
const uint32_t n_outputs_per_seq = 1 + common_speculative_n_max(&params.speculative);
- const uint64_t n_outputs = (uint64_t) params.n_parallel * n_outputs_per_seq;
+ // score tasks (SERVER_TASK_TYPE_SCORE) output logits for every candidate
+ // token, so reserve room for a bounded candidate tail per parallel slot
+ if (!params.score_enabled) {
+ return std::max<uint32_t>(1, std::min<uint64_t>(n_batch,
+ (uint64_t) params.n_parallel * n_outputs_per_seq));
+ }
+
result.total = std::max<int32_t>(1, result.total);
result.per_seq = std::max<int32_t>(1, result.per_seq);
return result;
@@ -239,6 +246,26 @@ struct server_slot {
+ const uint32_t n_outputs_score_seq = 1 + SERVER_SCORE_MAX_CAND_TOKENS;
+
+ const uint64_t n_outputs = (uint64_t) params.n_parallel * std::max(n_outputs_per_seq, n_outputs_score_seq);
return std::max<uint32_t>(1, std::min<uint64_t>(n_batch, n_outputs));
}
@@ -202,6 +211,26 @@ struct server_slot {
std::vector<completion_token_output> generated_token_probs;
@@ -86,7 +87,7 @@ index 3b5f6a1..d0e18e6 100644
bool has_next_token = true;
bool has_new_line = false;
bool truncated = false;
@@ -341,6 +368,10 @@ struct server_slot {
@@ -311,6 +340,10 @@ struct server_slot {
}
generated_tokens.clear();
generated_token_probs.clear();
@@ -96,8 +97,8 @@ index 3b5f6a1..d0e18e6 100644
+ score_divergence = -1;
json_schema = json();
task_prev = std::move(task);
@@ -2271,6 +2302,229 @@ private:
// clear speculative decoding stats
@@ -2205,6 +2238,229 @@ private:
queue_results.send(std::move(res));
}
@@ -327,7 +328,7 @@ index 3b5f6a1..d0e18e6 100644
//
// Functions to process the task
//
@@ -2407,6 +2661,7 @@ private:
@@ -2341,6 +2597,7 @@ private:
case SERVER_TASK_TYPE_INFILL:
case SERVER_TASK_TYPE_EMBEDDING:
case SERVER_TASK_TYPE_RERANK:
@@ -335,7 +336,7 @@ index 3b5f6a1..d0e18e6 100644
{
// special case: if input is provided via CLI, tokenize it first
// otherwise, no need to tokenize as it's already done inside the HTTP thread
@@ -2903,6 +3158,13 @@ private:
@@ -2832,6 +3089,13 @@ private:
break; // stop any further processing
}
}
@@ -349,7 +350,7 @@ index 3b5f6a1..d0e18e6 100644
}
void pre_decode() {
@@ -3222,6 +3484,16 @@ private:
@@ -3154,6 +3418,16 @@ private:
n_past = std::min(n_past, slot.alora_invocation_start - 1);
}
@@ -366,7 +367,7 @@ index 3b5f6a1..d0e18e6 100644
const auto n_cache_reuse = slot.task->params.n_cache_reuse;
const bool can_cache_reuse =
@@ -3455,8 +3727,12 @@ private:
@@ -3395,8 +3669,12 @@ private:
bool do_checkpoint = params_base.n_ctx_checkpoints > 0;
@@ -381,7 +382,7 @@ index 3b5f6a1..d0e18e6 100644
// make a checkpoint of the parts of the memory that cannot be rolled back.
// checkpoints are created only if:
@@ -3444,9 +3720,16 @@ private:
@@ -3463,10 +3741,17 @@ private:
// embedding requires all tokens in the batch to be output;
// MTP also wants logits at every prompt position so the
// streaming hook can mirror t_h_nextn into ctx_dft.
@@ -394,12 +395,16 @@ index 3b5f6a1..d0e18e6 100644
+ slot.prompt.n_tokens() + 1 < slot.task->n_tokens();
add_ok &= batch.add(slot.id,
cur_tok,
/* pos = */ slot.prompt.tokens.pos_next(),
- /* output = */ slot.need_embd(),
+ /* output = */ slot.need_embd() || need_score_logit,
/* is_prompt = */ true);
slot.prompt.tokens.pos_next(),
- slot.need_embd());
+ slot.need_embd() || need_score_logit);
slot.prompt.tokens.push_back(cur_tok);
@@ -3454,2 +3737,28 @@ private:
slot.n_prompt_tokens_processed++;
@@ -3481,6 +3766,32 @@ private:
}
}
+ // score tasks: break at the shared-prompt boundary so the checkpoint
+ // below lands exactly there — the other candidates of the same
+ // scoring call re-process only their own tokens. Also break at the
@@ -426,9 +431,10 @@ index 3b5f6a1..d0e18e6 100644
+ }
+ }
+
// break at the last user message, or at user messages at least min step past the last checkpoint
if (do_checkpoint && spans.is_user_start(slot.prompt.n_tokens())) {
@@ -3573,6 +3882,15 @@ private:
// process the last few tokens of the prompt separately in order to allow for a checkpoint to be created.
// create checkpoints that many tokens before the end of the prompt:
// - 4 + n_ubatch
@@ -3513,6 +3824,15 @@ private:
const bool is_user_start = spans.is_user_start(n_tokens_start);
const bool is_last_user_message = n_tokens_start == last_user_pos;
@@ -444,7 +450,7 @@ index 3b5f6a1..d0e18e6 100644
// entire prompt has been processed
if (slot.prompt.n_tokens() == slot.task->n_tokens()) {
slot.state = SLOT_STATE_DONE_PROMPT;
@@ -3588,8 +3906,8 @@ private:
@@ -3528,8 +3848,8 @@ private:
slot.init_sampler();
} else {
// skip ordinary mid-prompt checkpoints, unless the batch starts a user
@@ -455,7 +461,7 @@ index 3b5f6a1..d0e18e6 100644
do_checkpoint = false;
}
}
@@ -3606,10 +3924,10 @@ private:
@@ -3546,10 +3866,10 @@ private:
// do not checkpoint after mtmd chunks
do_checkpoint = do_checkpoint && !has_mtmd;
@@ -468,7 +474,7 @@ index 3b5f6a1..d0e18e6 100644
n_tokens_start > slot.prompt.checkpoints.back().n_tokens + params_base.checkpoint_min_step);
SLT_DBG(slot, "main/do_checkpoint = %s, pos_min = %d, pos_max = %d\n", do_checkpoint ? "yes" : "no", pos_min, pos_max);
@@ -3772,6 +4090,13 @@ private:
@@ -3703,6 +4023,13 @@ private:
}
}
@@ -482,7 +488,7 @@ index 3b5f6a1..d0e18e6 100644
if (!is_inside_view(slot.i_batch)) {
// the required token not in this sub-batch, skip
return;
@@ -3793,6 +4118,25 @@ private:
@@ -3724,6 +4051,25 @@ private:
return;
}
@@ -509,7 +515,7 @@ index 3b5f6a1..d0e18e6 100644
// prompt evaluated for next-token prediction
diff --git a/tools/server/server-task.h b/tools/server/server-task.h
index 6275ec7..5bedf19 100644
index c3eea2e..fb3c178 100644
--- a/tools/server/server-task.h
+++ b/tools/server/server-task.h
@@ -13,10 +13,25 @@
@@ -591,5 +597,3 @@ index 6275ec7..5bedf19 100644
struct server_task_result_error : server_task_result {
error_type err_type = ERROR_TYPE_SERVER;
std::string err_msg;
--
2.39.5
@@ -1,11 +1,57 @@
# Carries the server-side half of ggml-org/llama.cpp#26603 (POST /tts), which
# adds SERVER_TASK_TYPE_TTS to the shared server_context. LocalAI's gRPC
# adapter rides on that same server_context and cannot drive the mtmd gen-audio
# loop directly: server_context owns the llama_context and schedules slots on
# its own thread, so a handler calling llama_decode would corrupt state.
#
# The upstream HTTP route (tools/server/server.cpp) and the README/CLI hunks are
# intentionally excluded - LocalAI does not serve llama.cpp's HTTP surface.
#
# Rebased against LLAMA_VERSION 9de0fcf2b with 0001-add-server-task-type-score.patch
# already applied: the SERVER_TASK_TYPE_TTS case in the tokenize switch lands
# after the SCORE case that patch adds, so this patch must stay second in ls order.
#
# Three fixes on top of the draft, all ours, all candidates to send back to #26603:
#
# 1. Its lone SRV_WRN call passes only a format string, but the macro expands
# __VA_ARGS__ without the GNU comma-elision extension, so the expansion ends
# in a trailing comma and does not compile. The "%s" wrapper added here is the
# same idiom upstream already uses for its other argument-less SRV_WRN calls;
# drop it if the draft fixes the call before it merges.
#
# 2. The slot.prompt_clear() added to the SERVER_TASK_TYPE_TTS branch of
# launch_slot_with_task. Without it only the FIRST TTS request in a server
# process succeeds and every later one fails instantly in step_prompt. TTS
# slots never enter the shared batch (pre_decode() returns early for them and
# process_tts_slots() drives them), so they skip the prompt-cache bookkeeping
# that would otherwise clear the sequence between requests; meanwhile the
# gen-audio pipeline always decodes from position 0 and its reset() only
# clears host-side buffers, never the KV cache. The result is that request 2
# decodes over request 1's tokens. This one is a genuine defect in the draft,
# not a LocalAI integration artifact, and should be reported upstream.
#
# 3. The is_supported() guard in server_slot::tts_ctx::reset(). The draft calls
# mtmd_helper_gen_audio_reset() unconditionally, but it only ever init()s the
# gen-audio pipeline for models that carry a gen-audio mmproj, so the handle
# stays null for every ordinary model. Upstream's implementation
# (tools/mtmd/mtmd-helper-gen.cpp) reads ctx->pipeline before it null-checks
# anything, so the slot-init call to server_slot::reset() segfaults the
# process on any non-TTS model - which is every chat model LocalAI loads
# through this backend. The missing null check on mtmd_helper_gen_audio_*
# is upstream's bug, so carry this guard until they add one, even if the
# draft's own reset() call is fixed.
#
# REMOVE THIS PATCH once #26603 merges upstream and LLAMA_VERSION is bumped past
# the merge commit. It exists only because that PR is still a draft. If it merges
# without fixes 2 and 3 above, those hunks still need carrying.
diff --git a/tools/mtmd/mtmd-helper-gen.cpp b/tools/mtmd/mtmd-helper-gen.cpp
index 1c58d3ae1..196cbd433 100644
index b52dc8e..fd9d6ca 100644
--- a/tools/mtmd/mtmd-helper-gen.cpp
+++ b/tools/mtmd/mtmd-helper-gen.cpp
@@ -50,29 +50,38 @@ static llama_token find_special_token(const llama_vocab * vocab, const std::stri
@@ -48,29 +48,38 @@ static llama_token find_special_token(const llama_vocab * vocab, const std::stri
return LLAMA_TOKEN_NULL;
}
+static void put_bytes(std::vector<char> & buf, const void * p, size_t n) {
+ const char * c = (const char *) p;
+ buf.insert(buf.end(), c, c + n);
@@ -58,17 +104,17 @@ index 1c58d3ae1..196cbd433 100644
+ append_wav16_pcm(buf, pcm.data(), pcm.size());
return true;
}
@@ -92,6 +101,8 @@ public:
// set out_stop on end-of-speech, h_state_out must be null if no frame is generated
virtual int32_t step_gen(llama_token sampled, const float * h_state_in, const float ** h_state_out, bool * out_stop) = 0;
@@ -89,6 +98,8 @@ public:
// those read what they need from h_state_in instead
virtual int32_t step_gen(llama_token sampled, const float * h_state_in, const float ** h_state_out) = 0;
virtual int32_t get_output(int32_t * out_sample_rate, const char ** out_data, size_t * out_data_len, int64_t * out_n_samples) = 0;
+ // forces any buffered codes through code2wav now, regardless of window_frames
+ virtual int32_t flush() { return 0; }
+ virtual int32_t flush() = 0;
protected:
llama_context * lctx;
@@ -121,6 +132,9 @@ public:
@@ -119,6 +130,9 @@ public:
prompt_batch.reset();
n_prompt = 0;
prompt_pos = 0;
@@ -76,19 +122,19 @@ index 1c58d3ae1..196cbd433 100644
+ pcm_sent = 0;
+ wav_header_sent = false;
}
int32_t set_input(const mtmd_helper_gen_audio_inp * inp) override {
@@ -208,6 +222,7 @@ public:
top_p = inp->top_p > 0 ? inp->top_p : def.top_p;
seed = inp->seed;
@@ -204,6 +218,7 @@ public:
top_k = inp->top_k > 0 ? inp->top_k : 50;
top_p = inp->top_p > 0 ? inp->top_p : 1.0f;
out_type = inp->out_type;
+ stream = inp->stream;
// the prompt above holds the whole text stream up to tts_eos, so every generated
// frame adds tts_pad on top of the codes embedding
@@ -302,31 +317,60 @@ public:
// the text stream keeps flowing during generation: after frame k, the input adds
// trailing text row k on top of the codes embedding, then tts_eos, then tts_pad
@@ -289,31 +304,60 @@ public:
}
int32_t get_output(int32_t * out_sample_rate, const char ** out_data, size_t * out_data_len, int64_t * out_n_samples) override {
- if (!flush_gen_wav()) {
- return 1;
@@ -116,7 +162,7 @@ index 1c58d3ae1..196cbd433 100644
+ *out_data_len = out_buf.size();
+ return 0;
}
- *out_sample_rate = info.sample_rate;
+ // streaming: only return audio produced since the previous call
+ const size_t n_new = audio_pcm.size() - pcm_sent;
@@ -124,7 +170,7 @@ index 1c58d3ae1..196cbd433 100644
- *out_n_samples = (int64_t) audio_pcm.size();
+ *out_n_samples = (int64_t) n_new;
}
if (out_type == MTMD_HELPER_GEN_AUDIO_OUTTYPE_PCM) {
- *out_data = (const char *) audio_pcm.data();
- *out_data_len = audio_pcm.size() * sizeof(float);
@@ -133,7 +179,7 @@ index 1c58d3ae1..196cbd433 100644
+ pcm_sent = audio_pcm.size();
return 0;
}
out_buf.clear();
- if (!write_wav16(out_buf, audio_pcm, info.sample_rate)) {
- LOG_ERR("mtmd_helper_gen_audio: output too large for WAV\n");
@@ -148,7 +194,7 @@ index 1c58d3ae1..196cbd433 100644
*out_data_len = out_buf.size();
return 0;
}
+ int32_t flush() override {
+ return flush_gen_wav() ? 0 : 1;
+ }
@@ -156,7 +202,7 @@ index 1c58d3ae1..196cbd433 100644
private:
bool ensure_cache() {
if (specials_ok) {
@@ -370,7 +414,7 @@ private:
@@ -357,7 +401,7 @@ private:
LOG_ERR("mtmd_helper_gen_audio: mmproj has no speaker/audio encoder\n");
return false;
}
@@ -165,7 +211,7 @@ index 1c58d3ae1..196cbd433 100644
mtmd_input_text text{ marker.c_str(), marker.size(), false, true };
mtmd_input_chunks * chunks = mtmd_input_chunks_init();
const mtmd_bitmap * bptr = bitmap;
@@ -456,6 +500,9 @@ private:
@@ -442,6 +486,9 @@ private:
std::vector<float> h_state_buf;
mtmd_helper_gen_audio_outtype out_type = MTMD_HELPER_GEN_AUDIO_OUTTYPE_WAV;
std::vector<char> out_buf;
@@ -173,12 +219,12 @@ index 1c58d3ae1..196cbd433 100644
+ size_t pcm_sent = 0; // samples already returned by get_output()
+ bool wav_header_sent = false;
};
// settings that only live in the reference's per-pack yaml, not in the checkpoint
@@ -1024,6 +1071,14 @@ void mtmd_helper_gen_audio_reset(mtmd_helper_gen_audio * ctx) {
static std::unique_ptr<mtmd_gen_audio_pipeline> make_pipeline(llama_context * lctx, mtmd_context * mctx) {
@@ -473,6 +520,14 @@ void mtmd_helper_gen_audio_reset(mtmd_helper_gen_audio * ctx) {
}
}
+struct mtmd_helper_gen_audio_inp mtmd_helper_gen_audio_inp_default(void) {
+ mtmd_helper_gen_audio_inp inp{};
+ inp.top_k = 50;
@@ -190,7 +236,7 @@ index 1c58d3ae1..196cbd433 100644
int32_t mtmd_helper_gen_audio_set_input(mtmd_helper_gen_audio * ctx, const mtmd_helper_gen_audio_inp * inp) {
if (!ctx->pipeline) {
LOG_ERR("mtmd_helper_gen_audio: unsupported or missing gen-audio pipeline\n");
@@ -1060,3 +1115,10 @@ int32_t mtmd_helper_gen_audio_get_output(mtmd_helper_gen_audio * ctx, int32_t *
@@ -503,3 +558,10 @@ int32_t mtmd_helper_gen_audio_get_output(mtmd_helper_gen_audio * ctx, int32_t *
}
return ctx->pipeline->get_output(out_sample_rate, out_data, out_data_len, out_n_samples);
}
@@ -202,7 +248,7 @@ index 1c58d3ae1..196cbd433 100644
+ return ctx->pipeline->flush();
+}
diff --git a/tools/mtmd/mtmd-helper.h b/tools/mtmd/mtmd-helper.h
index 832f7171a..3eaa01aab 100644
index 7e5cf9b..1f3ec01 100644
--- a/tools/mtmd/mtmd-helper.h
+++ b/tools/mtmd/mtmd-helper.h
@@ -175,6 +175,7 @@ enum mtmd_helper_gen_audio_outtype {
@@ -211,19 +257,19 @@ index 832f7171a..3eaa01aab 100644
struct mtmd_helper_gen_audio_inp {
+ bool stream; // if true, output() must be called after each step_gen()
llama_seq_id seq_id;
const char * prompt;
@@ -190,6 +191,8 @@ struct mtmd_helper_gen_audio_inp {
@@ -189,6 +190,8 @@ struct mtmd_helper_gen_audio_inp {
enum mtmd_helper_gen_audio_outtype out_type;
};
+MTMD_API struct mtmd_helper_gen_audio_inp mtmd_helper_gen_audio_inp_default(void);
+
MTMD_API mtmd_helper_gen_audio * mtmd_helper_gen_audio_init(
struct llama_context * lctx,
struct mtmd_context * mctx);
@@ -221,6 +224,8 @@ MTMD_API int32_t mtmd_helper_gen_audio_step_gen(
@@ -217,6 +220,8 @@ MTMD_API int32_t mtmd_helper_gen_audio_step_gen(
// out_data valid until next get_output() or reset() call
// out_n_samples (optional, can be NULL) receives the number of generated PCM samples
+// if inp->stream is true: returns only audio produced since the previous call, and
@@ -231,10 +277,10 @@ index 832f7171a..3eaa01aab 100644
MTMD_API int32_t mtmd_helper_gen_audio_get_output(
mtmd_helper_gen_audio * ctx,
int32_t * out_sample_rate,
@@ -228,6 +233,10 @@ MTMD_API int32_t mtmd_helper_gen_audio_get_output(
@@ -224,6 +229,10 @@ MTMD_API int32_t mtmd_helper_gen_audio_get_output(
size_t * out_data_len,
int64_t * out_n_samples);
+// forces any buffered codes through code2wav now, regardless of window_frames;
+// call once when generation has ended, before the last get_output() in stream mode
+MTMD_API int32_t mtmd_helper_gen_audio_flush(mtmd_helper_gen_audio * ctx);
@@ -242,7 +288,7 @@ index 832f7171a..3eaa01aab 100644
#ifdef __cplusplus
} // extern "C"
#endif
@@ -254,8 +263,41 @@ struct mtmd_helper_gen_audio_deleter {
@@ -250,8 +259,41 @@ struct mtmd_helper_gen_audio_deleter {
};
using gen_audio_ptr = std::unique_ptr<mtmd_helper_gen_audio, mtmd_helper_gen_audio_deleter>;
struct gen_audio {
@@ -285,7 +331,7 @@ index 832f7171a..3eaa01aab 100644
void reset() {
mtmd_helper_gen_audio_reset(ctx.get());
}
@@ -271,6 +313,9 @@ struct gen_audio {
@@ -267,6 +309,9 @@ struct gen_audio {
int32_t get_output(int32_t * out_sample_rate, const char ** out_data, size_t * out_data_len, int64_t * out_n_samples = nullptr) {
return mtmd_helper_gen_audio_get_output(ctx.get(), out_sample_rate, out_data, out_data_len, out_n_samples);
}
@@ -293,10 +339,10 @@ index 832f7171a..3eaa01aab 100644
+ return mtmd_helper_gen_audio_flush(ctx.get());
+ }
};
} // namespace mtmd_helper
diff --git a/tools/server/server-context.cpp b/tools/server/server-context.cpp
index 9069463fe..b7fa1e534 100644
index 543dc43..4f01b1e 100644
--- a/tools/server/server-context.cpp
+++ b/tools/server/server-context.cpp
@@ -16,6 +16,7 @@
@@ -304,25 +350,23 @@ index 9069463fe..b7fa1e534 100644
#include "mtmd.h"
#include "mtmd-helper.h"
+#include "base64.hpp"
#include <algorithm>
#include <cstddef>
@@ -41,8 +42,9 @@ constexpr int HTTP_POLLING_SECONDS = 1;
static common_speculative_output_limits server_output_limits(const common_params & params) {
@@ -43,7 +44,8 @@ static uint32_t server_n_outputs_max(const common_params & params) {
const uint32_t n_batch = params.n_batch;
if (params.embedding ||
- (params.pooling_type != LLAMA_POOLING_TYPE_UNSPECIFIED && params.pooling_type != LLAMA_POOLING_TYPE_NONE)) {
- return { params.n_batch, 1 };
+ (params.pooling_type != LLAMA_POOLING_TYPE_UNSPECIFIED && params.pooling_type != LLAMA_POOLING_TYPE_NONE) ||
+ !params.mmproj.path.empty()) { // gen-audio (TTS) capability isn't known until the mmproj loads, size generously
+ return { params.n_batch, params.n_batch };
return n_batch;
}
auto result = common_speculative_get_output_limits(
@@ -212,6 +214,30 @@ struct server_slot {
@@ -214,6 +216,30 @@ struct server_slot {
mtmd_context * mctx = nullptr;
mtmd::batch_ptr mbatch = nullptr;
+ struct tts_ctx {
+ mtmd_helper::gen_audio ctx;
+ const float * h_state;
@@ -349,20 +393,20 @@ index 9069463fe..b7fa1e534 100644
+
// speculative decoding
common_speculative * spec;
@@ -391,6 +417,8 @@ struct server_slot {
@@ -403,6 +429,8 @@ struct server_slot {
// clear multimodal state
mbatch.reset();
+
+ tts.reset();
}
void init_sampler() const {
@@ -829,6 +857,14 @@ public:
@@ -949,6 +977,14 @@ public:
mtmd_context * mctx = nullptr;
const llama_vocab * vocab = nullptr;
+ bool has_cap_tts() const {
+ return mctx != nullptr && mtmd_gen_audio_get_info(mctx).type != MTMD_GEN_AUDIO_TYPE_NONE;
+ }
@@ -373,22 +417,22 @@ index 9069463fe..b7fa1e534 100644
+
server_queue queue_tasks;
server_response queue_results;
@@ -1288,6 +1324,10 @@ private:
@@ -1400,6 +1436,10 @@ private:
slot.mctx = mctx;
slot.prompt.tokens.has_mtmd = mctx != nullptr;
+ if (has_cap_tts()) {
+ slot.tts.ctx.init(ctx_tgt, mctx);
+ }
+
SLT_TRC(slot, "new slot, n_ctx = %d\n", slot.n_ctx);
slot.callback_on_release = [this](int id_slot) {
@@ -1748,6 +1788,28 @@ private:
@@ -1853,6 +1893,28 @@ private:
SLT_DBG(slot, "launching slot : %s\n", safe_json_to_str(slot.to_json()).c_str());
+ if (task.type == SERVER_TASK_TYPE_TTS) {
+ GGML_ASSERT(has_cap_tts()); // should already checked in route handler
+ if (!slot.tts.is_supported()) {
@@ -414,20 +458,20 @@ index 9069463fe..b7fa1e534 100644
// initialize samplers
if (task.need_sampling()) {
try {
@@ -1765,6 +1827,9 @@ private:
@@ -1875,6 +1937,9 @@ private:
// TODO: getting pre sampling logits is not yet supported with backend sampling
use_backend_sampling &= !need_pre_sample_logits;
backend_sampling &= !need_pre_sample_logits;
+ // TODO: check verify if this actually works with TTS
+ use_backend_sampling &= task.type != SERVER_TASK_TYPE_TTS;
+ backend_sampling &= task.type != SERVER_TASK_TYPE_TTS;
+
// TODO: tmp until backend sampling is fully implemented
if (use_backend_sampling) {
if (backend_sampling) {
llama_set_sampler(ctx_tgt, slot.id, common_sampler_get(slot.smpl.get()));
@@ -1783,9 +1848,13 @@ private:
@@ -1890,9 +1955,13 @@ private:
slot.task = std::make_unique<const server_task>(std::move(task));
- slot.state = slot.task->is_child()
- ? SLOT_STATE_WAIT_OTHER // wait for the parent to process prompt
- : SLOT_STATE_STARTED;
@@ -438,13 +482,13 @@ index 9069463fe..b7fa1e534 100644
+ ? SLOT_STATE_WAIT_OTHER // wait for the parent to process prompt
+ : SLOT_STATE_STARTED;
+ }
// reset server kill-switch counter
n_empty_consecutive = 0;
@@ -2050,6 +2119,18 @@ private:
@@ -2169,6 +2238,18 @@ private:
queue_results.send(std::move(res));
}
+ void send_tts_result(server_slot & slot, int32_t sample_rate, const char * data, size_t data_len, bool final) {
+ auto res = std::make_unique<server_task_result_tts>();
+
@@ -459,8 +503,8 @@ index 9069463fe..b7fa1e534 100644
+
void send_final_response(server_slot & slot) {
auto res = std::make_unique<server_task_result_cmpl_final>();
@@ -2556,6 +2637,7 @@ private:
@@ -2668,6 +2749,7 @@ private:
case SERVER_TASK_TYPE_EMBEDDING:
case SERVER_TASK_TYPE_RERANK:
case SERVER_TASK_TYPE_SCORE:
@@ -468,7 +512,10 @@ index 9069463fe..b7fa1e534 100644
{
// special case: if input is provided via CLI, tokenize it first
// otherwise, no need to tokenize as it's already done inside the HTTP thread
@@ -3007,1 +3089,9 @@ private:
@@ -3103,6 +3185,14 @@ private:
abort_all_slots("pre_decode() failed: " + std::string(e.what()));
}
+ // note: TTS slots bypass the shared batch entirely
+ try {
+ process_tts_slots();
@@ -478,10 +525,12 @@ index 9069463fe..b7fa1e534 100644
+ }
+
GGML_ASSERT(batch.slot_batched || batch.size() == 0);
@@ -3074,10 +3164,77 @@ private:
if (batch.slot_batched) {
@@ -3173,10 +3263,77 @@ private:
}
}
+ void process_tts_slots() {
+ iterate(slots, [&](server_slot & slot) {
+ if (!slot.is_processing() || slot.task->type != SERVER_TASK_TYPE_TTS) {
@@ -556,25 +605,25 @@ index 9069463fe..b7fa1e534 100644
if (slot.state == SLOT_STATE_GENERATING && slot.prompt.n_tokens() + 1 >= slot.n_ctx) {
if (!params_base.ctx_shift) {
// this check is redundant (for good)
@@ -3150,7 +3307,7 @@ private:
@@ -3249,7 +3406,7 @@ private:
// determine which slots are generating and drafting
iterate(slots, [&](server_slot & slot) {
- if (slot.state != SLOT_STATE_GENERATING) {
+ if (slot.state != SLOT_STATE_GENERATING || slot.task->type == SERVER_TASK_TYPE_TTS) {
return;
}
@@ -3284,7 +3441,7 @@ private:
@@ -3381,7 +3538,7 @@ private:
return; // batch is full, skip remaining slots
}
- if (!slot.is_processing()) {
+ if (!slot.is_processing() || slot.task->type == SERVER_TASK_TYPE_TTS) {
return;
}
@@ -4433,6 +4590,8 @@ server_context_meta server_context::get_meta() const {
@@ -4390,6 +4547,8 @@ server_context_meta server_context::get_meta() const {
/* has_inp_image */ impl->chat_params.allow_image,
/* has_inp_audio */ impl->chat_params.allow_audio,
/* has_inp_video */ impl->chat_params.allow_video,
@@ -583,22 +632,22 @@ index 9069463fe..b7fa1e534 100644
/* json_ui_settings */ impl->json_ui_settings,
/* slot_n_ctx */ impl->get_slot_n_ctx(),
/* pooling_type */ llama_pooling_type(impl->ctx_tgt),
@@ -4512,6 +4671,11 @@ std::unique_ptr<server_res_generator> server_routes::handle_completions_impl(
@@ -4469,6 +4628,11 @@ std::unique_ptr<server_res_generator> server_routes::handle_completions_impl(
res->set_req(&req); // will also set spipe if needed
+ if (!ctx_server.has_cap_chat()) {
+ res->error(format_error_response("this server does not support chat/completions", ERROR_TYPE_NOT_SUPPORTED));
+ return res;
+ }
+
int32_t sse_ping_interval = params.sse_ping_interval;
try {
@@ -5399,6 +5563,150 @@ void server_routes::init_routes() {
@@ -5446,6 +5610,150 @@ void server_routes::init_routes() {
return res;
};
+ this->post_tts = [this](const server_http_req & req) {
+ auto res = create_response();
+ res->set_req(&req); // will also set spipe if needed
@@ -659,7 +708,7 @@ index 9069463fe..b7fa1e534 100644
+ }
+
+ if (speaker_ref_len > 0) {
+ auto wrapper = mtmd_helper_bitmap_init_from_buf(ctx_server.mctx, speaker_ref_data, speaker_ref_len, false, ctx_server.init_opt);
+ auto wrapper = mtmd_helper_bitmap_init_from_buf(ctx_server.mctx, speaker_ref_data, speaker_ref_len, false);
+ if (!wrapper.bitmap) {
+ res->error(format_error_response("failed to decode \"speaker_ref\"", ERROR_TYPE_INVALID_REQUEST));
+ return res;
@@ -745,9 +794,9 @@ index 9069463fe..b7fa1e534 100644
+
this->get_lora_adapters = [this](const server_http_req & req) {
auto res = create_response();
diff --git a/tools/server/server-context.h b/tools/server/server-context.h
index f9ab1132b..610512678 100644
index f9ab113..6105126 100644
--- a/tools/server/server-context.h
+++ b/tools/server/server-context.h
@@ -22,6 +22,8 @@ struct server_context_meta {
@@ -766,15 +815,15 @@ index f9ab1132b..610512678 100644
+ server_http_context::handler_t post_tts;
server_http_context::handler_t get_lora_adapters;
server_http_context::handler_t post_lora_adapters;
diff --git a/tools/server/server-task.cpp b/tools/server/server-task.cpp
index 1ee677553..939630b8b 100644
index 1ee6775..939630b 100644
--- a/tools/server/server-task.cpp
+++ b/tools/server/server-task.cpp
@@ -1497,6 +1497,17 @@ json server_task_result_rerank::to_json() {
@@ -1523,6 +1523,17 @@ json server_task_result_rerank::to_json() {
};
}
+//
+// server_task_result_tts
+//
@@ -790,34 +839,34 @@ index 1ee677553..939630b8b 100644
// server_task_result_error
//
diff --git a/tools/server/server-task.h b/tools/server/server-task.h
index 5bedf1987..e6ca67a65 100644
index 5bedf19..e6ca67a 100644
--- a/tools/server/server-task.h
+++ b/tools/server/server-task.h
@@ -10,6 +10,7 @@
// TODO: prevent including the whole server-common.h as we only use server_tokens
#include "server-common.h"
+#include "mtmd-helper.h"
using json = nlohmann::ordered_json;
@@ -42,6 +43,7 @@ enum server_task_type {
SERVER_TASK_TYPE_SLOT_ERASE,
SERVER_TASK_TYPE_GET_LORA,
SERVER_TASK_TYPE_SET_LORA,
+ SERVER_TASK_TYPE_TTS,
};
// TODO: change this to more generic "response_format" to replace the "format_response_*" in server-common
@@ -202,6 +204,9 @@ struct server_task {
// used by SERVER_TASK_TYPE_SET_LORA
std::map<int, float> set_lora; // mapping adapter ID -> scale
+ // used by SERVER_TASK_TYPE_TTS
+ mtmd_helper::gen_audio::inp tts_inp;
+
server_task() = default;
server_task(server_task_type type) : type(type) {}
@@ -235,6 +240,7 @@ struct server_task {
switch (type) {
@@ -827,10 +876,10 @@ index 5bedf1987..e6ca67a65 100644
return true;
default:
return false;
@@ -494,5 +500,15 @@ struct server_task_result_embd : server_task_result {
@@ -514,6 +520,16 @@ struct server_task_result_embd : server_task_result {
json to_json_oaicompat();
};
+struct server_task_result_tts : server_task_result {
+ std::string audio; // raw bytes for this chunk (WAV or PCM, per request's out_type)
+ int32_t sample_rate = 0;
@@ -843,3 +892,4 @@ index 5bedf1987..e6ca67a65 100644
+
struct server_task_result_rerank : server_task_result {
float score = -1e6;
-45
View File
@@ -15,30 +15,6 @@ if [ -d "patches" ]; then
done
fi
## Apple RDMA link fixup.
## ggml-rpc hands Apple's librdma to the linker with
## target_link_options(ggml-rpc PRIVATE "LINKER:-weak_library,..."). Link options are not
## a usage requirement of a static library, so in our BUILD_SHARED_LIBS=OFF build the flag
## dies with libggml-rpc.a and every ibv_* symbol transport-apple.cpp reaches for comes out
## undefined when grpc-server and ggml-rpc-server link. Re-declare the same weak link as
## INTERFACE so it travels to whoever links the static library.
##
## Guarded on the marker so a second prepare.sh over the same checkout is a no-op, and on
## GGML_RPC_RDMA_APPLE so forks that branched before the Apple RDMA transport (turboquant,
## bonsai) are left alone.
RPC_CMAKE=llama.cpp/ggml/src/ggml-rpc/CMakeLists.txt
if [ -f "$RPC_CMAKE" ] && grep -q "GGML_RPC_RDMA_APPLE" "$RPC_CMAKE" && ! grep -q "LOCALAI_RDMA_IFACE" "$RPC_CMAKE"; then
echo "==> ggml-rpc carries the Apple RDMA transport, re-declaring its weak librdma link as INTERFACE"
cat >> "$RPC_CMAKE" <<'EOF'
# LOCALAI_RDMA_IFACE: added by backend/cpp/llama-cpp/prepare.sh
if (GGML_RPC_RDMA AND APPLE AND NOT BUILD_SHARED_LIBS)
target_link_options(ggml-rpc INTERFACE "LINKER:-weak_library,${RDMA_LIB}")
endif()
EOF
fi
for file in $(ls llama.cpp/tools/server/); do
cp -rfv llama.cpp/tools/server/$file llama.cpp/tools/grpc-server/
done
@@ -56,9 +32,6 @@ cp -r passthrough_options_test.cpp llama.cpp/tools/grpc-server/
# regression test.
cp -r tts_request_options.h llama.cpp/tools/grpc-server/
cp -r tts_request_options_test.cpp llama.cpp/tools/grpc-server/
# Thread-count default normalization and its standalone regression test.
cp -r thread_params.h llama.cpp/tools/grpc-server/
cp -r thread_params_test.cpp llama.cpp/tools/grpc-server/
# Parent-death watcher (included by grpc-server.cpp) and its standalone unit
# test (run via backend/cpp/run-unit-tests.sh; also buildable under ctest).
cp -r parent_watch.h llama.cpp/tools/grpc-server/
@@ -80,28 +53,10 @@ else
echo "==> llama.cpp predates the load-mode enum, using the legacy mmap/mlock/direct-io booleans"
LEGACY_LOAD_MODE=1
fi
if grep -q "server_metrics metrics;" llama.cpp/tools/server/server-task.h; then
HAS_SERVER_METRICS=1
else
HAS_SERVER_METRICS=0
fi
if grep -q "mtmd_helper_init_opt" llama.cpp/tools/mtmd/mtmd-helper.h; then
HAS_MTMD_INIT_OPT=1
else
HAS_MTMD_INIT_OPT=0
fi
if grep -q "llm_add_n_cpu_ffn_overrides" llama.cpp/common/common.h; then
HAS_N_CPU_FFN_HELPER=1
else
HAS_N_CPU_FFN_HELPER=0
fi
cat > llama.cpp/tools/grpc-server/llama_compat.h <<EOF
// Generated by backend/cpp/llama-cpp/prepare.sh. Do not edit.
#pragma once
#define LOCALAI_LEGACY_LOAD_MODE ${LEGACY_LOAD_MODE}
#define LOCALAI_HAS_SERVER_METRICS ${HAS_SERVER_METRICS}
#define LOCALAI_HAS_MTMD_INIT_OPT ${HAS_MTMD_INIT_OPT}
#define LOCALAI_HAS_N_CPU_FFN_HELPER ${HAS_N_CPU_FFN_HELPER}
EOF
set +e
-11
View File
@@ -1,11 +0,0 @@
#pragma once
#include <cstdint>
namespace llama_grpc {
inline int32_t resolve_batch_threads(int32_t batch_threads, int32_t inference_threads) {
return batch_threads < 0 ? inference_threads : batch_threads;
}
} // namespace llama_grpc
@@ -1,15 +0,0 @@
#include "thread_params.h"
#include <cstdio>
int main() {
if (llama_grpc::resolve_batch_threads(-1, 4) != 4) {
std::fprintf(stderr, "default batch threads did not inherit inference threads\n");
return 1;
}
if (llama_grpc::resolve_batch_threads(2, 4) != 2) {
std::fprintf(stderr, "explicit batch threads were overwritten\n");
return 1;
}
return 0;
}
@@ -8,8 +8,6 @@
# so the grpc-server option parser skips the two references to
# common_params::checkpoint_min_step (the default and the option handler).
# That field does not exist in the fork yet; drop this once it does.
# 3. Use nlohmann's parse_error type in JSON catch clauses because the fork
# predates upstream's common_json_error wrapper.
#
# The fork used to lag upstream on the whole common_params_speculative refactor
# (ggml-org/llama.cpp#22397/#22838/#22964), the model_tgt rename (#22838) and
@@ -102,16 +100,4 @@ else
echo "==> LOCALAI_TURBOQUANT_NO_CHECKPOINT_MIN_STEP define OK"
fi
# 3. The shared source follows current upstream and catches common_json_error.
# TurboQuant still exposes nlohmann::json directly, so its equivalent parse
# failures use json::parse_error instead.
if grep -q 'common_json_error' "$SRC"; then
echo "==> patching $SRC to use the TurboQuant JSON exception type"
awk '{ gsub(/common_json_error/, "json::parse_error"); print }' "$SRC" > "$SRC.tmp"
mv "$SRC.tmp" "$SRC"
echo "==> TurboQuant JSON exception patch OK"
else
echo "==> $SRC already uses a TurboQuant-compatible JSON exception type, skipping"
fi
echo "==> all patches applied"
+1 -1
View File
@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# CrispASR version (release tag)
CRISPASR_REPO?=https://github.com/CrispStrobe/CrispASR
CRISPASR_VERSION?=301acd87b036764973b8bfba71e0a21818036d33
CRISPASR_VERSION?=8898b0fee199b1765321a5d0d8314aee51a34583
SO_TARGET?=libgocrispasr.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
+1 -1
View File
@@ -615,10 +615,10 @@ func (w *CrispASR) TTSStream(req *pb.TTSRequest, results chan []byte) error {
return fmt.Errorf("crispasr: tempfile: %w", err)
}
dst := tmp.Name()
defer func() { _ = os.Remove(dst) }()
if err := tmp.Close(); err != nil {
return fmt.Errorf("crispasr: close tempfile: %w", err)
}
defer func() { _ = os.Remove(dst) }()
if err := writeWAV(dst, pcm, w.sampleRate); err != nil {
return err
+1 -1
View File
@@ -14,7 +14,7 @@ JOBS?=$(shell nproc --ignore=1)
# It is kept alive by the upstream tag da2-support (survives a squash-merge);
# repoint to the master merge commit once mudler/depth-anything.cpp PR #1 lands.
DEPTHANYTHING_REPO?=https://github.com/mudler/depth-anything.cpp.git
DEPTHANYTHING_VERSION?=14f7461d1f704761a038ac9f50dbde8fdb7275e2
DEPTHANYTHING_VERSION?=2028b47ac75a8659c6a9aa617baf09be193eb55f
ifeq ($(NATIVE),false)
CMAKE_ARGS+=-DGGML_NATIVE=OFF
+2 -7
View File
@@ -38,9 +38,8 @@ type Store struct {
// keysAreNormalized stays true until any non-unit-magnitude key
// is added; once false, the magnitude-aware fallback path is
// used by Find. Re-evaluated only at Set time, never again on
// its own — a partial deletion of the offending key does NOT flip
// it back to true (the bookkeeping cost would dominate the gain).
// An empty store returns to its initial state.
// its own — a deletion of the offending key does NOT flip it
// back to true (the bookkeeping cost would dominate the gain).
keysAreNormalized bool
// keyLen is the dimension of every stored key. -1 means "no
@@ -143,10 +142,6 @@ func (s *Store) StoresDelete(opts *pb.StoresDeleteOptions) error {
mergedV = append(mergedV, tailV...)
s.keys = mergedK
s.values = mergedV
if len(s.keys) == 0 {
s.keyLen = -1
s.keysAreNormalized = true
}
assert(slices.IsSortedFunc(s.keys, slices.Compare[[]float32]), "Delete: s.keys not sorted post-merge")
assert(len(s.keys) == len(s.values), "Delete: keys/values length skew")
return nil
-40
View File
@@ -105,46 +105,6 @@ var _ = Describe("StoresDelete", func() {
})).To(Succeed(), "delete of missing key should succeed")
Expect(s.keys).To(HaveLen(1))
})
It("reopens the dimension after deleting every key", func() {
s := NewStore()
oldKey := []float32{2, 0, 0}
mustSet(s, [][]float32{oldKey}, [][]byte{[]byte("3d")})
Expect(s.keysAreNormalized).To(BeFalse())
Expect(s.StoresDelete(&pb.StoresDeleteOptions{
Keys: wrapKeys([][]float32{oldKey}),
})).To(Succeed())
Expect(s.keys).To(BeEmpty())
Expect(s.keyLen).To(Equal(-1))
Expect(s.keysAreNormalized).To(BeTrue())
newKey := normalizeVec([]float32{1, 1})
mustSet(s, [][]float32{newKey}, [][]byte{[]byte("2d")})
res, err := s.StoresFind(&pb.StoresFindOptions{
Key: &pb.StoresKey{Floats: newKey},
TopK: 1,
})
Expect(err).NotTo(HaveOccurred())
Expect(res.Values).To(HaveLen(1))
Expect(string(res.Values[0].Bytes)).To(Equal("2d"))
})
It("retains the dimension after a partial delete", func() {
s := NewStore()
mustSet(s,
[][]float32{{1, 0, 0}, {0, 1, 0}},
[][]byte{[]byte("x"), []byte("y")},
)
Expect(s.StoresDelete(&pb.StoresDeleteOptions{
Keys: wrapKeys([][]float32{{1, 0, 0}}),
})).To(Succeed())
Expect(s.keyLen).To(Equal(3))
Expect(s.StoresSet(&pb.StoresSetOptions{
Keys: wrapKeys([][]float32{{1, 0}}),
Values: wrapValues([][]byte{[]byte("2d")}),
})).NotTo(Succeed())
})
})
var _ = Describe("StoresFind", func() {
@@ -11,7 +11,6 @@ import (
"fmt"
"os"
"path/filepath"
"runtime"
"unsafe"
"github.com/mudler/LocalAI/pkg/grpc/base"
@@ -110,25 +109,30 @@ func (r *LocateAnythingCpp) Detect(opts *pb.DetectOptions) (pb.DetectResponse, e
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: a text prompt is required (open-vocabulary detection)")
}
// Decode base64 image and write to temp file.
imgData, err := base64.StdEncoding.DecodeString(opts.Src)
if err != nil {
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: failed to decode base64 image: %w", err)
}
if len(imgData) == 0 {
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: decoded image is empty")
tmpFile, err := os.CreateTemp("", "locate-anything-*.img")
if err != nil {
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: failed to create temp file: %w", err)
}
defer func() { _ = os.Remove(tmpFile.Name()) }()
if _, err := tmpFile.Write(imgData); err != nil {
_ = tmpFile.Close()
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: failed to write temp file: %w", err)
}
if err := tmpFile.Close(); err != nil {
return pb.DetectResponse{}, fmt.Errorf("locate-anything-cpp: failed to close temp file: %w", err)
}
// mode 0 = hybrid (Parallel Box Decoding). The JSON return value is unused:
// structured detections are read via the accessor functions. Still must
// free the returned string.
jsonPtr := CapiLocateBuffer(
r.handle,
uintptr(unsafe.Pointer(unsafe.SliceData(imgData))),
uintptr(len(imgData)),
prompt,
0,
)
runtime.KeepAlive(imgData)
jsonPtr := CapiLocatePath(r.handle, tmpFile.Name(), prompt, 0)
if jsonPtr != 0 {
CapiFreeString(jsonPtr)
}
@@ -1,54 +0,0 @@
package main
import (
"encoding/base64"
"path/filepath"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
var _ = Describe("LocateAnythingCpp detection input", func() {
It("detects from memory when the temporary directory is unavailable", func() {
originalLocateBuffer := CapiLocateBuffer
originalLocatePath := CapiLocatePath
originalGetNDetections := CapiGetNDetections
defer func() {
CapiLocateBuffer = originalLocateBuffer
CapiLocatePath = originalLocatePath
CapiGetNDetections = originalGetNDetections
}()
image := []byte("encoded-image")
var receivedData uintptr
var receivedLength uintptr
CapiLocateBuffer = func(_ uintptr, data uintptr, length uintptr, _ string, _ int32) uintptr {
receivedData = data
receivedLength = length
return 0
}
CapiLocatePath = func(_ uintptr, _ string, _ string, _ int32) uintptr {
Fail("path-based detection must not be called")
return 0
}
CapiGetNDetections = func(uintptr) int32 { return 0 }
GinkgoT().Setenv("TMPDIR", filepath.Join(GinkgoT().TempDir(), "missing"))
result, err := (&LocateAnythingCpp{handle: 1}).Detect(&pb.DetectOptions{
Src: base64.StdEncoding.EncodeToString(image),
Prompt: "the object",
})
Expect(err).NotTo(HaveOccurred())
Expect(result.Detections).To(BeEmpty())
Expect(receivedData).NotTo(BeZero())
Expect(receivedLength).To(Equal(uintptr(len(image))))
})
It("rejects an empty decoded image", func() {
_, err := (&LocateAnythingCpp{handle: 1}).Detect(&pb.DetectOptions{Prompt: "the object"})
Expect(err).To(MatchError("locate-anything-cpp: decoded image is empty"))
})
})
+3 -32
View File
@@ -12,7 +12,7 @@
# runs 'make -C backend/go/$(BACKEND) build' and then copies package/), so it
# has to produce the binary and the package, not just the shared libraries.
NEMO_SPEECH_VERSION?=a5b6953c4a579a2bbd1c0913ad8a85c2a4d99953
NEMO_SPEECH_VERSION?=2e12e2def8a98ed06666f7ee3ca94e7193e04be4
NEMO_SPEECH_REPO?=https://github.com/NVIDIA/NeMo-Speech.cpp
GOCMD?=go
@@ -88,18 +88,6 @@ ITN_LIB_DIR=$(ITN_PREFIX)/lib
ITN_MARKER=$(ITN_LIB_DIR)/libsparrowhawk.so
ITN_FST_HEADER=$(ITN_PREFIX)/include/fst/fst.h
# SentencePiece became a core ASR dependency in 5be7bfb: RNNT context biasing
# uses it even when Flashlight and text normalization are disabled. Build the
# pinned static archive provided by upstream so every platform gets the same
# dependency instead of relying on an undeclared system package.
SENTENCEPIECE_PREFIX=sources/NeMo-Speech.cpp/.deps/sentencepiece
SENTENCEPIECE_MARKER=$(SENTENCEPIECE_PREFIX)/lib/libsentencepiece.a
# Linux's ASR CMake block looks in NEMO_SPEECH_DEPENDENCY_PREFIX directly, but
# the Apple branch uses generic find_library()/find_path(). Put the same private
# prefix on CMake's search path so Darwin consumes the archive built above too.
CMAKE_ARGS+=-DCMAKE_PREFIX_PATH=$(abspath $(SENTENCEPIECE_PREFIX))
ITN_CC?=gcc-12
ITN_CXX?=g++-12
@@ -164,7 +152,7 @@ else
endif
CMAKE_ARGS+=-DNEMO_SPEECH_GGML_PATCHED=$(GGML_PATCHED)
.PHONY: nemo-speech-cpp-grpc package build clean purge test all stage-libs patch-ggml engine itn sentencepiece patch-itn-headers
.PHONY: nemo-speech-cpp-grpc package build clean purge test all stage-libs patch-ggml engine itn patch-itn-headers
all: nemo-speech-cpp-grpc package
@@ -278,28 +266,11 @@ patch-itn-headers:
itn: $(ITN_MARKER)
$(SENTENCEPIECE_MARKER): | sources/NeMo-Speech.cpp
# Upstream's license copies use GNU install's -D flag, which BSD install
# does not support. Homebrew CMake 4 also rejects SentencePiece's old policy
# floor. Patch both incompatibilities before running the helper on Darwin.
@if [ "$(shell uname -s)" = Darwin ]; then \
cd sources/NeMo-Speech.cpp && \
mkdir -p .deps/sentencepiece/share/licenses/nemo-speech/third_party/sentencepiece && \
perl -pi \
-e 's/install -Dm0644/install -m 0644/g;' \
-e 's/-DCMAKE_BUILD_TYPE=Release /-DCMAKE_BUILD_TYPE=Release -DCMAKE_POLICY_VERSION_MINIMUM=3.5 /;' \
scripts/build_sentencepiece_static.sh; \
fi
cd sources/NeMo-Speech.cpp && JOBS=$(JOBS) scripts/build_sentencepiece_static.sh
sentencepiece: $(SENTENCEPIECE_MARKER)
# Only a WITH_NORM=ON build needs the ITN stack, and it must exist before cmake
# configures, since the WITH_NORM cmake block find_library()s into the prefix
# with REQUIRED.
NEMO_RUNTIME_PREREQS=$(SENTENCEPIECE_MARKER)
ifeq ($(WITH_NORM),ON)
NEMO_RUNTIME_PREREQS+=$(ITN_MARKER)
NEMO_RUNTIME_PREREQS=$(ITN_MARKER)
endif
# Upstream sets CMAKE_LIBRARY_OUTPUT_DIRECTORY to ${CMAKE_BINARY_DIR}/bin, so the
+1 -1
View File
@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# omnivoice.cpp version
OMNIVOICE_REPO?=https://github.com/ServeurpersoCom/omnivoice.cpp
OMNIVOICE_VERSION?=040c8b344d8c670ce1475194751d119b5ef82c78
OMNIVOICE_VERSION?=4f33af825d66e6ef1cb185e87b4589cacf747291
SO_TARGET?=libgomnivoicecpp.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
+2 -4
View File
@@ -1,6 +1,6 @@
# parakeet-cpp backend Makefile.
#
# Upstream pin lives below as PARAKEET_VERSION?=e75de9b6b9b688fd293aa22f7e27aa724ea286f8
# Upstream pin lives below as PARAKEET_VERSION?=1bfbebfaaf493866f49597cd3b7901959d395c60
# (.github/bump_deps.sh) can find and update it - matches the
# whisper.cpp / ds4 / vibevoice-cpp convention.
#
@@ -15,7 +15,7 @@
# That's what the L0 smoke test uses. The default target below does the
# proper clone-at-pin + cmake build so CI doesn't need a side-checkout.
PARAKEET_VERSION?=e75de9b6b9b688fd293aa22f7e27aa724ea286f8
PARAKEET_VERSION?=1bfbebfaaf493866f49597cd3b7901959d395c60
PARAKEET_REPO?=https://github.com/mudler/parakeet.cpp
GOCMD?=go
@@ -49,8 +49,6 @@ else ifeq ($(BUILD_TYPE),hipblas)
CMAKE_ARGS+=-DPARAKEET_GGML_HIP=ON
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DPARAKEET_GGML_VULKAN=ON
else ifeq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DPARAKEET_GGML_METAL=ON
endif
.PHONY: parakeet-cpp-grpc package build clean purge test all
+16 -13
View File
@@ -10,7 +10,6 @@ import (
"fmt"
"os"
"path/filepath"
"runtime"
"strconv"
"unsafe"
@@ -103,12 +102,24 @@ func (r *RFDetrCpp) Detect(opts *pb.DetectOptions) (pb.DetectResponse, error) {
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: model not loaded")
}
// Decode base64 image and write to temp file.
imgData, err := base64.StdEncoding.DecodeString(opts.Src)
if err != nil {
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: failed to decode base64 image: %w", err)
}
if len(imgData) == 0 {
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: decoded image is empty")
tmpFile, err := os.CreateTemp("", "rfdetr-*.img")
if err != nil {
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: failed to create temp file: %w", err)
}
defer func() { _ = os.Remove(tmpFile.Name()) }()
if _, err := tmpFile.Write(imgData); err != nil {
_ = tmpFile.Close()
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: failed to write temp file: %w", err)
}
if err := tmpFile.Close(); err != nil {
return pb.DetectResponse{}, fmt.Errorf("rfdetr-cpp: failed to close temp file: %w", err)
}
threshold := opts.Threshold
@@ -116,18 +127,10 @@ func (r *RFDetrCpp) Detect(opts *pb.DetectOptions) (pb.DetectResponse, error) {
threshold = 0.5
}
// JSON output from the detection ABI is unused: we read structured detections via
// JSON output from detect_path is unused: we read structured detections via
// the accessor functions. Still must free the returned string.
var jsonPtr uintptr
rc := CapiDetectBuffer(
r.handle,
uintptr(unsafe.Pointer(unsafe.SliceData(imgData))),
uintptr(len(imgData)),
threshold,
uint32(defaultTopK),
&jsonPtr,
)
runtime.KeepAlive(imgData)
rc := CapiDetectPath(r.handle, tmpFile.Name(), threshold, uint32(defaultTopK), &jsonPtr)
if jsonPtr != 0 {
CapiFreeString(jsonPtr)
}
@@ -1,56 +0,0 @@
package main
import (
"encoding/base64"
"path/filepath"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
)
var _ = Describe("RFDetrCpp detection input", func() {
It("detects from memory when the temporary directory is unavailable", func() {
originalDetectBuffer := CapiDetectBuffer
originalDetectPath := CapiDetectPath
originalFreeString := CapiFreeString
originalGetNDetections := CapiGetNDetections
defer func() {
CapiDetectBuffer = originalDetectBuffer
CapiDetectPath = originalDetectPath
CapiFreeString = originalFreeString
CapiGetNDetections = originalGetNDetections
}()
image := []byte("encoded-image")
var receivedData uintptr
var receivedLength uintptr
CapiDetectBuffer = func(_ uintptr, data uintptr, length uintptr, _ float32, _ uint32, _ *uintptr) int32 {
receivedData = data
receivedLength = length
return 0
}
CapiDetectPath = func(_ uintptr, _ string, _ float32, _ uint32, _ *uintptr) int32 {
Fail("path-based detection must not be called")
return -1
}
CapiFreeString = func(uintptr) {}
CapiGetNDetections = func(uintptr) int32 { return 0 }
GinkgoT().Setenv("TMPDIR", filepath.Join(GinkgoT().TempDir(), "missing"))
result, err := (&RFDetrCpp{handle: 1}).Detect(&pb.DetectOptions{
Src: base64.StdEncoding.EncodeToString(image),
})
Expect(err).NotTo(HaveOccurred())
Expect(result.Detections).To(BeEmpty())
Expect(receivedData).NotTo(BeZero())
Expect(receivedLength).To(Equal(uintptr(len(image))))
})
It("rejects an empty decoded image", func() {
_, err := (&RFDetrCpp{handle: 1}).Detect(&pb.DetectOptions{})
Expect(err).To(MatchError("rfdetr-cpp: decoded image is empty"))
})
})
+12 -10
View File
@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# stablediffusion.cpp (ggml)
STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
STABLEDIFFUSION_GGML_VERSION?=d04e8950c1ec8d30248cbe996682b3182fb1adf6
STABLEDIFFUSION_GGML_VERSION?=c6beeef35526c6dc94b74a7fb69f9d2e6a2a7a12
CMAKE_ARGS+=-DGGML_MAX_NAME=128
@@ -38,16 +38,17 @@ else ifeq ($(BUILD_TYPE),hipblas)
ROCM_PATH ?= /opt/rocm
export CXX=$(ROCM_HOME)/llvm/bin/clang++
export CC=$(ROCM_HOME)/llvm/bin/clang
AMDGPU_TARGETS?=gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201
# SD_HIPBLAS turns on ggml's HIP backend itself; GGML_HIPBLAS is the name ggml
# used before it was renamed to GGML_HIP, so passing it here only produced an
# unused-variable warning.
CMAKE_ARGS+=-DSD_HIPBLAS=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
AMDGPU_TARGETS?=gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1200,gfx1201
CMAKE_ARGS+=-DSD_HIPBLAS=ON -DGGML_HIPBLAS=ON -DAMDGPU_TARGETS=$(AMDGPU_TARGETS)
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DSD_VULKAN=ON -DGGML_VULKAN=ON
else ifeq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DSD_METAL=ON -DGGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
else ifeq ($(OS),Darwin)
ifneq ($(BUILD_TYPE),metal)
CMAKE_ARGS+=-DSD_METAL=OFF -DGGML_METAL=OFF
else
CMAKE_ARGS+=-DSD_METAL=ON -DGGML_METAL=ON
CMAKE_ARGS+=-DGGML_METAL_EMBED_LIBRARY=ON
endif
endif
ifeq ($(BUILD_TYPE),sycl_f16)
@@ -71,6 +72,7 @@ sources/stablediffusion-ggml.cpp:
git checkout $(STABLEDIFFUSION_GGML_VERSION) && \
git submodule update --init --recursive --depth 1 --single-branch
# Detect OS
UNAME_S := $(shell uname -s)
# Only build CPU variants on Linux
@@ -132,4 +134,4 @@ libgosd-custom: CMakeLists.txt cpp/gosd.cpp cpp/gosd.h
(mv build-$(SO_TARGET)/libgosd.so ./$(SO_TARGET) 2>/dev/null || \
mv build-$(SO_TARGET)/libgosd.dylib ./$(SO_TARGET) 2>/dev/null)
all: stablediffusion-ggml package
all: stablediffusion-ggml package
+11 -18
View File
@@ -401,6 +401,7 @@ int load_model(const char *model, char *model_path, char* options[], int threads
const char *params_backend_arg = "";
const char *rpc_servers_arg = "";
const char *max_vram_arg = "";
bool stream_layers = false;
int n_threads = threads;
enum sd_type_t wtype = SD_TYPE_COUNT;
@@ -509,10 +510,7 @@ int load_model(const char *model, char *model_path, char* options[], int threads
if (!strcmp(optname, "params_backend")) params_backend_arg = strdup(optval);
if (!strcmp(optname, "rpc_servers")) rpc_servers_arg = strdup(optval);
if (!strcmp(optname, "max_vram")) max_vram_arg = strdup(optval);
if (!strcmp(optname, "stream_layers")) {
// Retained as a no-op for existing configurations. Upstream now
// selects segmented weight streaming automatically.
}
if (!strcmp(optname, "stream_layers")) stream_layers = (strcmp(optval, "true") == 0 || strcmp(optval, "1") == 0);
// vae_decode_only is still accepted for backwards compatibility with
// existing gallery configs, but upstream dropped the option (the model
@@ -652,9 +650,11 @@ int load_model(const char *model, char *model_path, char* options[], int threads
ctx_params.rpc_servers = env_rpc_servers;
}
}
// max_vram is an optional GiB budget or per-backend spec for automatic
// graph-cut execution. A zero value uses the live free-VRAM budget.
// max_vram: GiB budget or per-backend spec for graph-cut segmented param
// offload ("0" = disabled, "-1" = auto). stream_layers only has effect when
// max_vram is set.
if (strlen(max_vram_arg) > 0) ctx_params.max_vram = max_vram_arg;
ctx_params.stream_layers = stream_layers;
ctx_params.diffusion_flash_attn = diffusion_flash_attn;
ctx_params.tae_preview_only = tae_preview_only;
ctx_params.diffusion_conv_direct = diffusion_conv_direct;
@@ -1144,25 +1144,17 @@ static uint8_t* load_and_resize_image(const char* path, int target_width, int ta
// Write sd.cpp's audio buffer to a temp WAV file (IEEE float, interleaved).
// sd_audio_t.data is planar (all channel 0 samples, then channel 1, etc.) — we
// interleave on the fly so ffmpeg's standard wav demuxer can read it directly.
// Returns 0 on success and fills wav_path.
// Returns 0 on success and fills wav_path (must be at least 64 bytes).
static int write_planar_float_wav(const sd_audio_t* a, char* wav_path, size_t wav_path_sz) {
if (!a || !a->data || a->sample_count == 0 || a->channels == 0 || a->sample_rate == 0) {
return -1;
}
const char* temp_dir = getenv("TMPDIR");
if (!temp_dir || temp_dir[0] == '\0') {
temp_dir = "/tmp";
}
int path_len = snprintf(wav_path, wav_path_sz, "%s/gosd-audio-XXXXXX.wav", temp_dir);
if (path_len < 0 || (size_t)path_len >= wav_path_sz) {
fprintf(stderr, "temporary directory path is too long\n");
return -1;
}
snprintf(wav_path, wav_path_sz, "/tmp/gosd-audio-XXXXXX.wav");
int fd = mkstemps(wav_path, 4);
if (fd < 0) { perror("mkstemps wav"); return -1; }
FILE* f = fdopen(fd, "wb");
if (!f) { perror("fdopen wav"); close(fd); unlink(wav_path); return -1; }
if (!f) { perror("fdopen wav"); close(fd); return -1; }
uint64_t frames = a->sample_count;
uint32_t channels = a->channels;
@@ -1229,7 +1221,7 @@ static int ffmpeg_mux_raw_to_mp4(sd_image_t* frames, int num_frames, int fps,
snprintf(fps_str, sizeof(fps_str), "%d", fps);
// Optional audio: write a temp WAV file if the model produced audio.
char wav_path[4096] = {0};
char wav_path[64] = {0};
bool have_audio = false;
if (audio && audio->data && audio->sample_count > 0 && audio->channels > 0 && audio->sample_rate > 0) {
if (write_planar_float_wav(audio, wav_path, sizeof(wav_path)) == 0) {
@@ -1446,3 +1438,4 @@ int unload() {
free_sd_ctx(sd_c);
return 0;
}
+19 -28
View File
@@ -11,7 +11,7 @@ JOBS?=$(shell nproc --ignore=1 2>/dev/null || sysctl -n hw.ncpu 2>/dev/null || e
# vllm.cpp version
VLLM_CPP_REPO?=https://github.com/mudler/vllm.cpp
VLLM_CPP_VERSION?=6bf3abb580982f4fd2e4525ef37802ee0ce28981
VLLM_CPP_VERSION?=2b08dd246e04b3f0a4bf1f276170fd28004ced01
# MLX GEMM provider (darwin/metal only; see the metal branch below for why).
# Consumed as the prebuilt pip wheel: building MLX from source needs `xcrun
@@ -47,35 +47,26 @@ CMAKE_ARGS+=-DCMAKE_BUILD_TYPE=Release
UNAME_M := $(shell uname -m)
ifeq ($(BUILD_TYPE),cublas)
# Every CUDA architecture upstream builds that the platform can actually
# host, split by where the silicon exists: Jetson (87 Orin, 110 Thor) is
# arm64-only, desktop 120a is amd64-only, and 90a/100a appear on both
# because of the SBSA parts (GH200, GB200).
#
# This deliberately matches vllm.cpp's own release archive rather than
# narrowing to the boxes we benchmark on. A narrower list does not degrade
# on an unlisted card, it dies at the first request with "no kernel image
# is available for execution on the device", long after `backends install`
# reported success -- so an arch we merely lack numbers for still belongs
# in the binary.
#
# Triton-AOT stays ON for both. A fat build is supported on the BUILDER
# path: it embeds every vendored cubin tree (sm_80/86/89/90a/100a/121a) and
# selects by exact SM at runtime, so the arches with no tree (87, 103a,
# 110, 120a) take the portable CUDA kernels and can never load a
# neighbouring cubin. Only maintainer REGEN needs a single pinned arch.
# See vllm.cpp cmake/TritonAOT.cmake `_triton_aot_arch_names`.
#
# CUDA builds REQUIRE the CUDA 13 toolchain: 12.x nvcc lacks compute_121a
# (GB10) and its ptxas rejects the sm_120a NVFP4 MMA kernels ("Vector type
# too large"), so no cuda-12 variant is shipped.
ifeq ($(CUDA_MAJOR_VERSION),12)
$(error vllm.cpp needs the CUDA 13 toolchain: CUDA 12.x cannot compile the Blackwell fp4 kernels)
endif
# Blackwell-family targets only: other CUDA arches are build-supported
# upstream but have no runtime-proven fast path. amd64 gets the consumer
# (120a) + GB10 (121a) fat binary; arm64 CUDA (l4t-style images, DGX
# Spark) is GB10 only. Triton-AOT GDN cubins are vendored per-arch, no
# Python needed to consume them.
ifeq ($(UNAME_M),x86_64)
CMAKE_ARGS+=-DVLLM_CPP_CUDA=ON "-DVLLM_CPP_CUDA_ARCHITECTURES=80;86;89;90a;100a;103a;120a;121a" -DVLLM_CPP_TRITON=ON
# NO -DVLLM_CPP_TRITON on fat builds: the vendored Triton-AOT cubin
# trees are per-arch and the engine refuses a multi-arch build unless
# pinned to one tree (unsound for the other arch). The non-AOT GDN
# path serves the fat binary; single-arch builds keep the cubins.
#
# CUDA builds REQUIRE the CUDA 13 toolchain: 12.x nvcc lacks
# compute_121a (GB10) and its ptxas rejects the sm_120a NVFP4 MMA
# kernels ("Vector type too large"), so no cuda-12 variant is shipped.
ifeq ($(CUDA_MAJOR_VERSION),12)
$(error vllm.cpp needs the CUDA 13 toolchain: CUDA 12.x cannot compile the Blackwell fp4 kernels)
endif
CMAKE_ARGS+=-DVLLM_CPP_CUDA=ON "-DVLLM_CPP_CUDA_ARCHITECTURES=120a;121a"
else
CMAKE_ARGS+=-DVLLM_CPP_CUDA=ON "-DVLLM_CPP_CUDA_ARCHITECTURES=87;90a;100a;110;121a" -DVLLM_CPP_TRITON=ON
CMAKE_ARGS+=-DVLLM_CPP_CUDA=ON -DVLLM_CPP_CUDA_ARCHITECTURES=121a -DVLLM_CPP_TRITON=ON
endif
else ifeq ($(BUILD_TYPE),vulkan)
CMAKE_ARGS+=-DVLLM_CPP_VULKAN=ON -DVLLM_CPP_CUDA=OFF
+1 -1
View File
@@ -9,7 +9,7 @@ It serves two things: text generation, and MiniMax-H3 joint video+audio
generation.
The backend dlopens the engine's stable C ABI (`libvllm`, `include/vllm.h`,
ABI v20) through purego:
ABI v16) through purego:
- `Load` -> `vllm_engine_load`: accepts a `.gguf` file or a HF-style model
directory (`config.json` + safetensors). `context_size` maps to
+18 -32
View File
@@ -1,6 +1,6 @@
package main
// purego bindings for the vllm.cpp stable C ABI (include/vllm.h, ABI v23).
// purego bindings for the vllm.cpp stable C ABI (include/vllm.h, ABI v16).
//
// The structs below are hand-mirrored PODs of the C declarations, with
// explicit padding so the Go layout matches the C layout on linux/darwin
@@ -21,7 +21,7 @@ import (
// the header of the VLLM_CPP_VERSION pinned in the Makefile: the build checks
// the two against each other, because a mismatch is only caught at runtime by
// registerLib, where it takes the backend down on every load (issue #11379).
const abiVersion = 23
const abiVersion = 17
// The ABI's tri-state toggles (enable_prefix_caching ABI v7,
// enable_jump_forward ABI v10) share one encoding: 0 is NOT "off", it is
@@ -69,7 +69,6 @@ type cModelParams struct {
MaxNumBatchedTokens int32 // <= 0 = per-arch default (ABI v9)
SchedulingPolicy uintptr // const char*; NULL = "fcfs" (ABI v9)
KVTransferConfig uintptr // const char* JSON; NULL = no connector (ABI v9)
OffloadConfig uintptr // const char* JSON; NULL = no weight offload
EnableJumpForward int32 // tri-state 0/1/2 (ABI v10)
// v14/v16 tail. LocalAI sets none of these (0 is "auto" for the device and
// "unset" for both sizing knobs, i.e. the pre-v14 engine byte for byte), but
@@ -80,10 +79,6 @@ type cModelParams struct {
Device int32 // 0 auto, 1 cpu, 2 cuda (ABI v14)
GPUMemoryUtil float64 // 0 => 0.92 (ABI v16)
KVCacheMemoryBytes int64 // 0 => unset (ABI v16)
LanguageModelOnly int32 // 0 = multimodal inputs enabled (ABI v19)
_ [4]byte
LimitMMPerPrompt uintptr // const char* JSON; NULL = default limits (ABI v19)
MMProjPath uintptr // const char*; NULL = no GGUF projector (ABI v22)
}
// cSamplingParams mirrors vllm_sampling_params (structured fields included).
@@ -152,11 +147,6 @@ type cVideoModelParams struct {
Device int32 // 0 cpu, 1 cuda
DequantBf16 int32 // 0 keep-quant, 1 dequant/stream bf16
Fp4Resident int32 // NVFP4+cuda: keep FP4 packed, Marlin W4A16
_ [4]byte
Family uintptr // const char*; NULL = detect (ABI v18)
ExtraKeys uintptr // const char* const* (ABI v18)
ExtraValues uintptr // const char* const* (ABI v18)
NExtras int32 // 0 = none (ABI v18)
_ [4]byte // trailing pad to the struct's 8-byte alignment
}
@@ -164,26 +154,22 @@ type cVideoModelParams struct {
// `steps` pair up into 8-byte slots; the uint64 seed forces the alignment after
// them, and the float noise_aug leaves a pad before output_dir.
type cVideoParams struct {
Prompt uintptr // const char*
Width int32
Height int32
NumFrames int32 // <= 1 => per-task default (124 for t2va/fl2va)
Steps int32 // <= 0 => the H3 default (50)
Seed uint64
HasSeed int32
_ [4]byte
FirstFrame uintptr // const char*; fl2va keyframe, binary PPM (P6)
LastFrame uintptr // const char*
RefImage uintptr // const char*; ref2va only
RefVideo uintptr // const char*; ref2va only, a frame_%06d.ppm DIRECTORY
RefAudio uintptr // const char*; ref2va only, 16-bit PCM WAV
NoiseAug float32 // <= 0 => 1.0
_ [4]byte
OutputDir uintptr // const char*; REQUIRED
ExtraKeys uintptr // const char* const* (ABI v18)
ExtraValues uintptr // const char* const* (ABI v18)
NExtras int32 // 0 = none (ABI v18)
_ [4]byte
Prompt uintptr // const char*
Width int32
Height int32
NumFrames int32 // <= 1 => per-task default (124 for t2va/fl2va)
Steps int32 // <= 0 => the H3 default (50)
Seed uint64
HasSeed int32
_ [4]byte
FirstFrame uintptr // const char*; fl2va keyframe, binary PPM (P6)
LastFrame uintptr // const char*
RefImage uintptr // const char*; ref2va only
RefVideo uintptr // const char*; ref2va only, a frame_%06d.ppm DIRECTORY
RefAudio uintptr // const char*; ref2va only, 16-bit PCM WAV
NoiseAug float32 // <= 0 => 1.0
_ [4]byte
OutputDir uintptr // const char*; REQUIRED
}
// cVideoResult mirrors vllm_video_result. Every member is library-allocated and
-31
View File
@@ -128,40 +128,9 @@ func parseOptions(opts *pb.ModelOptions) loadOptions {
lo := loadOptions{}
applyOptionsList(&lo, opts.GetOptions())
applyEngineArgs(&lo, opts.GetEngineArgs())
applyDraftModelOption(&lo, opts.GetOptions())
return lo
}
// applyDraftModelOption binds a managed companion snapshot after engine_args
// has supplied the speculative document. Companion paths do not exist until
// LocalAI materializes the artifact, so they must replace the gallery's static
// repository reference without disturbing the method or token budget.
func applyDraftModelOption(lo *loadOptions, options []string) {
if strings.TrimSpace(lo.speculativeConfig) == "" {
return
}
var draftModel string
for _, option := range options {
key, value, found := strings.Cut(option, ":")
if found && strings.TrimSpace(key) == "draft_model" {
draftModel = strings.TrimSpace(value)
}
}
if draftModel == "" {
return
}
var spec map[string]any
if err := json.Unmarshal([]byte(lo.speculativeConfig), &spec); err != nil {
return
}
spec["model"] = draftModel
encoded, err := json.Marshal(spec)
if err == nil {
lo.speculativeConfig = string(encoded)
}
}
// applyOptionsList reads the legacy free-form "key:value" list. strings.Cut
// splits on the FIRST colon only, so a JSON object value survives intact.
func applyOptionsList(lo *loadOptions, options []string) {
-38
View File
@@ -1,38 +0,0 @@
package main
import (
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
pb "github.com/mudler/LocalAI/pkg/grpc/proto"
)
var _ = Describe("managed DFlash companion options", func() {
It("replaces only the draft model in an existing speculative configuration", func() {
managedPath := ".artifacts/huggingface/0123456789abcdef/snapshot"
lo := parseOptions(&pb.ModelOptions{
Options: []string{"draft_model:" + managedPath},
EngineArgs: `{
"speculative_config": {
"method": "dflash",
"model": "Mia-AiLab/Qwen3.8-27B-DFlash2-EXL3-5.0bpw",
"num_speculative_tokens": 7
}
}`,
})
Expect(lo.speculativeConfig).To(MatchJSON(`{
"method": "dflash",
"model": ".artifacts/huggingface/0123456789abcdef/snapshot",
"num_speculative_tokens": 7
}`))
})
It("ignores a draft companion when speculative decoding is not configured", func() {
lo := parseOptions(&pb.ModelOptions{
Options: []string{"draft_model:.artifacts/huggingface/0123456789abcdef/snapshot"},
})
Expect(lo.speculativeConfig).To(BeEmpty())
})
})
+2 -9
View File
@@ -28,11 +28,7 @@ var _ = Describe("C ABI video struct mirrors", func() {
Expect(unsafe.Offsetof(p.Device)).To(Equal(uintptr(72)))
Expect(unsafe.Offsetof(p.DequantBf16)).To(Equal(uintptr(76)))
Expect(unsafe.Offsetof(p.Fp4Resident)).To(Equal(uintptr(80)))
Expect(unsafe.Offsetof(p.Family)).To(Equal(uintptr(88)))
Expect(unsafe.Offsetof(p.ExtraKeys)).To(Equal(uintptr(96)))
Expect(unsafe.Offsetof(p.ExtraValues)).To(Equal(uintptr(104)))
Expect(unsafe.Offsetof(p.NExtras)).To(Equal(uintptr(112)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(120)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(88)))
})
It("cVideoParams matches vllm_video_params", func() {
@@ -51,10 +47,7 @@ var _ = Describe("C ABI video struct mirrors", func() {
Expect(unsafe.Offsetof(p.RefAudio)).To(Equal(uintptr(72)))
Expect(unsafe.Offsetof(p.NoiseAug)).To(Equal(uintptr(80)))
Expect(unsafe.Offsetof(p.OutputDir)).To(Equal(uintptr(88)))
Expect(unsafe.Offsetof(p.ExtraKeys)).To(Equal(uintptr(96)))
Expect(unsafe.Offsetof(p.ExtraValues)).To(Equal(uintptr(104)))
Expect(unsafe.Offsetof(p.NExtras)).To(Equal(uintptr(112)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(120)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(96)))
})
It("cVideoResult matches vllm_video_result", func() {
+8 -12
View File
@@ -16,7 +16,7 @@ func TestVllmCpp(t *testing.T) {
RunSpecs(t, "vllm-cpp suite")
}
// The Go POD mirrors must match the C struct layout of vllm.h (ABI v23)
// The Go POD mirrors must match the C struct layout of vllm.h (ABI v16)
// byte-for-byte: these offsets are the C offsets on LP64 (linux/darwin
// amd64+arm64). A failure here means govllmcpp.go drifted from vllm.h.
var _ = Describe("C ABI struct mirrors", func() {
@@ -24,7 +24,7 @@ var _ = Describe("C ABI struct mirrors", func() {
// VLLM_ABI_VERSION in the vllm.h of VLLM_CPP_VERSION (Makefile).
// Moving the pin past this without growing the mirrors below ships a
// backend that refuses every load at startup (issue #11379).
Expect(abiVersion).To(Equal(23))
Expect(abiVersion).To(Equal(16))
})
It("cModelParams matches vllm_model_params", func() {
@@ -42,17 +42,13 @@ var _ = Describe("C ABI struct mirrors", func() {
Expect(unsafe.Offsetof(p.MaxNumBatchedTokens)).To(Equal(uintptr(60)))
Expect(unsafe.Offsetof(p.SchedulingPolicy)).To(Equal(uintptr(64)))
Expect(unsafe.Offsetof(p.KVTransferConfig)).To(Equal(uintptr(72)))
Expect(unsafe.Offsetof(p.OffloadConfig)).To(Equal(uintptr(80)))
Expect(unsafe.Offsetof(p.EnableJumpForward)).To(Equal(uintptr(88)))
Expect(unsafe.Offsetof(p.Device)).To(Equal(uintptr(92)))
// 96: gpu_memory_utilization is a double, so it takes the next
Expect(unsafe.Offsetof(p.EnableJumpForward)).To(Equal(uintptr(80)))
Expect(unsafe.Offsetof(p.Device)).To(Equal(uintptr(84)))
// 88, not 92: gpu_memory_utilization is a double, so it takes the next
// 8-aligned slot after the int32 pair. Go pads identically.
Expect(unsafe.Offsetof(p.GPUMemoryUtil)).To(Equal(uintptr(96)))
Expect(unsafe.Offsetof(p.KVCacheMemoryBytes)).To(Equal(uintptr(104)))
Expect(unsafe.Offsetof(p.LanguageModelOnly)).To(Equal(uintptr(112)))
Expect(unsafe.Offsetof(p.LimitMMPerPrompt)).To(Equal(uintptr(120)))
Expect(unsafe.Offsetof(p.MMProjPath)).To(Equal(uintptr(128)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(136)))
Expect(unsafe.Offsetof(p.GPUMemoryUtil)).To(Equal(uintptr(88)))
Expect(unsafe.Offsetof(p.KVCacheMemoryBytes)).To(Equal(uintptr(96)))
Expect(unsafe.Sizeof(p)).To(Equal(uintptr(104)))
})
It("cSamplingParams matches vllm_sampling_params (ABI v8)", func() {
+1 -1
View File
@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
# whisper.cpp version
WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
WHISPER_CPP_VERSION?=c44b60b8053bbf2a5c1e014f11323fb3f2485177
WHISPER_CPP_VERSION?=592feef04a1802b18cbeffd0fd0eb5d02570c2ec
SO_TARGET?=libgowhisper.so
CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF
+2 -12
View File
@@ -510,7 +510,7 @@
default: "cpu-stablediffusion-ggml"
nvidia: "cuda12-stablediffusion-ggml"
intel: "intel-sycl-f16-stablediffusion-ggml"
amd: "rocm-stablediffusion-ggml"
# amd: "rocm-stablediffusion-ggml"
vulkan: "vulkan-stablediffusion-ggml"
nvidia-l4t: "nvidia-l4t-arm64-stablediffusion-ggml"
metal: "metal-stablediffusion-ggml"
@@ -2109,7 +2109,7 @@
default: "cpu-stablediffusion-ggml-development"
nvidia: "cuda12-stablediffusion-ggml-development"
intel: "intel-sycl-f16-stablediffusion-ggml-development"
amd: "rocm-stablediffusion-ggml-development"
# amd: "rocm-stablediffusion-ggml-development"
vulkan: "vulkan-stablediffusion-ggml-development"
nvidia-l4t: "nvidia-l4t-arm64-stablediffusion-ggml-development"
metal: "metal-stablediffusion-ggml-development"
@@ -3904,11 +3904,6 @@
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-nvidia-cuda-12-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "rocm-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-stablediffusion-ggml"
mirrors:
- localai/localai-backends:latest-gpu-rocm-hipblas-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f32-stablediffusion-ggml"
uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-stablediffusion-ggml"
@@ -3922,11 +3917,6 @@
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-nvidia-cuda-12-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "rocm-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-stablediffusion-ggml"
mirrors:
- localai/localai-backends:master-gpu-rocm-hipblas-stablediffusion-ggml
- !!merge <<: *stablediffusionggml
name: "intel-sycl-f32-stablediffusion-ggml-development"
uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-sycl-f32-stablediffusion-ggml"
+18 -15
View File
@@ -19,7 +19,6 @@ import grpc
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
from grpc_auth import get_auth_interceptors
from temp_utils import cleanup_paths
import tempfile
@@ -116,6 +115,11 @@ def merge_audio_files(audio_files, output_path, sample_rate):
# Save the merged audio
ta.save(output_path, merged_waveform, sample_rate)
# Clean up temporary files
for audio_file in audio_files:
if os.path.exists(audio_file):
os.remove(audio_file)
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
@@ -222,20 +226,19 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
text_chunks = split_text_at_word_boundary(request.text, max_length=250)
print(f"Splitting text into chunks of 250 characters: {len(text_chunks)}", file=sys.stderr)
# Generate audio for each chunk
with cleanup_paths() as temp_audio_files:
for i, chunk in enumerate(text_chunks):
# Generate audio for this chunk
wav = self.model.generate(chunk, **kwargs)
# Register ownership before saving so a partial write is
# removed too when generation or encoding fails.
temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
temp_file.close()
temp_audio_files.append(temp_file.name)
ta.save(temp_file.name, wav, self.model.sr)
# Merge all audio files
merge_audio_files(temp_audio_files, request.dst, self.model.sr)
temp_audio_files = []
for i, chunk in enumerate(text_chunks):
# Generate audio for this chunk
wav = self.model.generate(chunk, **kwargs)
# Create temporary file for this chunk
temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
temp_file.close()
ta.save(temp_file.name, wav, self.model.sr)
temp_audio_files.append(temp_file.name)
# Merge all audio files
merge_audio_files(temp_audio_files, request.dst, self.model.sr)
else:
# Generate audio using ChatterboxTTS for short text
wav = self.model.generate(request.text, **kwargs)
-40
View File
@@ -37,46 +37,6 @@ def parse_options(options_list):
return opts
def attach_media_parts(messages_dicts, n_images=0, n_videos=0):
"""Rebuild the last user message as content *parts* carrying media markers.
Backends that let the tokenizer do the templating hand plain string content
to ``apply_chat_template``, but a chat template only emits the model's own
media tokens (``<|vision_start|><|image_pad|><|vision_end|>`` for the
Qwen-VL family, and the equivalents elsewhere) when the content is a list
of parts. Without those markers the engine's multimodal processor finds
nothing to substitute and silently discards the pixels, even though they
were forwarded correctly out of band.
Returns a new list whose last user message has
``[{"type": "image"} * n_images, {"type": "video"} * n_videos, text]`` as
its content, or ``None`` when there is nothing to attach - no media, no
user turn, or content that is already a list of parts - so the caller can
keep using the original string-content list.
"""
if not n_images and not n_videos:
return None
idx = next(
(
i
for i in reversed(range(len(messages_dicts)))
if messages_dicts[i].get("role") == "user"
),
None,
)
if idx is None:
return None
text = messages_dicts[idx].get("content") or ""
if not isinstance(text, str):
return None
parts = [{"type": "image"}] * n_images + [{"type": "video"}] * n_videos
if text:
parts.append({"type": "text", "text": text})
patched = list(messages_dicts)
patched[idx] = dict(patched[idx], content=parts)
return patched
def messages_to_dicts(proto_messages):
"""Convert proto ``Message`` objects to dicts suitable for ``apply_chat_template``.
+1 -59
View File
@@ -14,7 +14,7 @@ import json
import types
import unittest
from python_utils import attach_media_parts, messages_to_dicts, parse_options
from python_utils import messages_to_dicts, parse_options
def _msg(**fields):
@@ -118,63 +118,5 @@ class TestMessagesToDicts(unittest.TestCase):
self.assertNotIn("tool_calls", out[0])
class TestAttachMediaParts(unittest.TestCase):
def test_image_marker_added_to_last_user_turn(self):
messages = [
{"role": "system", "content": "be brief"},
{"role": "user", "content": "first"},
{"role": "assistant", "content": "ok"},
{"role": "user", "content": "how high is the water?"},
]
out = attach_media_parts(messages, n_images=1)
self.assertEqual(
out[3]["content"],
[{"type": "image"}, {"type": "text", "text": "how high is the water?"}],
)
# Earlier turns and the input list itself are untouched.
self.assertEqual(out[:3], messages[:3])
self.assertEqual(messages[3]["content"], "how high is the water?")
def test_counts_and_order_images_then_videos(self):
out = attach_media_parts(
[{"role": "user", "content": "describe"}], n_images=2, n_videos=1
)
self.assertEqual(
out[0]["content"],
[
{"type": "image"},
{"type": "image"},
{"type": "video"},
{"type": "text", "text": "describe"},
],
)
def test_empty_text_yields_media_only_parts(self):
out = attach_media_parts([{"role": "user", "content": ""}], n_images=1)
self.assertEqual(out[0]["content"], [{"type": "image"}])
def test_other_message_keys_are_preserved(self):
out = attach_media_parts(
[{"role": "user", "content": "hi", "name": "bob"}], n_images=1
)
self.assertEqual(out[0]["name"], "bob")
def test_no_media_is_a_no_op(self):
self.assertIsNone(attach_media_parts([{"role": "user", "content": "hi"}]))
def test_no_user_turn_is_a_no_op(self):
self.assertIsNone(
attach_media_parts([{"role": "system", "content": "hi"}], n_images=1)
)
def test_content_already_parts_is_a_no_op(self):
self.assertIsNone(
attach_media_parts(
[{"role": "user", "content": [{"type": "text", "text": "hi"}]}],
n_images=1,
)
)
if __name__ == "__main__":
unittest.main()
-36
View File
@@ -1,36 +0,0 @@
import base64
import contextlib
import os
import tempfile
@contextlib.contextmanager
def materialize_base64(data, suffix=""):
"""Materialize base64 data for a path-only library and always remove it."""
descriptor, path = tempfile.mkstemp(prefix="localai-media-", suffix=suffix)
try:
with os.fdopen(descriptor, "wb") as output:
descriptor = None
output.write(base64.b64decode(data))
yield path
finally:
if descriptor is not None:
os.close(descriptor)
try:
os.remove(path)
except OSError:
pass
@contextlib.contextmanager
def cleanup_paths():
"""Collect temporary paths and remove them on success or failure."""
paths = []
try:
yield paths
finally:
for path in paths:
try:
os.remove(path)
except OSError:
pass
-41
View File
@@ -1,41 +0,0 @@
import os
import tempfile
import unittest
from unittest import mock
from temp_utils import cleanup_paths, materialize_base64
class MaterializeBase64Test(unittest.TestCase):
def test_removes_materialized_file_after_success(self):
with tempfile.TemporaryDirectory() as directory:
with mock.patch.object(tempfile, "tempdir", directory):
with materialize_base64("aGVsbG8=", suffix=".data") as path:
with open(path, "rb") as materialized:
self.assertEqual(materialized.read(), b"hello")
self.assertFalse(os.path.exists(path))
def test_removes_materialized_file_when_consumer_fails(self):
with tempfile.TemporaryDirectory() as directory:
with mock.patch.object(tempfile, "tempdir", directory):
with self.assertRaisesRegex(RuntimeError, "decode failed"):
with materialize_base64("aGVsbG8="):
raise RuntimeError("decode failed")
self.assertEqual(os.listdir(directory), [])
class CleanupPathsTest(unittest.TestCase):
def test_removes_every_registered_path_after_failure(self):
with tempfile.TemporaryDirectory() as directory:
paths = [os.path.join(directory, name) for name in ("one.wav", "two.wav")]
with self.assertRaisesRegex(RuntimeError, "merge failed"):
with cleanup_paths() as registered:
for path in paths:
open(path, "wb").close()
registered.append(path)
raise RuntimeError("merge failed")
self.assertEqual(os.listdir(directory), [])
if __name__ == "__main__":
unittest.main()
@@ -1,4 +1,4 @@
--extra-index-url https://download.pytorch.org/whl/xpu
torch==2.14.0+xpu
torch==2.13.0+xpu
oneccl_bind_pt==2.8.0+xpu
optimum[openvino]
@@ -1,3 +1,3 @@
grpcio==1.83.1
grpcio==1.82.1
protobuf
grpcio-tools
+2 -2
View File
@@ -1,4 +1,4 @@
grpcio==1.83.1
grpcio==1.83.0
protobuf
certifi
packaging==26.3
packaging==26.2
+9 -25
View File
@@ -122,21 +122,6 @@ from diffusers.schedulers import (
UniPCMultistepScheduler,
)
def select_device(request_cuda, device_option, cuda_available, xpu, mps_available):
"""Pick the pipeline device. An explicit `device:` model option wins;
otherwise CUDA is used whenever torch reports it available (ROCm
builds included) or the model config forces it with `cuda: true`,
keeping the pre-existing XPU/MPS overrides. CPU is the fallback, not
the default."""
if device_option:
return device_option
device = "cuda" if (request_cuda or cuda_available) else "cpu"
if xpu:
device = "xpu"
if mps_available:
device = "mps"
return device
def is_float(s):
"""Check if a string can be converted to float."""
try:
@@ -642,13 +627,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
# modify LoraAdapter to be relative to modelFileBase
request.LoraAdapter = os.path.join(request.ModelPath, request.LoraAdapter)
device = select_device(
request.CUDA,
self.options.pop("device", None),
torch.cuda.is_available(),
XPU,
hasattr(torch.backends, "mps") and torch.backends.mps.is_available(),
)
device = "cpu" if not request.CUDA else "cuda"
if XPU:
device = "xpu"
mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
if mps_available:
device = "mps"
self.device = device
if request.LoraAdapter:
# Check if its a local file and not a directory ( we load lora differently for a safetensor file )
@@ -816,12 +800,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
image = image.resize((1024, 576))
generator = torch.manual_seed(request.seed)
frames = self.pipe(image=image, guidance_scale=self.cfg_scale, decode_chunk_size=CHUNK_SIZE, generator=generator).frames[0]
frames = self.pipe(image, guidance_scale=self.cfg_scale, decode_chunk_size=CHUNK_SIZE, generator=generator).frames[0]
export_to_video(frames, request.dst, fps=FPS)
return backend_pb2.Result(message="Media generated successfully", success=True)
if self.txt2vid:
video_frames = self.pipe(prompt=prompt, guidance_scale=self.cfg_scale, num_inference_steps=steps, num_frames=int(FRAMES)).frames
video_frames = self.pipe(prompt, guidance_scale=self.cfg_scale, num_inference_steps=steps, num_frames=int(FRAMES)).frames
export_to_video(video_frames, request.dst)
return backend_pb2.Result(message="Media generated successfully", success=True)
@@ -884,7 +868,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
else:
# pass the kwargs dictionary to the self.pipe method
image = self.pipe(
prompt=prompt,
prompt,
guidance_scale=self.cfg_scale,
**kwargs
).images[0]
-72
View File
@@ -7,7 +7,6 @@ import time
from unittest.mock import patch, MagicMock
# Import dynamic loader for testing (these don't need gRPC)
import backend
import diffusers_dynamic_loader as loader
from diffusers import DiffusionPipeline, StableDiffusionPipeline
@@ -374,74 +373,3 @@ class TestGenerateImageOptionsKwargsMerge(unittest.TestCase):
finally:
os.unlink(src_file.name)
os.unlink(dst_file.name)
def test_text_to_image_prompt_is_passed_by_keyword(self):
"""Test compatibility with pipelines that take image before prompt."""
import os
import tempfile
from PIL import Image
from backend import BackendServicer
class Flux2CompatiblePipeline:
"""Model the FLUX.2 call signature: image is before prompt."""
def __call__(self, image=None, prompt=None, **kwargs):
if prompt is None:
raise ValueError("prompt was not passed by keyword")
self.prompt = prompt
self.kwargs = kwargs
return MagicMock(images=[Image.new("RGB", (4, 4))])
pipeline = Flux2CompatiblePipeline()
svc = BackendServicer.__new__(BackendServicer)
svc.pipe = pipeline
svc.cfg_scale = 7.5
svc.controlnet = None
svc.img2vid = False
svc.txt2vid = False
svc.clip_skip = 0
svc.PipelineType = "Flux2KleinPipeline"
svc.options = {}
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as dst_file:
dst_path = dst_file.name
try:
request = MagicMock()
request.positive_prompt = "a red apple on a wooden table"
request.negative_prompt = ""
request.step = 4
request.seed = 0
request.width = 0
request.height = 0
request.src = ""
request.ref_images = []
request.dst = dst_path
svc.GenerateImage(request, context=None)
self.assertEqual(pipeline.prompt, request.positive_prompt)
self.assertEqual(pipeline.kwargs["num_inference_steps"], 4)
finally:
os.unlink(dst_path)
class TestDeviceSelection(unittest.TestCase):
"""Unit tests for backend.select_device (no GPU required)."""
def test_autodetect_cuda(self):
self.assertEqual(backend.select_device(False, None, True, False, False), "cuda")
def test_cpu_fallback(self):
self.assertEqual(backend.select_device(False, None, False, False, False), "cpu")
def test_forced_cuda(self):
self.assertEqual(backend.select_device(True, None, False, False, False), "cuda")
def test_device_option_wins(self):
self.assertEqual(backend.select_device(True, "cpu", True, True, True), "cpu")
def test_mps_overrides(self):
self.assertEqual(backend.select_device(False, None, True, False, True), "mps")
+2 -5
View File
@@ -1,10 +1,7 @@
.PHONY: fish-speech test-source-preparation
fish-speech: test-source-preparation
.PHONY: fish-speech
fish-speech:
bash install.sh
test-source-preparation:
bash prepare-source_test.sh
.PHONY: run
run: fish-speech
@echo "Running fish-speech..."
+4 -4
View File
@@ -39,10 +39,10 @@ else
cd "${FISH_SPEECH_DIR}" && git pull && cd -
fi
# Keep the platform-specific PyTorch installed above. Upstream pins the generic
# PyPI torch wheel, which replaces ROCm builds with a CUDA wheel during the
# editable install. pyaudio is only used by the upstream playback client.
bash "${backend_dir}/prepare-source.sh" "${BUILD_TYPE:-}" "${FISH_SPEECH_DIR}/pyproject.toml"
# Remove pyaudio from fish-speech deps — it's only used by the upstream client tool
# (tools/api_client.py) for speaker playback, not by our gRPC backend server.
# It requires native portaudio libs which aren't available on all build environments.
sed -i.bak '/"pyaudio"/d' "${FISH_SPEECH_DIR}/pyproject.toml"
# Install fish-speech deps from source (without the package itself since we use PYTHONPATH)
ensureVenv
@@ -1,18 +0,0 @@
#!/bin/bash
set -euo pipefail
build_type=${1:-}
pyproject=${2:?usage: prepare-source.sh BUILD_TYPE PYPROJECT}
prepared=$(mktemp "${pyproject}.XXXXXX")
trap 'rm -f "$prepared"' EXIT
awk -v build_type="$build_type" '
/^dependencies = \[$/ { in_project_dependencies = 1 }
build_type == "hipblas" && in_project_dependencies && /^[[:space:]]*"(torch|torchaudio)[^"]*",?[[:space:]]*$/ { next }
in_project_dependencies && /^[[:space:]]*"pyaudio",?[[:space:]]*$/ { next }
{ print }
in_project_dependencies && /^\]$/ { in_project_dependencies = 0 }
' "$pyproject" > "$prepared"
mv "$prepared" "$pyproject"
trap - EXIT
@@ -1,66 +0,0 @@
#!/bin/bash
set -euo pipefail
SCRIPT_DIR=$(dirname "$(realpath "$0")")
WORK_DIR=$(mktemp -d)
trap 'rm -rf "$WORK_DIR"' EXIT
write_fixture() {
cat > "$1" <<'EOF'
[project]
dependencies = [
"numpy",
"torch==2.8.0",
"torchaudio==2.8.0",
"pyaudio",
]
[project.optional-dependencies]
stable = [
"torch==2.8.0",
"torchaudio",
]
EOF
}
write_fixture "$WORK_DIR/rocm.toml"
write_fixture "$WORK_DIR/cuda.toml"
write_fixture "$WORK_DIR/cpu.toml"
bash "$SCRIPT_DIR/prepare-source.sh" hipblas "$WORK_DIR/rocm.toml"
bash "$SCRIPT_DIR/prepare-source.sh" cublas "$WORK_DIR/cuda.toml"
bash "$SCRIPT_DIR/prepare-source.sh" "" "$WORK_DIR/cpu.toml"
cat > "$WORK_DIR/expected-rocm.toml" <<'EOF'
[project]
dependencies = [
"numpy",
]
[project.optional-dependencies]
stable = [
"torch==2.8.0",
"torchaudio",
]
EOF
cat > "$WORK_DIR/expected-default.toml" <<'EOF'
[project]
dependencies = [
"numpy",
"torch==2.8.0",
"torchaudio==2.8.0",
]
[project.optional-dependencies]
stable = [
"torch==2.8.0",
"torchaudio",
]
EOF
diff -u "$WORK_DIR/expected-rocm.toml" "$WORK_DIR/rocm.toml"
diff -u "$WORK_DIR/expected-default.toml" "$WORK_DIR/cuda.toml"
diff -u "$WORK_DIR/expected-default.toml" "$WORK_DIR/cpu.toml"
echo "PASS: source preparation preserves each platform's PyTorch dependencies"
-1
View File
@@ -8,5 +8,4 @@ else
source $backend_dir/../common/libbackend.sh
fi
bash "${backend_dir}/prepare-source_test.sh"
runUnittests
+1 -4
View File
@@ -127,10 +127,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
context.set_code(grpc.StatusCode.NOT_FOUND)
context.set_details("no face detected")
return backend_pb2.EmbeddingResult()
return backend_pb2.EmbeddingResult(
embeddings=[float(x) for x in vec],
layout=backend_pb2.EMBEDDING_LAYOUT_FINAL,
)
return backend_pb2.EmbeddingResult(embeddings=[float(x) for x in vec])
def Detect(self, request, context):
if self.engine is None:
+1 -1
View File
@@ -11,7 +11,7 @@ RPC. It supports:
systems such as NVIDIA DGX Spark.
Install the `longcat-video` or `longcat-video-avatar-1.5` recipe from the
LocalAI Model Gallery. LongCat video backend
LocalAI Model Gallery. See the [LongCat user guide](../../../docs/content/features/longcat-video.md)
for Studio and API examples, hardware requirements, and manual configuration.
The upstream source is pinned in `Makefile` and patched at build time. The
-8
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@@ -6,7 +6,6 @@ import datetime
import gc
import math
import os
import shutil
import signal
import subprocess
import sys
@@ -889,13 +888,6 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
def _release_model(self):
self.pipeline = None
self.model_kind = None
try:
if hasattr(self, "dist") and self.dist.is_initialized():
self.dist.destroy_process_group()
finally:
if self._dist_store_dir is not None:
shutil.rmtree(self._dist_store_dir, ignore_errors=True)
self._dist_store_dir = None
gc.collect()
if hasattr(self, "torch") and self.torch.cuda.is_available():
self.torch.cuda.empty_cache()
+15 -5
View File
@@ -18,7 +18,6 @@ sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'common'))
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'common'))
from grpc_auth import get_auth_interceptors
from model_utils import resolve_model_reference
from device_utils import device_map_for, select_device
@@ -96,7 +95,13 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
def LoadModel(self, request, context):
device = select_device(torch)
if torch.cuda.is_available():
device = "cuda"
else:
device = "cpu"
mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
if mps_available:
device = "mps"
if not torch.cuda.is_available() and request.CUDA:
return backend_pb2.Result(success=False, message="CUDA is not available")
@@ -118,7 +123,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
model_path, local_only = resolve_model_reference(
request, "Qwen/Qwen3-ASR-1.7B"
)
default_dtype = torch.bfloat16 if self.device in ("cuda", "xpu") else torch.float32
default_dtype = torch.bfloat16 if self.device == "cuda" else torch.float32
load_dtype = default_dtype
if "torch_dtype" in self.options:
d = str(self.options["torch_dtype"]).lower()
@@ -140,7 +145,12 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
if attn_implementation is not None and isinstance(attn_implementation, str):
attn_implementation = attn_implementation.strip() or None
device_map = device_map_for(self.device)
if self.device == "mps":
device_map = None
elif self.device == "cuda":
device_map = "cuda:0"
else:
device_map = "cpu"
load_kwargs = dict(
dtype=load_dtype,
@@ -413,4 +423,4 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run the gRPC server.")
parser.add_argument("--addr", default="localhost:50051", help="The address to bind the server to.")
args = parser.parse_args()
serve(args.addr)
serve(args.addr)
-18
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@@ -1,18 +0,0 @@
def select_device(torch_module):
mps = getattr(getattr(torch_module, "backends", None), "mps", None)
if mps is not None and mps.is_available():
return "mps"
if torch_module.cuda.is_available():
return "cuda"
xpu = getattr(torch_module, "xpu", None)
if xpu is not None and xpu.is_available():
return "xpu"
return "cpu"
def device_map_for(device):
if device == "mps":
return None
if device in ("cuda", "xpu"):
return f"{device}:0"
return "cpu"
@@ -1,58 +0,0 @@
import unittest
from device_utils import device_map_for, select_device
class Availability:
def __init__(self, available):
self._available = available
def is_available(self):
return self._available
class TorchStub:
def __init__(self, *, cuda=False, mps=False, xpu=False):
self.cuda = Availability(cuda)
self.backends = type("Backends", (), {"mps": Availability(mps)})()
self.xpu = Availability(xpu)
class SelectDeviceTest(unittest.TestCase):
def test_preserves_cuda_selection(self):
torch_module = TorchStub(cuda=True)
self.assertEqual(select_device(torch_module), "cuda")
def test_preserves_mps_selection(self):
torch_module = TorchStub(mps=True)
self.assertEqual(select_device(torch_module), "mps")
def test_selects_xpu_when_intel_gpu_is_available(self):
torch_module = TorchStub(xpu=True)
self.assertEqual(select_device(torch_module), "xpu")
def test_falls_back_to_cpu(self):
torch_module = TorchStub()
self.assertEqual(select_device(torch_module), "cpu")
class DeviceMapTest(unittest.TestCase):
def test_preserves_cuda_model_placement(self):
self.assertEqual(device_map_for("cuda"), "cuda:0")
def test_preserves_mps_model_placement(self):
self.assertIsNone(device_map_for("mps"))
def test_places_the_model_on_the_first_xpu(self):
self.assertEqual(device_map_for("xpu"), "xpu:0")
def test_preserves_cpu_model_placement(self):
self.assertEqual(device_map_for("cpu"), "cpu")
if __name__ == "__main__":
unittest.main()
+1 -1
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@@ -1,3 +1,3 @@
grpcio==1.83.1
grpcio==1.82.1
protobuf
certifi
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