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Author SHA1 Message Date
Ettore Di Giacinto
2a03905920 Merge branch 'master' into cleanup_deps 2024-08-21 13:10:46 +02:00
Ettore Di Giacinto
35297ebc14 Drop also ttf files
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-08-21 13:03:26 +02:00
Ettore Di Giacinto
b303805df9 fix marked 2024-08-21 13:02:19 +02:00
Ettore Di Giacinto
32d51797d9 fix alpine.js 2024-08-21 13:02:19 +02:00
Ettore Di Giacinto
af09b019ed fix(assets): generate assets on build time
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-08-21 13:02:19 +02:00
2072 changed files with 63926 additions and 529608 deletions

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# Adding a New Backend
When adding a new backend to LocalAI, you need to update several files to ensure the backend is properly built, tested, and registered. Here's a step-by-step guide based on the pattern used for adding backends like `moonshine`:
## 1. Create Backend Directory Structure
Create the backend directory under the appropriate location:
- **Python backends**: `backend/python/<backend-name>/`
- **Go backends**: `backend/go/<backend-name>/`
- **C++ backends**: `backend/cpp/<backend-name>/`
For Python backends, you'll typically need:
- `backend.py` - Main gRPC server implementation
- `Makefile` - Build configuration
- `install.sh` - Installation script for dependencies
- `protogen.sh` - Protocol buffer generation script
- `requirements.txt` - Python dependencies
- `run.sh` - Runtime script
- `test.py` / `test.sh` - Test files
## 2. Add Build Configurations to `.github/workflows/backend.yml`
Add build matrix entries for each platform/GPU type you want to support. Look at similar backends (e.g., `chatterbox`, `faster-whisper`) for reference.
**Placement in file:**
- CPU builds: Add after other CPU builds (e.g., after `cpu-chatterbox`)
- CUDA 12 builds: Add after other CUDA 12 builds (e.g., after `gpu-nvidia-cuda-12-chatterbox`)
- CUDA 13 builds: Add after other CUDA 13 builds (e.g., after `gpu-nvidia-cuda-13-chatterbox`)
**Additional build types you may need:**
- ROCm/HIP: Use `build-type: 'hipblas'` with `base-image: "rocm/dev-ubuntu-24.04:7.2.1"`
- Intel/SYCL: Use `build-type: 'intel'` or `build-type: 'sycl_f16'`/`sycl_f32` with `base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"`
- L4T (ARM): Use `build-type: 'l4t'` with `platforms: 'linux/arm64'` and `runs-on: 'ubuntu-24.04-arm'`
## 3. Add Backend Metadata to `backend/index.yaml`
**Step 3a: Add Meta Definition**
Add a YAML anchor definition in the `## metas` section (around line 2-300). Look for similar backends to use as a template such as `diffusers` or `chatterbox`
**Step 3b: Add Image Entries**
Add image entries at the end of the file, following the pattern of similar backends such as `diffusers` or `chatterbox`. Include both `latest` (production) and `master` (development) tags.
## 4. Update the Makefile
The Makefile needs to be updated in several places to support building and testing the new backend:
**Step 4a: Add to `.NOTPARALLEL`**
Add `backends/<backend-name>` to the `.NOTPARALLEL` line (around line 2) to prevent parallel execution conflicts:
```makefile
.NOTPARALLEL: ... backends/<backend-name>
```
**Step 4b: Add to `prepare-test-extra`**
Add the backend to the `prepare-test-extra` target (around line 312) to prepare it for testing:
```makefile
prepare-test-extra: protogen-python
...
$(MAKE) -C backend/python/<backend-name>
```
**Step 4c: Add to `test-extra`**
Add the backend to the `test-extra` target (around line 319) to run its tests:
```makefile
test-extra: prepare-test-extra
...
$(MAKE) -C backend/python/<backend-name> test
```
**Step 4d: Add Backend Definition**
Add a backend definition variable in the backend definitions section (around line 428-457). The format depends on the backend type:
**For Python backends with root context** (like `faster-whisper`, `coqui`):
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|python|.|false|true
```
**For Python backends with `./backend` context** (like `chatterbox`, `moonshine`):
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|python|./backend|false|true
```
**For Go backends**:
```makefile
BACKEND_<BACKEND_NAME> = <backend-name>|golang|.|false|true
```
**Step 4e: Generate Docker Build Target**
Add an eval call to generate the docker-build target (around line 480-501):
```makefile
$(eval $(call generate-docker-build-target,$(BACKEND_<BACKEND_NAME>)))
```
**Step 4f: Add to `docker-build-backends`**
Add `docker-build-<backend-name>` to the `docker-build-backends` target (around line 507):
```makefile
docker-build-backends: ... docker-build-<backend-name>
```
**Determining the Context:**
- If the backend is in `backend/python/<backend-name>/` and uses `./backend` as context in the workflow file, use `./backend` context
- If the backend is in `backend/python/<backend-name>/` but uses `.` as context in the workflow file, use `.` context
- Check similar backends to determine the correct context
## 5. Verification Checklist
After adding a new backend, verify:
- [ ] Backend directory structure is complete with all necessary files
- [ ] Build configurations added to `.github/workflows/backend.yml` for all desired platforms
- [ ] Meta definition added to `backend/index.yaml` in the `## metas` section
- [ ] Image entries added to `backend/index.yaml` for all build variants (latest + development)
- [ ] Tag suffixes match between workflow file and index.yaml
- [ ] Makefile updated with all 6 required changes (`.NOTPARALLEL`, `prepare-test-extra`, `test-extra`, backend definition, docker-build target eval, `docker-build-backends`)
- [ ] No YAML syntax errors (check with linter)
- [ ] No Makefile syntax errors (check with linter)
- [ ] Follows the same pattern as similar backends (e.g., if it's a transcription backend, follow `faster-whisper` pattern)
## Bundling runtime shared libraries (`package.sh`)
The final `Dockerfile.python` stage is `FROM scratch` — there is no system `libc`, no `apt`, no fallback library path. Only files explicitly copied from the builder stage end up in the backend image. That means any runtime `dlopen` your backend (or its Python deps) needs **must** be packaged into `${BACKEND}/lib/`.
Pattern:
1. Make sure the library is installed in the builder stage of `backend/Dockerfile.python` (add it to the top-level `apt-get install`).
2. Drop a `package.sh` in your backend directory that copies the library — and its soname symlinks — into `$(dirname $0)/lib`. See `backend/python/vllm/package.sh` for a reference implementation that walks `/usr/lib/x86_64-linux-gnu`, `/usr/lib/aarch64-linux-gnu`, etc.
3. `Dockerfile.python` already runs `package.sh` automatically if it exists, after `package-gpu-libs.sh`.
4. `libbackend.sh` automatically prepends `${EDIR}/lib` to `LD_LIBRARY_PATH` at run time, so anything packaged this way is found by `dlopen`.
How to find missing libs: when a Python module silently fails to register torch ops or you see `AttributeError: '_OpNamespace' '...' object has no attribute '...'`, run the backend image's Python with `LD_DEBUG=libs` to see which `dlopen` failed. The filename in the error message (e.g. `libnuma.so.1`) is what you need to package.
To verify packaging works without trusting the host:
```bash
make docker-build-<backend>
CID=$(docker create --entrypoint=/run.sh local-ai-backend:<backend>)
docker cp $CID:/lib /tmp/check && docker rm $CID
ls /tmp/check # expect the bundled .so files + symlinks
```
Then boot it inside a fresh `ubuntu:24.04` (which intentionally does *not* have the lib installed) to confirm it actually loads from the backend dir.
## 6. Example: Adding a Python Backend
For reference, when `moonshine` was added:
- **Files created**: `backend/python/moonshine/{backend.py, Makefile, install.sh, protogen.sh, requirements.txt, run.sh, test.py, test.sh}`
- **Workflow entries**: 3 build configurations (CPU, CUDA 12, CUDA 13)
- **Index entries**: 1 meta definition + 6 image entries (cpu, cuda12, cuda13 x latest/development)
- **Makefile updates**:
- Added to `.NOTPARALLEL` line
- Added to `prepare-test-extra` and `test-extra` targets
- Added `BACKEND_MOONSHINE = moonshine|python|./backend|false|true`
- Added eval for docker-build target generation
- Added `docker-build-moonshine` to `docker-build-backends`

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# Adding GGUF Models from HuggingFace to the Gallery
When adding a GGUF model from HuggingFace to the LocalAI model gallery, follow this guide.
## Gallery file
All models are defined in `gallery/index.yaml`. Find the appropriate section (embedding models near other embeddings, chat models near similar chat models) and add a new entry.
## Getting the SHA256
GGUF files on HuggingFace expose their SHA256 via the `x-linked-etag` HTTP header. Fetch it with:
```bash
curl -sI "https://huggingface.co/<org>/<repo>/resolve/main/<filename>.gguf" | grep -i x-linked-etag
```
The value (without quotes) is the SHA256 hash. Example:
```bash
curl -sI "https://huggingface.co/ggml-org/embeddinggemma-300m-qat-q8_0-GGUF/resolve/main/embeddinggemma-300m-qat-Q8_0.gguf" | grep -i x-linked-etag
# x-linked-etag: "6fa0c02a9c302be6f977521d399b4de3a46310a4f2621ee0063747881b673f67"
```
**Important**: Pay attention to exact filename casing — HuggingFace filenames are case-sensitive (e.g., `Q8_0` vs `q8_0`). Check the repo's file listing to get the exact name.
## Entry format — Embedding models
Embedding models use `gallery/virtual.yaml` as the base config and set `embeddings: true`:
```yaml
- name: "model-name"
url: github:mudler/LocalAI/gallery/virtual.yaml@master
urls:
- https://huggingface.co/<original-model-org>/<original-model-name>
- https://huggingface.co/<gguf-org>/<gguf-repo-name>
description: |
Short description of the model, its size, and capabilities.
tags:
- embeddings
overrides:
backend: llama-cpp
embeddings: true
parameters:
model: <filename>.gguf
files:
- filename: <filename>.gguf
uri: huggingface://<gguf-org>/<gguf-repo-name>/<filename>.gguf
sha256: <sha256-hash>
```
## Entry format — Chat/LLM models
Chat models typically reference a template config (e.g., `gallery/gemma.yaml`, `gallery/chatml.yaml`) that defines the prompt format. Use YAML anchors (`&name` / `*name`) if adding multiple quantization variants of the same model:
```yaml
- &model-anchor
url: "github:mudler/LocalAI/gallery/<template>.yaml@master"
name: "model-name"
icon: https://example.com/icon.png
license: <license>
urls:
- https://huggingface.co/<org>/<model>
- https://huggingface.co/<gguf-org>/<gguf-repo>
description: |
Model description.
tags:
- llm
- gguf
- gpu
- cpu
overrides:
parameters:
model: <filename>-Q4_K_M.gguf
files:
- filename: <filename>-Q4_K_M.gguf
sha256: <sha256>
uri: huggingface://<gguf-org>/<gguf-repo>/<filename>-Q4_K_M.gguf
```
To add a variant (e.g., different quantization), use YAML merge:
```yaml
- !!merge <<: *model-anchor
name: "model-name-q8"
overrides:
parameters:
model: <filename>-Q8_0.gguf
files:
- filename: <filename>-Q8_0.gguf
sha256: <sha256>
uri: huggingface://<gguf-org>/<gguf-repo>/<filename>-Q8_0.gguf
```
## Available template configs
Look at existing `.yaml` files in `gallery/` to find the right prompt template for your model architecture:
- `gemma.yaml` — Gemma-family models (gemma, embeddinggemma, etc.)
- `chatml.yaml` — ChatML format (many Mistral/OpenHermes models)
- `deepseek.yaml` — DeepSeek models
- `virtual.yaml` — Minimal base (good for embedding models that don't need chat templates)
## Checklist
1. **Find the GGUF file** on HuggingFace — note exact filename (case-sensitive)
2. **Get the SHA256** using the `curl -sI` + `x-linked-etag` method above
3. **Choose the right template** config from `gallery/` based on model architecture
4. **Add the entry** to `gallery/index.yaml` near similar models
5. **Set `embeddings: true`** if it's an embedding model
6. **Include both URLs** — the original model page and the GGUF repo
7. **Write a description** — mention model size, capabilities, and quantization type

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# AI Coding Assistants
This document provides guidance for AI tools and developers using AI
assistance when contributing to LocalAI.
**LocalAI follows the same guidelines as the Linux kernel project for
AI-assisted contributions.** See the upstream policy here:
<https://docs.kernel.org/process/coding-assistants.html>
The rules below mirror that policy, adapted to LocalAI's license and
project layout. If anything is unclear, the kernel document is the
authoritative reference for intent.
AI tools helping with LocalAI development should follow the standard
project development process:
- [CONTRIBUTING.md](../CONTRIBUTING.md) — development workflow, commit
conventions, and PR guidelines
- [.agents/coding-style.md](coding-style.md) — code style, editorconfig,
logging, and documentation conventions
- [.agents/building-and-testing.md](building-and-testing.md) — build and
test procedures
## Licensing and Legal Requirements
All contributions must comply with LocalAI's licensing requirements:
- LocalAI is licensed under the **MIT License** — see the [LICENSE](../LICENSE)
file
- New source files should use the SPDX license identifier `MIT` where
applicable to the file type
- Contributions must be compatible with the MIT License and must not
introduce code under incompatible licenses (e.g., GPL) without an
explicit discussion with maintainers
## Signed-off-by and Developer Certificate of Origin
**AI agents MUST NOT add `Signed-off-by` tags.** Only humans can legally
certify the Developer Certificate of Origin (DCO). The human submitter
is responsible for:
- Reviewing all AI-generated code
- Ensuring compliance with licensing requirements
- Adding their own `Signed-off-by` tag (when the project requires DCO)
to certify the contribution
- Taking full responsibility for the contribution
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).
## Attribution
When AI tools contribute to LocalAI development, proper attribution helps
track the evolving role of AI in the development process. Contributions
should include an `Assisted-by` tag in the commit message trailer in the
following format:
```
Assisted-by: AGENT_NAME:MODEL_VERSION [TOOL1] [TOOL2]
```
Where:
- `AGENT_NAME` — name of the AI tool or framework (e.g., `Claude`,
`Copilot`, `Cursor`)
- `MODEL_VERSION` — specific model version used (e.g.,
`claude-opus-4-7`, `gpt-5`)
- `[TOOL1] [TOOL2]` — optional specialized analysis tools invoked by the
agent (e.g., `golangci-lint`, `staticcheck`, `go vet`)
Basic development tools (git, go, make, editors) should **not** be listed.
### Example
```
fix(llama-cpp): handle empty tool call arguments
Previously the parser panicked when the model returned a tool call with
an empty arguments object. Fall back to an empty JSON object in that
case so downstream consumers receive a valid payload.
Assisted-by: Claude:claude-opus-4-7 golangci-lint
Signed-off-by: Jane Developer <jane@example.com>
```
## Scope and Responsibility
Using an AI assistant does not reduce the contributor's responsibility.
The human submitter must:
- Understand every line that lands in the PR
- Verify that generated code compiles, passes tests, and follows the
project style
- Confirm that any referenced APIs, flags, or file paths actually exist
in the current tree (AI models may hallucinate identifiers)
- Not submit AI output verbatim without review
Reviewers may ask for clarification on any change regardless of how it
was produced. "An AI wrote it" is not an acceptable answer to a design
question.

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# API Endpoints and Authentication
This guide covers how to add new API endpoints and properly integrate them with the auth/permissions system.
> **Before you ship a new endpoint or capability surface**, re-read the [checklist at the bottom of this file](#checklist). LocalAI advertises its feature surface in several independent places — miss any one of them and clients/admins/UI won't know the endpoint exists.
## Architecture overview
Authentication and authorization flow through three layers:
1. **Global auth middleware** (`core/http/auth/middleware.go``auth.Middleware`) — applied to every request in `core/http/app.go`. Handles session cookies, Bearer tokens, API keys, and legacy API keys. Populates `auth_user` and `auth_role` in the Echo context.
2. **Feature middleware** (`auth.RequireFeature`) — per-feature access control applied to route groups or individual routes. Checks if the authenticated user has the specific feature enabled.
3. **Admin middleware** (`auth.RequireAdmin`) — restricts endpoints to admin users only.
When auth is disabled (no auth DB, no legacy API keys), all middleware becomes pass-through (`auth.NoopMiddleware`).
## Adding a new API endpoint
### Step 1: Create the handler
Write the endpoint handler in the appropriate package under `core/http/endpoints/`. Follow existing patterns:
```go
// core/http/endpoints/localai/my_feature.go
func MyFeatureEndpoint(app *application.Application) echo.HandlerFunc {
return func(c echo.Context) error {
// Use auth.GetUser(c) to get the authenticated user (may be nil if auth is disabled)
user := auth.GetUser(c)
// Your logic here
return c.JSON(http.StatusOK, result)
}
}
```
### Step 2: Register routes
Add routes in the appropriate file under `core/http/routes/`. The file you use depends on the endpoint category:
| File | Category |
|------|----------|
| `routes/openai.go` | OpenAI-compatible API endpoints (`/v1/...`) |
| `routes/localai.go` | LocalAI-specific endpoints (`/api/...`, `/models/...`, `/backends/...`) |
| `routes/agents.go` | Agent pool endpoints (`/api/agents/...`) |
| `routes/auth.go` | Auth endpoints (`/api/auth/...`) |
| `routes/ui_api.go` | UI backend API endpoints |
### Step 3: Apply the right middleware
Choose the appropriate protection level:
#### No auth required (public)
Exempt paths bypass auth entirely. Add to `isExemptPath()` in `middleware.go` or use the `/api/auth/` prefix (always exempt). Use sparingly — most endpoints should require auth.
#### Standard auth (any authenticated user)
The global middleware already handles this. API paths (`/api/`, `/v1/`, etc.) automatically require authentication when auth is enabled. You don't need to add any extra middleware.
```go
router.GET("/v1/my-endpoint", myHandler) // auth enforced by global middleware
```
#### Admin only
Pass `adminMiddleware` to the route. This is set up in `app.go` and passed to `Register*Routes` functions:
```go
// In the Register function signature, accept the middleware:
func RegisterMyRoutes(router *echo.Echo, app *application.Application, adminMiddleware echo.MiddlewareFunc) {
router.POST("/models/apply", myHandler, adminMiddleware)
}
```
#### Feature-gated
For endpoints that should be toggleable per-user, use feature middleware. There are two approaches:
**Approach A: Route-level middleware** (preferred for groups of related endpoints)
```go
// In app.go, create the feature middleware:
myFeatureMw := auth.RequireFeature(application.AuthDB(), auth.FeatureMyFeature)
// Pass it to the route registration function:
routes.RegisterMyRoutes(e, app, myFeatureMw)
// In the routes file, apply to a group:
g := e.Group("/api/my-feature", myFeatureMw)
g.GET("", listHandler)
g.POST("", createHandler)
```
**Approach B: RouteFeatureRegistry** (preferred for individual OpenAI-compatible endpoints)
Add an entry to `RouteFeatureRegistry` in `core/http/auth/features.go`. The `RequireRouteFeature` global middleware will automatically enforce it:
```go
var RouteFeatureRegistry = []RouteFeature{
// ... existing entries ...
{"POST", "/v1/my-endpoint", FeatureMyFeature},
}
```
## Adding a new feature
When you need a new toggleable feature (not just a new endpoint under an existing feature):
### 1. Define the feature constant
Add to `core/http/auth/permissions.go`:
```go
const (
// Add to the appropriate group:
// Agent features (default OFF for new users)
FeatureMyFeature = "my_feature"
// OR API features (default ON for new users)
FeatureMyFeature = "my_feature"
)
```
Then add it to the appropriate slice:
```go
// Default OFF — user must be explicitly granted access:
var AgentFeatures = []string{..., FeatureMyFeature}
// Default ON — user has access unless explicitly revoked:
var APIFeatures = []string{..., FeatureMyFeature}
```
### 2. Add feature metadata
In `core/http/auth/features.go`, add to the appropriate `FeatureMetas` function so the admin UI can display it:
```go
func AgentFeatureMetas() []FeatureMeta {
return []FeatureMeta{
// ... existing ...
{FeatureMyFeature, "My Feature", false}, // false = default OFF
}
}
```
### 3. Wire up the middleware
In `core/http/app.go`:
```go
myFeatureMw := auth.RequireFeature(application.AuthDB(), auth.FeatureMyFeature)
```
Then pass it to the route registration function.
### 4. Register route-feature mappings (if applicable)
If your feature gates standard API endpoints (like `/v1/...`), add entries to `RouteFeatureRegistry` in `features.go` instead of using per-route middleware.
## Accessing the authenticated user in handlers
```go
import "github.com/mudler/LocalAI/core/http/auth"
func MyHandler(c echo.Context) error {
// Get the user (nil when auth is disabled or unauthenticated)
user := auth.GetUser(c)
if user == nil {
// Handle unauthenticated — or let middleware handle it
}
// Check role
if user.Role == auth.RoleAdmin {
// admin-specific logic
}
// Check feature access programmatically (when you need conditional behavior, not full blocking)
if auth.HasFeatureAccess(db, user, auth.FeatureMyFeature) {
// feature-specific logic
}
// Check model access
if !auth.IsModelAllowed(db, user, modelName) {
return c.JSON(http.StatusForbidden, ...)
}
}
```
## Middleware composition patterns
Middleware can be composed at different levels. Here are the patterns used in the codebase:
### Group-level middleware (agents pattern)
```go
// All routes in the group share the middleware
g := e.Group("/api/agents", poolReadyMw, agentsMw)
g.GET("", listHandler)
g.POST("", createHandler)
```
### Per-route middleware (localai pattern)
```go
// Individual routes get middleware as extra arguments
router.POST("/models/apply", applyHandler, adminMiddleware)
router.GET("/metrics", metricsHandler, adminMiddleware)
```
### Middleware slice (openai pattern)
```go
// Build a middleware chain for a handler
chatMiddleware := []echo.MiddlewareFunc{
usageMiddleware,
traceMiddleware,
modelFilterMiddleware,
}
app.POST("/v1/chat/completions", chatHandler, chatMiddleware...)
```
## Error response format
Always use `schema.ErrorResponse` for auth/permission errors to stay consistent with the OpenAI-compatible API:
```go
return c.JSON(http.StatusForbidden, schema.ErrorResponse{
Error: &schema.APIError{
Message: "feature not enabled for your account",
Code: http.StatusForbidden,
Type: "authorization_error",
},
})
```
Use these HTTP status codes:
- `401 Unauthorized` — no valid credentials provided
- `403 Forbidden` — authenticated but lacking permission
- `429 Too Many Requests` — rate limited (auth endpoints)
## Usage tracking
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`.
## 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.
### 1. Swagger `@Tags` annotation (mandatory)
Every handler needs a swagger block so the endpoint appears in `/swagger/index.html` and in the `/api/instructions` output. The `@Tags` value is what groups the endpoint into a capability area:
```go
// MyEndpoint does X.
// @Summary Do X.
// @Tags my-capability
// @Param request body schema.MyRequest true "payload"
// @Success 200 {object} schema.MyResponse "Response"
// @Router /v1/my-endpoint [post]
func MyEndpoint(...) echo.HandlerFunc { ... }
```
Use an existing tag when the endpoint extends an existing area (e.g. `audio`, `images`, `face-recognition`). Create a new tag only when the endpoint introduces a genuinely new capability surface — and in that case, also register it in step 2.
After adding endpoints, regenerate the embedded spec so the runtime serves it:
```bash
make protogen-go # ensures gRPC codegen is fresh first
make swagger # regenerates swagger/swagger.json
```
### 2. `/api/instructions` registry (for new capability areas)
`core/http/endpoints/localai/api_instructions.go` defines `instructionDefs` — a lightweight, machine-readable index of capability areas that groups swagger endpoints by tag. It's the primary discovery surface for agents and SDKs ("what can this server do?").
**When to update:** only when adding a new capability area (a new swagger tag). Existing-tag additions automatically surface without any change here.
Add an entry to `instructionDefs`:
```go
{
Name: "my-capability", // URL segment at /api/instructions/my-capability
Description: "Short sentence describing the capability",
Tags: []string{"my-capability"}, // must match swagger @Tags
Intro: "Optional gotcha/context that isn't in the swagger descriptions (caveats, defaults, cross-references to other endpoints).",
},
```
Also bump the expected-length count in `api_instructions_test.go` and add the name to the `ContainElements` assertion.
### 3. `capabilities.js` symbol (for new model-config FLAG_* flags)
If your feature needs a new `FLAG_*` usecase flag in `core/config/model_config.go` (so users can filter gallery models by it, and so `/v1/models` surfaces it), also declare the matching symbol in `core/http/react-ui/src/utils/capabilities.js`:
```js
export const CAP_MY_CAPABILITY = 'FLAG_MY_CAPABILITY'
```
React pages that want to filter the ModelSelector by capability import this symbol. Declare it even if you're not building the UI page yet — the declaration keeps the Go/JS vocabularies in sync.
### 4. `docs/content/` (user-facing documentation)
A new capability deserves its own page under `docs/content/features/`, plus cross-links from related features and an entry in `docs/content/whats-new.md`. See the pattern used by `face-recognition.md` / `object-detection.md`.
## Path protection rules
The global auth middleware classifies paths as API paths or non-API paths:
- **API paths** (always require auth when auth is enabled): `/api/`, `/v1/`, `/models/`, `/backends/`, `/backend/`, `/tts`, `/vad`, `/video`, `/stores/`, `/system`, `/ws/`, `/metrics`
- **Exempt paths** (never require auth): `/api/auth/` prefix, anything in `appConfig.PathWithoutAuth`
- **Non-API paths** (UI, static assets): pass through without auth — the React UI handles login redirects client-side
If you add endpoints under a new top-level path prefix, add it to `isAPIPath()` in `middleware.go` to ensure it requires authentication.
## Checklist
When adding a new endpoint:
**Routing & auth**
- [ ] Handler in `core/http/endpoints/`
- [ ] Route registered in appropriate `core/http/routes/` file
- [ ] Auth level chosen: public / standard / admin / feature-gated
- [ ] Entry added to `RouteFeatureRegistry` in `core/http/auth/features.go` (one row per route/method — all /v1/* routes gate through this, not per-route middleware)
- [ ] If new feature: constant in `permissions.go`, added to the right slice (`APIFeatures` default-ON / `AgentFeatures` default-OFF), metadata in `features.go` `*FeatureMetas()`
- [ ] If feature uses group middleware: wired in `core/http/app.go` and passed to the route registration function
- [ ] If new path prefix: added to `isAPIPath()` in `middleware.go`
- [ ] If token-counting: `usageMiddleware` added to middleware chain
**Advertising surfaces (easy to miss — see the [Advertising surfaces](#advertising-surfaces--where-to-register-a-new-capability) section)**
- [ ] Swagger block on the handler: `@Summary`, `@Tags`, `@Param`, `@Success`, `@Router`
- [ ] If new capability area (new swagger tag): entry in `instructionDefs` in `core/http/endpoints/localai/api_instructions.go` + test count bumped in `api_instructions_test.go`
- [ ] If new `FLAG_*` usecase flag: matching `CAP_*` symbol exported from `core/http/react-ui/src/utils/capabilities.js`
- [ ] `docs/content/features/<feature>.md` created; cross-links from related feature pages; entry in `docs/content/whats-new.md`
**Quality**
- [ ] Error responses use `schema.ErrorResponse` format (or `echo.NewHTTPError` with a mapped gRPC status — see the `mapBackendError` helper in `core/http/endpoints/localai/images.go`)
- [ ] Tests cover both authenticated and unauthenticated access
- [ ] Swagger regenerated (`make swagger`) if you changed any `@Router`/`@Tags`/`@Param` annotation

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# Build and Testing
Building and testing the project depends on the components involved and the platform where development is taking place. Due to the amount of context required it's usually best not to try building or testing the project unless the user requests it. If you must build the project then inspect the Makefile in the project root and the Makefiles of any backends that are effected by changes you are making. In addition the workflows in .github/workflows can be used as a reference when it is unclear how to build or test a component. The primary Makefile contains targets for building inside or outside Docker, if the user has not previously specified a preference then ask which they would like to use.
## Building a specified backend
Let's say the user wants to build a particular backend for a given platform. For example let's say they want to build coqui for ROCM/hipblas
- The Makefile has targets like `docker-build-coqui` created with `generate-docker-build-target` at the time of writing. Recently added backends may require a new target.
- At a minimum we need to set the BUILD_TYPE, BASE_IMAGE build-args
- Use .github/workflows/backend.yml as a reference it lists the needed args in the `include` job strategy matrix
- l4t and cublas also requires the CUDA major and minor version
- You can pretty print a command like `DOCKER_MAKEFLAGS=-j$(nproc --ignore=1) BUILD_TYPE=hipblas BASE_IMAGE=rocm/dev-ubuntu-24.04:7.2.1 make docker-build-coqui`
- Unless the user specifies that they want you to run the command, then just print it because not all agent frontends handle long running jobs well and the output may overflow your context
- The user may say they want to build AMD or ROCM instead of hipblas, or Intel instead of SYCL or NVIDIA insted of l4t or cublas. Ask for confirmation if there is ambiguity.
- Sometimes the user may need extra parameters to be added to `docker build` (e.g. `--platform` for cross-platform builds or `--progress` to view the full logs), in which case you can generate the `docker build` command directly.

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# Coding Style
The project has the following .editorconfig:
```
root = true
[*]
indent_style = space
indent_size = 2
end_of_line = lf
charset = utf-8
trim_trailing_whitespace = true
insert_final_newline = true
[*.go]
indent_style = tab
[Makefile]
indent_style = tab
[*.proto]
indent_size = 2
[*.py]
indent_size = 4
[*.js]
indent_size = 2
[*.yaml]
indent_size = 2
[*.md]
trim_trailing_whitespace = false
```
- Use comments sparingly to explain why code does something, not what it does. Comments are there to add context that would be difficult to deduce from reading the code.
- Prefer modern Go e.g. use `any` not `interface{}`
## Logging
Use `github.com/mudler/xlog` for logging which has the same API as slog.
## Documentation
The project documentation is located in `docs/content`. When adding new features or changing existing functionality, it is crucial to update the documentation to reflect these changes. This helps users understand how to use the new capabilities and ensures the documentation stays relevant.
- **Feature Documentation**: If you add a new feature (like a new backend or API endpoint), create a new markdown file in `docs/content/features/` explaining what it is, how to configure it, and how to use it.
- **Configuration**: If you modify configuration options, update the relevant sections in `docs/content/`.
- **Examples**: providing concrete examples (like YAML configuration blocks) is highly encouraged to help users get started quickly.
- **Shortcodes**: Use `{{% notice note %}}`, `{{% notice tip %}}`, or `{{% notice warning %}}` for callout boxes. Do **not** use `{{% alert %}}` — that shortcode does not exist in this project's Hugo theme and will break the docs build.

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# Debugging and Rebuilding Backends
When a backend fails at runtime (e.g. a gRPC method error, a Python import error, or a dependency conflict), use this guide to diagnose, fix, and rebuild.
## Architecture Overview
- **Source directory**: `backend/python/<name>/` (or `backend/go/<name>/`, `backend/cpp/<name>/`)
- **Installed directory**: `backends/<name>/` — this is what LocalAI actually runs. It is populated by `make backends/<name>` which builds a Docker image, exports it, and installs it via `local-ai backends install`.
- **Virtual environment**: `backends/<name>/venv/` — the installed Python venv (for Python backends). The Python binary is at `backends/<name>/venv/bin/python`.
Editing files in `backend/python/<name>/` does **not** affect the running backend until you rebuild with `make backends/<name>`.
## Diagnosing Failures
### 1. Check the logs
Backend gRPC processes log to LocalAI's stdout/stderr. Look for lines tagged with the backend's model ID:
```
GRPC stderr id="trl-finetune-127.0.0.1:37335" line="..."
```
Common error patterns:
- **"Method not implemented"** — the backend is missing a gRPC method that the Go side calls. The model loader (`pkg/model/initializers.go`) always calls `LoadModel` after `Health`; fine-tuning backends must implement it even as a no-op stub.
- **Python import errors / `AttributeError`** — usually a dependency version mismatch (e.g. `pyarrow` removing `PyExtensionType`).
- **"failed to load backend"** — the gRPC process crashed or never started. Check stderr lines for the traceback.
### 2. Test the Python environment directly
You can run the installed venv's Python to check imports without starting the full server:
```bash
backends/<name>/venv/bin/python -c "import datasets; print(datasets.__version__)"
```
If `pip` is missing from the venv, bootstrap it:
```bash
backends/<name>/venv/bin/python -m ensurepip
```
Then use `backends/<name>/venv/bin/python -m pip install ...` to test fixes in the installed venv before committing them to the source requirements.
### 3. Check upstream dependency constraints
When you hit a dependency conflict, check what the main library expects. For example, TRL's upstream `requirements.txt`:
```
https://github.com/huggingface/trl/blob/main/requirements.txt
```
Pin minimum versions in the backend's requirements files to match upstream.
## Common Fixes
### Missing gRPC methods
If the Go side calls a method the backend doesn't implement (e.g. `LoadModel`), add a no-op stub in `backend.py`:
```python
def LoadModel(self, request, context):
"""No-op — actual loading happens elsewhere."""
return backend_pb2.Result(success=True, message="OK")
```
The gRPC contract requires `LoadModel` to succeed for the model loader to return a usable client, even if the backend doesn't need upfront model loading.
### Dependency version conflicts
Python backends often break when a transitive dependency releases a breaking change (e.g. `pyarrow` removing `PyExtensionType`). Steps:
1. Identify the broken import in the logs
2. Test in the installed venv: `backends/<name>/venv/bin/python -c "import <module>"`
3. Check upstream requirements for version constraints
4. Update **all** requirements files in `backend/python/<name>/`:
- `requirements.txt` — base deps (grpcio, protobuf)
- `requirements-cpu.txt` — CPU-specific (includes PyTorch CPU index)
- `requirements-cublas12.txt` — CUDA 12
- `requirements-cublas13.txt` — CUDA 13
5. Rebuild: `make backends/<name>`
### PyTorch index conflicts (uv resolver)
The Docker build uses `uv` for pip installs. When `--extra-index-url` points to the PyTorch wheel index, `uv` may refuse to fetch packages like `requests` from PyPI if it finds a different version on the PyTorch index first. Fix this by adding `--index-strategy=unsafe-first-match` to `install.sh`:
```bash
EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
installRequirements
```
Most Python backends already do this — check `backend/python/transformers/install.sh` or similar for reference.
## Rebuilding
### Rebuild a single backend
```bash
make backends/<name>
```
This runs the Docker build (`Dockerfile.python`), exports the image to `backend-images/<name>.tar`, and installs it into `backends/<name>/`. It also rebuilds the `local-ai` Go binary (without extra tags).
**Important**: If you were previously running with `GO_TAGS=auth`, the `make backends/<name>` step will overwrite your binary without that tag. Rebuild the Go binary afterward:
```bash
GO_TAGS=auth make build
```
### Rebuild and restart
After rebuilding a backend, you must restart LocalAI for it to pick up the new backend files. The backend gRPC process is spawned on demand when the model is first loaded.
```bash
# Kill existing process
kill <pid>
# Restart
./local-ai run --debug [your flags]
```
### Quick iteration (skip Docker rebuild)
For fast iteration on a Python backend's `backend.py` without a full Docker rebuild, you can edit the installed copy directly:
```bash
# Edit the installed copy
vim backends/<name>/backend.py
# Restart LocalAI to respawn the gRPC process
```
This is useful for testing but **does not persist** — the next `make backends/<name>` will overwrite it. Always commit fixes to the source in `backend/python/<name>/`.
## Verification
After fixing and rebuilding:
1. Start LocalAI and confirm the backend registers: look for `Registering backend name="<name>"` in the logs
2. Trigger the operation that failed (e.g. start a fine-tuning job)
3. Watch the GRPC stderr/stdout lines for the backend's model ID
4. Confirm no errors in the traceback

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# llama.cpp Backend
The llama.cpp backend (`backend/cpp/llama-cpp/grpc-server.cpp`) is a gRPC adaptation of the upstream HTTP server (`llama.cpp/tools/server/server.cpp`). It uses the same underlying server infrastructure from `llama.cpp/tools/server/server-context.cpp`.
## Building and Testing
- Test llama.cpp backend compilation: `make backends/llama-cpp`
- The backend is built as part of the main build process
- Check `backend/cpp/llama-cpp/Makefile` for build configuration
## Architecture
- **grpc-server.cpp**: gRPC server implementation, adapts HTTP server patterns to gRPC
- Uses shared server infrastructure: `server-context.cpp`, `server-task.cpp`, `server-queue.cpp`, `server-common.cpp`
- The gRPC server mirrors the HTTP server's functionality but uses gRPC instead of HTTP
## Common Issues When Updating llama.cpp
When fixing compilation errors after upstream changes:
1. Check how `server.cpp` (HTTP server) handles the same change
2. Look for new public APIs or getter methods
3. Store copies of needed data instead of accessing private members
4. Update function calls to match new signatures
5. Test with `make backends/llama-cpp`
## Key Differences from HTTP Server
- gRPC uses `BackendServiceImpl` class with gRPC service methods
- HTTP server uses `server_routes` with HTTP handlers
- Both use the same `server_context` and task queue infrastructure
- gRPC methods: `LoadModel`, `Predict`, `PredictStream`, `Embedding`, `Rerank`, `TokenizeString`, `GetMetrics`, `Health`
## Tool Call Parsing Maintenance
When working on JSON/XML tool call parsing functionality, always check llama.cpp for reference implementation and updates:
### Checking for XML Parsing Changes
1. **Review XML Format Definitions**: Check `llama.cpp/common/chat-parser-xml-toolcall.h` for `xml_tool_call_format` struct changes
2. **Review Parsing Logic**: Check `llama.cpp/common/chat-parser-xml-toolcall.cpp` for parsing algorithm updates
3. **Review Format Presets**: Check `llama.cpp/common/chat-parser.cpp` for new XML format presets (search for `xml_tool_call_format form`)
4. **Review Model Lists**: Check `llama.cpp/common/chat.h` for `COMMON_CHAT_FORMAT_*` enum values that use XML parsing:
- `COMMON_CHAT_FORMAT_GLM_4_5`
- `COMMON_CHAT_FORMAT_MINIMAX_M2`
- `COMMON_CHAT_FORMAT_KIMI_K2`
- `COMMON_CHAT_FORMAT_QWEN3_CODER_XML`
- `COMMON_CHAT_FORMAT_APRIEL_1_5`
- `COMMON_CHAT_FORMAT_XIAOMI_MIMO`
- Any new formats added
### Model Configuration Options
Always check `llama.cpp` for new model configuration options that should be supported in LocalAI:
1. **Check Server Context**: Review `llama.cpp/tools/server/server-context.cpp` for new parameters
2. **Check Chat Params**: Review `llama.cpp/common/chat.h` for `common_chat_params` struct changes
3. **Check Server Options**: Review `llama.cpp/tools/server/server.cpp` for command-line argument changes
4. **Examples of options to check**:
- `ctx_shift` - Context shifting support
- `parallel_tool_calls` - Parallel tool calling
- `reasoning_format` - Reasoning format options
- Any new flags or parameters
### Implementation Guidelines
1. **Feature Parity**: Always aim for feature parity with llama.cpp's implementation
2. **Test Coverage**: Add tests for new features matching llama.cpp's behavior
3. **Documentation**: Update relevant documentation when adding new formats or options
4. **Backward Compatibility**: Ensure changes don't break existing functionality
### Files to Monitor
- `llama.cpp/common/chat-parser-xml-toolcall.h` - Format definitions
- `llama.cpp/common/chat-parser-xml-toolcall.cpp` - Parsing logic
- `llama.cpp/common/chat-parser.cpp` - Format presets and model-specific handlers
- `llama.cpp/common/chat.h` - Format enums and parameter structures
- `llama.cpp/tools/server/server-context.cpp` - Server configuration options

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# Testing MCP Apps (Interactive Tool UIs)
MCP Apps is an extension to MCP where tools declare interactive HTML UIs via `_meta.ui.resourceUri`. When the LLM calls such a tool, the UI renders the app in a sandboxed iframe inline in the chat. The app communicates bidirectionally with the host via `postMessage` (JSON-RPC) and can call server tools, send messages, and update model context.
Spec: https://modelcontextprotocol.io/extensions/apps/overview
## Quick Start: Run a Test MCP App Server
The `@modelcontextprotocol/server-basic-react` npm package is a ready-to-use test server that exposes a `get-time` tool with an interactive React clock UI. It requires Node >= 20, so run it in Docker:
```bash
docker run -d --name mcp-app-test -p 3001:3001 node:22-slim \
sh -c 'npx -y @modelcontextprotocol/server-basic-react'
```
Wait ~10 seconds for it to start, then verify:
```bash
# Check it's running
docker logs mcp-app-test
# Expected: "MCP server listening on http://localhost:3001/mcp"
# Verify MCP protocol works
curl -s -X POST http://localhost:3001/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}'
# List tools — should show get-time with _meta.ui.resourceUri
curl -s -X POST http://localhost:3001/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":2,"method":"tools/list","params":{}}'
```
The `tools/list` response should contain:
```json
{
"name": "get-time",
"_meta": {
"ui": { "resourceUri": "ui://get-time/mcp-app.html" }
}
}
```
## Testing in LocalAI's UI
1. Make sure LocalAI is running (e.g. `http://localhost:8080`)
2. Build the React UI: `cd core/http/react-ui && npm install && npm run build`
3. Open the Chat page in your browser
4. Click **"Client MCP"** in the chat header
5. Add a new client MCP server:
- **URL**: `http://localhost:3001/mcp`
- **Use CORS proxy**: enabled (default) — required because the browser can't hit `localhost:3001` directly due to CORS; LocalAI's proxy at `/api/cors-proxy` handles it
6. The server should connect and discover the `get-time` tool
7. Select a model and send: **"What time is it?"**
8. The LLM should call the `get-time` tool
9. The tool result should render the interactive React clock app in an iframe as a standalone chat message (not inside the collapsed activity group)
## What to Verify
- [ ] Tool appears in the connected tools list (not filtered — `get-time` is callable by the LLM)
- [ ] The iframe renders as a standalone chat message with a puzzle-piece icon
- [ ] The app loads and is interactive (clock UI, buttons work)
- [ ] No "Reconnect to MCP server" overlay (connection is live)
- [ ] Console logs show bidirectional communication:
- `tools/call` messages from app to host (app calling server tools)
- `ui/message` notifications (app sending messages)
- [ ] After the app renders, the LLM continues and produces a text response with the time
- [ ] Non-UI tools continue to work normally (text-only results)
- [ ] Page reload shows the HTML statically with a reconnect overlay until you reconnect
## Console Log Patterns
Healthy bidirectional communication looks like:
```
Parsed message { jsonrpc: "2.0", id: N, result: {...} } // Bridge init
get-time result: { content: [...] } // Tool result received
Calling get-time tool... // App calls tool
Sending message { method: "tools/call", ... } // App -> host -> server
Parsed message { jsonrpc: "2.0", id: N, result: {...} } // Server response
Sending message text to Host: ... // App sends message
Sending message { method: "ui/message", ... } // Message notification
Message accepted // Host acknowledged
```
Benign warnings to ignore:
- `Source map error: ... about:srcdoc` — browser devtools can't find source maps for srcdoc iframes
- `Ignoring message from unknown source` — duplicate postMessage from iframe navigation
- `notifications/cancelled` — app cleaning up previous requests
## Architecture Notes
- **No server-side changes needed** — the MCP App protocol runs entirely in the browser
- `PostMessageTransport` wraps `window.postMessage` between host and `srcdoc` iframe
- `AppBridge` (from `@modelcontextprotocol/ext-apps`) auto-forwards `tools/call`, `resources/read`, `resources/list` from the app to the MCP server via the host's `Client`
- The iframe uses `sandbox="allow-scripts allow-forms"` (no `allow-same-origin`) — opaque origin, no access to host cookies/DOM/localStorage
- App-only tools (`_meta.ui.visibility: "app-only"`) are filtered from the LLM's tool list but remain callable by the app iframe
## Key Files
- `core/http/react-ui/src/components/MCPAppFrame.jsx` — iframe + AppBridge component
- `core/http/react-ui/src/hooks/useMCPClient.js` — MCP client hook with app UI helpers (`hasAppUI`, `getAppResource`, `getClientForTool`, `getToolDefinition`)
- `core/http/react-ui/src/hooks/useChat.js` — agentic loop, attaches `appUI` to tool_result messages
- `core/http/react-ui/src/pages/Chat.jsx` — renders MCPAppFrame as standalone chat messages
## Other Test Servers
The `@modelcontextprotocol/ext-apps` repo has many example servers:
- `@modelcontextprotocol/server-basic-react` — simple clock (React)
- More examples at https://github.com/modelcontextprotocol/ext-apps/tree/main/examples
All examples support both stdio and HTTP transport. Run without `--stdio` for HTTP mode on port 3001.
## Cleanup
```bash
docker rm -f mcp-app-test
```

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@@ -1,115 +0,0 @@
# Working on the vLLM Backend
The vLLM backend lives at `backend/python/vllm/backend.py` (async gRPC) and the multimodal variant at `backend/python/vllm-omni/backend.py` (sync gRPC). Both wrap vLLM's `AsyncLLMEngine` / `Omni` and translate the LocalAI gRPC `PredictOptions` into vLLM `SamplingParams` + outputs into `Reply.chat_deltas`.
This file captures the non-obvious bits — most of the bring-up was a single PR (`feat/vllm-parity`) and the things below are easy to get wrong.
## Tool calling and reasoning use vLLM's *native* parsers
Do not write regex-based tool-call extractors for vLLM. vLLM ships:
- `vllm.tool_parsers.ToolParserManager` — 50+ registered parsers (`hermes`, `llama3_json`, `llama4_pythonic`, `mistral`, `qwen3_xml`, `deepseek_v3`, `granite4`, `openai`, `kimi_k2`, `glm45`, …)
- `vllm.reasoning.ReasoningParserManager` — 25+ registered parsers (`deepseek_r1`, `qwen3`, `mistral`, `gemma4`, …)
Both can be used standalone: instantiate with a tokenizer, call `extract_tool_calls(text, request=None)` / `extract_reasoning(text, request=None)`. The backend stores the parser *classes* on `self.tool_parser_cls` / `self.reasoning_parser_cls` at LoadModel time and instantiates them per request.
**Selection:** vLLM does *not* auto-detect parsers from model name — neither does the LocalAI backend. The user (or `core/config/hooks_vllm.go`) must pick one and pass it via `Options[]`:
```yaml
options:
- tool_parser:hermes
- reasoning_parser:qwen3
```
Auto-defaults for known model families live in `core/config/parser_defaults.json` and are applied:
- at gallery import time by `core/gallery/importers/vllm.go`
- at model load time by the `vllm` / `vllm-omni` backend hook in `core/config/hooks_vllm.go`
User-supplied `tool_parser:`/`reasoning_parser:` in the config wins over defaults — the hook checks for existing entries before appending.
**When to update `parser_defaults.json`:** any time vLLM ships a new tool or reasoning parser, or you onboard a new model family that LocalAI users will pull from HuggingFace. The file is keyed by *family pattern* matched against `normalizeModelID(cfg.Model)` (lowercase, org-prefix stripped, `_``-`). Patterns are checked **longest-first** — keep `qwen3.5` before `qwen3`, `llama-3.3` before `llama-3`, etc., or the wrong family wins. Add a covering test in `core/config/hooks_test.go`.
**Sister file — `core/config/inference_defaults.json`:** same pattern but for sampling parameters (temperature, top_p, top_k, min_p, repeat_penalty, presence_penalty). Loaded by `core/config/inference_defaults.go` and applied by `ApplyInferenceDefaults()`. The schema is `map[string]float64` only — *strings don't fit*, which is why parser defaults needed their own JSON file. The inference file is **auto-generated from unsloth** via `go generate ./core/config/` (see `core/config/gen_inference_defaults/`) — don't hand-edit it; instead update the upstream source or regenerate. Both files share `normalizeModelID()` and the longest-first pattern ordering.
**Constructor compatibility gotcha:** the abstract `ToolParser.__init__` accepts `tools=`, but several concrete parsers (Hermes2ProToolParser, etc.) override `__init__` and *only* accept `tokenizer`. Always:
```python
try:
tp = self.tool_parser_cls(self.tokenizer, tools=tools)
except TypeError:
tp = self.tool_parser_cls(self.tokenizer)
```
## ChatDelta is the streaming contract
The Go side (`core/backend/llm.go`, `pkg/functions/chat_deltas.go`) consumes `Reply.chat_deltas` to assemble the OpenAI response. For tool calls to surface in `chat/completions`, the Python backend **must** populate `Reply.chat_deltas[].tool_calls` with `ToolCallDelta{index, id, name, arguments}`. Returning the raw `<tool_call>...</tool_call>` text in `Reply.message` is *not* enough — the Go regex fallback exists for llama.cpp, not for vllm.
Same story for `reasoning_content` — emit it on `ChatDelta.reasoning_content`, not as part of `content`.
## Message conversion to chat templates
`tokenizer.apply_chat_template()` expects a list of dicts, not proto Messages. The shared helper in `backend/python/common/vllm_utils.py` (`messages_to_dicts`) handles the mapping including:
- `tool_call_id` and `name` for `role="tool"` messages
- `tool_calls` JSON-string field → parsed Python list for `role="assistant"`
- `reasoning_content` for thinking models
Pass `tools=json.loads(request.Tools)` and (when `request.Metadata.get("enable_thinking") == "true"`) `enable_thinking=True` to `apply_chat_template`. Wrap in `try/except TypeError` because not every tokenizer template accepts those kwargs.
## CPU support and the SIMD/library minefield
vLLM publishes prebuilt CPU wheels at `https://github.com/vllm-project/vllm/releases/...`. The pin lives in `backend/python/vllm/requirements-cpu-after.txt`.
**Version compatibility — important:** newer vllm CPU wheels (≥ 0.15) declare `torch==2.10.0+cpu` as a hard dep, but `torch==2.10.0` only exists on the PyTorch test channel and pulls in an incompatible `torchvision`. Stay on **`vllm 0.14.1+cpu` + `torch 2.9.1+cpu`** until both upstream catch up. Bumping requires verifying torchvision/torchaudio match.
`requirements-cpu.txt` uses `--extra-index-url https://download.pytorch.org/whl/cpu`. `install.sh` adds `--index-strategy=unsafe-best-match` for the `cpu` profile so uv resolves transformers/vllm from PyPI while pulling torch from the PyTorch index.
**SIMD baseline:** the prebuilt CPU wheel is compiled with AVX-512 VNNI/BF16. On a CPU without those instructions, importing `vllm.model_executor.models.registry` SIGILLs at `_run_in_subprocess` time during model inspection. There is no runtime flag to disable it. Workarounds:
1. **Run on a host with the right SIMD baseline** (default — fast)
2. **Build from source** with `FROM_SOURCE=true` env var. Plumbing exists end-to-end:
- `install.sh` hides `requirements-cpu-after.txt`, runs `installRequirements` for the base deps, then clones vllm and `VLLM_TARGET_DEVICE=cpu uv pip install --no-deps .`
- `backend/Dockerfile.python` declares `ARG FROM_SOURCE` + `ENV FROM_SOURCE`
- `Makefile` `docker-build-backend` macro forwards `--build-arg FROM_SOURCE=$(FROM_SOURCE)` when set
- Source build takes 3050 minutes — too slow for per-PR CI but fine for local.
**Runtime shared libraries:** vLLM's `vllm._C` extension `dlopen`s `libnuma.so.1` at import time. If missing, the C extension silently fails and `torch.ops._C_utils.init_cpu_threads_env` is never registered → `EngineCore` crashes on `init_device` with:
```
AttributeError: '_OpNamespace' '_C_utils' object has no attribute 'init_cpu_threads_env'
```
`backend/python/vllm/package.sh` bundles `libnuma.so.1` and `libgomp.so.1` into `${BACKEND}/lib/`, which `libbackend.sh` adds to `LD_LIBRARY_PATH` at run time. The builder stage in `backend/Dockerfile.python` installs `libnuma1`/`libgomp1` so package.sh has something to copy. Do *not* assume the production host has these — backend images are `FROM scratch`.
## Backend hook system (`core/config/backend_hooks.go`)
Per-backend defaults that used to be hardcoded in `ModelConfig.Prepare()` now live in `core/config/hooks_*.go` files and self-register via `init()`:
- `hooks_llamacpp.go` → GGUF metadata parsing, context size, GPU layers, jinja template
- `hooks_vllm.go` → tool/reasoning parser auto-selection from `parser_defaults.json`
Hook keys:
- `"llama-cpp"`, `"vllm"`, `"vllm-omni"`, … — backend-specific
- `""` — runs only when `cfg.Backend` is empty (auto-detect case)
- `"*"` — global catch-all, runs for every backend before specific hooks
Multiple hooks per key are supported and run in registration order. Adding a new backend default:
```go
// core/config/hooks_<backend>.go
func init() {
RegisterBackendHook("<backend>", myDefaults)
}
func myDefaults(cfg *ModelConfig, modelPath string) {
// only fill in fields the user didn't set
}
```
## The `Messages.ToProto()` fields you need to set
`core/schema/message.go:ToProto()` must serialize:
- `ToolCallID``proto.Message.ToolCallId` (for `role="tool"` messages — links result back to the call)
- `Reasoning``proto.Message.ReasoningContent`
- `ToolCalls``proto.Message.ToolCalls` (JSON-encoded string)
These were originally not serialized and tool-calling conversations broke silently — the C++ llama.cpp backend reads them but always got empty strings. Any new field added to `schema.Message` *and* `proto.Message` needs a matching line in `ToProto()`.

View File

@@ -1,8 +0,0 @@
# .air.toml
[build]
cmd = "make build"
bin = "./local-ai"
args_bin = [ "--debug" ]
include_ext = ["go", "html", "yaml", "toml", "json", "txt", "md"]
exclude_dir = ["pkg/grpc/proto"]
delay = 1000

View File

@@ -2,6 +2,9 @@
cd /workspace
# Grab the pre-stashed backend assets to avoid build issues
cp -r /build/backend-assets /workspace/backend-assets
# Ensures generated source files are present upon load
make prepare

View File

@@ -9,7 +9,6 @@
# Param 2: email
#
config_user() {
echo "Configuring git for $1 <$2>"
local gcn=$(git config --global user.name)
if [ -z "${gcn}" ]; then
echo "Setting up git user / remote"
@@ -25,7 +24,6 @@ config_user() {
# Param 2: remote url
#
config_remote() {
echo "Adding git remote and fetching $2 as $1"
local gr=$(git remote -v | grep $1)
if [ -z "${gr}" ]; then
git remote add $1 $2
@@ -34,22 +32,18 @@ config_remote() {
}
# Setup special .ssh files
# Prints out lines of text to make things pretty
#
# Param 1: bash array, filenames relative to the customization directory that should be copied to ~/.ssh
setup_ssh() {
echo "starting ~/.ssh directory setup..."
mkdir -p "${HOME}.ssh"
chmod 0700 "${HOME}/.ssh"
echo "-----"
local files=("$@")
for file in "${files[@]}" ; do
for file in "${files[@]}"; then
local cfile="/devcontainer-customization/${file}"
local hfile="${HOME}/.ssh/${file}"
local hfile="~/.ssh/${file}"
if [ ! -f "${hfile}" ]; then
echo "copying \"${file}\""
echo "copying ${file}"
cp "${cfile}" "${hfile}"
chmod 600 "${hfile}"
fi
done
echo "~/.ssh directory setup complete!"
ls ~/.ssh
}

View File

@@ -4,14 +4,17 @@ services:
context: ..
dockerfile: Dockerfile
target: devcontainer
args:
- FFMPEG=true
- IMAGE_TYPE=extras
- GO_TAGS=stablediffusion p2p tts
env_file:
- ../.env
ports:
- 8080:8080
volumes:
- localai_workspace:/workspace
- models:/host-models
- backends:/host-backends
- ../models:/host-models
- ./customization:/devcontainer-customization
command: /bin/sh -c "while sleep 1000; do :; done"
cap_add:
@@ -40,9 +43,6 @@ services:
- GF_SECURITY_ADMIN_PASSWORD=grafana
volumes:
- ./grafana:/etc/grafana/provisioning/datasources
volumes:
prom_data:
localai_workspace:
models:
backends:
localai_workspace:

View File

@@ -3,13 +3,7 @@
.vscode
.devcontainer
models
backends
examples/chatbot-ui/models
backend/go/image/stablediffusion-ggml/build/
backend/go/*/build
backend/go/*/.cache
backend/go/*/sources
backend/go/*/package
examples/rwkv/models
examples/**/models
Dockerfile*
@@ -20,4 +14,4 @@ __pycache__
# backend virtual environments
**/venv
backend/python/**/source
backend/python/**/source

31
.env
View File

@@ -26,14 +26,24 @@
## Disables COMPEL (Diffusers)
# COMPEL=0
## Disables SD_EMBED (Diffusers)
# SD_EMBED=0
## Enable/Disable single backend (useful if only one GPU is available)
# LOCALAI_SINGLE_ACTIVE_BACKEND=true
# Forces shutdown of the backends if busy (only if LOCALAI_SINGLE_ACTIVE_BACKEND is set)
# LOCALAI_FORCE_BACKEND_SHUTDOWN=true
## Specify a build type. Available: cublas, openblas, clblas.
## cuBLAS: This is a GPU-accelerated version of the complete standard BLAS (Basic Linear Algebra Subprograms) library. It's provided by Nvidia and is part of their CUDA toolkit.
## OpenBLAS: This is an open-source implementation of the BLAS library that aims to provide highly optimized code for various platforms. It includes support for multi-threading and can be compiled to use hardware-specific features for additional performance. OpenBLAS can run on many kinds of hardware, including CPUs from Intel, AMD, and ARM.
## clBLAS: This is an open-source implementation of the BLAS library that uses OpenCL, a framework for writing programs that execute across heterogeneous platforms consisting of CPUs, GPUs, and other processors. clBLAS is designed to take advantage of the parallel computing power of GPUs but can also run on any hardware that supports OpenCL. This includes hardware from different vendors like Nvidia, AMD, and Intel.
# BUILD_TYPE=openblas
## Uncomment and set to true to enable rebuilding from source
# REBUILD=true
## Enable go tags, available: stablediffusion, tts
## stablediffusion: image generation with stablediffusion
## tts: enables text-to-speech with go-piper
## (requires REBUILD=true)
#
# GO_TAGS=stablediffusion
## Path where to store generated images
# LOCALAI_IMAGE_PATH=/tmp/generated/images
@@ -63,7 +73,7 @@
### Define a list of GRPC Servers for llama-cpp workers to distribute the load
# https://github.com/ggerganov/llama.cpp/pull/6829
# https://github.com/ggerganov/llama.cpp/blob/master/tools/rpc/README.md
# https://github.com/ggerganov/llama.cpp/blob/master/examples/rpc/README.md
# LLAMACPP_GRPC_SERVERS=""
### Enable to run parallel requests
@@ -72,15 +82,6 @@
# Enable to allow p2p mode
# LOCALAI_P2P=true
# Enable to use federated mode
# LOCALAI_FEDERATED=true
# Enable to start federation server
# FEDERATED_SERVER=true
# Define to use federation token
# TOKEN=""
### Watchdog settings
###
# Enables watchdog to kill backends that are inactive for too much time

1
.gitattributes vendored
View File

@@ -1,2 +1 @@
*.sh text eol=lf
backend/cpp/llama/*.hpp linguist-vendored

View File

@@ -3,20 +3,15 @@ set -xe
REPO=$1
BRANCH=$2
VAR=$3
FILE=$4
if [ -z "$FILE" ]; then
FILE="Makefile"
fi
LAST_COMMIT=$(curl -s -H "Accept: application/vnd.github.VERSION.sha" "https://api.github.com/repos/$REPO/commits/$BRANCH")
# Read $VAR from Makefile (only first match)
set +e
CURRENT_COMMIT="$(grep -m1 "^$VAR?=" $FILE | cut -d'=' -f2)"
CURRENT_COMMIT="$(grep -m1 "^$VAR?=" Makefile | cut -d'=' -f2)"
set -e
sed -i $FILE -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
sed -i Makefile -e "s/$VAR?=.*/$VAR?=$LAST_COMMIT/"
if [ -z "$CURRENT_COMMIT" ]; then
echo "Could not find $VAR in Makefile."

View File

@@ -29,14 +29,9 @@ def calculate_sha256(file_path):
def manual_safety_check_hf(repo_id):
scanResponse = requests.get('https://huggingface.co/api/models/' + repo_id + "/scan")
scan = scanResponse.json()
# Check if 'hasUnsafeFile' exists in the response
if 'hasUnsafeFile' in scan:
if scan['hasUnsafeFile']:
return scan
else:
return None
else:
return None
if scan['hasUnsafeFile']:
return scan
return None
download_type, repo_id_or_url = parse_uri(uri)

View File

@@ -6,7 +6,6 @@ import (
"io/ioutil"
"os"
"github.com/microcosm-cc/bluemonday"
"gopkg.in/yaml.v3"
)
@@ -280,12 +279,6 @@ func main() {
return
}
// Ensure that all arbitrary text content is sanitized before display
for i, m := range models {
models[i].Name = bluemonday.StrictPolicy().Sanitize(m.Name)
models[i].Description = bluemonday.StrictPolicy().Sanitize(m.Description)
}
// render the template
data := struct {
Models []*GalleryModel

View File

@@ -9,8 +9,6 @@ updates:
directory: "/"
schedule:
interval: "weekly"
ignore:
- dependency-name: "github.com/mudler/LocalAI/pkg/grpc/proto"
- package-ecosystem: "github-actions"
# Workflow files stored in the default location of `.github/workflows`. (You don't need to specify `/.github/workflows` for `directory`. You can use `directory: "/"`.)
directory: "/"
@@ -29,6 +27,10 @@ updates:
schedule:
# Check for updates to GitHub Actions every weekday
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/autogptq"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/bark"
schedule:
@@ -61,6 +63,10 @@ updates:
directory: "/backend/python/openvoice"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/parler-tts"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/rerankers"
schedule:
@@ -73,6 +79,14 @@ updates:
directory: "/backend/python/transformers"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/transformers-musicgen"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vall-e-x"
schedule:
interval: "weekly"
- package-ecosystem: "pip"
directory: "/backend/python/vllm"
schedule:

View File

@@ -1,213 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"strings"
"github.com/mudler/LocalAI/core/gallery/importers"
"sigs.k8s.io/yaml"
)
func formatTextContent(text string) string {
return formatTextContentWithIndent(text, 4, 6)
}
// formatTextContentWithIndent formats text content with specified base and list item indentation
func formatTextContentWithIndent(text string, baseIndent int, listItemIndent int) string {
var formattedLines []string
lines := strings.Split(text, "\n")
for _, line := range lines {
trimmed := strings.TrimRight(line, " \t\r")
if trimmed == "" {
// Keep empty lines as empty (no indentation)
formattedLines = append(formattedLines, "")
} else {
// Preserve relative indentation from yaml.Marshal output
// Count existing leading spaces to preserve relative structure
leadingSpaces := len(trimmed) - len(strings.TrimLeft(trimmed, " \t"))
trimmedStripped := strings.TrimLeft(trimmed, " \t")
var totalIndent int
if strings.HasPrefix(trimmedStripped, "-") {
// List items: use listItemIndent (ignore existing leading spaces)
totalIndent = listItemIndent
} else {
// Regular lines: use baseIndent + preserve relative indentation
// This handles both top-level keys (leadingSpaces=0) and nested properties (leadingSpaces>0)
totalIndent = baseIndent + leadingSpaces
}
indentStr := strings.Repeat(" ", totalIndent)
formattedLines = append(formattedLines, indentStr+trimmedStripped)
}
}
formattedText := strings.Join(formattedLines, "\n")
// Remove any trailing spaces from the formatted description
formattedText = strings.TrimRight(formattedText, " \t")
return formattedText
}
// generateYAMLEntry generates a YAML entry for a model using the specified anchor
func generateYAMLEntry(model ProcessedModel, quantization string) string {
modelConfig, err := importers.DiscoverModelConfig("https://huggingface.co/"+model.ModelID, json.RawMessage(`{ "quantization": "`+quantization+`"}`))
if err != nil {
panic(err)
}
// Extract model name from ModelID
parts := strings.Split(model.ModelID, "/")
modelName := model.ModelID
if len(parts) > 0 {
modelName = strings.ToLower(parts[len(parts)-1])
}
// Remove common suffixes
modelName = strings.ReplaceAll(modelName, "-gguf", "")
modelName = strings.ReplaceAll(modelName, "-q4_k_m", "")
modelName = strings.ReplaceAll(modelName, "-q4_k_s", "")
modelName = strings.ReplaceAll(modelName, "-q3_k_m", "")
modelName = strings.ReplaceAll(modelName, "-q2_k", "")
description := model.ReadmeContent
if description == "" {
description = fmt.Sprintf("AI model: %s", modelName)
}
// Clean up description to prevent YAML linting issues
description = cleanTextContent(description)
formattedDescription := formatTextContent(description)
// Strip name and description from config file since they are
// already present at the gallery entry level and should not
// appear under overrides.
configFileContent := modelConfig.ConfigFile
var cfgMap map[string]any
if err := yaml.Unmarshal([]byte(configFileContent), &cfgMap); err == nil {
delete(cfgMap, "name")
delete(cfgMap, "description")
if cleaned, err := yaml.Marshal(cfgMap); err == nil {
configFileContent = string(cleaned)
}
}
configFile := formatTextContent(configFileContent)
filesYAML, _ := yaml.Marshal(modelConfig.Files)
// Files section: list items need 4 spaces (not 6), since files: is at 2 spaces
files := formatTextContentWithIndent(string(filesYAML), 4, 4)
// Build metadata sections
var metadataSections []string
// Add license if present
if model.License != "" {
metadataSections = append(metadataSections, fmt.Sprintf(` license: "%s"`, model.License))
}
// Add tags if present
if len(model.Tags) > 0 {
tagsYAML, _ := yaml.Marshal(model.Tags)
tagsFormatted := formatTextContentWithIndent(string(tagsYAML), 4, 4)
tagsFormatted = strings.TrimRight(tagsFormatted, "\n")
metadataSections = append(metadataSections, fmt.Sprintf(" tags:\n%s", tagsFormatted))
}
// Add icon if present
if model.Icon != "" {
metadataSections = append(metadataSections, fmt.Sprintf(` icon: %s`, model.Icon))
}
// Build the metadata block
metadataBlock := ""
if len(metadataSections) > 0 {
metadataBlock = strings.Join(metadataSections, "\n") + "\n"
}
yamlTemplate := ""
yamlTemplate = `- name: "%s"
url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
urls:
- https://huggingface.co/%s
description: |
%s%s
overrides:
%s
files:
%s`
// Trim trailing newlines from formatted sections to prevent extra blank lines
formattedDescription = strings.TrimRight(formattedDescription, "\n")
configFile = strings.TrimRight(configFile, "\n")
files = strings.TrimRight(files, "\n")
// Add newline before metadata block if present
if metadataBlock != "" {
metadataBlock = "\n" + strings.TrimRight(metadataBlock, "\n")
}
return fmt.Sprintf(yamlTemplate,
modelName,
model.ModelID,
formattedDescription,
metadataBlock,
configFile,
files,
)
}
// generateYAMLForModels generates YAML entries for selected models and appends to index.yaml
func generateYAMLForModels(ctx context.Context, models []ProcessedModel, quantization string) error {
// Generate YAML entries for each model
var yamlEntries []string
for _, model := range models {
fmt.Printf("Generating YAML entry for model: %s\n", model.ModelID)
// Generate YAML entry
yamlEntry := generateYAMLEntry(model, quantization)
yamlEntries = append(yamlEntries, yamlEntry)
}
// Prepend to index.yaml (write at the top)
if len(yamlEntries) > 0 {
indexPath := getGalleryIndexPath()
fmt.Printf("Prepending YAML entries to %s...\n", indexPath)
// Read current content
content, err := os.ReadFile(indexPath)
if err != nil {
return fmt.Errorf("failed to read %s: %w", indexPath, err)
}
existingContent := string(content)
yamlBlock := strings.Join(yamlEntries, "\n")
// Check if file starts with "---"
var newContent string
if strings.HasPrefix(existingContent, "---\n") {
// File starts with "---", prepend new entries after it
restOfContent := strings.TrimPrefix(existingContent, "---\n")
// Ensure proper spacing: "---\n" + new entries + "\n" + rest of content
newContent = "---\n" + yamlBlock + "\n" + restOfContent
} else if strings.HasPrefix(existingContent, "---") {
// File starts with "---" but no newline after
restOfContent := strings.TrimPrefix(existingContent, "---")
newContent = "---\n" + yamlBlock + "\n" + strings.TrimPrefix(restOfContent, "\n")
} else {
// No "---" at start, prepend new entries at the very beginning
// Trim leading whitespace from existing content
existingContent = strings.TrimLeft(existingContent, " \t\n\r")
newContent = yamlBlock + "\n" + existingContent
}
// Write back to file
err = os.WriteFile(indexPath, []byte(newContent), 0644)
if err != nil {
return fmt.Errorf("failed to write %s: %w", indexPath, err)
}
fmt.Printf("Successfully prepended %d models to %s\n", len(yamlEntries), indexPath)
}
return nil
}

View File

@@ -1,301 +0,0 @@
package main
import (
"encoding/json"
"fmt"
"io"
"net/http"
"os"
"regexp"
"strings"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
"sigs.k8s.io/yaml"
)
var galleryIndexPath = os.Getenv("GALLERY_INDEX_PATH")
// getGalleryIndexPath returns the gallery index file path, with a default fallback
func getGalleryIndexPath() string {
if galleryIndexPath != "" {
return galleryIndexPath
}
return "gallery/index.yaml"
}
type galleryModel struct {
Name string `yaml:"name"`
Urls []string `yaml:"urls"`
}
// loadGalleryURLSet parses gallery/index.yaml once and returns the set of
// HuggingFace model URLs already present in the gallery.
func loadGalleryURLSet() (map[string]struct{}, error) {
indexPath := getGalleryIndexPath()
content, err := os.ReadFile(indexPath)
if err != nil {
return nil, fmt.Errorf("failed to read %s: %w", indexPath, err)
}
var galleryModels []galleryModel
if err := yaml.Unmarshal(content, &galleryModels); err != nil {
return nil, fmt.Errorf("failed to unmarshal %s: %w", indexPath, err)
}
set := make(map[string]struct{}, len(galleryModels))
for _, gm := range galleryModels {
for _, u := range gm.Urls {
set[u] = struct{}{}
}
}
// Also skip URLs already proposed in open (unmerged) gallery-agent PRs.
// The workflow injects these via EXTRA_SKIP_URLS so we don't keep
// re-proposing the same model every run while a PR is waiting to merge.
for _, line := range strings.FieldsFunc(os.Getenv("EXTRA_SKIP_URLS"), func(r rune) bool {
return r == '\n' || r == ',' || r == ' '
}) {
u := strings.TrimSpace(line)
if u != "" {
set[u] = struct{}{}
}
}
return set, nil
}
// modelAlreadyInGallery checks whether a HuggingFace model repo is already
// referenced in the gallery URL set.
func modelAlreadyInGallery(set map[string]struct{}, modelID string) bool {
_, ok := set["https://huggingface.co/"+modelID]
return ok
}
// baseModelFromTags returns the first `base_model:<repo>` value found in the
// tag list, or "" if none is present. HuggingFace surfaces the base model
// declared in the model card's YAML frontmatter as such a tag.
func baseModelFromTags(tags []string) string {
for _, t := range tags {
if strings.HasPrefix(t, "base_model:") {
return strings.TrimPrefix(t, "base_model:")
}
}
return ""
}
// licenseFromTags returns the `license:<id>` value from the tag list, or "".
func licenseFromTags(tags []string) string {
for _, t := range tags {
if strings.HasPrefix(t, "license:") {
return strings.TrimPrefix(t, "license:")
}
}
return ""
}
// curatedTags produces the gallery tag list from HuggingFace's raw tag set.
// Always includes llm + gguf, then adds whitelisted family / capability
// markers when they appear in the HF tag list.
func curatedTags(hfTags []string) []string {
whitelist := []string{
"gpu", "cpu",
"llama", "mistral", "mixtral", "qwen", "qwen2", "qwen3",
"gemma", "gemma2", "gemma3", "phi", "phi3", "phi4",
"deepseek", "yi", "falcon", "command-r",
"vision", "multimodal", "code", "chat",
"instruction-tuned", "reasoning", "thinking",
}
seen := map[string]struct{}{}
out := []string{"llm", "gguf"}
seen["llm"] = struct{}{}
seen["gguf"] = struct{}{}
hfSet := map[string]struct{}{}
for _, t := range hfTags {
hfSet[strings.ToLower(t)] = struct{}{}
}
for _, w := range whitelist {
if _, ok := hfSet[w]; ok {
if _, dup := seen[w]; !dup {
out = append(out, w)
seen[w] = struct{}{}
}
}
}
return out
}
// resolveReadme fetches a description-quality README for a (possibly
// quantized) repo: if a `base_model:` tag is present, fetch the base repo's
// README; otherwise fall back to the repo's own README.
func resolveReadme(client *hfapi.Client, modelID string, hfTags []string) (string, error) {
if base := baseModelFromTags(hfTags); base != "" && base != modelID {
if content, err := client.GetReadmeContent(base, "README.md"); err == nil && strings.TrimSpace(content) != "" {
return cleanTextContent(content), nil
}
}
content, err := client.GetReadmeContent(modelID, "README.md")
if err != nil {
return "", err
}
return cleanTextContent(content), nil
}
// extractDescription turns a raw HuggingFace README into a concise plain-text
// description suitable for embedding in gallery/index.yaml: strips YAML
// frontmatter, HTML tags/comments, markdown images, link URLs (keeping the
// link text), markdown tables, and then truncates at a paragraph boundary
// around ~1200 characters. Raw README should still be used for icon
// extraction — call this only for the `description:` field.
func extractDescription(readme string) string {
s := readme
// Strip leading YAML frontmatter: `---\n...\n---\n` at start of file.
if strings.HasPrefix(strings.TrimLeft(s, " \t\n"), "---") {
trimmed := strings.TrimLeft(s, " \t\n")
rest := strings.TrimPrefix(trimmed, "---")
if idx := strings.Index(rest, "\n---"); idx >= 0 {
after := rest[idx+len("\n---"):]
after = strings.TrimPrefix(after, "\n")
s = after
}
}
// Strip HTML comments and tags.
s = regexp.MustCompile(`(?s)<!--.*?-->`).ReplaceAllString(s, "")
s = regexp.MustCompile(`(?is)<[^>]+>`).ReplaceAllString(s, "")
// Strip markdown images entirely.
s = regexp.MustCompile(`!\[[^\]]*\]\([^)]*\)`).ReplaceAllString(s, "")
// Replace markdown links `[text](url)` with just `text`.
s = regexp.MustCompile(`\[([^\]]+)\]\([^)]+\)`).ReplaceAllString(s, "$1")
// Drop table lines and horizontal rules, and flatten all leading
// whitespace: generateYAMLEntry embeds this under a `description: |`
// literal block whose indentation is set by the first non-empty line.
// If any line has extra leading whitespace (e.g. from an indented
// `<p align="center">` block in the original README), YAML will pick
// that up as the block's indent and every later line at a smaller
// indent blows the block scalar. Stripping leading whitespace here
// guarantees uniform 4-space indentation after formatTextContent runs.
var kept []string
for _, line := range strings.Split(s, "\n") {
t := strings.TrimLeft(line, " \t")
ts := strings.TrimSpace(t)
if strings.HasPrefix(ts, "|") {
continue
}
if strings.HasPrefix(ts, ":--") || strings.HasPrefix(ts, "---") || strings.HasPrefix(ts, "===") {
continue
}
kept = append(kept, t)
}
s = strings.Join(kept, "\n")
// Normalise whitespace and drop any leading blank lines so the literal
// block in YAML doesn't start with a blank first line (which would
// break the indentation detector the same way).
s = cleanTextContent(s)
s = strings.TrimLeft(s, " \t\n")
// Truncate at a paragraph boundary around maxLen chars.
const maxLen = 1200
if len(s) > maxLen {
cut := strings.LastIndex(s[:maxLen], "\n\n")
if cut < maxLen/3 {
cut = maxLen
}
s = strings.TrimRight(s[:cut], " \t\n") + "\n\n..."
}
return s
}
// cleanTextContent removes trailing spaces/tabs and collapses multiple empty
// lines so README content embeds cleanly into YAML without lint noise.
func cleanTextContent(text string) string {
lines := strings.Split(text, "\n")
var cleaned []string
var prevEmpty bool
for _, line := range lines {
trimmed := strings.TrimRight(line, " \t\r")
if trimmed == "" {
if !prevEmpty {
cleaned = append(cleaned, "")
}
prevEmpty = true
} else {
cleaned = append(cleaned, trimmed)
prevEmpty = false
}
}
return strings.TrimRight(strings.Join(cleaned, "\n"), "\n")
}
// extractIconFromReadme scans README content for an image URL usable as a
// gallery entry icon.
func extractIconFromReadme(readmeContent string) string {
if readmeContent == "" {
return ""
}
markdownImageRegex := regexp.MustCompile(`(?i)!\[[^\]]*\]\(([^)]+\.(png|jpg|jpeg|svg|webp|gif))\)`)
htmlImageRegex := regexp.MustCompile(`(?i)<img[^>]+src=["']([^"']+\.(png|jpg|jpeg|svg|webp|gif))["']`)
plainImageRegex := regexp.MustCompile(`(?i)https?://[^\s<>"']+\.(png|jpg|jpeg|svg|webp|gif)`)
if m := markdownImageRegex.FindStringSubmatch(readmeContent); len(m) > 1 && strings.HasPrefix(strings.ToLower(m[1]), "http") {
return strings.TrimSpace(m[1])
}
if m := htmlImageRegex.FindStringSubmatch(readmeContent); len(m) > 1 && strings.HasPrefix(strings.ToLower(m[1]), "http") {
return strings.TrimSpace(m[1])
}
if m := plainImageRegex.FindStringSubmatch(readmeContent); len(m) > 0 && strings.HasPrefix(strings.ToLower(m[0]), "http") {
return strings.TrimSpace(m[0])
}
return ""
}
// getHuggingFaceAvatarURL returns the HF avatar URL for a user, or "".
func getHuggingFaceAvatarURL(author string) string {
if author == "" {
return ""
}
userURL := fmt.Sprintf("https://huggingface.co/api/users/%s/overview", author)
resp, err := http.Get(userURL)
if err != nil {
return ""
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusOK {
return ""
}
body, err := io.ReadAll(resp.Body)
if err != nil {
return ""
}
var info map[string]any
if err := json.Unmarshal(body, &info); err != nil {
return ""
}
if v, ok := info["avatarUrl"].(string); ok && v != "" {
return v
}
if v, ok := info["avatar"].(string); ok && v != "" {
return v
}
return ""
}
// extractModelIcon extracts an icon URL from the README, falling back to the
// HuggingFace user avatar.
func extractModelIcon(model ProcessedModel) string {
if icon := extractIconFromReadme(model.ReadmeContent); icon != "" {
return icon
}
if model.Author != "" {
if avatar := getHuggingFaceAvatarURL(model.Author); avatar != "" {
return avatar
}
}
return ""
}

View File

@@ -1,280 +0,0 @@
package main
import (
"context"
"encoding/json"
"fmt"
"os"
"strconv"
"time"
hfapi "github.com/mudler/LocalAI/pkg/huggingface-api"
)
// ProcessedModelFile represents a processed model file with additional metadata
type ProcessedModelFile struct {
Path string `json:"path"`
Size int64 `json:"size"`
SHA256 string `json:"sha256"`
IsReadme bool `json:"is_readme"`
FileType string `json:"file_type"` // "model", "readme", "other"
}
// ProcessedModel represents a processed model with all gathered metadata
type ProcessedModel struct {
ModelID string `json:"model_id"`
Author string `json:"author"`
Downloads int `json:"downloads"`
LastModified string `json:"last_modified"`
Files []ProcessedModelFile `json:"files"`
PreferredModelFile *ProcessedModelFile `json:"preferred_model_file,omitempty"`
ReadmeFile *ProcessedModelFile `json:"readme_file,omitempty"`
ReadmeContent string `json:"readme_content,omitempty"`
ReadmeContentPreview string `json:"readme_content_preview,omitempty"`
QuantizationPreferences []string `json:"quantization_preferences"`
ProcessingError string `json:"processing_error,omitempty"`
Tags []string `json:"tags,omitempty"`
License string `json:"license,omitempty"`
Icon string `json:"icon,omitempty"`
}
// AddedModelSummary represents a summary of models added to the gallery
type AddedModelSummary struct {
SearchTerm string `json:"search_term"`
TotalFound int `json:"total_found"`
ModelsAdded int `json:"models_added"`
AddedModelIDs []string `json:"added_model_ids"`
AddedModelURLs []string `json:"added_model_urls"`
Quantization string `json:"quantization"`
ProcessingTime string `json:"processing_time"`
}
func main() {
startTime := time.Now()
// Synthetic mode for local testing
if sm := os.Getenv("SYNTHETIC_MODE"); sm == "true" || sm == "1" {
fmt.Println("Running in SYNTHETIC MODE - generating random test data")
if err := runSyntheticMode(); err != nil {
fmt.Fprintf(os.Stderr, "Error in synthetic mode: %v\n", err)
os.Exit(1)
}
return
}
searchTerm := os.Getenv("SEARCH_TERM")
if searchTerm == "" {
searchTerm = "GGUF"
}
limitStr := os.Getenv("LIMIT")
if limitStr == "" {
limitStr = "15"
}
limit, err := strconv.Atoi(limitStr)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing LIMIT: %v\n", err)
os.Exit(1)
}
quantization := os.Getenv("QUANTIZATION")
if quantization == "" {
quantization = "Q4_K_M"
}
maxModelsStr := os.Getenv("MAX_MODELS")
if maxModelsStr == "" {
maxModelsStr = "1"
}
maxModels, err := strconv.Atoi(maxModelsStr)
if err != nil {
fmt.Fprintf(os.Stderr, "Error parsing MAX_MODELS: %v\n", err)
os.Exit(1)
}
fmt.Printf("Gallery Agent Configuration:\n")
fmt.Printf(" Search Term: %s\n", searchTerm)
fmt.Printf(" Limit: %d\n", limit)
fmt.Printf(" Quantization: %s\n", quantization)
fmt.Printf(" Max Models to Add: %d\n", maxModels)
fmt.Printf(" Gallery Index Path: %s\n", getGalleryIndexPath())
fmt.Println()
// Phase 1: load current gallery and query HuggingFace.
gallerySet, err := loadGalleryURLSet()
if err != nil {
fmt.Fprintf(os.Stderr, "Error loading gallery index: %v\n", err)
os.Exit(1)
}
fmt.Printf("Loaded %d existing gallery entries\n", len(gallerySet))
client := hfapi.NewClient()
fmt.Println("Searching for trending models on HuggingFace...")
rawModels, err := client.GetTrending(searchTerm, limit)
if err != nil {
fmt.Fprintf(os.Stderr, "Error fetching models: %v\n", err)
os.Exit(1)
}
fmt.Printf("Found %d trending models matching %q\n", len(rawModels), searchTerm)
totalFound := len(rawModels)
// Phase 2: drop anything already in the gallery *before* any expensive
// per-model work (GetModelDetails, README fetches, icon lookups).
fresh := rawModels[:0]
for _, m := range rawModels {
if modelAlreadyInGallery(gallerySet, m.ModelID) {
fmt.Printf("Skipping existing model: %s\n", m.ModelID)
continue
}
fresh = append(fresh, m)
}
fmt.Printf("%d candidates after gallery dedup\n", len(fresh))
// Phase 3: HuggingFace already returned these in trendingScore order —
// just cap to MAX_MODELS.
if len(fresh) > maxModels {
fresh = fresh[:maxModels]
}
if len(fresh) == 0 {
fmt.Println("No new models to add to the gallery.")
writeSummary(AddedModelSummary{
SearchTerm: searchTerm,
TotalFound: totalFound,
ModelsAdded: 0,
Quantization: quantization,
ProcessingTime: time.Since(startTime).String(),
})
return
}
// Phase 4: fetch details and build ProcessedModel entries for survivors.
var processed []ProcessedModel
quantPrefs := []string{quantization, "Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K", "Q8_0"}
for _, m := range fresh {
fmt.Printf("Processing model: %s (downloads=%d)\n", m.ModelID, m.Downloads)
pm := ProcessedModel{
ModelID: m.ModelID,
Author: m.Author,
Downloads: m.Downloads,
LastModified: m.LastModified,
QuantizationPreferences: quantPrefs,
}
details, err := client.GetModelDetails(m.ModelID)
if err != nil {
fmt.Printf(" Error getting model details: %v (skipping)\n", err)
continue
}
preferred := hfapi.FindPreferredModelFile(details.Files, quantPrefs)
if preferred == nil {
fmt.Printf(" No GGUF file matching %v — skipping\n", quantPrefs)
continue
}
pm.Files = make([]ProcessedModelFile, len(details.Files))
for j, f := range details.Files {
fileType := "other"
if f.IsReadme {
fileType = "readme"
} else if f.Path == preferred.Path {
fileType = "model"
}
pm.Files[j] = ProcessedModelFile{
Path: f.Path,
Size: f.Size,
SHA256: f.SHA256,
IsReadme: f.IsReadme,
FileType: fileType,
}
if f.Path == preferred.Path {
copyFile := pm.Files[j]
pm.PreferredModelFile = &copyFile
}
if f.IsReadme {
copyFile := pm.Files[j]
pm.ReadmeFile = &copyFile
}
}
// Deterministic README resolution: follow base_model tag if set.
// Keep the raw (HTML-bearing) README around while we extract the
// icon, then strip it down to a plain-text description for the
// `description:` YAML field.
readme, err := resolveReadme(client, m.ModelID, m.Tags)
if err != nil {
fmt.Printf(" Warning: failed to fetch README: %v\n", err)
}
pm.ReadmeContent = readme
pm.License = licenseFromTags(m.Tags)
pm.Tags = curatedTags(m.Tags)
pm.Icon = extractModelIcon(pm)
if pm.ReadmeContent != "" {
pm.ReadmeContent = extractDescription(pm.ReadmeContent)
pm.ReadmeContentPreview = truncateString(pm.ReadmeContent, 200)
}
fmt.Printf(" License: %s, Tags: %v, Icon: %s\n", pm.License, pm.Tags, pm.Icon)
processed = append(processed, pm)
}
if len(processed) == 0 {
fmt.Println("No processable models after detail fetch.")
writeSummary(AddedModelSummary{
SearchTerm: searchTerm,
TotalFound: totalFound,
ModelsAdded: 0,
Quantization: quantization,
ProcessingTime: time.Since(startTime).String(),
})
return
}
// Phase 5: write YAML entries.
var addedIDs, addedURLs []string
for _, pm := range processed {
addedIDs = append(addedIDs, pm.ModelID)
addedURLs = append(addedURLs, "https://huggingface.co/"+pm.ModelID)
}
fmt.Println("Generating YAML entries for selected models...")
if err := generateYAMLForModels(context.Background(), processed, quantization); err != nil {
fmt.Fprintf(os.Stderr, "Error generating YAML entries: %v\n", err)
os.Exit(1)
}
writeSummary(AddedModelSummary{
SearchTerm: searchTerm,
TotalFound: totalFound,
ModelsAdded: len(addedIDs),
AddedModelIDs: addedIDs,
AddedModelURLs: addedURLs,
Quantization: quantization,
ProcessingTime: time.Since(startTime).String(),
})
}
func writeSummary(summary AddedModelSummary) {
data, err := json.MarshalIndent(summary, "", " ")
if err != nil {
fmt.Fprintf(os.Stderr, "Error marshaling summary: %v\n", err)
return
}
if err := os.WriteFile("gallery-agent-summary.json", data, 0644); err != nil {
fmt.Fprintf(os.Stderr, "Error writing summary file: %v\n", err)
return
}
fmt.Println("Summary written to gallery-agent-summary.json")
}
func truncateString(s string, maxLen int) string {
if len(s) <= maxLen {
return s
}
return s[:maxLen] + "..."
}

View File

@@ -1,224 +0,0 @@
package main
import (
"context"
"fmt"
"math/rand/v2"
"strings"
"time"
)
// runSyntheticMode generates synthetic test data and appends it to the gallery
func runSyntheticMode() error {
generator := NewSyntheticDataGenerator()
// Generate a random number of synthetic models (1-3)
numModels := generator.rand.IntN(3) + 1
fmt.Printf("Generating %d synthetic models for testing...\n", numModels)
var models []ProcessedModel
for range numModels {
model := generator.GenerateProcessedModel()
models = append(models, model)
fmt.Printf("Generated synthetic model: %s\n", model.ModelID)
}
// Generate YAML entries and append to gallery/index.yaml
fmt.Println("Generating YAML entries for synthetic models...")
err := generateYAMLForModels(context.Background(), models, "Q4_K_M")
if err != nil {
return fmt.Errorf("error generating YAML entries: %w", err)
}
fmt.Printf("Successfully added %d synthetic models to the gallery for testing!\n", len(models))
return nil
}
// SyntheticDataGenerator provides methods to generate synthetic test data
type SyntheticDataGenerator struct {
rand *rand.Rand
}
// NewSyntheticDataGenerator creates a new synthetic data generator
func NewSyntheticDataGenerator() *SyntheticDataGenerator {
return &SyntheticDataGenerator{
rand: rand.New(rand.NewPCG(uint64(time.Now().UnixNano()), 0)),
}
}
// GenerateProcessedModelFile creates a synthetic ProcessedModelFile
func (g *SyntheticDataGenerator) GenerateProcessedModelFile() ProcessedModelFile {
fileTypes := []string{"model", "readme", "other"}
fileType := fileTypes[g.rand.IntN(len(fileTypes))]
var path string
var isReadme bool
switch fileType {
case "model":
path = fmt.Sprintf("model-%s.gguf", g.randomString(8))
isReadme = false
case "readme":
path = "README.md"
isReadme = true
default:
path = fmt.Sprintf("file-%s.txt", g.randomString(6))
isReadme = false
}
return ProcessedModelFile{
Path: path,
Size: int64(g.rand.IntN(1000000000) + 1000000), // 1MB to 1GB
SHA256: g.randomSHA256(),
IsReadme: isReadme,
FileType: fileType,
}
}
// GenerateProcessedModel creates a synthetic ProcessedModel
func (g *SyntheticDataGenerator) GenerateProcessedModel() ProcessedModel {
authors := []string{"microsoft", "meta", "google", "openai", "anthropic", "mistralai", "huggingface"}
modelNames := []string{"llama", "gpt", "claude", "mistral", "gemma", "phi", "qwen", "codellama"}
author := authors[g.rand.IntN(len(authors))]
modelName := modelNames[g.rand.IntN(len(modelNames))]
modelID := fmt.Sprintf("%s/%s-%s", author, modelName, g.randomString(6))
// Generate files
numFiles := g.rand.IntN(5) + 2 // 2-6 files
files := make([]ProcessedModelFile, numFiles)
// Ensure at least one model file and one readme
hasModelFile := false
hasReadme := false
for i := range numFiles {
files[i] = g.GenerateProcessedModelFile()
if files[i].FileType == "model" {
hasModelFile = true
}
if files[i].FileType == "readme" {
hasReadme = true
}
}
// Add required files if missing
if !hasModelFile {
modelFile := g.GenerateProcessedModelFile()
modelFile.FileType = "model"
modelFile.Path = fmt.Sprintf("%s-Q4_K_M.gguf", modelName)
files = append(files, modelFile)
}
if !hasReadme {
readmeFile := g.GenerateProcessedModelFile()
readmeFile.FileType = "readme"
readmeFile.Path = "README.md"
readmeFile.IsReadme = true
files = append(files, readmeFile)
}
// Find preferred model file
var preferredModelFile *ProcessedModelFile
for i := range files {
if files[i].FileType == "model" {
preferredModelFile = &files[i]
break
}
}
// Find readme file
var readmeFile *ProcessedModelFile
for i := range files {
if files[i].FileType == "readme" {
readmeFile = &files[i]
break
}
}
readmeContent := g.generateReadmeContent(modelName, author)
// Generate sample metadata
licenses := []string{"apache-2.0", "mit", "llama2", "gpl-3.0", "bsd", ""}
license := licenses[g.rand.IntN(len(licenses))]
sampleTags := []string{"llm", "gguf", "gpu", "cpu", "text-to-text", "chat", "instruction-tuned"}
numTags := g.rand.IntN(4) + 3 // 3-6 tags
tags := make([]string, numTags)
for i := range numTags {
tags[i] = sampleTags[g.rand.IntN(len(sampleTags))]
}
// Remove duplicates
tags = g.removeDuplicates(tags)
// Optionally include icon (50% chance)
icon := ""
if g.rand.IntN(2) == 0 {
icon = fmt.Sprintf("https://cdn-avatars.huggingface.co/v1/production/uploads/%s.png", g.randomString(24))
}
return ProcessedModel{
ModelID: modelID,
Author: author,
Downloads: g.rand.IntN(1000000) + 1000,
LastModified: g.randomDate(),
Files: files,
PreferredModelFile: preferredModelFile,
ReadmeFile: readmeFile,
ReadmeContent: readmeContent,
ReadmeContentPreview: truncateString(readmeContent, 200),
QuantizationPreferences: []string{"Q4_K_M", "Q4_K_S", "Q3_K_M", "Q2_K"},
ProcessingError: "",
Tags: tags,
License: license,
Icon: icon,
}
}
// Helper methods for synthetic data generation
func (g *SyntheticDataGenerator) randomString(length int) string {
const charset = "abcdefghijklmnopqrstuvwxyz0123456789"
b := make([]byte, length)
for i := range b {
b[i] = charset[g.rand.IntN(len(charset))]
}
return string(b)
}
func (g *SyntheticDataGenerator) randomSHA256() string {
const charset = "0123456789abcdef"
b := make([]byte, 64)
for i := range b {
b[i] = charset[g.rand.IntN(len(charset))]
}
return string(b)
}
func (g *SyntheticDataGenerator) randomDate() string {
now := time.Now()
daysAgo := g.rand.IntN(365) // Random date within last year
pastDate := now.AddDate(0, 0, -daysAgo)
return pastDate.Format("2006-01-02T15:04:05.000Z")
}
func (g *SyntheticDataGenerator) removeDuplicates(slice []string) []string {
keys := make(map[string]bool)
result := []string{}
for _, item := range slice {
if !keys[item] {
keys[item] = true
result = append(result, item)
}
}
return result
}
func (g *SyntheticDataGenerator) generateReadmeContent(modelName, author string) string {
templates := []string{
fmt.Sprintf("# %s Model\n\nThis is a %s model developed by %s. It's designed for various natural language processing tasks including text generation, question answering, and conversation.\n\n## Features\n\n- High-quality text generation\n- Efficient inference\n- Multiple quantization options\n- Easy to use with LocalAI\n\n## Usage\n\nUse this model with LocalAI for various AI tasks.", strings.Title(modelName), modelName, author),
fmt.Sprintf("# %s\n\nA powerful language model from %s. This model excels at understanding and generating human-like text across multiple domains.\n\n## Capabilities\n\n- Text completion\n- Code generation\n- Creative writing\n- Technical documentation\n\n## Model Details\n\n- Architecture: Transformer-based\n- Training: Large-scale supervised learning\n- Quantization: Available in multiple formats", strings.Title(modelName), author),
fmt.Sprintf("# %s Language Model\n\nDeveloped by %s, this model represents state-of-the-art performance in natural language understanding and generation.\n\n## Key Features\n\n- Multilingual support\n- Context-aware responses\n- Efficient memory usage\n- Fast inference speed\n\n## Applications\n\n- Chatbots and virtual assistants\n- Content generation\n- Code completion\n- Educational tools", strings.Title(modelName), author),
}
return templates[g.rand.IntN(len(templates))]
}

11
.github/labeler.yml vendored
View File

@@ -1,15 +1,6 @@
enhancement:
enhancements:
- head-branch: ['^feature', 'feature']
dependencies:
- any:
- changed-files:
- any-glob-to-any-file: 'Makefile'
- changed-files:
- any-glob-to-any-file: '*.mod'
- changed-files:
- any-glob-to-any-file: '*.sum'
kind/documentation:
- any:
- changed-files:

View File

File diff suppressed because it is too large Load Diff

View File

@@ -1,257 +0,0 @@
---
name: 'build backend container images (reusable)'
on:
workflow_call:
inputs:
base-image:
description: 'Base image'
required: true
type: string
build-type:
description: 'Build type'
default: ''
type: string
cuda-major-version:
description: 'CUDA major version'
default: "12"
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "1"
type: string
platforms:
description: 'Platforms'
default: ''
type: string
tag-latest:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
runs-on:
description: 'Runs on'
required: true
default: ''
type: string
backend:
description: 'Backend to build'
required: true
type: string
context:
description: 'Build context'
required: true
type: string
dockerfile:
description: 'Build Dockerfile'
required: true
type: string
skip-drivers:
description: 'Skip drivers'
default: 'false'
type: string
ubuntu-version:
description: 'Ubuntu version'
required: false
default: '2204'
type: string
amdgpu-targets:
description: 'AMD GPU targets for ROCm/HIP builds'
required: false
default: 'gfx908,gfx90a,gfx942,gfx950,gfx1030,gfx1100,gfx1101,gfx1102,gfx1151,gfx1200,gfx1201'
type: string
secrets:
dockerUsername:
required: false
dockerPassword:
required: false
quayUsername:
required: true
quayPassword:
required: true
jobs:
backend-build:
runs-on: ${{ inputs.runs-on }}
env:
quay_username: ${{ secrets.quayUsername }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
run: |
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
sudo apt-get remove -y '^mono-.*' || true
sudo apt-get remove -y '^ghc-.*' || true
sudo apt-get remove -y '.*jdk.*|.*jre.*' || true
sudo apt-get remove -y 'php.*' || true
sudo apt-get remove -y hhvm powershell firefox monodoc-manual msbuild || true
sudo apt-get remove -y '^google-.*' || true
sudo apt-get remove -y azure-cli || true
sudo apt-get remove -y '^mongo.*-.*|^postgresql-.*|^mysql-.*|^mssql-.*' || true
sudo apt-get remove -y '^gfortran-.*' || true
sudo apt-get remove -y microsoft-edge-stable || true
sudo apt-get remove -y firefox || true
sudo apt-get remove -y powershell || true
sudo apt-get remove -y r-base-core || true
sudo apt-get autoremove -y
sudo apt-get clean
echo
echo "Listing top largest packages"
pkgs=$(dpkg-query -Wf '${Installed-Size}\t${Package}\t${Status}\n' | awk '$NF == "installed"{print $1 "\t" $2}' | sort -nr)
head -n 30 <<< "${pkgs}"
echo
sudo rm -rfv build || true
sudo rm -rf /usr/share/dotnet || true
sudo rm -rf /opt/ghc || true
sudo rm -rf "/usr/local/share/boost" || true
sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
df -h
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v6
with:
images: |
quay.io/go-skynet/local-ai-backends
localai/localai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v6
with:
images: |
quay.io/go-skynet/ci-tests
tags: |
type=ref,event=branch,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=semver,pattern={{raw}},suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=sha,suffix=${{ github.event.number }}-${{ inputs.backend }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
## End testing image
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
platforms: all
- name: Set up Docker Buildx
id: buildx
uses: docker/setup-buildx-action@master
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v4
with:
username: ${{ secrets.dockerUsername }}
password: ${{ secrets.dockerPassword }}
- name: Login to Quay.io
if: ${{ env.quay_username != '' }}
uses: docker/login-action@v4
with:
registry: quay.io
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v7
if: github.event_name != 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
AMDGPU_TARGETS=${{ inputs.amdgpu-targets }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
- name: Build and push (PR)
uses: docker/build-push-action@v7
if: github.event_name == 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BUILD_TYPE=${{ inputs.build-type }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
BASE_IMAGE=${{ inputs.base-image }}
BACKEND=${{ inputs.backend }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
AMDGPU_TARGETS=${{ inputs.amdgpu-targets }}
context: ${{ inputs.context }}
file: ${{ inputs.dockerfile }}
cache-from: type=gha
platforms: ${{ inputs.platforms }}
push: ${{ env.quay_username != '' }}
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
- name: job summary
run: |
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

View File

@@ -1,144 +0,0 @@
---
name: 'build darwin python backend container images (reusable)'
on:
workflow_call:
inputs:
backend:
description: 'Backend to build'
required: true
type: string
build-type:
description: 'Build type (e.g., mps)'
default: ''
type: string
use-pip:
description: 'Use pip to install dependencies'
default: false
type: boolean
lang:
description: 'Programming language (e.g. go)'
default: 'python'
type: string
go-version:
description: 'Go version to use'
default: '1.24.x'
type: string
tag-suffix:
description: 'Tag suffix for the built image'
required: true
type: string
runs-on:
description: 'Runner to use'
default: 'macOS-14'
type: string
secrets:
dockerUsername:
required: false
dockerPassword:
required: false
quayUsername:
required: true
quayPassword:
required: true
jobs:
darwin-backend-build:
runs-on: ${{ inputs.runs-on }}
strategy:
matrix:
go-version: ['${{ inputs.go-version }}']
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm
- name: Build ${{ inputs.backend }}-darwin
run: |
make protogen-go
BACKEND=${{ inputs.backend }} BUILD_TYPE=${{ inputs.build-type }} USE_PIP=${{ inputs.use-pip }} make build-darwin-${{ inputs.lang }}-backend
- name: Upload ${{ inputs.backend }}.tar
uses: actions/upload-artifact@v7
with:
name: ${{ inputs.backend }}-tar
path: backend-images/${{ inputs.backend }}.tar
darwin-backend-publish:
needs: darwin-backend-build
if: github.event_name != 'pull_request'
runs-on: ubuntu-latest
steps:
- name: Download ${{ inputs.backend }}.tar
uses: actions/download-artifact@v8
with:
name: ${{ inputs.backend }}-tar
path: .
- name: Install crane
run: |
curl -L https://github.com/google/go-containerregistry/releases/latest/download/go-containerregistry_Linux_x86_64.tar.gz | tar -xz
sudo mv crane /usr/local/bin/
- name: Log in to DockerHub
run: |
echo "${{ secrets.dockerPassword }}" | crane auth login docker.io -u "${{ secrets.dockerUsername }}" --password-stdin
- name: Log in to quay.io
run: |
echo "${{ secrets.quayPassword }}" | crane auth login quay.io -u "${{ secrets.quayUsername }}" --password-stdin
- name: Docker meta
id: meta
uses: docker/metadata-action@v6
with:
images: |
localai/localai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=auto
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Docker meta
id: quaymeta
uses: docker/metadata-action@v6
with:
images: |
quay.io/go-skynet/local-ai-backends
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=auto
suffix=${{ inputs.tag-suffix }},onlatest=true
- name: Push Docker image (DockerHub)
run: |
for tag in $(echo "${{ steps.meta.outputs.tags }}" | tr ',' '\n'); do
crane push ${{ inputs.backend }}.tar $tag
done
- name: Push Docker image (Quay)
run: |
for tag in $(echo "${{ steps.quaymeta.outputs.tags }}" | tr ',' '\n'); do
crane push ${{ inputs.backend }}.tar $tag
done

View File

@@ -1,79 +0,0 @@
name: 'build backend container images (PR-filtered)'
on:
pull_request:
concurrency:
group: ci-backends-pr-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
generate-matrix:
runs-on: ubuntu-latest
outputs:
matrix: ${{ steps.set-matrix.outputs.matrix }}
matrix-darwin: ${{ steps.set-matrix.outputs.matrix-darwin }}
has-backends: ${{ steps.set-matrix.outputs.has-backends }}
has-backends-darwin: ${{ steps.set-matrix.outputs.has-backends-darwin }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Setup Bun
uses: oven-sh/setup-bun@v2
- name: Install dependencies
run: |
bun add js-yaml
bun add @octokit/core
# filters the matrix in backend.yml
- name: Filter matrix for changed backends
id: set-matrix
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_EVENT_PATH: ${{ github.event_path }}
run: bun run scripts/changed-backends.js
backend-jobs:
needs: generate-matrix
uses: ./.github/workflows/backend_build.yml
if: needs.generate-matrix.outputs.has-backends == 'true'
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
backend: ${{ matrix.backend }}
dockerfile: ${{ matrix.dockerfile }}
skip-drivers: ${{ matrix.skip-drivers }}
context: ${{ matrix.context }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
fail-fast: true
matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix) }}
backend-jobs-darwin:
needs: generate-matrix
uses: ./.github/workflows/backend_build_darwin.yml
if: needs.generate-matrix.outputs.has-backends-darwin == 'true'
with:
backend: ${{ matrix.backend }}
build-type: ${{ matrix.build-type }}
go-version: "1.24.x"
tag-suffix: ${{ matrix.tag-suffix }}
lang: ${{ matrix.lang || 'python' }}
use-pip: ${{ matrix.backend == 'diffusers' }}
runs-on: "macos-latest"
secrets:
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
fail-fast: true
matrix: ${{ fromJson(needs.generate-matrix.outputs.matrix-darwin) }}

View File

@@ -1,67 +0,0 @@
name: Build test
on:
push:
branches:
- master
pull_request:
jobs:
build-test:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Run GoReleaser
run: |
make dev-dist
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
ls -liah dist
- name: Upload macOS launcher artifacts
uses: actions/upload-artifact@v7
with:
name: launcher-macos
path: dist/
retention-days: 30
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.25
- name: Build launcher for Linux
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: actions/upload-artifact@v7
with:
name: launcher-linux
path: local-ai-launcher-linux.tar.xz
retention-days: 30

View File

@@ -1,48 +0,0 @@
name: Bump inference defaults
on:
schedule:
# Run daily at 06:00 UTC
- cron: '0 6 * * *'
workflow_dispatch: # Allow manual trigger
permissions:
contents: write
pull-requests: write
jobs:
bump:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/setup-go@v5
with:
go-version-file: go.mod
- name: Re-fetch inference defaults
run: make generate-force
- name: Check for changes
id: diff
run: |
if git diff --quiet core/config/inference_defaults.json; then
echo "changed=false" >> "$GITHUB_OUTPUT"
else
echo "changed=true" >> "$GITHUB_OUTPUT"
fi
- name: Create Pull Request
if: steps.diff.outputs.changed == 'true'
uses: peter-evans/create-pull-request@v8
with:
commit-message: "chore: bump inference defaults from unsloth"
title: "chore: bump inference defaults from unsloth"
body: |
Auto-generated update of `core/config/inference_defaults.json` from
[unsloth's inference_defaults.json](https://github.com/unslothai/unsloth/blob/main/studio/backend/assets/configs/inference_defaults.json).
This PR was created automatically by the `bump-inference-defaults` workflow.
branch: chore/bump-inference-defaults
delete-branch: true
labels: automated

View File

@@ -1,62 +1,48 @@
name: Bump Backend dependencies
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-backends:
if: github.repository == 'mudler/LocalAI'
bump:
strategy:
fail-fast: false
matrix:
include:
- repository: "ggml-org/llama.cpp"
variable: "LLAMA_VERSION"
- repository: "ggerganov/llama.cpp"
variable: "CPPLLAMA_VERSION"
branch: "master"
file: "backend/cpp/llama-cpp/Makefile"
- repository: "ikawrakow/ik_llama.cpp"
variable: "IK_LLAMA_VERSION"
- repository: "go-skynet/go-ggml-transformers.cpp"
variable: "GOGGMLTRANSFORMERS_VERSION"
branch: "master"
- repository: "donomii/go-rwkv.cpp"
variable: "RWKV_VERSION"
branch: "main"
file: "backend/cpp/ik-llama-cpp/Makefile"
- repository: "TheTom/llama-cpp-turboquant"
variable: "TURBOQUANT_VERSION"
branch: "feature/turboquant-kv-cache"
file: "backend/cpp/turboquant/Makefile"
- repository: "ggml-org/whisper.cpp"
- repository: "ggerganov/whisper.cpp"
variable: "WHISPER_CPP_VERSION"
branch: "master"
file: "backend/go/whisper/Makefile"
- repository: "leejet/stable-diffusion.cpp"
variable: "STABLEDIFFUSION_GGML_VERSION"
- repository: "go-skynet/go-bert.cpp"
variable: "BERT_VERSION"
branch: "master"
- repository: "go-skynet/bloomz.cpp"
variable: "BLOOMZ_VERSION"
branch: "main"
- repository: "mudler/go-ggllm.cpp"
variable: "GOGGLLM_VERSION"
branch: "master"
- repository: "mudler/go-stable-diffusion"
variable: "STABLEDIFFUSION_VERSION"
branch: "master"
file: "backend/go/stablediffusion-ggml/Makefile"
- repository: "mudler/go-piper"
variable: "PIPER_VERSION"
branch: "master"
file: "backend/go/piper/Makefile"
- repository: "antirez/voxtral.c"
variable: "VOXTRAL_VERSION"
branch: "main"
file: "backend/go/voxtral/Makefile"
- repository: "ace-step/acestep.cpp"
variable: "ACESTEP_CPP_VERSION"
branch: "master"
file: "backend/go/acestep-cpp/Makefile"
- repository: "PABannier/sam3.cpp"
variable: "SAM3_VERSION"
branch: "main"
file: "backend/go/sam3-cpp/Makefile"
- repository: "predict-woo/qwen3-tts.cpp"
variable: "QWEN3TTS_CPP_VERSION"
branch: "main"
file: "backend/go/qwen3-tts-cpp/Makefile"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
id: bump
run: |
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }} ${{ matrix.file }}
bash .github/bump_deps.sh ${{ matrix.repository }} ${{ matrix.branch }} ${{ matrix.variable }}
{
echo 'message<<EOF'
cat "${{ matrix.variable }}_message.txt"
@@ -70,7 +56,7 @@ jobs:
rm -rfv ${{ matrix.variable }}_message.txt
rm -rfv ${{ matrix.variable }}_commit.txt
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -1,11 +1,10 @@
name: Bump Documentation
name: Bump dependencies
on:
schedule:
- cron: 0 20 * * *
workflow_dispatch:
jobs:
bump-docs:
if: github.repository == 'mudler/LocalAI'
bump:
strategy:
fail-fast: false
matrix:
@@ -13,12 +12,12 @@ jobs:
- repository: "mudler/LocalAI"
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Bump dependencies 🔧
run: |
bash .github/bump_docs.sh ${{ matrix.repository }}
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -5,8 +5,7 @@ on:
workflow_dispatch:
jobs:
checksum_check:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
@@ -16,14 +15,15 @@ jobs:
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- name: Install dependencies
run: |
sudo apt-get update
sudo apt-get install -y pip wget
sudo pip install --upgrade pip
pip install huggingface_hub
- name: 'Setup yq'
uses: dcarbone/install-yq-action@v1.3.1
uses: dcarbone/install-yq-action@v1.1.1
with:
version: 'v4.44.2'
download-compressed: true
@@ -36,7 +36,7 @@ jobs:
sudo chmod 777 /hf_cache
bash .github/checksum_checker.sh gallery/index.yaml
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -9,18 +9,18 @@ permissions:
jobs:
dependabot:
if: github.repository == 'mudler/LocalAI' && github.actor == 'dependabot[bot]'
runs-on: ubuntu-latest
if: ${{ github.actor == 'dependabot[bot]' }}
steps:
- name: Dependabot metadata
id: metadata
uses: dependabot/fetch-metadata@v2.5.0
uses: dependabot/fetch-metadata@v2.2.0
with:
github-token: "${{ secrets.GITHUB_TOKEN }}"
skip-commit-verification: true
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |

View File

@@ -12,11 +12,10 @@ concurrency:
jobs:
build-linux:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
@@ -32,9 +31,9 @@ jobs:
make protogen-go
- name: Build api
run: |
CGO_ENABLED=0 make build
CGO_ENABLED=0 make build-api
- name: rm
uses: appleboy/ssh-action@v1.2.5
uses: appleboy/ssh-action@v1.0.3
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -43,7 +42,7 @@ jobs:
script: |
sudo rm -rf local-ai/ || true
- name: copy file via ssh
uses: appleboy/scp-action@v1.0.0
uses: appleboy/scp-action@v0.1.7
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}
@@ -54,7 +53,7 @@ jobs:
rm: true
target: ./local-ai
- name: restarting
uses: appleboy/ssh-action@v1.2.5
uses: appleboy/ssh-action@v1.0.3
with:
host: ${{ secrets.EXPLORER_SSH_HOST }}
username: ${{ secrets.EXPLORER_SSH_USERNAME }}

View File

@@ -1,214 +0,0 @@
name: Gallery Agent
on:
schedule:
- cron: '0 */3 * * *' # Run every 4 hours
workflow_dispatch:
inputs:
search_term:
description: 'Search term for models'
required: false
default: 'GGUF'
type: string
limit:
description: 'Maximum number of models to process'
required: false
default: '15'
type: string
quantization:
description: 'Preferred quantization format'
required: false
default: 'Q4_K_M'
type: string
max_models:
description: 'Maximum number of models to add to the gallery'
required: false
default: '1'
type: string
jobs:
gallery-agent:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
steps:
- name: Checkout repository
uses: actions/checkout@v6
with:
token: ${{ secrets.GITHUB_TOKEN }}
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: '1.21'
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Process gallery-agent PR commands
env:
GH_TOKEN: ${{ secrets.UPDATE_BOT_TOKEN }}
REPO: ${{ github.repository }}
SEARCH: 'gallery agent in:title'
run: |
# Walk gallery-agent PRs and act on maintainer comments:
# /gallery-agent blacklist → label `gallery-agent/blacklisted` + close (never repropose)
# /gallery-agent recreate → close without label (next run may repropose)
# Only comments from OWNER / MEMBER / COLLABORATOR are honored so
# random users can't drive the bot.
#
# We scan both open PRs AND recently-closed PRs that don't already
# carry the blacklist label. This covers the common flow where a
# maintainer writes /gallery-agent blacklist and immediately clicks
# Close — without this, the next scheduled run wouldn't see the
# command (PR is already closed) and would repropose the model.
gh label create gallery-agent/blacklisted \
--repo "$REPO" --color ededed \
--description "gallery-agent must not repropose this model" 2>/dev/null || true
prs_open=$(gh pr list --repo "$REPO" --state open --search "$SEARCH" \
--json number --jq '.[].number')
# Closed PRs from the last 14 days that don't yet have the blacklist label.
# Bounded window keeps the scan cheap while covering late-applied commands.
since=$(date -u -d '14 days ago' +%Y-%m-%d)
prs_closed=$(gh pr list --repo "$REPO" --state closed \
--search "$SEARCH closed:>=$since -label:gallery-agent/blacklisted" \
--json number --jq '.[].number')
prs=$(printf '%s\n%s\n' "$prs_open" "$prs_closed" | sort -u | sed '/^$/d')
for pr in $prs; do
state=$(gh pr view "$pr" --repo "$REPO" --json state --jq '.state')
cmds=$(gh pr view "$pr" --repo "$REPO" --json comments \
--jq '.comments[] | select(.authorAssociation=="OWNER" or .authorAssociation=="MEMBER" or .authorAssociation=="COLLABORATOR") | .body')
if echo "$cmds" | grep -qE '(^|[[:space:]])/gallery-agent[[:space:]]+blacklist([[:space:]]|$)'; then
echo "PR #$pr: blacklist command found (state=$state)"
gh pr edit "$pr" --repo "$REPO" --add-label gallery-agent/blacklisted || true
if [ "$state" = "OPEN" ]; then
gh pr close "$pr" --repo "$REPO" --comment "Blacklisted via \`/gallery-agent blacklist\`. This model will not be reproposed." || true
fi
elif [ "$state" = "OPEN" ] && echo "$cmds" | grep -qE '(^|[[:space:]])/gallery-agent[[:space:]]+recreate([[:space:]]|$)'; then
echo "PR #$pr: recreate command found"
gh pr close "$pr" --repo "$REPO" --comment "Closed via \`/gallery-agent recreate\`. The next scheduled run will propose this model again." || true
fi
done
- name: Collect skip URLs for the gallery agent
id: open_prs
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
REPO: ${{ github.repository }}
SEARCH: 'gallery agent in:title'
run: |
# Skip set =
# URLs from any open gallery-agent PR (avoid duplicate PRs for the same model while one is pending)
# + URLs from closed PRs carrying the `gallery-agent/blacklisted` label (hard blacklist)
# Plain-closed PRs without the label are ignored — closing a PR is
# not by itself a "never propose again" signal; maintainers must
# opt in via the /gallery-agent blacklist comment command.
urls_open=$(gh pr list --repo "$REPO" --state open --search "$SEARCH" \
--json body --jq '[.[].body] | join("\n")' \
| grep -oE 'https://huggingface\.co/[^ )]+' || true)
urls_blacklist=$(gh pr list --repo "$REPO" --state closed --search "$SEARCH" \
--label gallery-agent/blacklisted \
--json body --jq '[.[].body] | join("\n")' \
| grep -oE 'https://huggingface\.co/[^ )]+' || true)
urls=$(printf '%s\n%s\n' "$urls_open" "$urls_blacklist" | sort -u | sed '/^$/d')
echo "Skip URLs:"
echo "$urls"
{
echo "urls<<EOF"
echo "$urls"
echo "EOF"
} >> "$GITHUB_OUTPUT"
- name: Run gallery agent
env:
SEARCH_TERM: ${{ github.event.inputs.search_term || 'GGUF' }}
LIMIT: ${{ github.event.inputs.limit || '15' }}
QUANTIZATION: ${{ github.event.inputs.quantization || 'Q4_K_M' }}
MAX_MODELS: ${{ github.event.inputs.max_models || '1' }}
EXTRA_SKIP_URLS: ${{ steps.open_prs.outputs.urls }}
run: |
export GALLERY_INDEX_PATH=$PWD/gallery/index.yaml
go run ./.github/gallery-agent
- name: Check for changes
id: check_changes
run: |
if git diff --quiet gallery/index.yaml; then
echo "changes=false" >> $GITHUB_OUTPUT
echo "No changes detected in gallery/index.yaml"
else
echo "changes=true" >> $GITHUB_OUTPUT
echo "Changes detected in gallery/index.yaml"
git diff gallery/index.yaml
fi
- name: Read gallery agent summary
id: read_summary
if: steps.check_changes.outputs.changes == 'true'
run: |
if [ -f "./gallery-agent-summary.json" ]; then
echo "summary_exists=true" >> $GITHUB_OUTPUT
# Extract summary data using jq
echo "search_term=$(jq -r '.search_term' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "total_found=$(jq -r '.total_found' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "models_added=$(jq -r '.models_added' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "quantization=$(jq -r '.quantization' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
echo "processing_time=$(jq -r '.processing_time' ./gallery-agent-summary.json)" >> $GITHUB_OUTPUT
# Create a formatted list of added models with URLs
added_models=$(jq -r 'range(0; .added_model_ids | length) as $i | "- [\(.added_model_ids[$i])](\(.added_model_urls[$i]))"' ./gallery-agent-summary.json | tr '\n' '\n')
echo "added_models<<EOF" >> $GITHUB_OUTPUT
echo "$added_models" >> $GITHUB_OUTPUT
echo "EOF" >> $GITHUB_OUTPUT
rm -f ./gallery-agent-summary.json
else
echo "summary_exists=false" >> $GITHUB_OUTPUT
fi
- name: Create Pull Request
if: steps.check_changes.outputs.changes == 'true'
uses: peter-evans/create-pull-request@v8
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI
commit-message: 'chore(model gallery): :robot: add new models via gallery agent'
title: 'chore(model gallery): :robot: add ${{ steps.read_summary.outputs.models_added || 0 }} new models via gallery agent'
# Branch has to be unique so PRs are not overriding each other
branch-suffix: timestamp
body: |
This PR was automatically created by the gallery agent workflow.
**Summary:**
- **Search Term:** ${{ steps.read_summary.outputs.search_term || github.event.inputs.search_term || 'GGUF' }}
- **Models Found:** ${{ steps.read_summary.outputs.total_found || 'N/A' }}
- **Models Added:** ${{ steps.read_summary.outputs.models_added || '0' }}
- **Quantization:** ${{ steps.read_summary.outputs.quantization || github.event.inputs.quantization || 'Q4_K_M' }}
- **Processing Time:** ${{ steps.read_summary.outputs.processing_time || 'N/A' }}
**Added Models:**
${{ steps.read_summary.outputs.added_models || '- No models added' }}
### Bot commands
Maintainers (owner / member / collaborator) can control this PR
by leaving a comment with one of:
- `/gallery-agent recreate` — close this PR; the next scheduled
run will propose this model again (useful if the entry needs
to be regenerated with fresh metadata).
- `/gallery-agent blacklist` — close this PR and permanently
prevent the gallery agent from ever reproposing this model.
Plain "Close" (without a command) is treated as a no-op: the
model may be reproposed by a future run.
**Workflow Details:**
- Triggered by: `${{ github.event_name }}`
- Run ID: `${{ github.run_id }}`
- Commit: `${{ github.sha }}`
signoff: true
delete-branch: true

View File

@@ -2,10 +2,9 @@ name: 'generate and publish GRPC docker caches'
on:
workflow_dispatch:
schedule:
# daily at midnight
- cron: '0 0 * * *'
push:
branches:
- master
concurrency:
group: grpc-cache-${{ github.head_ref || github.ref }}-${{ github.repository }}
@@ -13,11 +12,10 @@ concurrency:
jobs:
generate_caches:
if: github.repository == 'mudler/LocalAI'
strategy:
matrix:
include:
- grpc-base-image: ubuntu:24.04
- grpc-base-image: ubuntu:22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64,linux/arm64'
runs-on: ${{matrix.runs-on}}
@@ -74,10 +72,10 @@ jobs:
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Cache GRPC
uses: docker/build-push-action@v7
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
# The build-args MUST be an EXACT match between the image cache and other workflow steps that want to use that cache.

View File

@@ -12,12 +12,11 @@ concurrency:
jobs:
generate_caches:
if: github.repository == 'mudler/LocalAI'
strategy:
matrix:
include:
- base-image: intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04
runs-on: 'arc-runner-set'
- base-image: intel/oneapi-basekit:2024.2.0-devel-ubuntu22.04
runs-on: 'ubuntu-latest'
platforms: 'linux/amd64'
runs-on: ${{matrix.runs-on}}
steps:
@@ -27,14 +26,14 @@ jobs:
platforms: all
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v4
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKERHUB_USERNAME }}
password: ${{ secrets.DOCKERHUB_PASSWORD }}
- name: Login to quay
if: github.event_name != 'pull_request'
uses: docker/login-action@v4
uses: docker/login-action@v3
with:
registry: quay.io
username: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
@@ -44,17 +43,17 @@ jobs:
uses: docker/setup-buildx-action@master
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Cache Intel images
uses: docker/build-push-action@v7
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=${{ matrix.base-image }}
context: .
file: ./Dockerfile
tags: quay.io/go-skynet/intel-oneapi-base:24.04
tags: quay.io/go-skynet/intel-oneapi-base:latest
push: true
target: intel
platforms: ${{ matrix.platforms }}

View File

@@ -1,75 +0,0 @@
name: Deploy docs to GitHub Pages
on:
push:
branches:
- master
paths:
- 'docs/**'
- 'gallery/**'
- 'images/**'
- '.github/ci/modelslist.go'
- '.github/workflows/gh-pages.yml'
workflow_dispatch:
permissions:
contents: read
pages: write
id-token: write
concurrency:
group: pages
cancel-in-progress: false
jobs:
build:
runs-on: ubuntu-latest
env:
HUGO_VERSION: "0.146.3"
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0 # needed for enableGitInfo
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.22'
cache: false
- name: Setup Hugo
uses: peaceiris/actions-hugo@v3
with:
hugo-version: ${{ env.HUGO_VERSION }}
extended: true
- name: Setup Pages
id: pages
uses: actions/configure-pages@v6
- name: Generate gallery
run: go run ./.github/ci/modelslist.go ./gallery/index.yaml > docs/static/gallery.html
- name: Build site
working-directory: docs
run: |
mkdir -p layouts/_default
hugo --minify --baseURL "${{ steps.pages.outputs.base_url }}/"
- name: Upload artifact
uses: actions/upload-pages-artifact@v5
with:
path: docs/public
deploy:
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
runs-on: ubuntu-latest
needs: build
steps:
- name: Deploy to GitHub Pages
id: deployment
uses: actions/deploy-pages@v5

View File

@@ -1,95 +1,140 @@
---
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
fail-fast: false
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "8"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'sycl'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
tag-suffix: 'sycl'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'vulkan'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'false'
tag-suffix: '-vulkan-core'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'false'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
name: 'build container images tests'
on:
pull_request:
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
extras-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 4 || 8 }}
matrix:
include:
# This is basically covered by the AIO test
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'hipblas'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-hipblas'
# ffmpeg: 'false'
# image-type: 'extras'
# base-image: "rocm/dev-ubuntu-22.04:6.1"
# grpc-base-image: "ubuntu:22.04"
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg'
# ffmpeg: 'true'
# image-type: 'extras'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# core-image-build:
# uses: ./.github/workflows/image_build.yml
# with:
# tag-latest: ${{ matrix.tag-latest }}
# tag-suffix: ${{ matrix.tag-suffix }}
# ffmpeg: ${{ matrix.ffmpeg }}
# image-type: ${{ matrix.image-type }}
# build-type: ${{ matrix.build-type }}
# cuda-major-version: ${{ matrix.cuda-major-version }}
# cuda-minor-version: ${{ matrix.cuda-minor-version }}
# platforms: ${{ matrix.platforms }}
# runs-on: ${{ matrix.runs-on }}
# base-image: ${{ matrix.base-image }}
# grpc-base-image: ${{ matrix.grpc-base-image }}
# makeflags: ${{ matrix.makeflags }}
# secrets:
# dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
# dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
# quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
# quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
# strategy:
# matrix:
# include:
# - build-type: ''
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'sycl_f16'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
# grpc-base-image: "ubuntu:22.04"
# tag-suffix: 'sycl-f16-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'arc-runner-set'
# makeflags: "--jobs=3 --output-sync=target"
# - build-type: 'cublas'
# cuda-major-version: "12"
# cuda-minor-version: "0"
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-cublas-cuda12-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"
# - build-type: 'vulkan'
# platforms: 'linux/amd64'
# tag-latest: 'false'
# tag-suffix: '-vulkan-ffmpeg-core'
# ffmpeg: 'true'
# image-type: 'core'
# runs-on: 'ubuntu-latest'
# base-image: "ubuntu:22.04"
# makeflags: "--jobs=4 --output-sync=target"

View File

@@ -1,181 +1,328 @@
---
name: 'build container images'
on:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
hipblas-jobs:
if: github.repository == 'mudler/LocalAI'
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
ubuntu-version: ${{ matrix.ubuntu-version }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-hipblas'
base-image: "rocm/dev-ubuntu-24.04:7.2.1"
grpc-base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
core-image-build:
if: github.repository == 'mudler/LocalAI'
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
#max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: ''
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-latest'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "8"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-12'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-gpu-nvidia-cuda-13'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:22.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'vulkan'
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-gpu-vulkan'
runs-on: 'ubuntu-latest'
base-image: "ubuntu:24.04"
skip-drivers: 'false'
makeflags: "--jobs=4 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
- build-type: 'intel'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
grpc-base-image: "ubuntu:24.04"
tag-suffix: '-gpu-intel'
runs-on: 'ubuntu-latest'
makeflags: "--jobs=3 --output-sync=target"
ubuntu-version: '2404'
ubuntu-codename: 'noble'
gh-runner:
if: github.repository == 'mudler/LocalAI'
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
skip-drivers: ${{ matrix.skip-drivers }}
ubuntu-version: ${{ matrix.ubuntu-version }}
ubuntu-codename: ${{ matrix.ubuntu-codename }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
matrix:
include:
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64'
base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'true'
ubuntu-version: "2204"
ubuntu-codename: 'jammy'
- build-type: 'cublas'
cuda-major-version: "13"
cuda-minor-version: "0"
platforms: 'linux/arm64'
tag-latest: 'auto'
tag-suffix: '-nvidia-l4t-arm64-cuda-13'
base-image: "ubuntu:24.04"
runs-on: 'ubuntu-24.04-arm'
makeflags: "--jobs=4 --output-sync=target"
skip-drivers: 'false'
ubuntu-version: '2404'
ubuntu-codename: 'noble'
name: 'build container images'
on:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
self-hosted-jobs:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
aio: ${{ matrix.aio }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
# Pushing with all jobs in parallel
# eats the bandwidth of all the nodes
max-parallel: ${{ github.event_name != 'pull_request' && 6 || 10 }}
matrix:
include:
# Extra images
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12'
ffmpeg: ''
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda11-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-11"
latest-image: 'latest-gpu-nvidia-cuda-11'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-11'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-cublas-cuda12-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
aio: "-aio-gpu-nvidia-cuda-12"
latest-image: 'latest-gpu-nvidia-cuda-12'
latest-image-aio: 'latest-aio-gpu-nvidia-cuda-12'
makeflags: "--jobs=3 --output-sync=target"
- build-type: ''
#platforms: 'linux/amd64,linux/arm64'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: ''
ffmpeg: ''
image-type: 'extras'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'auto'
tag-suffix: '-hipblas-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
aio: "-aio-gpu-hipblas"
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
latest-image: 'latest-gpu-hipblas'
latest-image-aio: 'latest-aio-gpu-hipblas'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas'
ffmpeg: 'false'
image-type: 'extras'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f16"
latest-image: 'latest-gpu-intel-f16'
latest-image-aio: 'latest-aio-gpu-intel-f16'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'auto'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg'
ffmpeg: 'true'
image-type: 'extras'
runs-on: 'arc-runner-set'
aio: "-aio-gpu-intel-f32"
latest-image: 'latest-gpu-intel-f32'
latest-image-aio: 'latest-aio-gpu-intel-f32'
makeflags: "--jobs=3 --output-sync=target"
# Core images
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-core'
ffmpeg: 'false'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f16'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f16-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'sycl_f32'
platforms: 'linux/amd64'
tag-latest: 'false'
base-image: "quay.io/go-skynet/intel-oneapi-base:latest"
grpc-base-image: "ubuntu:22.04"
tag-suffix: '-sycl-f32-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
- build-type: 'hipblas'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-hipblas-core'
ffmpeg: 'false'
image-type: 'core'
base-image: "rocm/dev-ubuntu-22.04:6.1"
grpc-base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=3 --output-sync=target"
core-image-build:
uses: ./.github/workflows/image_build.yml
with:
tag-latest: ${{ matrix.tag-latest }}
tag-suffix: ${{ matrix.tag-suffix }}
ffmpeg: ${{ matrix.ffmpeg }}
image-type: ${{ matrix.image-type }}
build-type: ${{ matrix.build-type }}
cuda-major-version: ${{ matrix.cuda-major-version }}
cuda-minor-version: ${{ matrix.cuda-minor-version }}
platforms: ${{ matrix.platforms }}
runs-on: ${{ matrix.runs-on }}
aio: ${{ matrix.aio }}
base-image: ${{ matrix.base-image }}
grpc-base-image: ${{ matrix.grpc-base-image }}
makeflags: ${{ matrix.makeflags }}
latest-image: ${{ matrix.latest-image }}
latest-image-aio: ${{ matrix.latest-image-aio }}
secrets:
dockerUsername: ${{ secrets.DOCKERHUB_USERNAME }}
dockerPassword: ${{ secrets.DOCKERHUB_PASSWORD }}
quayUsername: ${{ secrets.LOCALAI_REGISTRY_USERNAME }}
quayPassword: ${{ secrets.LOCALAI_REGISTRY_PASSWORD }}
strategy:
max-parallel: ${{ github.event_name != 'pull_request' && 2 || 4 }}
matrix:
include:
- build-type: ''
platforms: 'linux/amd64,linux/arm64'
tag-latest: 'auto'
tag-suffix: '-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
aio: "-aio-cpu"
latest-image: 'latest-cpu'
latest-image-aio: 'latest-aio-cpu'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-core'
ffmpeg: ''
image-type: 'core'
base-image: "ubuntu:22.04"
runs-on: 'arc-runner-set'
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "11"
cuda-minor-version: "7"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda11-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'cublas'
cuda-major-version: "12"
cuda-minor-version: "0"
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-cublas-cuda12-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"
- build-type: 'vulkan'
platforms: 'linux/amd64'
tag-latest: 'false'
tag-suffix: '-vulkan-ffmpeg-core'
latest-image: 'latest-vulkan-ffmpeg-core'
ffmpeg: 'true'
image-type: 'core'
runs-on: 'arc-runner-set'
base-image: "ubuntu:22.04"
makeflags: "--jobs=4 --output-sync=target"

View File

@@ -23,7 +23,7 @@ on:
type: string
cuda-minor-version:
description: 'CUDA minor version'
default: "9"
default: "4"
type: string
platforms:
description: 'Platforms'
@@ -33,13 +33,25 @@ on:
description: 'Tag latest'
default: ''
type: string
latest-image:
description: 'Tag latest'
default: ''
type: string
latest-image-aio:
description: 'Tag latest'
default: ''
type: string
tag-suffix:
description: 'Tag suffix'
default: ''
type: string
skip-drivers:
description: 'Skip drivers by default'
default: 'false'
ffmpeg:
description: 'FFMPEG'
default: ''
type: string
image-type:
description: 'Image type'
default: ''
type: string
runs-on:
description: 'Runs on'
@@ -51,15 +63,10 @@ on:
required: false
default: '--jobs=4 --output-sync=target'
type: string
ubuntu-version:
description: 'Ubuntu version'
aio:
description: 'AIO Image Name'
required: false
default: '2204'
type: string
ubuntu-codename:
description: 'Ubuntu codename'
required: false
default: 'noble'
default: ''
type: string
secrets:
dockerUsername:
@@ -74,22 +81,6 @@ jobs:
reusable_image-build:
runs-on: ${{ inputs.runs-on }}
steps:
- name: Free Disk Space (Ubuntu)
if: inputs.runs-on == 'ubuntu-latest'
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Force Install GIT latest
run: |
sudo apt-get update \
@@ -99,7 +90,7 @@ jobs:
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Checkout
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Release space from worker
if: inputs.runs-on == 'ubuntu-latest'
@@ -111,8 +102,8 @@ jobs:
df -h
echo
sudo apt-get remove -y '^llvm-.*|^libllvm.*' || true
sudo apt-get remove --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get purge --auto-remove android-sdk-platform-tools snapd || true
sudo apt-get remove --auto-remove android-sdk-platform-tools || true
sudo apt-get purge --auto-remove android-sdk-platform-tools || true
sudo rm -rf /usr/local/lib/android
sudo apt-get remove -y '^dotnet-.*|^aspnetcore-.*' || true
sudo rm -rf /usr/share/dotnet
@@ -146,7 +137,7 @@ jobs:
- name: Docker meta
id: meta
if: github.event_name != 'pull_request'
uses: docker/metadata-action@v6
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai
@@ -157,21 +148,48 @@ jobs:
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }},onlatest=true
suffix=${{ inputs.tag-suffix }}
- name: Docker meta for PR
id: meta_pull_request
if: github.event_name == 'pull_request'
uses: docker/metadata-action@v6
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/ci-tests
ttl.sh/localai-ci-pr-${{ github.event.number }}
tags: |
type=ref,event=branch,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=semver,pattern={{raw}},suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=sha,suffix=localai${{ github.event.number }}-${{ inputs.build-type }}-${{ inputs.cuda-major-version }}-${{ inputs.cuda-minor-version }}
type=ref,event=branch
type=semver,pattern={{raw}}
type=sha
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.tag-suffix }}
- name: Docker meta AIO (quay.io)
if: inputs.aio != ''
id: meta_aio
uses: docker/metadata-action@v5
with:
images: |
quay.io/go-skynet/local-ai
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
latest=${{ inputs.tag-latest }}
suffix=${{ inputs.aio }}
- name: Docker meta AIO (dockerhub)
if: inputs.aio != ''
id: meta_aio_dockerhub
uses: docker/metadata-action@v5
with:
images: |
localai/localai
tags: |
type=ref,event=branch
type=semver,pattern={{raw}}
flavor: |
suffix=${{ inputs.aio }}
- name: Set up QEMU
uses: docker/setup-qemu-action@master
with:
@@ -183,21 +201,21 @@ jobs:
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v4
uses: docker/login-action@v3
with:
username: ${{ secrets.dockerUsername }}
password: ${{ secrets.dockerPassword }}
- name: Login to DockerHub
if: github.event_name != 'pull_request'
uses: docker/login-action@v4
uses: docker/login-action@v3
with:
registry: quay.io
username: ${{ secrets.quayUsername }}
password: ${{ secrets.quayPassword }}
- name: Build and push
uses: docker/build-push-action@v7
uses: docker/build-push-action@v6
if: github.event_name != 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
@@ -209,14 +227,13 @@ jobs:
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
FFMPEG=${{ inputs.ffmpeg }}
IMAGE_TYPE=${{ inputs.image-type }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
context: .
file: ./Dockerfile
cache-from: type=gha
@@ -226,7 +243,7 @@ jobs:
labels: ${{ steps.meta.outputs.labels }}
### Start testing image
- name: Build and push
uses: docker/build-push-action@v7
uses: docker/build-push-action@v6
if: github.event_name == 'pull_request'
with:
builder: ${{ steps.buildx.outputs.name }}
@@ -238,22 +255,81 @@ jobs:
BUILD_TYPE=${{ inputs.build-type }}
CUDA_MAJOR_VERSION=${{ inputs.cuda-major-version }}
CUDA_MINOR_VERSION=${{ inputs.cuda-minor-version }}
FFMPEG=${{ inputs.ffmpeg }}
IMAGE_TYPE=${{ inputs.image-type }}
BASE_IMAGE=${{ inputs.base-image }}
GRPC_BASE_IMAGE=${{ inputs.grpc-base-image || inputs.base-image }}
GRPC_MAKEFLAGS=--jobs=4 --output-sync=target
GRPC_VERSION=v1.65.0
MAKEFLAGS=${{ inputs.makeflags }}
SKIP_DRIVERS=${{ inputs.skip-drivers }}
UBUNTU_VERSION=${{ inputs.ubuntu-version }}
UBUNTU_CODENAME=${{ inputs.ubuntu-codename }}
context: .
file: ./Dockerfile
cache-from: type=gha
platforms: ${{ inputs.platforms }}
#push: true
push: true
tags: ${{ steps.meta_pull_request.outputs.tags }}
labels: ${{ steps.meta_pull_request.outputs.labels }}
- name: Testing image
if: github.event_name == 'pull_request'
run: |
echo "Image is available at ttl.sh/localai-ci-pr-${{ github.event.number }}:${{ steps.meta_pull_request.outputs.version }}" >> $GITHUB_STEP_SUMMARY
## End testing image
- name: Build and push AIO image
if: inputs.aio != ''
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile.aio
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta_aio.outputs.tags }}
labels: ${{ steps.meta_aio.outputs.labels }}
- name: Build and push AIO image (dockerhub)
if: inputs.aio != ''
uses: docker/build-push-action@v6
with:
builder: ${{ steps.buildx.outputs.name }}
build-args: |
BASE_IMAGE=localai/localai:${{ steps.meta.outputs.version }}
MAKEFLAGS=${{ inputs.makeflags }}
context: .
file: ./Dockerfile.aio
platforms: ${{ inputs.platforms }}
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta_aio_dockerhub.outputs.tags }}
labels: ${{ steps.meta_aio_dockerhub.outputs.labels }}
- name: Latest tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta.outputs.version }}
docker tag localai/localai:${{ steps.meta.outputs.version }} localai/localai:${{ inputs.latest-image }}
docker push localai/localai:${{ inputs.latest-image }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image }}
- name: Latest AIO tag
# run this on branches, when it is a tag and there is a latest-image defined
if: github.event_name != 'pull_request' && inputs.latest-image-aio != '' && github.ref_type == 'tag'
run: |
docker pull localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }}
docker tag localai/localai:${{ steps.meta_aio_dockerhub.outputs.version }} localai/localai:${{ inputs.latest-image-aio }}
docker push localai/localai:${{ inputs.latest-image-aio }}
docker pull quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }}
docker tag quay.io/go-skynet/local-ai:${{ steps.meta_aio.outputs.version }} quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
docker push quay.io/go-skynet/local-ai:${{ inputs.latest-image-aio }}
- name: job summary
run: |
echo "Built image: ${{ steps.meta.outputs.labels }}" >> $GITHUB_STEP_SUMMARY
- name: job summary(AIO)
if: inputs.aio != ''
run: |
echo "Built image: ${{ steps.meta_aio.outputs.labels }}" >> $GITHUB_STEP_SUMMARY

View File

@@ -9,4 +9,4 @@ jobs:
pull-requests: write
runs-on: ubuntu-latest
steps:
- uses: actions/labeler@v6
- uses: actions/labeler@v5

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@@ -6,15 +6,14 @@ permissions:
contents: write
pull-requests: write
packages: read
issues: write # for Homebrew/actions/post-comment
actions: write # to dispatch publish workflow
jobs:
dependabot:
if: github.repository == 'mudler/LocalAI' && github.actor == 'localai-bot' && contains(github.event.pull_request.title, 'chore:')
runs-on: ubuntu-latest
if: ${{ github.actor == 'localai-bot' }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
uses: actions/checkout@v4
- name: Approve a PR if not already approved
run: |

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@@ -1,29 +1,24 @@
name: Notifications for new models
on:
pull_request_target:
pull_request:
types:
- closed
permissions:
contents: read
pull-requests: read
jobs:
notify-discord:
if: github.repository == 'mudler/LocalAI' && (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model'))
if: ${{ (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model')) }}
env:
MODEL_NAME: gemma-3-12b-it-qat
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
ref: ${{ github.event.pull_request.head.sha }} # Checkout the PR head to get the actual changes
- uses: mudler/localai-github-action@v1
with:
model: 'gemma-3-12b-it-qat' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.8.1
- uses: GrantBirki/git-diff-action@v2.7.0
id: git-diff-action
with:
json_diff_file_output: diff.json
@@ -84,28 +79,27 @@ jobs:
args: ${{ steps.summarize.outputs.message }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
notify-twitter:
if: github.repository == 'mudler/LocalAI' && (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model'))
if: ${{ (github.event.pull_request.merged == true) && (contains(github.event.pull_request.labels.*.name, 'area/ai-model')) }}
env:
MODEL_NAME: gemma-3-12b-it-qat
MODEL_NAME: hermes-2-theta-llama-3-8b
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
with:
fetch-depth: 0 # needed to checkout all branches for this Action to work
ref: ${{ github.event.pull_request.head.sha }} # Checkout the PR head to get the actual changes
- name: Start LocalAI
run: |
echo "Starting LocalAI..."
docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master run --debug $MODEL_NAME
docker run -e -ti -d --name local-ai -p 8080:8080 localai/localai:master-ffmpeg-core run --debug $MODEL_NAME
until [ "`docker inspect -f {{.State.Health.Status}} local-ai`" == "healthy" ]; do echo "Waiting for container to be ready"; docker logs --tail 10 local-ai; sleep 2; done
# Check the PR diff using the current branch and the base branch of the PR
- uses: GrantBirki/git-diff-action@v2.8.1
- uses: GrantBirki/git-diff-action@v2.7.0
id: git-diff-action
with:
json_diff_file_output: diff.json
@@ -167,7 +161,7 @@ jobs:
TWITTER_ACCESS_TOKEN_SECRET: ${{ secrets.TWITTER_ACCESS_TOKEN_SECRET }}
- name: Setup tmate session if fails
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -6,17 +6,15 @@ on:
jobs:
notify-discord:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
env:
RELEASE_BODY: ${{ github.event.release.body }}
RELEASE_TITLE: ${{ github.event.release.name }}
RELEASE_TAG_NAME: ${{ github.event.release.tag_name }}
MODEL_NAME: gemma-3-12b-it-qat
steps:
- uses: mudler/localai-github-action@v1
with:
model: 'gemma-3-12b-it-qat' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
model: 'hermes-2-theta-llama-3-8b' # Any from models.localai.io, or from huggingface.com with: "huggingface://<repository>/file"
- name: Summarize
id: summarize
run: |
@@ -62,4 +60,4 @@ jobs:
DISCORD_AVATAR: "https://avatars.githubusercontent.com/u/139863280?v=4"
uses: Ilshidur/action-discord@master
with:
args: ${{ steps.summarize.outputs.message }}
args: ${{ steps.summarize.outputs.message }}

View File

@@ -1,64 +1,357 @@
name: goreleaser
name: Build and Release
on:
push:
branches:
- master
tags:
- 'v*'
pull_request:
env:
GRPC_VERSION: v1.65.0
permissions:
contents: write
concurrency:
group: ci-releases-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
goreleaser:
build-linux-arm:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
- name: Clone
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
submodules: true
- uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Run GoReleaser
uses: goreleaser/goreleaser-action@v7
with:
version: v2.11.0
args: release --clean
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
launcher-build-darwin:
runs-on: macos-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for macOS ARM64
run: |
make build-launcher-darwin
- name: Upload DMG to Release
uses: softprops/action-gh-release@v3
with:
files: ./dist/LocalAI.dmg
launcher-build-linux:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@v6
with:
fetch-depth: 0
- name: Set up Go
uses: actions/setup-go@v5
with:
go-version: 1.23
- name: Build launcher for Linux
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install golang gcc libgl1-mesa-dev xorg-dev libxkbcommon-dev
make build-launcher-linux
- name: Upload Linux launcher artifacts
uses: softprops/action-gh-release@v3
sudo apt-get install build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk
sudo apt-get install -qy binutils-aarch64-linux-gnu gcc-aarch64-linux-gnu g++-aarch64-linux-gnu libgmock-dev
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/cross-linux-aarch64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-cross-aarch64 cuda-nvcc-cross-aarch64-${CUDA_VERSION} libcublas-cross-aarch64-${CUDA_VERSION}
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
files: ./local-ai-launcher-linux.tar.xz
path: grpc
key: ${{ runner.os }}-arm-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
# https://cmake.org/cmake/help/v3.13/manual/cmake-toolchains.7.html#cross-compiling-for-linux
echo "set(CMAKE_SYSTEM_NAME Linux)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSTEM_PROCESSOR arm)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_STAGING_PREFIX $CROSS_STAGING_PREFIX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_SYSROOT ${CROSS_TOOLCHAIN}/sysroot)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_C_COMPILER /usr/bin/$C_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_CXX_COMPILER /usr/bin/$CXX_COMPILER_ARM_LINUX)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN && \
echo "set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY)" >> $CMAKE_CROSS_TOOLCHAIN
GRPC_DIR=$PWD/grpc
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install && \
GRPC_CROSS_BUILD_DIR=$GRPC_DIR/cmake/cross_build && \
mkdir -p $GRPC_CROSS_BUILD_DIR && \
cd $GRPC_CROSS_BUILD_DIR && \
cmake -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_INSTALL_PREFIX=$CROSS_TOOLCHAIN/grpc_install \
../.. && \
sudo make -j`nproc` install
- name: Build
id: build
run: |
GNU_HOST=aarch64-linux-gnu
C_COMPILER_ARM_LINUX=$GNU_HOST-gcc
CXX_COMPILER_ARM_LINUX=$GNU_HOST-g++
CROSS_TOOLCHAIN=/usr/$GNU_HOST
CROSS_STAGING_PREFIX=$CROSS_TOOLCHAIN/stage
CMAKE_CROSS_TOOLCHAIN=/tmp/arm.toolchain.cmake
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
sudo rm -rf /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp -rf /usr/aarch64-linux-gnu/lib/libstdc++.so* /usr/aarch64-linux-gnu/lib/libstdc++.so.6
sudo cp /usr/aarch64-linux-gnu/lib/ld-linux-aarch64.so.1 ld.so
BACKEND_LIBS="./grpc/cmake/cross_build/third_party/re2/libre2.a ./grpc/cmake/cross_build/libgrpc.a ./grpc/cmake/cross_build/libgrpc++.a ./grpc/cmake/cross_build/third_party/protobuf/libprotobuf.a /usr/aarch64-linux-gnu/lib/libc.so.6 /usr/aarch64-linux-gnu/lib/libstdc++.so.6 /usr/aarch64-linux-gnu/lib/libgomp.so.1 /usr/aarch64-linux-gnu/lib/libm.so.6 /usr/aarch64-linux-gnu/lib/libgcc_s.so.1 /usr/aarch64-linux-gnu/lib/libdl.so.2 /usr/aarch64-linux-gnu/lib/libpthread.so.0 ./ld.so" \
GOOS=linux \
GOARCH=arm64 \
CMAKE_ARGS="-DProtobuf_INCLUDE_DIRS=$CROSS_STAGING_PREFIX/include -DProtobuf_DIR=$CROSS_STAGING_PREFIX/lib/cmake/protobuf -DgRPC_DIR=$CROSS_STAGING_PREFIX/lib/cmake/grpc -DCMAKE_TOOLCHAIN_FILE=$CMAKE_CROSS_TOOLCHAIN -DCMAKE_C_COMPILER=aarch64-linux-gnu-gcc -DCMAKE_CXX_COMPILER=aarch64-linux-gnu-g++" make dist-cross-linux-arm64
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-linux:
runs-on: arc-runner-set
steps:
- name: Force Install GIT latest
run: |
sudo apt-get update \
&& sudo apt-get install -y software-properties-common \
&& sudo apt-get update \
&& sudo add-apt-repository -y ppa:git-core/ppa \
&& sudo apt-get update \
&& sudo apt-get install -y git
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y wget curl build-essential ffmpeg protobuf-compiler ccache upx-ucl gawk cmake libgmock-dev
- name: Intel Dependencies
run: |
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null
echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
sudo apt update
sudo apt install -y intel-basekit
- name: Install CUDA Dependencies
run: |
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
env:
CUDA_VERSION: 12-5
- name: "Install Hipblas"
env:
ROCM_VERSION: "6.1"
AMDGPU_VERSION: "6.1"
run: |
set -ex
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends ca-certificates curl libnuma-dev gnupg
curl -sL https://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
printf "deb [arch=amd64] https://repo.radeon.com/rocm/apt/$ROCM_VERSION/ jammy main" | sudo tee /etc/apt/sources.list.d/rocm.list
printf "deb [arch=amd64] https://repo.radeon.com/amdgpu/$AMDGPU_VERSION/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
printf 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
sudo apt-get update
sudo DEBIAN_FRONTEND=noninteractive apt-get install -y \
hipblas-dev rocm-dev \
rocblas-dev
sudo apt-get clean
sudo rm -rf /var/lib/apt/lists/*
sudo ldconfig
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && \
cd cmake/build && cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5 --output-sync=target
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 --output-sync=target install
# BACKEND_LIBS needed for gpu-workload: /opt/intel/oneapi/*/lib/libiomp5.so /opt/intel/oneapi/*/lib/libmkl_core.so /opt/intel/oneapi/*/lib/libmkl_core.so.2 /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so /opt/intel/oneapi/*/lib/libmkl_intel_ilp64.so.2 /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so /opt/intel/oneapi/*/lib/libmkl_sycl_blas.so.4 /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so /opt/intel/oneapi/*/lib/libmkl_tbb_thread.so.2 /opt/intel/oneapi/*/lib/libsycl.so /opt/intel/oneapi/*/lib/libsycl.so.7 /opt/intel/oneapi/*/lib/libsycl.so.7.1.0 /opt/rocm-*/lib/libamdhip64.so /opt/rocm-*/lib/libamdhip64.so.5 /opt/rocm-*/lib/libamdhip64.so.6 /opt/rocm-*/lib/libamdhip64.so.6.1.60100 /opt/rocm-*/lib/libhipblas.so /opt/rocm-*/lib/libhipblas.so.2 /opt/rocm-*/lib/libhipblas.so.2.1.60100 /opt/rocm-*/lib/librocblas.so /opt/rocm-*/lib/librocblas.so.4 /opt/rocm-*/lib/librocblas.so.4.1.60100 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1 /usr/lib/x86_64-linux-gnu/libOpenCL.so.1.0.0 /usr/lib/x86_64-linux-gnu/libm.so.6 /usr/lib/x86_64-linux-gnu/libgcc_s.so.1 /usr/lib/x86_64-linux-gnu/libc.so.6 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/local/cuda-*/targets/x86_64-linux/lib/libcublas.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcublasLt.so /usr/local/cuda-*/targets/x86_64-linux/lib/libcudart.so /usr/local/cuda-*/targets/x86_64-linux/lib/stubs/libcuda.so
- name: Build
id: build
run: |
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
export PATH=$PATH:$GOPATH/bin
export PATH=/usr/local/cuda/bin:$PATH
export PATH=/opt/rocm/bin:$PATH
source /opt/intel/oneapi/setvars.sh
sudo cp /lib64/ld-linux-x86-64.so.2 ld.so
BACKEND_LIBS="./ld.so ./sources/go-piper/piper/build/fi/lib/libfmt.a ./sources/go-piper/piper-phonemize/pi/lib/libonnxruntime.so.1.14.1 ./sources/go-piper/piper-phonemize/pi/src/libespeak-ng/libespeak-ng.so /usr/lib/x86_64-linux-gnu/libdl.so.2 /usr/lib/x86_64-linux-gnu/librt.so.1 /usr/lib/x86_64-linux-gnu/libpthread.so.0 ./sources/go-piper/piper-phonemize/pi/lib/libpiper_phonemize.so.1 ./sources/go-piper/piper/build/si/lib/libspdlog.a ./sources/go-piper/espeak/ei/lib/libucd.so" \
make -j4 dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-linux
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-stablediffusion:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends libopencv-dev protobuf-compiler ccache upx-ucl
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build stablediffusion
run: |
export PATH=$PATH:$GOPATH/bin
make backend-assets/grpc/stablediffusion
mkdir -p release && cp backend-assets/grpc/stablediffusion release
env:
GO_TAGS: stablediffusion
- uses: actions/upload-artifact@v4
with:
name: stablediffusion
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
build-macOS-x86_64:
runs-on: macos-13
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@8ba23be9613c672d40ae261d2a1335d639bdd59b
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.0
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-x86_64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
build-macOS-arm64:
runs-on: macos-14
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- uses: actions/setup-go@v5
with:
go-version: '1.21.x'
cache: false
- name: Dependencies
run: |
brew install protobuf grpc
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
- name: Build
id: build
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export PATH=$PATH:$GOPATH/bin
make dist
- uses: actions/upload-artifact@v4
with:
name: LocalAI-MacOS-arm64
path: release/
- name: Release
uses: softprops/action-gh-release@v2
if: startsWith(github.ref, 'refs/tags/')
with:
files: |
release/*
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -14,17 +14,17 @@ jobs:
GO111MODULE: on
steps:
- name: Checkout Source
uses: actions/checkout@v6
uses: actions/checkout@v4
if: ${{ github.actor != 'dependabot[bot]' }}
- name: Run Gosec Security Scanner
if: ${{ github.actor != 'dependabot[bot]' }}
uses: securego/gosec@v2.22.9
uses: securego/gosec@master
with:
# we let the report trigger content trigger a failure using the GitHub Security features.
args: '-no-fail -fmt sarif -out results.sarif ./...'
- name: Upload SARIF file
if: ${{ github.actor != 'dependabot[bot]' }}
uses: github/codeql-action/upload-sarif@v4
uses: github/codeql-action/upload-sarif@v3
with:
# Path to SARIF file relative to the root of the repository
sarif_file: results.sarif

View File

@@ -1,25 +0,0 @@
name: 'Close stale issues and PRs'
permissions:
issues: write
pull-requests: write
on:
schedule:
- cron: '30 1 * * *'
jobs:
stale:
if: github.repository == 'mudler/LocalAI'
runs-on: ubuntu-latest
steps:
- uses: actions/stale@b5d41d4e1d5dceea10e7104786b73624c18a190f # v9
with:
stale-issue-message: 'This issue is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 5 days.'
stale-pr-message: 'This PR is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 10 days.'
close-issue-message: 'This issue was closed because it has been stalled for 5 days with no activity.'
close-pr-message: 'This PR was closed because it has been stalled for 10 days with no activity.'
days-before-issue-stale: 90
days-before-pr-stale: 90
days-before-issue-close: 5
days-before-pr-close: 10
exempt-issue-labels: 'roadmap'
exempt-pr-labels: 'roadmap'

View File

@@ -14,74 +14,11 @@ concurrency:
cancel-in-progress: true
jobs:
detect-changes:
runs-on: ubuntu-latest
outputs:
run-all: ${{ steps.detect.outputs.run-all }}
transformers: ${{ steps.detect.outputs.transformers }}
rerankers: ${{ steps.detect.outputs.rerankers }}
diffusers: ${{ steps.detect.outputs.diffusers }}
coqui: ${{ steps.detect.outputs.coqui }}
moonshine: ${{ steps.detect.outputs.moonshine }}
pocket-tts: ${{ steps.detect.outputs.pocket-tts }}
qwen-tts: ${{ steps.detect.outputs.qwen-tts }}
qwen-asr: ${{ steps.detect.outputs.qwen-asr }}
nemo: ${{ steps.detect.outputs.nemo }}
voxcpm: ${{ steps.detect.outputs.voxcpm }}
llama-cpp-quantization: ${{ steps.detect.outputs.llama-cpp-quantization }}
llama-cpp: ${{ steps.detect.outputs.llama-cpp }}
ik-llama-cpp: ${{ steps.detect.outputs.ik-llama-cpp }}
turboquant: ${{ steps.detect.outputs.turboquant }}
vllm: ${{ steps.detect.outputs.vllm }}
sglang: ${{ steps.detect.outputs.sglang }}
acestep-cpp: ${{ steps.detect.outputs.acestep-cpp }}
qwen3-tts-cpp: ${{ steps.detect.outputs.qwen3-tts-cpp }}
voxtral: ${{ steps.detect.outputs.voxtral }}
kokoros: ${{ steps.detect.outputs.kokoros }}
insightface: ${{ steps.detect.outputs.insightface }}
steps:
- name: Checkout repository
uses: actions/checkout@v6
- name: Setup Bun
uses: oven-sh/setup-bun@v2
- name: Install dependencies
run: bun add js-yaml @octokit/core
- name: Detect changed backends
id: detect
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_EVENT_PATH: ${{ github.event_path }}
run: bun run scripts/changed-backends.js
# Requires CUDA
# tests-chatterbox-tts:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test chatterbox-tts
# run: |
# make --jobs=5 --output-sync=target -C backend/python/chatterbox
# make --jobs=5 --output-sync=target -C backend/python/chatterbox test
tests-transformers:
needs: detect-changes
if: needs.detect-changes.outputs.transformers == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -98,13 +35,35 @@ jobs:
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers
make --jobs=5 --output-sync=target -C backend/python/transformers test
tests-rerankers:
needs: detect-changes
if: needs.detect-changes.outputs.rerankers == 'true' || needs.detect-changes.outputs.run-all == 'true'
tests-sentencetransformers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test sentencetransformers
run: |
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers
make --jobs=5 --output-sync=target -C backend/python/sentencetransformers test
tests-rerankers:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -123,12 +82,10 @@ jobs:
make --jobs=5 --output-sync=target -C backend/python/rerankers test
tests-diffusers:
needs: detect-changes
if: needs.detect-changes.outputs.diffusers == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
@@ -145,47 +102,71 @@ jobs:
make --jobs=5 --output-sync=target -C backend/python/diffusers
make --jobs=5 --output-sync=target -C backend/python/diffusers test
#tests-vllm:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install -y build-essential ffmpeg
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test vllm backend
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
# tests-transformers-musicgen:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install build-essential ffmpeg
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# sudo apt-get install -y libopencv-dev
# pip install --user --no-cache-dir grpcio-tools==1.64.1
tests-parler-tts:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test transformers-musicgen
# run: |
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
# make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
- name: Test parler-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/parler-tts
make --jobs=5 --output-sync=target -C backend/python/parler-tts test
tests-openvoice:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test openvoice
run: |
make --jobs=5 --output-sync=target -C backend/python/openvoice
make --jobs=5 --output-sync=target -C backend/python/openvoice test
tests-transformers-musicgen:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test transformers-musicgen
run: |
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen
make --jobs=5 --output-sync=target -C backend/python/transformers-musicgen test
# tests-bark:
# runs-on: ubuntu-latest
@@ -231,7 +212,7 @@ jobs:
# sudo rm -rf "$AGENT_TOOLSDIRECTORY" || true
# df -h
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -256,7 +237,7 @@ jobs:
# runs-on: ubuntu-latest
# steps:
# - name: Clone
# uses: actions/checkout@v6
# uses: actions/checkout@v4
# with:
# submodules: true
# - name: Dependencies
@@ -272,20 +253,38 @@ jobs:
# run: |
# make --jobs=5 --output-sync=target -C backend/python/vllm
# make --jobs=5 --output-sync=target -C backend/python/vllm test
tests-coqui:
needs: detect-changes
if: needs.detect-changes.outputs.coqui == 'true' || needs.detect-changes.outputs.run-all == 'true'
tests-vallex:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install build-essential ffmpeg
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
sudo apt-get install -y libopencv-dev
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test vall-e-x
run: |
make --jobs=5 --output-sync=target -C backend/python/vall-e-x
make --jobs=5 --output-sync=target -C backend/python/vall-e-x test
tests-coqui:
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch espeak espeak-ng python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
@@ -294,487 +293,3 @@ jobs:
run: |
make --jobs=5 --output-sync=target -C backend/python/coqui
make --jobs=5 --output-sync=target -C backend/python/coqui test
tests-moonshine:
needs: detect-changes
if: needs.detect-changes.outputs.moonshine == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test moonshine
run: |
make --jobs=5 --output-sync=target -C backend/python/moonshine
make --jobs=5 --output-sync=target -C backend/python/moonshine test
tests-pocket-tts:
needs: detect-changes
if: needs.detect-changes.outputs.pocket-tts == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test pocket-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/pocket-tts
make --jobs=5 --output-sync=target -C backend/python/pocket-tts test
tests-qwen-tts:
needs: detect-changes
if: needs.detect-changes.outputs.qwen-tts == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test qwen-tts
run: |
make --jobs=5 --output-sync=target -C backend/python/qwen-tts
make --jobs=5 --output-sync=target -C backend/python/qwen-tts test
# TODO: s2-pro model is too large to load on CPU-only CI runners — re-enable
# when we have GPU runners or a smaller test model.
# tests-fish-speech:
# runs-on: ubuntu-latest
# timeout-minutes: 45
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install -y build-essential ffmpeg portaudio19-dev
# sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# # Install UV
# curl -LsSf https://astral.sh/uv/install.sh | sh
# pip install --user --no-cache-dir grpcio-tools==1.64.1
# - name: Test fish-speech
# run: |
# make --jobs=5 --output-sync=target -C backend/python/fish-speech
# make --jobs=5 --output-sync=target -C backend/python/fish-speech test
tests-qwen-asr:
needs: detect-changes
if: needs.detect-changes.outputs.qwen-asr == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg sox
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test qwen-asr
run: |
make --jobs=5 --output-sync=target -C backend/python/qwen-asr
make --jobs=5 --output-sync=target -C backend/python/qwen-asr test
tests-nemo:
needs: detect-changes
if: needs.detect-changes.outputs.nemo == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential ffmpeg sox
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test nemo
run: |
make --jobs=5 --output-sync=target -C backend/python/nemo
make --jobs=5 --output-sync=target -C backend/python/nemo test
tests-voxcpm:
needs: detect-changes
if: needs.detect-changes.outputs.voxcpm == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install build-essential ffmpeg
sudo apt-get install -y ca-certificates cmake curl patch python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test voxcpm
run: |
make --jobs=5 --output-sync=target -C backend/python/voxcpm
make --jobs=5 --output-sync=target -C backend/python/voxcpm test
tests-llama-cpp-quantization:
needs: detect-changes
if: needs.detect-changes.outputs.llama-cpp-quantization == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 30
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake curl git python3-pip
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Build llama-quantize from llama.cpp
run: |
git clone --depth 1 https://github.com/ggml-org/llama.cpp.git /tmp/llama.cpp
cmake -B /tmp/llama.cpp/build -S /tmp/llama.cpp -DGGML_NATIVE=OFF
cmake --build /tmp/llama.cpp/build --target llama-quantize -j$(nproc)
sudo cp /tmp/llama.cpp/build/bin/llama-quantize /usr/local/bin/
- name: Install backend
run: |
make --jobs=5 --output-sync=target -C backend/python/llama-cpp-quantization
- name: Test llama-cpp-quantization
run: |
make --jobs=5 --output-sync=target -C backend/python/llama-cpp-quantization test
tests-llama-cpp-grpc:
needs: detect-changes
if: needs.detect-changes.outputs.llama-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build llama-cpp backend image and run gRPC e2e tests
run: |
make test-extra-backend-llama-cpp
tests-llama-cpp-grpc-transcription:
needs: detect-changes
if: needs.detect-changes.outputs.llama-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build llama-cpp backend image and run audio transcription gRPC e2e tests
run: |
make test-extra-backend-llama-cpp-transcription
tests-ik-llama-cpp-grpc:
needs: detect-changes
if: needs.detect-changes.outputs.ik-llama-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
- name: Build ik-llama-cpp backend image and run gRPC e2e tests
run: |
make test-extra-backend-ik-llama-cpp
tests-turboquant-grpc:
needs: detect-changes
if: needs.detect-changes.outputs.turboquant == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.25.4'
# Exercises the turboquant (llama.cpp fork) backend with KV-cache
# quantization enabled. The convenience target sets
# BACKEND_TEST_CACHE_TYPE_K / _V=q8_0, which are plumbed into the
# ModelOptions.CacheTypeKey/Value gRPC fields. LoadModel-success +
# backend stdout/stderr (captured by the Ginkgo suite) prove the
# cache-type config path reaches the fork's KV-cache init.
- name: Build turboquant backend image and run gRPC e2e tests
run: |
make test-extra-backend-turboquant
# tests-vllm-grpc is currently disabled in CI.
#
# The prebuilt vllm CPU wheel is compiled with AVX-512 VNNI/BF16
# instructions, and neither ubuntu-latest nor the bigger-runner pool
# offers a stable CPU baseline that supports them — runners come
# back with different hardware between runs and SIGILL on import of
# vllm.model_executor.models.registry. Compiling vllm from source
# via FROM_SOURCE=true works on any CPU but takes 30-50 minutes per
# run, which is too slow for a smoke test.
#
# The test itself (tests/e2e-backends + make test-extra-backend-vllm)
# is fully working and validated locally on a host with the right
# SIMD baseline. Run it manually with:
#
# make test-extra-backend-vllm
#
# Re-enable this job once we have a self-hosted runner label with
# guaranteed AVX-512 VNNI/BF16 support, or once the vllm project
# publishes a CPU wheel with a wider baseline.
#
# tests-vllm-grpc:
# needs: detect-changes
# if: needs.detect-changes.outputs.vllm == 'true' || needs.detect-changes.outputs.run-all == 'true'
# runs-on: bigger-runner
# timeout-minutes: 90
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install -y --no-install-recommends \
# make build-essential curl unzip ca-certificates git tar
# - name: Setup Go
# uses: actions/setup-go@v5
# with:
# go-version: '1.25.4'
# - name: Free disk space
# run: |
# sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /opt/hostedtoolcache/CodeQL || true
# df -h
# - name: Build vllm (cpu) backend image and run gRPC e2e tests
# run: |
# make test-extra-backend-vllm
# tests-sglang-grpc is currently disabled in CI for the same reason as
# tests-vllm-grpc: sglang's CPU kernel (sgl-kernel) uses __m512 AVX-512
# intrinsics unconditionally in shm.cpp, so the from-source build
# requires `-march=sapphirerapids` (already set in install.sh) and the
# resulting binary SIGILLs at import on CPUs without AVX-512 VNNI/BF16.
# The ubuntu-latest runner pool does not guarantee that ISA baseline.
#
# The test itself (tests/e2e-backends + make test-extra-backend-sglang)
# is fully working and validated locally on a host with the right
# SIMD baseline. Run it manually with:
#
# make test-extra-backend-sglang
#
# Re-enable this job once we have a self-hosted runner label with
# guaranteed AVX-512 VNNI/BF16 support.
#
# tests-sglang-grpc:
# needs: detect-changes
# if: needs.detect-changes.outputs.sglang == 'true' || needs.detect-changes.outputs.run-all == 'true'
# runs-on: bigger-runner
# timeout-minutes: 90
# steps:
# - name: Clone
# uses: actions/checkout@v6
# with:
# submodules: true
# - name: Dependencies
# run: |
# sudo apt-get update
# sudo apt-get install -y --no-install-recommends \
# make build-essential curl unzip ca-certificates git tar
# - name: Setup Go
# uses: actions/setup-go@v5
# with:
# go-version: '1.25.4'
# - name: Free disk space
# run: |
# sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /opt/hostedtoolcache/CodeQL || true
# df -h
# - name: Build sglang (cpu) backend image and run gRPC e2e tests
# run: |
# make test-extra-backend-sglang
tests-acestep-cpp:
needs: detect-changes
if: needs.detect-changes.outputs.acestep-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake curl libopenblas-dev ffmpeg
- name: Setup Go
uses: actions/setup-go@v5
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build acestep-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/acestep-cpp
- name: Test acestep-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/acestep-cpp test
tests-qwen3-tts-cpp:
needs: detect-changes
if: needs.detect-changes.outputs.qwen3-tts-cpp == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake curl libopenblas-dev ffmpeg
- name: Setup Go
uses: actions/setup-go@v5
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build qwen3-tts-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/qwen3-tts-cpp
- name: Test qwen3-tts-cpp
run: |
make --jobs=5 --output-sync=target -C backend/go/qwen3-tts-cpp test
tests-voxtral:
needs: detect-changes
if: needs.detect-changes.outputs.voxtral == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake curl libopenblas-dev ffmpeg
- name: Setup Go
uses: actions/setup-go@v5
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Build voxtral
run: |
make --jobs=5 --output-sync=target -C backend/go/voxtral
- name: Test voxtral
run: |
make --jobs=5 --output-sync=target -C backend/go/voxtral test
tests-kokoros:
needs: detect-changes
if: needs.detect-changes.outputs.kokoros == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential cmake pkg-config protobuf-compiler clang libclang-dev
sudo apt-get install -y espeak-ng libespeak-ng-dev libsonic-dev libpcaudio-dev libopus-dev libssl-dev
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
echo "$HOME/.cargo/bin" >> $GITHUB_PATH
- name: Build kokoros
run: |
make -C backend/rust/kokoros kokoros-grpc
- name: Test kokoros
run: |
make -C backend/rust/kokoros test
tests-insightface-grpc:
needs: detect-changes
if: needs.detect-changes.outputs.insightface == 'true' || needs.detect-changes.outputs.run-all == 'true'
runs-on: ubuntu-latest
timeout-minutes: 90
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
make build-essential curl unzip ca-certificates git tar
- name: Setup Go
uses: actions/setup-go@v5
with:
go-version: '1.26.0'
- name: Free disk space
run: |
sudo rm -rf /usr/share/dotnet /opt/ghc /usr/local/lib/android /opt/hostedtoolcache/CodeQL || true
df -h
- name: Build insightface backend image and run both model configurations
run: |
make test-extra-backend-insightface-all

View File

@@ -21,22 +21,8 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
go-version: ['1.26.x']
go-version: ['1.21.x']
steps:
- name: Free Disk Space (Ubuntu)
uses: jlumbroso/free-disk-space@main
with:
# this might remove tools that are actually needed,
# if set to "true" but frees about 6 GB
tool-cache: true
# all of these default to true, but feel free to set to
# "false" if necessary for your workflow
android: true
dotnet: true
haskell: true
large-packages: true
docker-images: true
swap-storage: true
- name: Release space from worker
run: |
echo "Listing top largest packages"
@@ -70,7 +56,7 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -81,42 +67,79 @@ jobs:
# You can test your matrix by printing the current Go version
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install curl ffmpeg libopus-dev
- name: Setup Node.js
uses: actions/setup-node@v6
sudo apt-get install build-essential ccache upx-ucl curl ffmpeg
sudo apt-get install -y libgmock-dev
curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
sudo install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring --fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" > /etc/apt/sources.list.d/conda.list' && \
sudo /bin/bash -c 'echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" | tee -a /etc/apt/sources.list.d/conda.list' && \
sudo apt-get update && \
sudo apt-get install -y conda
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
sudo apt-get install -y ca-certificates cmake patch python3-pip unzip
sudo apt-get install -y libopencv-dev
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get install -y cuda-nvcc-${CUDA_VERSION} libcublas-dev-${CUDA_VERSION}
export CUDACXX=/usr/local/cuda/bin/nvcc
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
# The python3-grpc-tools package in 22.04 is too old
pip install --user grpcio-tools
sudo rm -rfv /usr/bin/conda || true
PATH=$PATH:/opt/conda/bin make -C backend/python/sentencetransformers
# Pre-build piper before we start tests in order to have shared libraries in place
make sources/go-piper && \
GO_TAGS="tts" make -C sources/go-piper piper.o && \
sudo cp -rfv sources/go-piper/piper-phonemize/pi/lib/. /usr/lib/ && \
# Pre-build stable diffusion before we install a newer version of abseil (not compatible with stablediffusion-ncn)
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
env:
CUDA_VERSION: 12-4
- name: Cache grpc
id: cache-grpc
uses: actions/cache@v4
with:
node-version: '22'
- name: Build React UI
run: make react-ui
- name: Build backends
path: grpc
key: ${{ runner.os }}-grpc-${{ env.GRPC_VERSION }}
- name: Build grpc
if: steps.cache-grpc.outputs.cache-hit != 'true'
run: |
make backends/transformers
mkdir external && mv backends/transformers external/transformers
make backends/llama-cpp backends/local-store backends/silero-vad backends/piper backends/whisper backends/stablediffusion-ggml
git clone --recurse-submodules -b ${{ env.GRPC_VERSION }} --depth 1 --jobs 5 --shallow-submodules https://github.com/grpc/grpc && \
cd grpc && sed -i "216i\ TESTONLY" "third_party/abseil-cpp/absl/container/CMakeLists.txt" && mkdir -p cmake/build && cd cmake/build && \
cmake -DgRPC_INSTALL=ON \
-DgRPC_BUILD_TESTS=OFF \
../.. && sudo make --jobs 5
- name: Install gRPC
run: |
cd grpc && cd cmake/build && sudo make --jobs 5 install
- name: Test
run: |
TRANSFORMER_BACKEND=$PWD/external/transformers/run.sh PATH="$PATH:/root/go/bin" GO_TAGS="tts" make --jobs 5 --output-sync=target test
PATH="$PATH:/root/go/bin" GO_TAGS="stablediffusion tts" make --jobs 5 --output-sync=target test
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
tests-e2e-container:
tests-aio-container:
runs-on: ubuntu-latest
steps:
- name: Release space from worker
@@ -152,37 +175,33 @@ jobs:
sudo rm -rfv build || true
df -h
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Dependencies
- name: Build images
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
docker build --build-arg FFMPEG=true --build-arg IMAGE_TYPE=extras --build-arg EXTRA_BACKENDS=rerankers --build-arg MAKEFLAGS="--jobs=5 --output-sync=target" -t local-ai:tests -f Dockerfile .
BASE_IMAGE=local-ai:tests DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
- name: Test
run: |
PATH="$PATH:$HOME/go/bin" make backends/local-store backends/silero-vad backends/llama-cpp backends/whisper backends/piper backends/stablediffusion-ggml docker-build-e2e e2e-aio
LOCALAI_MODELS_DIR=$PWD/models LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio \
make run-e2e-aio
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true
tests-apple:
runs-on: macos-latest
runs-on: macOS-14
strategy:
matrix:
go-version: ['1.26.x']
go-version: ['1.21.x']
steps:
- name: Clone
uses: actions/checkout@v6
uses: actions/checkout@v4
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
@@ -195,30 +214,18 @@ jobs:
run: go version
- name: Dependencies
run: |
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc libomp llvm opus
pip install --user --no-cache-dir grpcio-tools grpcio
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: '22'
- name: Build React UI
run: make react-ui
- name: Build llama-cpp-darwin
run: |
make protogen-go
make backends/llama-cpp-darwin
brew install protobuf grpc make protoc-gen-go protoc-gen-go-grpc
pip install --user --no-cache-dir grpcio-tools==1.64.1
- name: Test
run: |
export C_INCLUDE_PATH=/usr/local/include
export CPLUS_INCLUDE_PATH=/usr/local/include
export CC=/opt/homebrew/opt/llvm/bin/clang
# Used to run the newer GNUMake version from brew that supports --output-sync
export PATH="/opt/homebrew/opt/make/libexec/gnubin:$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
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
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
uses: mxschmitt/action-tmate@v3.18
with:
detached: true
connect-timeout-seconds: 180

View File

@@ -1,62 +0,0 @@
---
name: 'E2E Backend Tests'
on:
pull_request:
push:
branches:
- master
tags:
- '*'
concurrency:
group: ci-tests-e2e-backend-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-e2e-backend:
runs-on: ubuntu-latest
strategy:
matrix:
go-version: ['1.25.x']
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
- name: Display Go version
run: go version
- name: Proto Dependencies
run: |
# Install protoc
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
PATH="$PATH:$HOME/go/bin" make protogen-go
- name: Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential libopus-dev
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: '22'
- name: Build React UI
run: make react-ui
- name: Test Backend E2E
run: |
PATH="$PATH:$HOME/go/bin" make build-mock-backend test-e2e
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -1,72 +0,0 @@
---
name: 'UI E2E Tests'
on:
pull_request:
paths:
- 'core/http/**'
- 'tests/e2e-ui/**'
- 'tests/e2e/mock-backend/**'
push:
branches:
- master
concurrency:
group: ci-tests-ui-e2e-${{ github.head_ref || github.ref }}-${{ github.repository }}
cancel-in-progress: true
jobs:
tests-ui-e2e:
runs-on: ubuntu-latest
strategy:
matrix:
go-version: ['1.26.x']
steps:
- name: Clone
uses: actions/checkout@v6
with:
submodules: true
- name: Setup Go ${{ matrix.go-version }}
uses: actions/setup-go@v5
with:
go-version: ${{ matrix.go-version }}
cache: false
- name: Setup Node.js
uses: actions/setup-node@v6
with:
node-version: '22'
- name: Proto Dependencies
run: |
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v26.1/protoc-26.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
- name: System Dependencies
run: |
sudo apt-get update
sudo apt-get install -y build-essential libopus-dev
- name: Build UI test server
run: PATH="$PATH:$HOME/go/bin" make build-ui-test-server
- name: Install Playwright
working-directory: core/http/react-ui
run: |
npm install
npx playwright install --with-deps chromium
- name: Run Playwright tests
working-directory: core/http/react-ui
run: npx playwright test
- name: Upload Playwright report
if: ${{ failure() }}
uses: actions/upload-artifact@v7
with:
name: playwright-report
path: core/http/react-ui/playwright-report/
retention-days: 7
- name: Setup tmate session if tests fail
if: ${{ failure() }}
uses: mxschmitt/action-tmate@v3.23
with:
detached: true
connect-timeout-seconds: 180
limit-access-to-actor: true

View File

@@ -5,12 +5,11 @@ on:
workflow_dispatch:
jobs:
swagger:
if: github.repository == 'mudler/LocalAI'
strategy:
fail-fast: false
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v6
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
with:
go-version: 'stable'
@@ -26,7 +25,7 @@ jobs:
run: |
make protogen-go swagger
- name: Create Pull Request
uses: peter-evans/create-pull-request@v8
uses: peter-evans/create-pull-request@v6
with:
token: ${{ secrets.UPDATE_BOT_TOKEN }}
push-to-fork: ci-forks/LocalAI

View File

@@ -8,7 +8,7 @@ jobs:
steps:
- name: 'Checkout'
uses: actions/checkout@master
- name: 'Yamllint model gallery'
- name: 'Yamllint'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'gallery'
@@ -16,11 +16,3 @@ jobs:
yamllint_comment: true
env:
GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: 'Yamllint Backend gallery'
uses: karancode/yamllint-github-action@master
with:
yamllint_file_or_dir: 'backend'
yamllint_strict: false
yamllint_comment: true
env:
GITHUB_ACCESS_TOKEN: ${{ secrets.GITHUB_TOKEN }}

30
.gitignore vendored
View File

@@ -2,30 +2,24 @@
/sources/
__pycache__/
*.a
*.o
get-sources
prepare-sources
/backend/cpp/llama-cpp/grpc-server
/backend/cpp/llama-cpp/llama.cpp
/backend/cpp/llama/grpc-server
/backend/cpp/llama/llama.cpp
/backend/cpp/llama-*
!backend/cpp/llama-cpp
/backends
/backend-images
/result.yaml
protoc
*.log
go-ggml-transformers
go-gpt2
go-rwkv
whisper.cpp
/bloomz
go-bert
# LocalAI build binary
LocalAI
/local-ai
/local-ai-launcher
local-ai
# prevent above rules from omitting the helm chart
!charts/*
# prevent above rules from omitting the api/localai folder
@@ -36,8 +30,6 @@ LocalAI
models/*
test-models/
test-dir/
tests/e2e-aio/backends
mock-backend
release/
@@ -64,16 +56,4 @@ docs/static/gallery.html
**/venv
# per-developer customization files for the development container
.devcontainer/customization/*
# React UI build artifacts (keep placeholder dist/index.html)
core/http/react-ui/node_modules/
core/http/react-ui/dist
# Extracted backend binaries for container-based testing
local-backends/
# UI E2E test artifacts
tests/e2e-ui/ui-test-server
core/http/react-ui/playwright-report/
core/http/react-ui/test-results/
.devcontainer/customization/*

6
.gitmodules vendored
View File

@@ -1,6 +1,6 @@
[submodule "docs/themes/hugo-theme-relearn"]
path = docs/themes/hugo-theme-relearn
url = https://github.com/McShelby/hugo-theme-relearn.git
[submodule "backend/rust/kokoros/sources/Kokoros"]
path = backend/rust/kokoros/sources/Kokoros
url = https://github.com/lucasjinreal/Kokoros
[submodule "docs/themes/lotusdocs"]
path = docs/themes/lotusdocs
url = https://github.com/colinwilson/lotusdocs

View File

@@ -1,37 +0,0 @@
version: 2
before:
hooks:
- make protogen-go
- make react-ui
- go mod tidy
dist: release
source:
enabled: true
name_template: '{{ .ProjectName }}-{{ .Tag }}-source'
builds:
- main: ./cmd/local-ai
env:
- CGO_ENABLED=0
ldflags:
- -s -w
- -X "github.com/mudler/LocalAI/internal.Version={{ .Tag }}"
- -X "github.com/mudler/LocalAI/internal.Commit={{ .FullCommit }}"
goos:
- linux
- darwin
#- windows
goarch:
- amd64
- arm64
ignore:
- goos: darwin
goarch: amd64
archives:
- formats: [ 'binary' ] # this removes the tar of the archives, leaving the binaries alone
name_template: local-ai-{{ .Tag }}-{{ .Os }}-{{ .Arch }}{{ if .Arm }}v{{ .Arm }}{{ end }}
checksum:
name_template: '{{ .ProjectName }}-{{ .Tag }}-checksums.txt'
snapshot:
version_template: "{{ .Tag }}-next"
changelog:
use: github-native

2
.vscode/launch.json vendored
View File

@@ -26,7 +26,7 @@
"LOCALAI_P2P": "true",
"LOCALAI_FEDERATED": "true"
},
"buildFlags": ["-tags", "", "-v"],
"buildFlags": ["-tags", "stablediffusion p2p tts", "-v"],
"envFile": "${workspaceFolder}/.env",
"cwd": "${workspaceRoot}"
}

View File

@@ -1,39 +0,0 @@
# LocalAI Agent Instructions
This file is the entry point for AI coding assistants (Claude Code, Cursor, Copilot, Codex, Aider, etc.) working on LocalAI. It is an index to detailed topic guides in the `.agents/` directory. Read the relevant file(s) for the task at hand — you don't need to load all of them.
Human contributors: see [CONTRIBUTING.md](CONTRIBUTING.md) for the development workflow.
## Policy for AI-Assisted Contributions
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.
- **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.
## Topics
| File | When to read |
|------|-------------|
| [.agents/ai-coding-assistants.md](.agents/ai-coding-assistants.md) | Policy for AI-assisted contributions — licensing, DCO, attribution |
| [.agents/building-and-testing.md](.agents/building-and-testing.md) | Building the project, running tests, Docker builds for specific platforms |
| [.agents/adding-backends.md](.agents/adding-backends.md) | Adding a new backend (Python, Go, or C++) — full step-by-step checklist |
| [.agents/coding-style.md](.agents/coding-style.md) | Code style, editorconfig, logging, documentation conventions |
| [.agents/llama-cpp-backend.md](.agents/llama-cpp-backend.md) | Working on the llama.cpp backend — architecture, updating, tool call parsing |
| [.agents/vllm-backend.md](.agents/vllm-backend.md) | Working on the vLLM / vLLM-omni backends — native parsers, ChatDelta, CPU build, libnuma packaging, backend hooks |
| [.agents/testing-mcp-apps.md](.agents/testing-mcp-apps.md) | Testing MCP Apps (interactive tool UIs) in the React UI |
| [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) | Adding API endpoints, auth middleware, feature permissions, user access control |
| [.agents/debugging-backends.md](.agents/debugging-backends.md) | Debugging runtime backend failures, dependency conflicts, rebuilding backends |
| [.agents/adding-gallery-models.md](.agents/adding-gallery-models.md) | Adding GGUF models from HuggingFace to the model gallery |
## Quick Reference
- **Logging**: Use `github.com/mudler/xlog` (same API as slog)
- **Go style**: Prefer `any` over `interface{}`
- **Comments**: Explain *why*, not *what*
- **Docs**: Update `docs/content/` when adding features or changing config
- **New API endpoints**: LocalAI advertises its capability surface in several independent places — swagger `@Tags`, `/api/instructions` registry, auth `RouteFeatureRegistry`, React UI `capabilities.js`, docs. Read [.agents/api-endpoints-and-auth.md](.agents/api-endpoints-and-auth.md) and follow its checklist — missing any surface means clients, admins, and the UI won't know the endpoint exists.
- **Build**: Inspect `Makefile` and `.github/workflows/` — ask the user before running long builds
- **UI**: The active UI is the React app in `core/http/react-ui/`. The older Alpine.js/HTML UI in `core/http/static/` is pending deprecation — all new UI work goes in the React UI

View File

@@ -1 +0,0 @@
AGENTS.md

View File

@@ -7,137 +7,31 @@ Thank you for your interest in contributing to LocalAI! We appreciate your time
- [Getting Started](#getting-started)
- [Prerequisites](#prerequisites)
- [Setting up the Development Environment](#setting-up-the-development-environment)
- [Environment Variables](#environment-variables)
- [Contributing](#contributing)
- [Submitting an Issue](#submitting-an-issue)
- [Development Workflow](#development-workflow)
- [Creating a Pull Request (PR)](#creating-a-pull-request-pr)
- [Coding Guidelines](#coding-guidelines)
- [AI Coding Assistants](#ai-coding-assistants)
- [Testing](#testing)
- [Documentation](#documentation)
- [Community and Communication](#community-and-communication)
## Getting Started
### Prerequisites
- **Go 1.21+** (the project currently uses Go 1.26 in `go.mod`, but 1.21 is the minimum supported version)
- [Download Go](https://go.dev/dl/) or install via your package manager
- macOS: `brew install go`
- Ubuntu/Debian: follow the [official instructions](https://go.dev/doc/install) (the `apt` version is often outdated)
- Verify: `go version`
- **Git**
- **GNU Make**
- **GCC / C/C++ toolchain** (required for CGo and native backends)
- **Protocol Buffers compiler** (`protoc`) — needed for gRPC code generation
- Golang [1.21]
- Git
- macOS/Linux
#### System dependencies by platform
### Setting up the Development Environment and running localAI in the local environment
<details>
<summary><strong>Ubuntu / Debian</strong></summary>
```bash
sudo apt-get update
sudo apt-get install -y build-essential gcc g++ cmake git wget \
protobuf-compiler libprotobuf-dev pkg-config \
libopencv-dev libgrpc-dev
```
</details>
<details>
<summary><strong>CentOS / RHEL / Fedora</strong></summary>
```bash
sudo dnf groupinstall -y "Development Tools"
sudo dnf install -y cmake git wget protobuf-compiler protobuf-devel \
opencv-devel grpc-devel
```
</details>
<details>
<summary><strong>macOS</strong></summary>
```bash
xcode-select --install
brew install cmake git protobuf grpc opencv wget
```
</details>
<details>
<summary><strong>Windows</strong></summary>
Use [WSL 2](https://learn.microsoft.com/en-us/windows/wsl/install) with an Ubuntu distribution, then follow the Ubuntu instructions above.
</details>
### Setting up the Development Environment
1. **Clone the repository:**
```bash
git clone https://github.com/mudler/LocalAI.git
cd LocalAI
```
2. **Build LocalAI:**
```bash
make build
```
This runs protobuf generation, installs Go tools, builds the React UI, and compiles the `local-ai` binary. Key build variables you can set:
| Variable | Description | Example |
|---|---|---|
| `BUILD_TYPE` | GPU/accelerator type (`cublas`, `hipblas`, `intel`, ``) | `BUILD_TYPE=cublas make build` |
| `GO_TAGS` | Additional Go build tags | `GO_TAGS=debug make build` |
| `CUDA_MAJOR_VERSION` | CUDA major version (default: `13`) | `CUDA_MAJOR_VERSION=12` |
3. **Run LocalAI:**
```bash
./local-ai
```
4. **Development mode with live reload:**
```bash
make build-dev
```
This installs [`air`](https://github.com/air-verse/air) automatically and watches for file changes, rebuilding and restarting the server on each save.
5. **Containerized build** (no local toolchain needed):
```bash
make docker
```
For GPU-specific Docker builds, see the `docker-build-*` targets in the Makefile and refer to [CLAUDE.md](CLAUDE.md) for detailed backend build instructions.
### Environment Variables
LocalAI is configured primarily through environment variables (or equivalent CLI flags). The most useful ones for development are:
| Variable | Description | Default |
|---|---|---|
| `LOCALAI_DEBUG` | Enable debug mode | `false` |
| `LOCALAI_LOG_LEVEL` | Log verbosity (`error`, `warn`, `info`, `debug`, `trace`) | — |
| `LOCALAI_LOG_FORMAT` | Log format (`default`, `text`, `json`) | `default` |
| `LOCALAI_MODELS_PATH` | Path to model files | `./models` |
| `LOCALAI_BACKENDS_PATH` | Path to backend binaries | `./backends` |
| `LOCALAI_CONFIG_DIR` | Directory for dynamic config files (API keys, external backends) | `./configuration` |
| `LOCALAI_THREADS` | Number of threads for inference | — |
| `LOCALAI_ADDRESS` | Bind address for the API server | `:8080` |
| `LOCALAI_API_KEY` | API key(s) for authentication | — |
| `LOCALAI_CORS` | Enable CORS | `false` |
| `LOCALAI_DISABLE_WEBUI` | Disable the web UI | `false` |
See `core/cli/run.go` for the full list of supported environment variables.
1. Clone the repository: `git clone https://github.com/go-skynet/LocalAI.git`
2. Navigate to the project directory: `cd LocalAI`
3. Install the required dependencies ( see https://localai.io/basics/build/#build-localai-locally )
4. Build LocalAI: `make build`
5. Run LocalAI: `./local-ai`
## Contributing
@@ -147,165 +41,48 @@ We welcome contributions from everyone! To get started, follow these steps:
If you find a bug, have a feature request, or encounter any issues, please check the [issue tracker](https://github.com/go-skynet/LocalAI/issues) to see if a similar issue has already been reported. If not, feel free to [create a new issue](https://github.com/go-skynet/LocalAI/issues/new) and provide as much detail as possible.
### Development Workflow
#### Branch naming conventions
Use a descriptive branch name that indicates the type and scope of the change:
- `feature/<short-description>` — new functionality
- `fix/<short-description>` — bug fixes
- `docs/<short-description>` — documentation changes
- `refactor/<short-description>` — code refactoring
#### Commit messages
- Use a short, imperative subject line (e.g., "feat: add whisper backend support", not "Added whisper backend support")
- Keep the subject under 72 characters
- Use the body to explain **why** the change was made when the subject alone is not sufficient
- Use [conventional commits](https://www.conventionalcommits.org/en/v1.0.0/)
#### Creating a Pull Request (PR)
Before jumping into a PR for a massive feature or big change, it is preferred to discuss it first via an issue.
### Creating a Pull Request (PR)
1. Fork the repository.
2. Create a new branch: `git checkout -b feature/my-change`
3. Make your changes, keeping commits focused and atomic.
4. Run tests locally before pushing (see [Testing](#testing) below).
5. Push to your fork: `git push origin feature/my-change`
6. Open a pull request against the `master` branch.
7. Fill in the PR description with:
- What the change does and why
- How it was tested
- Any breaking changes or migration steps
8. Respond to review feedback promptly. Push follow-up commits rather than force-pushing amended commits so reviewers can see incremental changes.
9. Once approved, a maintainer will merge your PR.
2. Create a new branch with a descriptive name: `git checkout -b [branch name]`
3. Make your changes and commit them.
4. Push the changes to your fork: `git push origin [branch name]`
5. Create a new pull request from your branch to the main project's `main` or `master` branch.
6. Provide a clear description of your changes in the pull request.
7. Make any requested changes during the review process.
8. Once your PR is approved, it will be merged into the main project.
## Coding Guidelines
This project uses an [`.editorconfig`](.editorconfig) file to define formatting standards (indentation, line endings, charset, etc.). Please configure your editor to respect it.
For AI-assisted development, see [`AGENTS.md`](AGENTS.md) (or the equivalent [`CLAUDE.md`](CLAUDE.md) symlink) for agent-specific guidelines including build instructions and backend architecture details. Contributions produced with AI assistance must follow the rules in the [AI Coding Assistants](#ai-coding-assistants) section below.
### General Principles
- Write code that can be tested. All new features and bug fixes should include test coverage.
- Use comments sparingly to explain **why** code does something, not **what** it does. Comments should add context that would be difficult to deduce from reading the code alone.
- Keep changes focused. Avoid unrelated refactors, formatting changes, or feature additions in the same PR.
### Go Code
- Prefer modern Go idioms — for example, use `any` instead of `interface{}`.
- Use [`golangci-lint`](https://golangci-lint.run) to catch common issues before submitting a PR.
- Use [`github.com/mudler/xlog`](https://github.com/mudler/xlog) for logging (same API as `slog`). Do not use `fmt.Println` or the standard `log` package for operational logging.
- Use tab indentation for Go files (as defined in `.editorconfig`).
### Python Code
- Use 4-space indentation (as defined in `.editorconfig`).
- Include a `requirements.txt` for any new dependencies.
### Code Review
- All contributions go through code review via pull requests.
- Reviewers will check for correctness, test coverage, adherence to these guidelines, and clarity of intent.
- Be responsive to review feedback and keep discussions constructive.
## AI Coding Assistants
LocalAI follows the **same guidelines as the Linux kernel project** for AI-assisted contributions: <https://docs.kernel.org/process/coding-assistants.html>.
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.
- **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:
```
Assisted-by: AGENT_NAME:MODEL_VERSION [TOOL1] [TOOL2]
```
Example: `Assisted-by: Claude:claude-opus-4-7 golangci-lint`
Basic development tools (git, go, make, editors) should not be listed.
- **The human submitter is responsible** for reviewing, testing, and fully understanding every line of AI-generated code — including verifying that any referenced APIs, flags, or file paths actually exist in the tree.
- Contributions must remain compatible with LocalAI's **MIT License**.
- No specific coding guidelines at the moment. Please make sure the code can be tested. The most popular lint tools like []`golangci-lint`](https://golangci-lint.run) can help you here.
## Testing
All new features and bug fixes should include test coverage. The project uses [Ginkgo](https://onsi.github.io/ginkgo/) as its test framework.
`make test` cannot handle all the model now. Please be sure to add a test case for the new features or the part was changed.
### Running unit tests
### Running AIO tests
```bash
make test
```
This downloads test model fixtures, runs protobuf generation, and executes the full test suite including llama-gguf, TTS, and stable-diffusion tests. Note: some tests require model files to be downloaded, so the first run may take longer.
To run tests for a specific package:
```bash
go test ./core/config/...
go test ./pkg/model/...
```
To run a specific test by name using Ginkgo's `--focus` flag:
```bash
go run github.com/onsi/ginkgo/v2/ginkgo --focus="should load a model" -v -r ./core/
```
### Running end-to-end tests
The e2e tests run LocalAI in a Docker container and exercise the API:
```bash
make test-e2e
```
### Running E2E container tests
These tests build a standard LocalAI Docker image and run it with pre-configured model configs to verify that most endpoints work correctly:
All-In-One images has a set of tests that automatically verifies that most of the endpoints works correctly, a flow can be :
```bash
# Build the LocalAI docker image
make docker-build-e2e
make DOCKER_IMAGE=local-ai docker
# Run the e2e tests (uses model configs from tests/e2e-aio/models/)
make e2e-aio
```
# Build the corresponding AIO image
BASE_IMAGE=local-ai DOCKER_AIO_IMAGE=local-ai-aio:test make docker-aio
### Testing backends
To prepare and test extra (Python) backends:
```bash
make prepare-test-extra # build Python backends for testing
make test-extra # run backend-specific tests
# Run the AIO e2e tests
LOCALAI_IMAGE_TAG=test LOCALAI_IMAGE=local-ai-aio make run-e2e-aio
```
## Documentation
We welcome contributions to the documentation. Please open a new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
### Gallery YAML Schema
LocalAI provides a JSON Schema for gallery model YAML files at:
`core/schema/gallery-model.schema.json`
This schema mirrors the internal gallery model configuration and can be used by editors (such as VS Code) to enable autocomplete, validation, and inline documentation when creating or modifying gallery files.
To use it with the YAML language server, add the following comment at the top of a gallery YAML file:
```yaml
# yaml-language-server: $schema=../core/schema/gallery-model.schema.json
```
We are welcome the contribution of the documents, please open new PR or create a new issue. The documentation is available under `docs/` https://github.com/mudler/LocalAI/tree/master/docs
## Community and Communication
- You can reach out via the Github issue tracker.
- Open a new discussion at [Discussion](https://github.com/go-skynet/LocalAI/discussions)
- Join the Discord channel [Discord](https://discord.gg/uJAeKSAGDy)
---

View File

@@ -1,213 +1,33 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG IMAGE_TYPE=extras
ARG BASE_IMAGE=ubuntu:22.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
ARG INTEL_BASE_IMAGE=${BASE_IMAGE}
ARG UBUNTU_CODENAME=noble
FROM ${BASE_IMAGE} AS requirements
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates curl wget espeak-ng libgomp1 \
ffmpeg libopenblas0 libopenblas-dev libopus0 sox && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
FROM requirements AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ARG SKIP_DRIVERS=false
ARG TARGETARCH
ARG TARGETVARIANT
ENV BUILD_TYPE=${BUILD_TYPE}
ARG UBUNTU_VERSION=2404
RUN mkdir -p /run/localai
RUN echo "default" > /run/localai/capability
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils mesa-vulkan-drivers
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "vulkan" > /run/localai/capability
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "nvidia-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
fi
EOT
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
echo "nvidia-l4t-cuda-${CUDA_MAJOR_VERSION}" > /run/localai/capability
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
echo "amd" > /run/localai/capability && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
RUN expr "${BUILD_TYPE}" = intel && echo "intel" > /run/localai/capability || echo "not intel"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
###################################
###################################
# The requirements-core target is common to all images. It should not be placed in requirements-core unless every single build will use it.
FROM requirements-drivers AS build-requirements
FROM ${BASE_IMAGE} AS requirements-core
ARG GO_VERSION=1.26.0
ARG CMAKE_VERSION=3.31.10
ARG CMAKE_FROM_SOURCE=false
USER root
ARG GO_VERSION=1.22.6
ARG TARGETARCH
ARG TARGETVARIANT
ENV DEBIAN_FRONTEND=noninteractive
ENV EXTERNAL_GRPC_BACKENDS="coqui:/build/backend/python/coqui/run.sh,huggingface-embeddings:/build/backend/python/sentencetransformers/run.sh,transformers:/build/backend/python/transformers/run.sh,sentencetransformers:/build/backend/python/sentencetransformers/run.sh,rerankers:/build/backend/python/rerankers/run.sh,autogptq:/build/backend/python/autogptq/run.sh,bark:/build/backend/python/bark/run.sh,diffusers:/build/backend/python/diffusers/run.sh,exllama:/build/backend/python/exllama/run.sh,openvoice:/build/backend/python/openvoice/run.sh,vall-e-x:/build/backend/python/vall-e-x/run.sh,vllm:/build/backend/python/vllm/run.sh,mamba:/build/backend/python/mamba/run.sh,exllama2:/build/backend/python/exllama2/run.sh,transformers-musicgen:/build/backend/python/transformers-musicgen/run.sh,parler-tts:/build/backend/python/parler-tts/run.sh"
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates espeak-ng \
curl libssl-dev \
ca-certificates \
cmake \
curl \
git \
git-lfs \
libopus-dev pkg-config \
unzip upx-ucl python3 python-is-python3 && \
unzip upx-ucl && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin
@@ -226,11 +46,126 @@ RUN test -n "$TARGETARCH" \
RUN echo "Target Architecture: $TARGETARCH"
RUN echo "Target Variant: $TARGETVARIANT"
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# OpenBLAS requirements and stable diffusion
RUN apt-get update && \
apt-get install -y --no-install-recommends \
libopenblas-dev \
libopencv-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Set up OpenCV
RUN ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
WORKDIR /build
###################################
###################################
# The requirements-extras target is for any builds with IMAGE_TYPE=extras. It should not be placed in this target unless every IMAGE_TYPE=extras build will use it
FROM requirements-core AS requirements-extras
RUN curl -LsSf https://astral.sh/uv/install.sh | sh
ENV PATH="/root/.cargo/bin:${PATH}"
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
RUN apt-get update && \
apt-get install -y --no-install-recommends \
espeak-ng \
espeak \
python3-pip \
python-is-python3 \
python3-dev llvm \
python3-venv && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
pip install --upgrade pip
# Install grpcio-tools (the version in 22.04 is too old)
RUN pip install --user grpcio-tools
###################################
###################################
# The requirements-drivers target is for BUILD_TYPE specific items. If you need to install something specific to CUDA, or specific to ROCM, it goes here.
# This target will be built on top of requirements-core or requirements-extras as retermined by the IMAGE_TYPE build-arg
FROM requirements-${IMAGE_TYPE} AS requirements-drivers
ARG BUILD_TYPE
ARG CUDA_MAJOR_VERSION=12
ARG CUDA_MINOR_VERSION=0
ENV BUILD_TYPE=${BUILD_TYPE}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
wget -qO - https://packages.lunarg.com/lunarg-signing-key-pub.asc | apt-key add - && \
wget -qO /etc/apt/sources.list.d/lunarg-vulkan-jammy.list https://packages.lunarg.com/vulkan/lunarg-vulkan-jammy.list && \
apt-get update && \
apt-get install -y \
vulkan-sdk && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/arm64/cuda-keyring_1.1-1_all.deb
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
###################################
###################################
@@ -239,29 +174,58 @@ WORKDIR /build
# https://community.intel.com/t5/Intel-oneAPI-Math-Kernel-Library/APT-Repository-not-working-signatures-invalid/m-p/1599436/highlight/true#M36143
# This is a temporary workaround until Intel fixes their repository
FROM ${INTEL_BASE_IMAGE} AS intel
ARG UBUNTU_CODENAME=noble
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu ${UBUNTU_CODENAME}/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
RUN echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy/lts/2350 unified" > /etc/apt/sources.list.d/intel-graphics.list
###################################
###################################
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
intel-oneapi-runtime-libs && \
ca-certificates \
build-essential \
cmake \
git && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
###################################
###################################
# The builder-base target has the arguments, variables, and copies shared between full builder images and the uncompiled devcontainer
FROM build-requirements AS builder-base
FROM requirements-drivers AS builder-base
ARG GO_TAGS="auth"
ARG GO_TAGS="stablediffusion tts p2p"
ARG GRPC_BACKENDS
ARG MAKEFLAGS
ARG LD_FLAGS="-s -w"
ARG TARGETARCH
ARG TARGETVARIANT
ENV GRPC_BACKENDS=${GRPC_BACKENDS}
ENV GO_TAGS=${GO_TAGS}
ENV MAKEFLAGS=${MAKEFLAGS}
@@ -275,7 +239,9 @@ RUN echo "GO_TAGS: $GO_TAGS" && echo "TARGETARCH: $TARGETARCH"
WORKDIR /build
# We need protoc installed, and the version in 22.04 is too old.
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
@@ -289,56 +255,44 @@ RUN <<EOT bash
fi
EOT
###################################
###################################
# Build React UI
FROM node:25-slim AS react-ui-builder
WORKDIR /app
COPY core/http/react-ui/package*.json ./
RUN npm install
COPY core/http/react-ui/ ./
RUN npm run build
###################################
###################################
# Compile backends first in a separate stage
FROM builder-base AS builder-backends
ARG TARGETARCH
ARG TARGETVARIANT
# This first portion of builder holds the layers specifically used to build backend-assets/grpc/stablediffusion
# In most cases, builder is the image you should be using - however, this can save build time if one just needs to copy backend-assets/grpc/stablediffusion and nothing else.
FROM builder-base AS builder-sd
WORKDIR /build
COPY . .
COPY .git .
COPY ./Makefile .
COPY ./backend ./backend
COPY ./go.mod .
COPY ./go.sum .
COPY ./.git ./.git
RUN make prepare
# Some of the Go backends use libs from the main src, we could further optimize the caching by building the CPP backends before here
COPY ./pkg/grpc ./pkg/grpc
COPY ./pkg/utils ./pkg/utils
RUN ls -l ./
RUN make protogen-go
# stablediffusion does not tolerate a newer version of abseil, build it first
RUN GRPC_BACKENDS=backend-assets/grpc/stablediffusion make build
###################################
###################################
# The builder target compiles LocalAI. This target is not the target that will be uploaded to the registry.
# Adjustments to the build process should likely be made here.
FROM builder-backends AS builder
FROM builder-sd AS builder
# Install the pre-built GRPC
COPY --from=grpc /opt/grpc /usr/local
# Rebuild with defaults backends
WORKDIR /build
COPY . .
# Copy pre-built React UI
COPY --from=react-ui-builder /app/dist ./core/http/react-ui/dist
## Build the binary
## If we're on arm64 AND using cublas/hipblas, skip some of the llama-compat backends to save space
## Otherwise just run the normal build
RUN make build
RUN if [ ! -d "/build/sources/go-piper/piper-phonemize/pi/lib/" ]; then \
mkdir -p /build/sources/go-piper/piper-phonemize/pi/lib/ \
touch /build/sources/go-piper/piper-phonemize/pi/lib/keep \
; fi
###################################
###################################
@@ -347,12 +301,28 @@ RUN make build
FROM builder-base AS devcontainer
ARG FFMPEG
COPY --from=grpc /opt/grpc /usr/local
COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion /build/backend-assets/grpc/stablediffusion
COPY .devcontainer-scripts /.devcontainer-scripts
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ssh less
# For the devcontainer, leave apt functional in case additional devtools are needed at runtime.
ssh less && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN go install github.com/go-delve/delve/cmd/dlv@latest
@@ -365,30 +335,115 @@ RUN go install github.com/mikefarah/yq/v4@latest
# If you cannot find a more suitable place for an addition, this layer is a suitable place for it.
FROM requirements-drivers
ARG FFMPEG
ARG BUILD_TYPE
ARG TARGETARCH
ARG IMAGE_TYPE=extras
ARG EXTRA_BACKENDS
ARG MAKEFLAGS
ENV BUILD_TYPE=${BUILD_TYPE}
ENV REBUILD=false
ENV HEALTHCHECK_ENDPOINT=http://localhost:8080/readyz
ENV MAKEFLAGS=${MAKEFLAGS}
ARG CUDA_MAJOR_VERSION=12
ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
ENV NVIDIA_REQUIRE_CUDA="cuda>=${CUDA_MAJOR_VERSION}.0"
ENV NVIDIA_VISIBLE_DEVICES=all
WORKDIR /
# Add FFmpeg
RUN if [ "${FFMPEG}" = "true" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
ffmpeg && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
COPY ./entrypoint.sh .
WORKDIR /build
# we start fresh & re-copy all assets because `make build` does not clean up nicely after itself
# so when `entrypoint.sh` runs `make build` again (which it does by default), the build would fail
# see https://github.com/go-skynet/LocalAI/pull/658#discussion_r1241971626 and
# https://github.com/go-skynet/LocalAI/pull/434
COPY . .
COPY --from=builder /build/sources ./sources/
COPY --from=grpc /opt/grpc /usr/local
RUN make prepare-sources
# Copy the binary
COPY --from=builder /build/local-ai ./
# Copy the opus shim if it was built
RUN --mount=from=builder,src=/build/,dst=/mnt/build \
if [ -f /mnt/build/libopusshim.so ]; then cp /mnt/build/libopusshim.so ./; fi
# Copy shared libraries for piper
COPY --from=builder /build/sources/go-piper/piper-phonemize/pi/lib/* /usr/lib/
# do not let stablediffusion rebuild (requires an older version of absl)
COPY --from=builder-sd /build/backend-assets/grpc/stablediffusion ./backend-assets/grpc/stablediffusion
# Change the shell to bash so we can use [[ tests below
SHELL ["/bin/bash", "-c"]
# We try to strike a balance between individual layer size (as that affects total push time) and total image size
# Splitting the backends into more groups with fewer items results in a larger image, but a smaller size for the largest layer
# Splitting the backends into fewer groups with more items results in a smaller image, but a larger size for the largest layer
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "coqui" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/coqui \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "parler-tts" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/parler-tts \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "diffusers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/diffusers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers-musicgen" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers-musicgen \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama1" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vall-e-x" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vall-e-x \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "openvoice" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/openvoice \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "sentencetransformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/sentencetransformers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "exllama2" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/exllama2 \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "transformers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/transformers \
; fi
RUN if [[ ( "${EXTRA_BACKENDS}" =~ "vllm" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/vllm \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "autogptq" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/autogptq \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "bark" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/bark \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "rerankers" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/rerankers \
; fi && \
if [[ ( "${EXTRA_BACKENDS}" =~ "mamba" || -z "${EXTRA_BACKENDS}" ) && "$IMAGE_TYPE" == "extras" ]]; then \
make -C backend/python/mamba \
; fi
# Make sure the models directory exists
RUN mkdir -p /models /backends /data
RUN mkdir -p /build/models
# Define the health check command
HEALTHCHECK --interval=1m --timeout=10m --retries=10 \
CMD curl -f ${HEALTHCHECK_ENDPOINT} || exit 1
VOLUME /models /backends /configuration /data
VOLUME /build/models
EXPOSE 8080
ENTRYPOINT [ "/entrypoint.sh" ]
ENTRYPOINT [ "/build/entrypoint.sh" ]

8
Dockerfile.aio Normal file
View File

@@ -0,0 +1,8 @@
ARG BASE_IMAGE=ubuntu:22.04
FROM ${BASE_IMAGE}
RUN apt-get update && apt-get install -y pciutils && apt-get clean
COPY aio/ /aio
ENTRYPOINT [ "/aio/entrypoint.sh" ]

5
Earthfile Normal file
View File

@@ -0,0 +1,5 @@
VERSION 0.7
build:
FROM DOCKERFILE -f Dockerfile .
SAVE ARTIFACT /usr/bin/local-ai AS LOCAL local-ai

View File

@@ -1,6 +1,6 @@
MIT License
Copyright (c) 2023-2025 Ettore Di Giacinto (mudler@localai.io)
Copyright (c) 2023-2024 Ettore Di Giacinto (mudler@localai.io)
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal

1518
Makefile
View File

File diff suppressed because it is too large Load Diff

286
README.md
View File

@@ -1,212 +1,164 @@
<h1 align="center">
<br>
<img width="300" src="./core/http/static/logo.png"> <br>
<img height="300" src="https://github.com/go-skynet/LocalAI/assets/2420543/0966aa2a-166e-4f99-a3e5-6c915fc997dd"> <br>
LocalAI
<br>
</h1>
<p align="center">
<a href="https://github.com/go-skynet/LocalAI/fork" target="blank">
<img src="https://img.shields.io/github/forks/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI forks"/>
</a>
<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/pulls" target="blank">
<img src="https://img.shields.io/github/issues-pr/go-skynet/LocalAI?style=for-the-badge" alt="LocalAI pull-requests"/>
</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>
<a href="LICENSE" target="blank">
<img src="https://img.shields.io/badge/License-MIT-yellow.svg?style=for-the-badge" alt="LocalAI License"/>
</p>
<p align="center">
<a href="https://hub.docker.com/r/localai/localai" target="blank">
<img src="https://img.shields.io/badge/dockerhub-images-important.svg?logo=Docker" alt="LocalAI Docker hub"/>
</a>
<a href="https://quay.io/repository/go-skynet/local-ai?tab=tags&tag=latest" target="blank">
<img src="https://img.shields.io/badge/quay.io-images-important.svg?" alt="LocalAI Quay.io"/>
</a>
</p>
<p align="center">
<a href="https://twitter.com/LocalAI_API" target="blank">
<img src="https://img.shields.io/badge/X-%23000000.svg?style=for-the-badge&logo=X&logoColor=white&label=LocalAI_API" alt="Follow LocalAI_API"/>
<img src="https://img.shields.io/twitter/follow/LocalAI_API?label=Follow: LocalAI_API&style=social" alt="Follow LocalAI_API"/>
</a>
<a href="https://discord.gg/uJAeKSAGDy" target="blank">
<img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Discord&style=for-the-badge&query=approximate_member_count&url=https%3A%2F%2Fdiscordapp.com%2Fapi%2Finvites%2FuJAeKSAGDy%3Fwith_counts%3Dtrue&logo=discord" alt="Join LocalAI Discord Community"/>
<img src="https://dcbadge.vercel.app/api/server/uJAeKSAGDy?style=flat-square&theme=default-inverted" alt="Join LocalAI Discord Community"/>
</a>
</p>
<p align="center">
<a href="https://trendshift.io/repositories/5539" target="_blank"><img src="https://trendshift.io/api/badge/repositories/5539" alt="mudler%2FLocalAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>
> :bulb: Get help - [❓FAQ](https://localai.io/faq/) [💭Discussions](https://github.com/go-skynet/LocalAI/discussions) [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) [:book: Documentation website](https://localai.io/)
>
> [💻 Quickstart](https://localai.io/basics/getting_started/) [📣 News](https://localai.io/basics/news/) [ 🛫 Examples ](https://github.com/go-skynet/LocalAI/tree/master/examples/) [ 🖼️ Models ](https://localai.io/models/) [ 🚀 Roadmap ](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
**LocalAI** is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
[![tests](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/test.yml)[![Build and Release](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/release.yaml)[![build container images](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/image.yml)[![Bump dependencies](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml/badge.svg)](https://github.com/go-skynet/LocalAI/actions/workflows/bump_deps.yaml)[![Artifact Hub](https://img.shields.io/endpoint?url=https://artifacthub.io/badge/repository/localai)](https://artifacthub.io/packages/search?repo=localai)
- **Drop-in API compatibility** — OpenAI, Anthropic, ElevenLabs APIs
- **36+ backends** — llama.cpp, vLLM, transformers, whisper, diffusers, MLX...
- **Any hardware** — NVIDIA, AMD, Intel, Apple Silicon, Vulkan, or CPU-only
- **Multi-user ready** — API key auth, user quotas, role-based access
- **Built-in AI agents** — autonomous agents with tool use, RAG, MCP, and skills
- **Privacy-first** — your data never leaves your infrastructure
**LocalAI** is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API thats compatible with OpenAI (Elevenlabs, Anthropic... ) API specifications for local AI inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families. Does not require GPU. It is created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
Created and maintained by [Ettore Di Giacinto](https://github.com/mudler).
![screen](https://github.com/mudler/LocalAI/assets/2420543/20b5ccd2-8393-44f0-aaf6-87a23806381e)
> [:book: Documentation](https://localai.io/) | [:speech_balloon: Discord](https://discord.gg/uJAeKSAGDy) | [💻 Quickstart](https://localai.io/basics/getting_started/) | [🖼️ Models](https://models.localai.io/) | [❓FAQ](https://localai.io/faq/)
## Guided tour
https://github.com/user-attachments/assets/08cbb692-57da-48f7-963d-2e7b43883c18
<details>
<summary>
Click to see more!
</summary>
#### User and auth
https://github.com/user-attachments/assets/228fa9ad-81a3-4d43-bfb9-31557e14a36c
#### Agents
https://github.com/user-attachments/assets/6270b331-e21d-4087-a540-6290006b381a
#### Usage metrics per user
https://github.com/user-attachments/assets/cbb03379-23b4-4e3d-bd26-d152f057007f
#### Fine-tuning and Quantization
https://github.com/user-attachments/assets/5ba4ace9-d3df-4795-b7d4-b0b404ea71ee
#### WebRTC
https://github.com/user-attachments/assets/ed88e34c-fed3-4b83-8a67-4716a9feeb7b
</details>
## Quickstart
### macOS
<a href="https://github.com/mudler/LocalAI/releases/latest/download/LocalAI.dmg">
<img src="https://img.shields.io/badge/Download-macOS-blue?style=for-the-badge&logo=apple&logoColor=white" alt="Download LocalAI for macOS"/>
</a>
> **Note:** The DMG is not signed by Apple. After installing, run: `sudo xattr -d com.apple.quarantine /Applications/LocalAI.app`. See [#6268](https://github.com/mudler/LocalAI/issues/6268) for details.
### Containers (Docker, podman, ...)
> Already ran LocalAI before? Use `docker start -i local-ai` to restart an existing container.
#### CPU only:
Run the installer script:
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
curl https://localai.io/install.sh | sh
```
#### NVIDIA GPU:
Or run with docker:
```bash
# CUDA 13
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-13
# CUDA 12
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
# NVIDIA Jetson ARM64 (CUDA 12, for AGX Orin and similar)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64
# NVIDIA Jetson ARM64 (CUDA 13, for DGX Spark)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-aio-cpu
# Alternative images:
# - if you have an Nvidia GPU:
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-aio-gpu-nvidia-cuda-12
# - without preconfigured models
# docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
# - without preconfigured models for Nvidia GPUs
# docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12
```
#### AMD GPU (ROCm):
[💻 Getting started](https://localai.io/basics/getting_started/index.html)
```bash
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas
```
## 🔥🔥 Hot topics / Roadmap
#### Intel GPU (oneAPI):
[Roadmap](https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3Aroadmap)
```bash
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
```
- July 2024: 🔥🔥 🆕 P2P Dashboard, LocalAI Federated mode and AI Swarms: https://github.com/mudler/LocalAI/pull/2723
- June 2024: 🆕 You can browse now the model gallery without LocalAI! Check out https://models.localai.io
- June 2024: Support for models from OCI registries: https://github.com/mudler/LocalAI/pull/2628
- May 2024: 🔥🔥 Decentralized P2P llama.cpp: https://github.com/mudler/LocalAI/pull/2343 (peer2peer llama.cpp!) 👉 Docs https://localai.io/features/distribute/
- May 2024: 🔥🔥 Openvoice: https://github.com/mudler/LocalAI/pull/2334
- May 2024: 🆕 Function calls without grammars and mixed mode: https://github.com/mudler/LocalAI/pull/2328
- May 2024: 🔥🔥 Distributed inferencing: https://github.com/mudler/LocalAI/pull/2324
- May 2024: Chat, TTS, and Image generation in the WebUI: https://github.com/mudler/LocalAI/pull/2222
- April 2024: Reranker API: https://github.com/mudler/LocalAI/pull/2121
#### Vulkan GPU:
Hot topics (looking for contributors):
```bash
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
```
- 🔥🔥 Distributed, P2P Global community pools: https://github.com/mudler/LocalAI/issues/3113
- WebUI improvements: https://github.com/mudler/LocalAI/issues/2156
- Backends v2: https://github.com/mudler/LocalAI/issues/1126
- Improving UX v2: https://github.com/mudler/LocalAI/issues/1373
- Assistant API: https://github.com/mudler/LocalAI/issues/1273
- Moderation endpoint: https://github.com/mudler/LocalAI/issues/999
- Vulkan: https://github.com/mudler/LocalAI/issues/1647
- Anthropic API: https://github.com/mudler/LocalAI/issues/1808
### Loading models
If you want to help and contribute, issues up for grabs: https://github.com/mudler/LocalAI/issues?q=is%3Aissue+is%3Aopen+label%3A%22up+for+grabs%22
```bash
# From the model gallery (see available models with `local-ai models list` or at https://models.localai.io)
local-ai run llama-3.2-1b-instruct:q4_k_m
# From Huggingface
local-ai run huggingface://TheBloke/phi-2-GGUF/phi-2.Q8_0.gguf
# From the Ollama OCI registry
local-ai run ollama://gemma:2b
# From a YAML config
local-ai run https://gist.githubusercontent.com/.../phi-2.yaml
# From a standard OCI registry (e.g., Docker Hub)
local-ai run oci://localai/phi-2:latest
```
## 🚀 [Features](https://localai.io/features/)
> **Automatic Backend Detection**: LocalAI automatically detects your GPU capabilities and downloads the appropriate backend. For advanced options, see [GPU Acceleration](https://localai.io/features/gpu-acceleration/).
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
- 🔥 [OpenAI-alike tools API](https://localai.io/features/openai-functions/)
- 🧠 [Embeddings generation for vector databases](https://localai.io/features/embeddings/)
- ✍️ [Constrained grammars](https://localai.io/features/constrained_grammars/)
- 🖼️ [Download Models directly from Huggingface ](https://localai.io/models/)
- 🥽 [Vision API](https://localai.io/features/gpt-vision/)
- 📈 [Reranker API](https://localai.io/features/reranker/)
- 🆕🖧 [P2P Inferencing](https://localai.io/features/distribute/)
- 🌍 Integrated WebUI!
For more details, see the [Getting Started guide](https://localai.io/basics/getting_started/).
## 💻 Usage
## Latest News
Check out the [Getting started](https://localai.io/basics/getting_started/index.html) section in our documentation.
- **March 2026**: [Agent management](https://github.com/mudler/LocalAI/pull/8820), [New React UI](https://github.com/mudler/LocalAI/pull/8772), [WebRTC](https://github.com/mudler/LocalAI/pull/8790), [MLX-distributed via P2P and RDMA](https://github.com/mudler/LocalAI/pull/8801), [MCP Apps, MCP Client-side](https://github.com/mudler/LocalAI/pull/8947)
- **February 2026**: [Realtime API for audio-to-audio with tool calling](https://github.com/mudler/LocalAI/pull/6245), [ACE-Step 1.5 support](https://github.com/mudler/LocalAI/pull/8396)
- **January 2026**: **LocalAI 3.10.0** — Anthropic API support, Open Responses API, video & image generation (LTX-2), unified GPU backends, tool streaming, Moonshine, Pocket-TTS. [Release notes](https://github.com/mudler/LocalAI/releases/tag/v3.10.0)
- **December 2025**: [Dynamic Memory Resource reclaimer](https://github.com/mudler/LocalAI/pull/7583), [Automatic multi-GPU model fitting (llama.cpp)](https://github.com/mudler/LocalAI/pull/7584), [Vibevoice backend](https://github.com/mudler/LocalAI/pull/7494)
- **November 2025**: [Import models via URL](https://github.com/mudler/LocalAI/pull/7245), [Multiple chats and history](https://github.com/mudler/LocalAI/pull/7325)
- **October 2025**: [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/) support for agentic capabilities
- **September 2025**: New Launcher for macOS and Linux, extended backend support for Mac and Nvidia L4T, MLX-Audio, WAN 2.2
- **August 2025**: MLX, MLX-VLM, Diffusers, llama.cpp now supported on Apple Silicon
- **July 2025**: All backends migrated outside the main binary — [lightweight, modular architecture](https://github.com/mudler/LocalAI/releases/tag/v3.2.0)
### 🔗 Community and integrations
For older news and full release notes, see [GitHub Releases](https://github.com/mudler/LocalAI/releases) and the [News page](https://localai.io/basics/news/).
Build and deploy custom containers:
- https://github.com/sozercan/aikit
## Features
WebUIs:
- https://github.com/Jirubizu/localai-admin
- https://github.com/go-skynet/LocalAI-frontend
- QA-Pilot(An interactive chat project that leverages LocalAI LLMs for rapid understanding and navigation of GitHub code repository) https://github.com/reid41/QA-Pilot
- [Text generation](https://localai.io/features/text-generation/) (`llama.cpp`, `transformers`, `vllm` ... [and more](https://localai.io/model-compatibility/))
- [Text to Audio](https://localai.io/features/text-to-audio/)
- [Audio to Text](https://localai.io/features/audio-to-text/)
- [Image generation](https://localai.io/features/image-generation)
- [OpenAI-compatible tools API](https://localai.io/features/openai-functions/)
- [Realtime API](https://localai.io/features/openai-realtime/) (Speech-to-speech)
- [Embeddings generation](https://localai.io/features/embeddings/)
- [Constrained grammars](https://localai.io/features/constrained_grammars/)
- [Download models from Huggingface](https://localai.io/models/)
- [Vision API](https://localai.io/features/gpt-vision/)
- [Object Detection](https://localai.io/features/object-detection/)
- [Reranker API](https://localai.io/features/reranker/)
- [P2P Inferencing](https://localai.io/features/distribute/)
- [Distributed Mode](https://localai.io/features/distributed-mode/) — Horizontal scaling with PostgreSQL + NATS
- [Model Context Protocol (MCP)](https://localai.io/docs/features/mcp/)
- [Built-in Agents](https://localai.io/features/agents/) — Autonomous AI agents with tool use, RAG, skills, SSE streaming, and [Agent Hub](https://agenthub.localai.io)
- [Backend Gallery](https://localai.io/backends/) — Install/remove backends on the fly via OCI images
- Voice Activity Detection (Silero-VAD)
- Integrated WebUI
Model galleries
- https://github.com/go-skynet/model-gallery
## Supported Backends & Acceleration
Other:
- Helm chart https://github.com/go-skynet/helm-charts
- VSCode extension https://github.com/badgooooor/localai-vscode-plugin
- Terminal utility https://github.com/djcopley/ShellOracle
- Local Smart assistant https://github.com/mudler/LocalAGI
- Home Assistant https://github.com/sammcj/homeassistant-localai / https://github.com/drndos/hass-openai-custom-conversation / https://github.com/valentinfrlch/ha-gpt4vision
- Discord bot https://github.com/mudler/LocalAGI/tree/main/examples/discord
- Slack bot https://github.com/mudler/LocalAGI/tree/main/examples/slack
- Shell-Pilot(Interact with LLM using LocalAI models via pure shell scripts on your Linux or MacOS system) https://github.com/reid41/shell-pilot
- Telegram bot https://github.com/mudler/LocalAI/tree/master/examples/telegram-bot
- Github Actions: https://github.com/marketplace/actions/start-localai
- Examples: https://github.com/mudler/LocalAI/tree/master/examples/
LocalAI supports **36+ backends** including llama.cpp, vLLM, transformers, whisper.cpp, diffusers, MLX, MLX-VLM, and many more. Hardware acceleration is available for **NVIDIA** (CUDA 12/13), **AMD** (ROCm), **Intel** (oneAPI/SYCL), **Apple Silicon** (Metal), **Vulkan**, and **NVIDIA Jetson** (L4T). All backends can be installed on-the-fly from the [Backend Gallery](https://localai.io/backends/).
### 🔗 Resources
See the full [Backend & Model Compatibility Table](https://localai.io/model-compatibility/) and [GPU Acceleration guide](https://localai.io/features/gpu-acceleration/).
- [LLM finetuning guide](https://localai.io/docs/advanced/fine-tuning/)
- [How to build locally](https://localai.io/basics/build/index.html)
- [How to install in Kubernetes](https://localai.io/basics/getting_started/index.html#run-localai-in-kubernetes)
- [Projects integrating LocalAI](https://localai.io/docs/integrations/)
- [How tos section](https://io.midori-ai.xyz/howtos/) (curated by our community)
## Resources
## :book: 🎥 [Media, Blogs, Social](https://localai.io/basics/news/#media-blogs-social)
- [Documentation](https://localai.io/)
- [LLM fine-tuning guide](https://localai.io/docs/advanced/fine-tuning/)
- [Build from source](https://localai.io/basics/build/)
- [Kubernetes installation](https://localai.io/basics/getting_started/#run-localai-in-kubernetes)
- [Integrations & community projects](https://localai.io/docs/integrations/)
- [Installation video walkthrough](https://www.youtube.com/watch?v=cMVNnlqwfw4)
- [Media & blog posts](https://localai.io/basics/news/#media-blogs-social)
- [Examples](https://github.com/mudler/LocalAI-examples)
## Autonomous Development Team
LocalAI is helped being maintained by a team of autonomous AI agents led by an AI Scrum Master.
- **Live Reports**: [reports.localai.io](http://reports.localai.io)
- **Project Board**: [Agent task tracking](https://github.com/users/mudler/projects/6)
- **Blog Post**: [Learn about the experiment](https://mudler.pm/posts/2026/02/28/a-call-to-open-source-maintainers-stop-babysitting-ai-how-i-built-a-100-local-autonomous-dev-team-to-maintain-localai-and-why-you-should-too/)
- [Run Visual studio code with LocalAI (SUSE)](https://www.suse.com/c/running-ai-locally/)
- 🆕 [Run LocalAI on Jetson Nano Devkit](https://mudler.pm/posts/local-ai-jetson-nano-devkit/)
- [Run LocalAI on AWS EKS with Pulumi](https://www.pulumi.com/blog/low-code-llm-apps-with-local-ai-flowise-and-pulumi/)
- [Run LocalAI on AWS](https://staleks.hashnode.dev/installing-localai-on-aws-ec2-instance)
- [Create a slackbot for teams and OSS projects that answer to documentation](https://mudler.pm/posts/smart-slackbot-for-teams/)
- [LocalAI meets k8sgpt](https://www.youtube.com/watch?v=PKrDNuJ_dfE)
- [Question Answering on Documents locally with LangChain, LocalAI, Chroma, and GPT4All](https://mudler.pm/posts/localai-question-answering/)
- [Tutorial to use k8sgpt with LocalAI](https://medium.com/@tyler_97636/k8sgpt-localai-unlock-kubernetes-superpowers-for-free-584790de9b65)
## Citation
@@ -222,7 +174,7 @@ If you utilize this repository, data in a downstream project, please consider ci
howpublished = {\url{https://github.com/go-skynet/LocalAI}},
```
## Sponsors
## ❤️ Sponsors
> Do you find LocalAI useful?
@@ -232,28 +184,24 @@ A huge thank you to our generous sponsors who support this project covering CI e
<p align="center">
<a href="https://www.spectrocloud.com/" target="blank">
<img height="200" src="https://github.com/user-attachments/assets/72eab1dd-8b93-4fc0-9ade-84db49f24962">
<img height="200" src="https://github.com/go-skynet/LocalAI/assets/2420543/68a6f3cb-8a65-4a4d-99b5-6417a8905512">
</a>
<a href="https://www.premai.io/" target="blank">
<img height="200" src="https://github.com/mudler/LocalAI/assets/2420543/42e4ca83-661e-4f79-8e46-ae43689683d6"> <br>
</a>
</p>
### Individual 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
## 🌟 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
## 📖 License
LocalAI is a community-driven project created by [Ettore Di Giacinto](https://github.com/mudler/).
MIT - Author Ettore Di Giacinto <mudler@localai.io>
## Acknowledgements
## 🙇 Acknowledgements
LocalAI couldn't have been built without the help of great software already available from the community. Thank you!
@@ -263,12 +211,12 @@ LocalAI couldn't have been built without the help of great software already avai
- https://github.com/antimatter15/alpaca.cpp
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/ggerganov/whisper.cpp
- https://github.com/saharNooby/rwkv.cpp
- https://github.com/rhasspy/piper
- [exo](https://github.com/exo-explore/exo) for the MLX distributed auto-parallel sharding implementation
## Contributors
## 🤗 Contributors
This is a community project, a special thanks to our contributors!
This is a community project, a special thanks to our contributors! 🤗
<a href="https://github.com/go-skynet/LocalAI/graphs/contributors">
<img src="https://contrib.rocks/image?repo=go-skynet/LocalAI" />
</a>

View File

@@ -8,24 +8,10 @@ At LocalAI, we take the security of our software seriously. We understand the im
We provide support and updates for certain versions of our software. The following table outlines which versions are currently supported with security updates:
| Version Series | Support Level | Details |
| -------------- | ------------- | ------- |
| 3.x | :white_check_mark: Actively supported | Full security updates and bug fixes for the latest minor versions. |
| 2.x | :warning: Security fixes only | Critical security patches only, until **December 31, 2025**. |
| 1.x | :x: End-of-life (EOL) | No longer supported as of **January 1, 2024**. No security fixes will be provided. |
### What each support level means
- **Actively supported (3.x):** Receives all security updates, bug fixes, and new features. Users should stay on the latest 3.x minor release for the best protection.
- **Security fixes only (2.x):** Receives only critical security patches (e.g., remote code execution, authentication bypass, data exposure). No bug fixes or new features. Support ends December 31, 2025.
- **End-of-life (1.x):** No updates of any kind. Users on 1.x are strongly encouraged to upgrade immediately, as known vulnerabilities will not be patched.
### Migrating from older versions
If you are running an unsupported or soon-to-be-unsupported version, we recommend upgrading as soon as possible:
- **From 1.x to 3.x:** Version 1.x reached end-of-life on January 1, 2024. Review the [release notes](https://github.com/mudler/LocalAI/releases) for breaking changes across major versions, and upgrade directly to the latest 3.x release.
- **From 2.x to 3.x:** While 2.x still receives critical security patches until December 31, 2025, we recommend planning your migration to 3.x to benefit from ongoing improvements and full support.
| Version | Supported |
| ------- | ------------------ |
| > 2.0 | :white_check_mark: |
| < 2.0 | :x: |
Please ensure that you are using a supported version to receive the latest security updates.

5
aio/cpu/README.md Normal file
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@@ -0,0 +1,5 @@
## AIO CPU size
Use this image with CPU-only.
Please keep using only C++ backends so the base image is as small as possible (without CUDA, cuDNN, python, etc).

12
aio/cpu/embeddings.yaml Normal file
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@@ -0,0 +1,12 @@
name: text-embedding-ada-002
backend: bert-embeddings
parameters:
model: huggingface://mudler/all-MiniLM-L6-v2/ggml-model-q4_0.bin
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

62
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@@ -0,0 +1,62 @@
name: stablediffusion
backend: stablediffusion
parameters:
model: stablediffusion_assets
license: "BSD-3"
urls:
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/EdVince/Stable-Diffusion-NCNN/blob/main/LICENSE
description: |
Stable Diffusion in NCNN with c++, supported txt2img and img2img
download_files:
- filename: "stablediffusion_assets/AutoencoderKL-256-256-fp16-opt.param"
sha256: "18ca4b66685e21406bcf64c484b3b680b4949900415536d599cc876579c85c82"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-256-256-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-512-512-fp16-opt.param"
sha256: "cf45f63aacf3dbbab0f59ed92a6f2c14d9a1801314631cd3abe91e3c85639a20"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-512-512-fp16-opt.param"
- filename: "stablediffusion_assets/AutoencoderKL-base-fp16.param"
sha256: "0254a056dce61b0c27dc9ec1b78b53bcf55315c540f55f051eb841aa992701ba"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/AutoencoderKL-base-fp16.param"
- filename: "stablediffusion_assets/AutoencoderKL-encoder-512-512-fp16.bin"
sha256: "ddcb79a9951b9f91e05e087739ed69da2c1c4ae30ba4168cce350b49d617c9fa"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-encoder-512-512-fp16.bin"
- filename: "stablediffusion_assets/AutoencoderKL-fp16.bin"
sha256: "f02e71f80e70252734724bbfaed5c4ddd3a8ed7e61bb2175ff5f53099f0e35dd"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/AutoencoderKL-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.bin"
sha256: "1c9a12f4e1dd1b295a388045f7f28a2352a4d70c3dc96a542189a3dd7051fdd6"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/FrozenCLIPEmbedder-fp16.bin"
- filename: "stablediffusion_assets/FrozenCLIPEmbedder-fp16.param"
sha256: "471afbe678dd1fd3fe764ef9c6eccaccb0a7d7e601f27b462aa926b20eb368c9"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/FrozenCLIPEmbedder-fp16.param"
- filename: "stablediffusion_assets/log_sigmas.bin"
sha256: "a2089f8aa4c61f9c200feaec541ab3f5c94233b28deb6d5e8bcd974fa79b68ac"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/raw/main/x86/linux/assets/log_sigmas.bin"
- filename: "stablediffusion_assets/UNetModel-256-256-MHA-fp16-opt.param"
sha256: "a58c380229f09491776df837b7aa7adffc0a87821dc4708b34535da2e36e3da1"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-256-256-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-512-512-MHA-fp16-opt.param"
sha256: "f12034067062827bd7f43d1d21888d1f03905401acf6c6eea22be23c259636fa"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-512-512-MHA-fp16-opt.param"
- filename: "stablediffusion_assets/UNetModel-base-MHA-fp16.param"
sha256: "696f6975de49f4325b53ce32aff81861a6d6c07cd9ce3f0aae2cc405350af38d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/UNetModel-base-MHA-fp16.param"
- filename: "stablediffusion_assets/UNetModel-MHA-fp16.bin"
sha256: "d618918d011bfc1f644c0f2a33bf84931bd53b28a98492b0a8ed6f3a818852c3"
uri: "https://github.com/EdVince/Stable-Diffusion-NCNN/releases/download/naifu/UNetModel-MHA-fp16.bin"
- filename: "stablediffusion_assets/vocab.txt"
sha256: "e30e57b6f1e47616982ef898d8922be24e535b4fa3d0110477b3a6f02ebbae7d"
uri: "https://raw.githubusercontent.com/EdVince/Stable-Diffusion-NCNN/main/x86/linux/assets/vocab.txt"
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

27
aio/cpu/rerank.yaml Normal file
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name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

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@@ -0,0 +1,18 @@
name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

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@@ -0,0 +1,15 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"voice-en-us-amy-low",
"input": "Hi, this is a test."
}'

101
aio/cpu/text-to-text.yaml Normal file
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name: gpt-4
mmap: true
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
context_size: 8192
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

31
aio/cpu/vision.yaml Normal file
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backend: llama-cpp
context_size: 4096
f16: true
mmap: true
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: bakllava-mmproj.gguf
parameters:
model: bakllava.gguf
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: bakllava.gguf
uri: huggingface://mys/ggml_bakllava-1/ggml-model-q4_k.gguf
- filename: bakllava-mmproj.gguf
uri: huggingface://mys/ggml_bakllava-1/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

138
aio/entrypoint.sh Executable file
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#!/bin/bash
echo "===> LocalAI All-in-One (AIO) container starting..."
GPU_ACCELERATION=false
GPU_VENDOR=""
function check_intel() {
if lspci | grep -E 'VGA|3D' | grep -iq intel; then
echo "Intel GPU detected"
if [ -d /opt/intel ]; then
GPU_ACCELERATION=true
GPU_VENDOR=intel
else
echo "Intel GPU detected, but Intel GPU drivers are not installed. GPU acceleration will not be available."
fi
fi
}
function check_nvidia_wsl() {
if lspci | grep -E 'VGA|3D' | grep -iq "Microsoft Corporation Device 008e"; then
# We make the assumption this WSL2 cars is NVIDIA, then check for nvidia-smi
# Make sure the container was run with `--gpus all` as the only required parameter
echo "NVIDIA GPU detected via WSL2"
# nvidia-smi should be installed in the container
if nvidia-smi; then
GPU_ACCELERATION=true
GPU_VENDOR=nvidia
else
echo "NVIDIA GPU detected via WSL2, but nvidia-smi is not installed. GPU acceleration will not be available."
fi
fi
}
function check_amd() {
if lspci | grep -E 'VGA|3D' | grep -iq amd; then
echo "AMD GPU detected"
# Check if ROCm is installed
if [ -d /opt/rocm ]; then
GPU_ACCELERATION=true
GPU_VENDOR=amd
else
echo "AMD GPU detected, but ROCm is not installed. GPU acceleration will not be available."
fi
fi
}
function check_nvidia() {
if lspci | grep -E 'VGA|3D' | grep -iq nvidia; then
echo "NVIDIA GPU detected"
# nvidia-smi should be installed in the container
if nvidia-smi; then
GPU_ACCELERATION=true
GPU_VENDOR=nvidia
else
echo "NVIDIA GPU detected, but nvidia-smi is not installed. GPU acceleration will not be available."
fi
fi
}
function check_metal() {
if system_profiler SPDisplaysDataType | grep -iq 'Metal'; then
echo "Apple Metal supported GPU detected"
GPU_ACCELERATION=true
GPU_VENDOR=apple
fi
}
function detect_gpu() {
case "$(uname -s)" in
Linux)
check_nvidia
check_amd
check_intel
check_nvidia_wsl
;;
Darwin)
check_metal
;;
esac
}
function detect_gpu_size() {
# Attempting to find GPU memory size for NVIDIA GPUs
if [ "$GPU_ACCELERATION" = true ] && [ "$GPU_VENDOR" = "nvidia" ]; then
echo "NVIDIA GPU detected. Attempting to find memory size..."
# Using head -n 1 to get the total memory of the 1st NVIDIA GPU detected.
# If handling multiple GPUs is required in the future, this is the place to do it
nvidia_sm=$(nvidia-smi --query-gpu=memory.total --format=csv,noheader,nounits | head -n 1)
if [ ! -z "$nvidia_sm" ]; then
echo "Total GPU Memory: $nvidia_sm MiB"
# if bigger than 8GB, use 16GB
#if [ "$nvidia_sm" -gt 8192 ]; then
# GPU_SIZE=gpu-16g
#else
GPU_SIZE=gpu-8g
#fi
else
echo "Unable to determine NVIDIA GPU memory size. Falling back to CPU."
GPU_SIZE=gpu-8g
fi
elif [ "$GPU_ACCELERATION" = true ] && [ "$GPU_VENDOR" = "intel" ]; then
GPU_SIZE=intel
# Default to a generic GPU size until we implement GPU size detection for non NVIDIA GPUs
elif [ "$GPU_ACCELERATION" = true ]; then
echo "Non-NVIDIA GPU detected. Specific GPU memory size detection is not implemented."
GPU_SIZE=gpu-8g
# default to cpu if GPU_SIZE is not set
else
echo "GPU acceleration is not enabled or supported. Defaulting to CPU."
GPU_SIZE=cpu
fi
}
function check_vars() {
if [ -z "$MODELS" ]; then
echo "MODELS environment variable is not set. Please set it to a comma-separated list of model YAML files to load."
exit 1
fi
if [ -z "$PROFILE" ]; then
echo "PROFILE environment variable is not set. Please set it to one of the following: cpu, gpu-8g, gpu-16g, apple"
exit 1
fi
}
detect_gpu
detect_gpu_size
PROFILE="${PROFILE:-$GPU_SIZE}" # default to cpu
export MODELS="${MODELS:-/aio/${PROFILE}/embeddings.yaml,/aio/${PROFILE}/rerank.yaml,/aio/${PROFILE}/text-to-speech.yaml,/aio/${PROFILE}/image-gen.yaml,/aio/${PROFILE}/text-to-text.yaml,/aio/${PROFILE}/speech-to-text.yaml,/aio/${PROFILE}/vision.yaml}"
check_vars
echo "===> Starting LocalAI[$PROFILE] with the following models: $MODELS"
exec /build/entrypoint.sh "$@"

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@@ -0,0 +1,12 @@
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

25
aio/gpu-8g/image-gen.yaml Normal file
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name: stablediffusion
parameters:
model: DreamShaper_8_pruned.safetensors
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps"
scheduler_type: "k_dpmpp_2m"
download_files:
- filename: DreamShaper_8_pruned.safetensors
uri: huggingface://Lykon/DreamShaper/DreamShaper_8_pruned.safetensors
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

27
aio/gpu-8g/rerank.yaml Normal file
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@@ -0,0 +1,27 @@
name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

View File

@@ -0,0 +1,18 @@
name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

View File

@@ -0,0 +1,15 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"tts-1",
"input": "Hi, this is a test."
}'

View File

@@ -0,0 +1,101 @@
name: gpt-4
mmap: true
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
context_size: 8192
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

35
aio/gpu-8g/vision.yaml Normal file
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@@ -0,0 +1,35 @@
backend: llama-cpp
context_size: 4096
f16: true
mmap: true
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

12
aio/intel/embeddings.yaml Normal file
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@@ -0,0 +1,12 @@
name: text-embedding-ada-002
backend: sentencetransformers
parameters:
model: all-MiniLM-L6-v2
usage: |
You can test this model with curl like this:
curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json" -d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'

20
aio/intel/image-gen.yaml Normal file
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name: stablediffusion
parameters:
model: runwayml/stable-diffusion-v1-5
backend: diffusers
step: 25
f16: true
diffusers:
pipeline_type: StableDiffusionPipeline
cuda: true
enable_parameters: "negative_prompt,num_inference_steps"
scheduler_type: "k_dpmpp_2m"
usage: |
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "<positive prompt>|<negative prompt>",
"step": 25,
"size": "512x512"
}'

27
aio/intel/rerank.yaml Normal file
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name: jina-reranker-v1-base-en
backend: rerankers
parameters:
model: cross-encoder
usage: |
You can test this model with curl like this:
curl http://localhost:8080/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"model": "jina-reranker-v1-base-en",
"query": "Organic skincare products for sensitive skin",
"documents": [
"Eco-friendly kitchenware for modern homes",
"Biodegradable cleaning supplies for eco-conscious consumers",
"Organic cotton baby clothes for sensitive skin",
"Natural organic skincare range for sensitive skin",
"Tech gadgets for smart homes: 2024 edition",
"Sustainable gardening tools and compost solutions",
"Sensitive skin-friendly facial cleansers and toners",
"Organic food wraps and storage solutions",
"All-natural pet food for dogs with allergies",
"Yoga mats made from recycled materials"
],
"top_n": 3
}'

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name: whisper-1
backend: whisper
parameters:
model: ggml-whisper-base.bin
usage: |
## example audio file
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
## Send the example audio file to the transcriptions endpoint
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
download_files:
- filename: "ggml-whisper-base.bin"
sha256: "60ed5bc3dd14eea856493d334349b405782ddcaf0028d4b5df4088345fba2efe"
uri: "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"

View File

@@ -0,0 +1,15 @@
name: tts-1
download_files:
- filename: voice-en-us-amy-low.tar.gz
uri: https://github.com/rhasspy/piper/releases/download/v0.0.2/voice-en-us-amy-low.tar.gz
parameters:
model: en-us-amy-low.onnx
usage: |
To test if this model works as expected, you can use the following curl command:
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
"model":"tts-1",
"input": "Hi, this is a test."
}'

103
aio/intel/text-to-text.yaml Normal file
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name: gpt-4
mmap: false
context_size: 8192
f16: false
parameters:
model: huggingface://NousResearch/Hermes-2-Pro-Llama-3-8B-GGUF/Hermes-2-Pro-Llama-3-8B-Q4_K_M.gguf
stopwords:
- "<|im_end|>"
- "<dummy32000>"
- "</tool_call>"
- "<|eot_id|>"
- "<|end_of_text|>"
function:
# disable injecting the "answer" tool
disable_no_action: true
grammar:
# This allows the grammar to also return messages
mixed_mode: true
# Suffix to add to the grammar
#prefix: '<tool_call>\n'
# Force parallel calls in the grammar
# parallel_calls: true
return_name_in_function_response: true
# Without grammar uncomment the lines below
# Warning: this is relying only on the capability of the
# LLM model to generate the correct function call.
json_regex_match:
- "(?s)<tool_call>(.*?)</tool_call>"
- "(?s)<tool_call>(.*?)"
replace_llm_results:
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
replace_function_results:
# Replace everything that is not JSON array or object
#
- key: '(?s)^[^{\[]*'
value: ""
- key: '(?s)[^}\]]*$'
value: ""
- key: "'([^']*?)'"
value: "_DQUOTE_${1}_DQUOTE_"
- key: '\\"'
value: "__TEMP_QUOTE__"
- key: "\'"
value: "'"
- key: "_DQUOTE_"
value: '"'
- key: "__TEMP_QUOTE__"
value: '"'
# Drop the scratchpad content from responses
- key: "(?s)<scratchpad>.*</scratchpad>"
value: ""
template:
chat: |
{{.Input -}}
<|im_start|>assistant
chat_message: |
<|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "tool"}}tool{{else if eq .RoleName "user"}}user{{end}}
{{- if .FunctionCall }}
<tool_call>
{{- else if eq .RoleName "tool" }}
<tool_response>
{{- end }}
{{- if .Content}}
{{.Content }}
{{- end }}
{{- if .FunctionCall}}
{{toJson .FunctionCall}}
{{- end }}
{{- if .FunctionCall }}
</tool_call>
{{- else if eq .RoleName "tool" }}
</tool_response>
{{- end }}<|im_end|>
completion: |
{{.Input}}
function: |-
<|im_start|>system
You are a function calling AI model.
Here are the available tools:
<tools>
{{range .Functions}}
{'type': 'function', 'function': {'name': '{{.Name}}', 'description': '{{.Description}}', 'parameters': {{toJson .Parameters}} }}
{{end}}
</tools>
You should call the tools provided to you sequentially
Please use <scratchpad> XML tags to record your reasoning and planning before you call the functions as follows:
<scratchpad>
{step-by-step reasoning and plan in bullet points}
</scratchpad>
For each function call return a json object with function name and arguments within <tool_call> XML tags as follows:
<tool_call>
{"arguments": <args-dict>, "name": <function-name>}
</tool_call><|im_end|>
{{.Input -}}
<|im_start|>assistant

35
aio/intel/vision.yaml Normal file
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backend: llama-cpp
context_size: 4096
mmap: false
f16: false
name: gpt-4-vision-preview
roles:
user: "USER:"
assistant: "ASSISTANT:"
system: "SYSTEM:"
mmproj: llava-v1.6-7b-mmproj-f16.gguf
parameters:
model: llava-v1.6-mistral-7b.Q5_K_M.gguf
temperature: 0.2
top_k: 40
top_p: 0.95
seed: -1
template:
chat: |
A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.
{{.Input}}
ASSISTANT:
download_files:
- filename: llava-v1.6-mistral-7b.Q5_K_M.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/llava-v1.6-mistral-7b.Q5_K_M.gguf
- filename: llava-v1.6-7b-mmproj-f16.gguf
uri: huggingface://cjpais/llava-1.6-mistral-7b-gguf/mmproj-model-f16.gguf
usage: |
curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "gpt-4-vision-preview",
"messages": [{"role": "user", "content": [{"type":"text", "text": "What is in the image?"}, {"type": "image_url", "image_url": {"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg" }}], "temperature": 0.9}]}'

6
assets.go Normal file
View File

@@ -0,0 +1,6 @@
package main
import "embed"
//go:embed backend-assets/*
var backendAssets embed.FS

View File

@@ -1,197 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
git ccache \
ca-certificates \
make cmake wget libopenblas-dev \
curl unzip \
libssl-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
# Install Go
RUN curl -L -s https://go.dev/dl/go${GO_VERSION}.linux-${TARGETARCH}.tar.gz | tar -C /usr/local -xz
ENV PATH=$PATH:/root/go/bin:/usr/local/go/bin:/usr/local/bin
# Install grpc compilers
RUN go install google.golang.org/protobuf/cmd/protoc-gen-go@v1.34.2 && \
go install google.golang.org/grpc/cmd/protoc-gen-go-grpc@1958fcbe2ca8bd93af633f11e97d44e567e945af
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
RUN if [ "${BACKEND}" = "opus" ]; then \
apt-get update && apt-get install -y --no-install-recommends libopus-dev pkg-config && \
apt-get clean && rm -rf /var/lib/apt/lists/*; \
fi
COPY . /LocalAI
RUN git config --global --add safe.directory /LocalAI
RUN cd /LocalAI && make protogen-go && make -C /LocalAI/backend/go/${BACKEND} build
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /LocalAI/backend/go/${BACKEND}/package/. ./

View File

@@ -1,281 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI
RUN <<'EOT' bash
set -euxo pipefail
if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
rm -rf /LocalAI/backend/cpp/ik-llama-cpp-*-build
fi
cd /LocalAI/backend/cpp/ik-llama-cpp
if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
# ARM64 / ROCm: build without x86 SIMD
make ik-llama-cpp-fallback
else
# ik_llama.cpp's IQK kernels require at least AVX2
make ik-llama-cpp-avx2
fi
EOT
# Copy libraries using a script to handle architecture differences
RUN make -BC /LocalAI/backend/cpp/ik-llama-cpp package
FROM scratch
# Copy all available binaries (the build process only creates the appropriate ones for the target architecture)
COPY --from=builder /LocalAI/backend/cpp/ik-llama-cpp/package/. ./

View File

@@ -1,292 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
ARG GRPC_BASE_IMAGE=${BASE_IMAGE}
# The grpc target does one thing, it builds and installs GRPC. This is in it's own layer so that it can be effectively cached by CI.
# You probably don't need to change anything here, and if you do, make sure that CI is adjusted so that the cache continues to work.
FROM ${GRPC_BASE_IMAGE} AS grpc
# This is a bit of a hack, but it's required in order to be able to effectively cache this layer in CI
ARG GRPC_MAKEFLAGS="-j4 -Otarget"
ARG GRPC_VERSION=v1.65.0
ARG CMAKE_FROM_SOURCE=false
# CUDA Toolkit 13.x compatibility: CMake 3.31.9+ fixes toolchain detection/arch table issues
ARG CMAKE_VERSION=3.31.10
ENV MAKEFLAGS=${GRPC_MAKEFLAGS}
WORKDIR /build
RUN apt-get update && \
apt-get install -y --no-install-recommends \
ca-certificates \
build-essential curl libssl-dev \
git wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# We install GRPC to a different prefix here so that we can copy in only the build artifacts later
# saves several hundred MB on the final docker image size vs copying in the entire GRPC source tree
# and running make install in the target container
RUN git clone --recurse-submodules --jobs 4 -b ${GRPC_VERSION} --depth 1 --shallow-submodules https://github.com/grpc/grpc && \
mkdir -p /build/grpc/cmake/build && \
cd /build/grpc/cmake/build && \
sed -i "216i\ TESTONLY" "../../third_party/abseil-cpp/absl/container/CMakeLists.txt" && \
cmake -DgRPC_INSTALL=ON -DgRPC_BUILD_TESTS=OFF -DCMAKE_INSTALL_PREFIX:PATH=/opt/grpc ../.. && \
make && \
make install && \
rm -rf /build
FROM ${BASE_IMAGE} AS builder
ARG CMAKE_FROM_SOURCE=false
ARG CMAKE_VERSION=3.31.10
# We can target specific CUDA ARCHITECTURES like --build-arg CUDA_DOCKER_ARCH='75;86;89;120'
ARG CUDA_DOCKER_ARCH
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
ARG CMAKE_ARGS
ENV CMAKE_ARGS=${CMAKE_ARGS}
ARG AMDGPU_TARGETS
ENV AMDGPU_TARGETS=${AMDGPU_TARGETS}
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG GO_VERSION=1.25.4
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache git \
ca-certificates \
make \
pkg-config libcurl4-openssl-dev \
curl unzip \
libssl-dev wget && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig && \
# Log which GPU architectures have rocBLAS kernel support
echo "rocBLAS library data architectures:" && \
(ls /opt/rocm*/lib/rocblas/library/Kernels* 2>/dev/null || ls /opt/rocm*/lib64/rocblas/library/Kernels* 2>/dev/null) | grep -oP 'gfx[0-9a-z+-]+' | sort -u || \
echo "WARNING: No rocBLAS kernel data found" \
; fi
RUN echo "TARGETARCH: $TARGETARCH"
# We need protoc installed, and the version in 22.04 is too old. We will create one as part installing the GRPC build below
# but that will also being in a newer version of absl which stablediffusion cannot compile with. This version of protoc is only
# here so that we can generate the grpc code for the stablediffusion build
RUN <<EOT bash
if [ "amd64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-x86_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
if [ "arm64" = "$TARGETARCH" ]; then
curl -L -s https://github.com/protocolbuffers/protobuf/releases/download/v27.1/protoc-27.1-linux-aarch_64.zip -o protoc.zip && \
unzip -j -d /usr/local/bin protoc.zip bin/protoc && \
rm protoc.zip
fi
EOT
# Install CMake (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${CMAKE_FROM_SOURCE}" = "true" ]; then
curl -L -s https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}.tar.gz -o cmake.tar.gz && tar xvf cmake.tar.gz && cd cmake-${CMAKE_VERSION} && ./configure && make && make install
else
apt-get update && \
apt-get install -y \
cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
COPY --from=grpc /opt/grpc /usr/local
COPY . /LocalAI
RUN <<'EOT' bash
set -euxo pipefail
if [[ -n "${CUDA_DOCKER_ARCH:-}" ]]; then
CUDA_ARCH_ESC="${CUDA_DOCKER_ARCH//;/\\;}"
export CMAKE_ARGS="${CMAKE_ARGS:-} -DCMAKE_CUDA_ARCHITECTURES=${CUDA_ARCH_ESC}"
echo "CMAKE_ARGS(env) = ${CMAKE_ARGS}"
rm -rf /LocalAI/backend/cpp/llama-cpp-*-build
fi
if [ "${TARGETARCH}" = "arm64" ] || [ "${BUILD_TYPE}" = "hipblas" ]; then
cd /LocalAI/backend/cpp/llama-cpp
make llama-cpp-fallback
make llama-cpp-grpc
make llama-cpp-rpc-server
else
cd /LocalAI/backend/cpp/llama-cpp
make llama-cpp-avx
make llama-cpp-avx2
make llama-cpp-avx512
make llama-cpp-fallback
make llama-cpp-grpc
make llama-cpp-rpc-server
fi
EOT
# Copy libraries using a script to handle architecture differences
RUN make -BC /LocalAI/backend/cpp/llama-cpp package
FROM scratch
# Copy all available binaries (the build process only creates the appropriate ones for the target architecture)
COPY --from=builder /LocalAI/backend/cpp/llama-cpp/package/. ./

View File

@@ -1,219 +0,0 @@
ARG BASE_IMAGE=ubuntu:24.04
FROM ${BASE_IMAGE} AS builder
ARG BACKEND=rerankers
ARG BUILD_TYPE
ENV BUILD_TYPE=${BUILD_TYPE}
ARG CUDA_MAJOR_VERSION
ARG CUDA_MINOR_VERSION
ARG SKIP_DRIVERS=false
ENV CUDA_MAJOR_VERSION=${CUDA_MAJOR_VERSION}
ENV CUDA_MINOR_VERSION=${CUDA_MINOR_VERSION}
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETARCH
ARG TARGETVARIANT
ARG UBUNTU_VERSION=2404
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential \
ccache \
ca-certificates \
espeak-ng \
curl \
libssl-dev \
git wget \
git-lfs \
unzip clang \
upx-ucl \
curl python3-pip \
python-is-python3 \
python3-dev llvm \
libnuma1 libgomp1 \
python3-venv make cmake && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user --upgrade pip
else
pip install --upgrade pip
fi
EOT
# Cuda
ENV PATH=/usr/local/cuda/bin:${PATH}
# HipBLAS requirements
ENV PATH=/opt/rocm/bin:${PATH}
# Vulkan requirements
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "vulkan" ] && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils wget gpg-agent && \
apt-get install -y libglm-dev cmake libxcb-dri3-0 libxcb-present0 libpciaccess0 \
libpng-dev libxcb-keysyms1-dev libxcb-dri3-dev libx11-dev g++ gcc \
libwayland-dev libxrandr-dev libxcb-randr0-dev libxcb-ewmh-dev \
git python-is-python3 bison libx11-xcb-dev liblz4-dev libzstd-dev \
ocaml-core ninja-build pkg-config libxml2-dev wayland-protocols python3-jsonschema \
clang-format qtbase5-dev qt6-base-dev libxcb-glx0-dev sudo xz-utils
if [ "amd64" = "$TARGETARCH" ]; then
wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
mkdir -p /opt/vulkan-sdk && \
mv 1.4.335.0 /opt/vulkan-sdk/ && \
cd /opt/vulkan-sdk/1.4.335.0 && \
./vulkansdk --no-deps --maxjobs \
vulkan-loader \
vulkan-validationlayers \
vulkan-extensionlayer \
vulkan-tools \
shaderc && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
rm -rf /opt/vulkan-sdk
fi
if [ "arm64" = "$TARGETARCH" ]; then
mkdir vulkan && cd vulkan && \
curl -L -o vulkan-sdk.tar.xz https://github.com/mudler/vulkan-sdk-arm/releases/download/1.4.335.0/vulkansdk-ubuntu-24.04-arm-1.4.335.0.tar.xz && \
tar -xvf vulkan-sdk.tar.xz && \
rm vulkan-sdk.tar.xz && \
cd 1.4.335.0 && \
cp -rfv aarch64/bin/* /usr/bin/ && \
cp -rfv aarch64/lib/* /usr/lib/aarch64-linux-gnu/ && \
cp -rfv aarch64/include/* /usr/include/ && \
cp -rfv aarch64/share/* /usr/share/ && \
cd ../.. && \
rm -rf vulkan
fi
ldconfig && \
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# CuBLAS requirements
RUN <<EOT bash
if ( [ "${BUILD_TYPE}" = "cublas" ] || [ "${BUILD_TYPE}" = "l4t" ] ) && [ "${SKIP_DRIVERS}" = "false" ]; then
apt-get update && \
apt-get install -y --no-install-recommends \
software-properties-common pciutils
if [ "amd64" = "$TARGETARCH" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/x86_64/cuda-keyring_1.1-1_all.deb
fi
if [ "arm64" = "$TARGETARCH" ]; then
if [ "${CUDA_MAJOR_VERSION}" = "13" ]; then
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/sbsa/cuda-keyring_1.1-1_all.deb
else
curl -O https://developer.download.nvidia.com/compute/cuda/repos/ubuntu${UBUNTU_VERSION}/arm64/cuda-keyring_1.1-1_all.deb
fi
fi
dpkg -i cuda-keyring_1.1-1_all.deb && \
rm -f cuda-keyring_1.1-1_all.deb && \
apt-get update && \
apt-get install -y --no-install-recommends \
cuda-nvcc-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcufft-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcurand-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcublas-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusparse-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} \
libcusolver-dev-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
if [ "${CUDA_MAJOR_VERSION}" = "13" ] && [ "arm64" = "$TARGETARCH" ]; then
apt-get install -y --no-install-recommends \
libcufile-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libcudnn9-cuda-${CUDA_MAJOR_VERSION} cuda-cupti-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION} libnvjitlink-${CUDA_MAJOR_VERSION}-${CUDA_MINOR_VERSION}
fi
apt-get clean && \
rm -rf /var/lib/apt/lists/*
fi
EOT
# https://github.com/NVIDIA/Isaac-GR00T/issues/343
RUN <<EOT bash
if [ "${BUILD_TYPE}" = "cublas" ] && [ "${TARGETARCH}" = "arm64" ]; then
wget https://developer.download.nvidia.com/compute/cudss/0.6.0/local_installers/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
dpkg -i cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0_0.6.0-1_arm64.deb && \
cp /var/cudss-local-tegra-repo-ubuntu${UBUNTU_VERSION}-0.6.0/cudss-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get -y install cudss cudss-cuda-${CUDA_MAJOR_VERSION} && \
wget https://developer.download.nvidia.com/compute/nvpl/25.5/local_installers/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
dpkg -i nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5_1.0-1_arm64.deb && \
cp /var/nvpl-local-repo-ubuntu${UBUNTU_VERSION}-25.5/nvpl-*-keyring.gpg /usr/share/keyrings/ && \
apt-get update && apt-get install -y nvpl
fi
EOT
# If we are building with clblas support, we need the libraries for the builds
RUN if [ "${BUILD_TYPE}" = "clblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
libclblast-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ] && [ "${SKIP_DRIVERS}" = "false" ]; then \
apt-get update && \
apt-get install -y --no-install-recommends \
hipblas-dev \
rocblas-dev && \
apt-get clean && \
rm -rf /var/lib/apt/lists/* && \
# I have no idea why, but the ROCM lib packages don't trigger ldconfig after they install, which results in local-ai and others not being able
# to locate the libraries. We run ldconfig ourselves to work around this packaging deficiency
ldconfig \
; fi
RUN if [ "${BUILD_TYPE}" = "hipblas" ]; then \
ln -s /opt/rocm-**/lib/llvm/lib/libomp.so /usr/lib/libomp.so \
; fi
# Install uv as a system package
RUN curl -LsSf https://astral.sh/uv/install.sh | UV_INSTALL_DIR=/usr/bin sh
ENV PATH="/root/.cargo/bin:${PATH}"
# Increase timeout for uv installs behind slow networks
ENV UV_HTTP_TIMEOUT=180
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
# Install grpcio-tools (the version in 22.04 is too old)
RUN <<EOT bash
if [ "${UBUNTU_VERSION}" = "2404" ]; then
pip install --break-system-packages --user grpcio-tools==1.71.0 grpcio==1.71.0
else
pip install grpcio-tools==1.71.0 grpcio==1.71.0
fi
EOT
COPY backend/python/${BACKEND} /${BACKEND}
COPY backend/backend.proto /${BACKEND}/backend.proto
COPY backend/python/common/ /${BACKEND}/common
COPY scripts/build/package-gpu-libs.sh /package-gpu-libs.sh
# Optional per-backend source build toggle (e.g. vllm on CPU can set
# FROM_SOURCE=true to compile against the build host SIMD instead of
# pulling a prebuilt wheel). Default empty — most backends ignore it.
ARG FROM_SOURCE=""
ENV FROM_SOURCE=${FROM_SOURCE}
RUN cd /${BACKEND} && PORTABLE_PYTHON=true make
# Package GPU libraries into the backend's lib directory
RUN mkdir -p /${BACKEND}/lib && \
TARGET_LIB_DIR="/${BACKEND}/lib" BUILD_TYPE="${BUILD_TYPE}" CUDA_MAJOR_VERSION="${CUDA_MAJOR_VERSION}" \
bash /package-gpu-libs.sh "/${BACKEND}/lib"
# Run backend-specific packaging if a package.sh exists
RUN if [ -f "/${BACKEND}/package.sh" ]; then \
cd /${BACKEND} && bash package.sh; \
fi
FROM scratch
ARG BACKEND=rerankers
COPY --from=builder /${BACKEND}/ /

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