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* feat(schema): add Conversation schema for chat history (#9432) Persist WebUI chat conversations server-side so browser refresh, private windows, or device changes preserve user history (issue #9432). This commit adds the on-disk representation: - Conversation holds id, name, model, opaque history, MCP / sampling settings, and timestamps. - ConversationsFile is the per-user list serialised to JSON. History is stored as json.RawMessage so the server stays agnostic to React message shapes (user / assistant / thinking / tool_call / tool_result mixed with text / image_url / audio_url / file attachments). Assisted-by: Claude:claude-opus-4-7 Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * feat(chathistory): add file-based per-user conversation store (#9432) File-backed persister for chat history. Each user's conversations live under {baseDir}/{userID}/conversations.json (anonymous/ when auth is disabled). Design choices: - In-memory cache backed by sync.Mutex so concurrent saves don't interleave writes. - Atomic write via tmp file + os.Rename so a crash mid-save never leaves a corrupted history. - ID validation regex blocks path-traversal payloads at the store boundary, in addition to the auth context constraint. Tests cover round-trip persistence across instances, user isolation, unsafe-ID rejection, bulk replace migration, and the anonymous fallback path. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * feat(api): expose chat conversation CRUD endpoints (#9432) Wire the chathistory store into the HTTP layer. New endpoints under /api/conversations: - GET /api/conversations list - POST /api/conversations upsert (id in body) - DELETE /api/conversations delete all - PUT /api/conversations/bulk replace entire set (localStorage migration) - GET /api/conversations/:id fetch one - PUT /api/conversations/:id upsert (id in path; path id wins over body) - DELETE /api/conversations/:id delete one All endpoints scope queries to the authenticated user via getUserID(c) - callers cannot impersonate other users by passing a user_id in the body. The endpoints are gated behind the new chat_history feature permission (default ON in APIFeatures), registered through the existing RouteFeatureRegistry so the unified feature middleware picks them up automatically. Application.ChatHistoryStore() returns nil when DisableWebUI is set or no persistence path is configured, in which case route registration is skipped entirely rather than registering handlers that always 503. Also adds the chat-history instruction entry and Swagger tag so the endpoint surfaces in /api/instructions and /swagger. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * feat(react-ui): sync chat history to server with localStorage fallback (#9432) useChat now probes /api/conversations on mount. When the endpoint responds 200, the server becomes the authoritative source: the hook merges remote conversations into local state and pushes per-chat PUT updates on each debounced save. When the endpoint 404s - older LocalAI deploys or the feature disabled - the hook silently keeps the old localStorage-only behaviour, so the change is backward-compatible. Migration: when the server is reachable but empty and the browser has local conversations with history, the hook fires a single PUT /api/conversations/bulk to seed the server. The atomic bulk endpoint avoids partial-upload states where a retry would skip already-uploaded entries. Delete operations propagate to the server when it's available; failures are silently swallowed so the local UI stays responsive on transient network errors. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * test(chathistory): rewrite tests in Ginkgo/Gomega The initial test file used the stdlib testing package (t.Fatalf / t.Errorf), which is forbidden by the forbidigo linter rule in .golangci.yml — LocalAI mandates Ginkgo/Gomega for all Go tests (see .agents/coding-style.md). Restructured the same six scenarios into Describe / Context / It blocks, with a chathistory_suite_test.go bootstrap that registers the Ginkgo fail handler. Test coverage is unchanged: basic CRUD round-trip, cross- instance persistence, user isolation, unsafe ID rejection (now via DescribeTable), bulk replace overwrite, and the anonymous fallback path. Assisted-by: Claude:claude-opus-4-7 Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * refactor(chathistory): switch store to GORM-backed authDB Addresses mudler's review on #9902. Chat history was the only per-user state in LocalAI sitting in a separate filesystem store instead of the shared GORM database — AgentStore and JobStore both live there. Move it onto Application.authDB so per-user state stays in one place. * ConversationRecord (GORM model) with composite primary key (user_id, conv_id) — React mints IDs locally with no global coordination so per-user uniqueness is the natural shape. * Store.New(db *gorm.DB) replaces Store.New(baseDir string). Save / Get / List / Delete / DeleteAll / ReplaceAll keep their signatures so HTTP handlers and the React UI are untouched. * ReplaceAll runs in a transaction with an Unscoped() pre-clear so a future retention sweep cannot resurrect a stale ID on re-upload. * gorm.DeletedAt in the schema means a future retention pruner is a one-line query — addresses the second half of the review (unbounded in-memory map). The map is gone: reads go straight to the DB. Trade-off worth flagging in the PR reply: chat history persistence now requires auth.Enabled = true (that's what initialises Application.authDB). With auth disabled the React UI transparently falls back to localStorage, the same path the original PR took on 404. Consistent with AgentStore / JobStore; if a "chat history always on" mode is preferred we can pull DB init out of auth.InitDB into a shared helper. Assisted-by: Claude:claude-opus-4-7 [Read Edit Bash] Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * refactor(schema): drop now-unused ConversationsFile envelope ConversationsFile was the JSON wrapper for the old file-based chat history store — a {Conversations: [...], UpdatedAt: ...} pair serialised to disk under {baseDir}/{userID}/conversations.json. The previous commit replaced that store with a GORM-backed one that writes rows directly as ConversationRecord, leaving the envelope without a consumer. Assisted-by: Claude:claude-opus-4-7 [Read Edit Bash] Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * test(chathistory): switch tests to testutil.SetupTestDB Mirror the AgentStore test setup: spin up a PostgreSQL 16 container via testutil.SetupTestDB(), construct a Store on top of it, exercise CRUD round-trips. The previous file-based fixtures (TempDir, filepath.Join checks) are no longer meaningful now that the store talks GORM. Tests are skipped on macOS (testcontainers needs Docker) and run on CI, same as the other GORM-backed suites in the repo. Also reframed two cases: * "unsafe IDs" → "malformed IDs" — the DB-backed store doesn't care about path traversal, but idRegex still rejects whitespace / control characters so IDs stay safe in logs and HTTP responses. * "anonymous user" no longer pins a directory path (no directory exists anymore); instead it checks the round-trip plus the per-user isolation guarantee. Added a DeleteAll round-trip to cover the bulk-clear endpoint. Assisted-by: Claude:claude-opus-4-7 [Read Edit Bash] Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> * test(chathistory): cover the conversation HTTP handlers The seven /api/conversations handlers had no tests. Inject the *chathistory.Store into the handlers instead of the whole Application and move the route table into RegisterChatHistoryRoutes, so a spec can drive the real registration and middleware chain (auth.Middleware plus the chat_history feature gate) against an in-memory SQLite auth database. The new specs cover 401 without credentials on every route, 403 when an admin revoked chat_history, the CRUD round trip, path id over body id, 400 on malformed ids and bodies, per-user isolation, bulk replace and delete-all, and that a nil store registers nothing (the UI then falls back to localStorage). The handlers' nil-store branches are gone: the routes are only registered with a store, so those branches could never run. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(chathistory): make deletions final with tombstones and versions A conversation deleted on one device came back as soon as a client with a stale copy wrote it again: Delete soft-deleted the row, and the next Save went through GORM's upsert, which cleared deleted_at and resurrected it for every device. The lookup that recovered CreatedAt also ran outside any transaction, so concurrent writers raced on it. The server is now authoritative over deletions: * Delete turns the row into a tombstone: content dropped, deleted_at set. It is idempotent, and deleting an id the server has not seen yet still records a tombstone, so a delete that overtakes the UI's in-flight debounced save of the same chat still wins. * Save runs in a transaction, refuses a tombstoned id with ErrDeleted (HTTP 410 Gone), and bumps the version with a single UPDATE ... SET version = version + 1 guarded by deleted_at IS NULL, so concurrent writers each count and a delete committed between the lookup and the write still wins. Two concurrent first writes of the same id retry once (ON CONFLICT DO NOTHING, then update). * Every row carries a server-assigned version (1 on the first save, +1 per write including the delete), returned to the client. A non-zero version tells the UI the server has seen a conversation, which is how it can tell a never-synced draft from a server-side deletion. * GET /api/conversations returns the tombstones under "deleted". * DeleteAll and ReplaceAll leave tombstones too. ReplaceAll no longer hard-deletes everything first; it upserts the payload, skips ids that were deleted (reported in "skipped"), and tombstones the rest. * createdAt/updatedAt are stored as the client sends them (only zero values are stamped), so clients compare updatedAt from their own clocks rather than against the server's. The store specs now run against PostgreSQL (testcontainers) and, with the auth tag, SQLite through auth.InitDB, since both back the auth database. The API specs cover a stale client reconnecting after a remote deletion. Swagger is regenerated with swag v1.16.6 (json.RawMessage fields get swaggertype), and the feature is documented, including that it needs user auth. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(react-ui): let the server decide which chats were deleted mergeRemoteAndLocal kept every chat that was only in the browser and let the server copy win for every shared id. A stale browser therefore uploaded chats deleted on another device as if they were new drafts, and a message sent while the list request was still in flight was replaced by the older server copy and then lost from localStorage too. The first load now reconciles with the server's tombstones and versions: * a chat the server lists under "deleted" is dropped locally; * a chat on both sides keeps the copy with the newer updatedAt, so an edit made during the load wins and is uploaded afterwards; * a chat only in the browser is uploaded only if it was never synced (no version). With a version the server has seen it and no longer has it, so it is dropped instead of resurrected (this also keeps one account's cached chats out of another account on a shared browser); * deletes made while the list is loading are queued and sent once it arrives. Saves record the version the server returns, and a 410 on save drops the chat locally instead of retrying it forever. Chats received from the server count as already sent, so adopting a server copy no longer echoes it straight back. The bulk localStorage migration is gone: it replaced the whole server set from a possibly stale browser, and the per-chat saves already upload never-synced drafts through the tombstone check. The Playwright spec drives each case against a stubbed /api/conversations that follows the server contract. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(chathistory): keep the LocalAI Assistant toggle on synced chats master's createNewChat sets localaiAssistant, but serializeChat did not send it and schema.Conversation had no field for it, so a chat with the Assistant mode on came back with it off after a reload from the server (and the local cache dropped it too). Add the field on both sides. The other fields createNewChat sets were already covered; a handler spec now round-trips all of them, and the UI spec checks the toggle on the way up and in the local cache. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(react-ui): scope chat cache per account, retry unconfirmed deletes Two gaps in the client half of server-side chat history, both found in review: The browser cache was one shared localStorage key. A draft that one account could not upload (a failed first save) stayed in it, and after that account signed out and another signed in, the reconcile kept the unversioned draft and the save pass uploaded it into the second account. The cache now lives under localai_chats_data:<user id>, Chat remounts its state when the account changes, and nothing is synced without a signed-in account. The shared key is left for browser-only use without auth and is not uploaded when signed in, because nothing tells which account it belongs to. Deletes were dropped locally and their DELETE errors swallowed; only deletes made while the first list was loading were queued, and not persisted. A delete made while the server was unreachable therefore came back with the next list. Deletes (single, delete all, and deletes on the Home page) are now kept as pending deletes in the account's cache until the server confirms them, override the server list in the reconcile, and are sent again on the next change, on the online event and on the next load. While a delete-all is pending no conversation is uploaded, so a chat started after it is not caught by it. The Playwright specs replay both review scenarios (account switch after a failed first save; delete and delete-all while offline) with counter-checks that the same account keeps and uploads its own draft and that a confirmed delete is neither re-sent nor resurrected. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(react-ui): persist cleared chats immediately Navigation cancels the debounced cache write and can restore unsynced chats after Clear all. Save the cleared list with its pending deletion before returning, and cover immediate navigation in the browser spec. Assisted-by: Codex:GPT-6 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * test(react-ui): make the chat history sync specs deterministic - "clear all persists before navigation" opened a single chat, and the menu offers no Clear all for one chat, so the spec timed out in every run. It now opens two unsynced chats and checks that neither survives. Reverting 03cd9c115's save in clearAllChats turns it red again. - "a delete the server confirmed is not sent again" reopened the page as soon as the server had the request, before the page had the answer; the unconfirmed delete was then rightly sent again (4 of 5 runs). It now waits until the cache holds no pending delete. Docs-Not-Needed: test-only change. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * fix(chathistory): keep the chat's reasoning effort on the server reasoningEffort (#12700, #12716) is part of the chat the UI syncs since the master merge, but schema.Conversation had no field for it, so the server dropped it and a reload from the server reset the setting. Add the field. The handler spec that round-trips every chat field now includes reasoningEffort. A schema test reads serializeChat in useChat.js and fails for any key the UI sends that schema.Conversation cannot hold, so the next such drift shows up as a failing test rather than in review (it reports reasoningEffort on the previous head). Swagger and docs updated. Assisted-by: Claude Code:claude-opus-5-5 Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> * test(chat): use Ginkgo for the schema drift guard The new drift guard uses testing methods forbidden by repository lint. Keep its field coverage and fail-fast parser checks in Ginkgo/Gomega. Assisted-by: nib:gpt-6.1-sol --------- Signed-off-by: TLoE419 <tloemizuchizu@gmail.com> Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de> Co-authored-by: TLoE419 <tloemizuchizu@gmail.com> Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com> Co-authored-by: mudler-agent <mudler-bot@c3os.io>
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LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
A small core, not a bundle. Each backend wraps a best-in-class engine (llama.cpp, vLLM, whisper.cpp, stable-diffusion, MLX...) in its own image, pulled only when a model needs it. You install nothing you don't use.
- Composable by design: backends are separate and pulled on demand, so you install only what your model needs
- Open and extensible: load any model, or build your own backend in any language against an open interface
- Drop-in API compatibility: OpenAI, Anthropic, and ElevenLabs APIs across every backend
- Any model, any modality: LLMs, vision, voice, image, and video behind one API
- 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
Created by Ettore Di Giacinto and maintained by the LocalAI team.
📖 Documentation | 💬 Discord | 💻 Quickstart | 🖼️ Models | ❓FAQ
Guided tour
https://github.com/user-attachments/assets/08cbb692-57da-48f7-963d-2e7b43883c18
Click to see more!
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
Quickstart
macOS
Note: The DMG is not signed by Apple. After installing, run:
sudo xattr -d com.apple.quarantine /Applications/LocalAI.app. See #6268 for details.
Containers (Docker, podman, ...)
Already ran LocalAI before? Use
docker start -i local-aito restart an existing container.
CPU only:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
NVIDIA GPU:
# 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
AMD GPU (ROCm):
docker run -ti --name local-ai -p 8080:8080 --device=/dev/kfd --device=/dev/dri --group-add=video localai/localai:latest-gpu-hipblas
Intel GPU (oneAPI):
docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
Vulkan GPU:
docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
Loading models
# 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
To work with a running LocalAI server from the terminal, start the built-in agent from another shell. It answers questions, reads your files and runs commands on your machine, asking you to approve anything that changes state. Inside a session, /models lists installed models and /model <name> switches between them. See the Terminal agent docs.
# Terminal 1
local-ai run llama-3.2-1b-instruct:q4_k_m
# Terminal 2
local-ai chat --model llama-3.2-1b-instruct:q4_k_m
Automatic Backend Detection: LocalAI automatically detects your GPU capabilities and downloads the appropriate backend. For advanced options, see GPU Acceleration.
For more details, see the Getting Started guide.
Latest News
- October 2026: LocalAI 4.11.0 — Audio scenes with transcription, speaker labels, and sound detection. Also the Decisions API (
/v1/systemone), model failover chains, signed OCI galleries, and Kimodo text-to-animation. Release notes - September 2026: LocalAI 4.10.0 — A fleet operations dashboard, one credentials file for private model sources, and
local-ai benchmarkfor measuring model latency and throughput. Release notes - August 2026: LocalAI 4.9.0 — Deny-by-default authentication, opt-in chat context compression, unified model and backend management, and MiniMax-H3 video generation with audio. Release notes
- August 2026: LocalAI 4.8.0 — Introducing vllm.cpp (alpha development builds), image-to-3D generation with a built-in viewer, and
audio.cppfor speech, transcription, VAD, diarization, source separation and sound generation. Release notes - July 2026: LocalAI 4.7.0 — Managed voice cloning profiles, local video and talking-avatar generation, and interleaved reasoning with tool calls. Release notes
- July 2026: LocalAI 4.6.0 — AMD ROCm fixes, predictable realtime pipeline warmup, conversation forking, and more reliable distributed model loading. Release notes
- June 2026: LocalAI 4.5.0 — Native depth estimation and sound-event detection, NER-based PII filtering, and speaker-aware realtime conversations with automatic history compaction. Release notes
Older news
- June 2026: New native biometric backends from the LocalAI team: voice-detect.cpp for speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion) and face-detect.cpp for face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace). Both are from-scratch C++/ggml engines with no Python or onnxruntime at inference, self-contained GGUF weights, bit-exact parity with the reference, and GPU cuDNN parity, replacing the heavier Python
insightfaceandspeaker-recognitionbackends (PR #10441). - June 2026: New realtime voice assistant demo (a tiny Go client for the Realtime API with a full talk-back voice loop and tool calling), plus streaming of the realtime LLM / TTS / transcription pipeline stages and configurable WebRTC ICE candidates.
- June 2026: Big speech push: the parakeet.cpp ASR engine gains NeMo-faithful segment timestamps, a multilingual streaming Nemotron-3.5 model, dynamic batching for concurrent transcription and CUDA graphs; the new CrispASR backend adds multi-architecture ASR + TTS, and 60 Piper TTS voices across 42 languages land in the gallery (plus per-request TTS instructions and params).
- June 2026: New backends and models: locate-anything.cpp for open-vocabulary object detection via ggml, Ideogram4 image generation in stablediffusion-ggml, llama.cpp video input, and the Gemma 4 QAT family with MTP speculative-decoding pairs. Plus an interactive CLI chat mode and RAG source citations in agent responses.
- June 2026: Distributed mode hardening: prefix-cache-aware routing, a production-ready request router with auto-sized embedding/rerank batches, ds4 layer-split distributed inference, NATS JWT auth + TLS/mTLS, and resumable file uploads.
- May 2026: LocalAI 4.3.0 -
llama.cppprompt cache on by default (repeated system prompts collapse from minutes to seconds), keyless cosign signing of backend OCI images, per-API-key + per-user usage attribution, Distributed v3 with per-request replica routing. Release notes - May 2026: LocalAI 4.2.0 - LocalAI sees and hears: voice recognition, face recognition + antispoofing liveness, speaker diarization. Plus drop-in Ollama API, video generation, redesigned UI with i18n + admin-configurable branding, vLLM at feature parity with llama.cpp, and 11 new backends. Release notes
- April 2026: LocalAI 4.1.0 - LocalAI becomes a control tower: distributed cluster mode with VRAM-aware smart routing + autoscaling, multi-user platform with OIDC and API keys, per-user quotas with predictive analytics, in-UI fine-tuning with TRL (auto-export to GGUF), on-the-fly quantization backend, visual pipeline editor. Release notes
- March 2026: LocalAI 4.0.0 - native agentic orchestration with the new Agenthub community hub, full React UI rewrite with Canvas mode, MCP Apps + client-side with tool streaming, WebRTC realtime audio, MLX-distributed. Release notes
- February 2026: Realtime API for audio-to-audio with tool calling, ACE-Step 1.5 support
- 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
- December 2025: Dynamic Memory Resource reclaimer, Automatic multi-GPU model fitting (llama.cpp), Vibevoice backend
- November 2025: Import models via URL, Multiple chats and history
- October 2025: Model Context Protocol (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
For older news and full release notes, see GitHub Releases and the blog.
Features
- Text generation (
llama.cpp,transformers,vllm... and more) - Text to Audio
- Audio to Text
- Image generation
- OpenAI-compatible tools API
- Realtime API (Speech-to-speech)
- Embeddings generation
- Constrained grammars
- Download models from Huggingface
- Vision API
- Object Detection
- Reranker API
- P2P Inferencing
- Distributed Mode — Horizontal scaling with PostgreSQL + NATS
- Model Context Protocol (MCP)
- Built-in Agents — Autonomous AI agents with tool use, RAG, skills, SSE streaming, and Agent Hub
- Backend Gallery — Install/remove backends on the fly via OCI images
- Voice Activity Detection (Silero-VAD)
- Integrated WebUI
Supported Backends & Acceleration
LocalAI supports 60+ backends including llama.cpp, vLLM, SGLang, 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.
See the full Backend & Model Compatibility Table and GPU Acceleration guide.
Backends built by us
Most backends wrap a best-in-class upstream engine. A handful of them are native C/C++/GGML engines (no Python at inference) developed and maintained by the LocalAI project itself:
| Backend | What it does |
|---|---|
| vllm.cpp | From-scratch C++20 port of vLLM for text generation: paged KV cache, continuous batching, prefix caching, safetensors + GGUF loading, engine-enforced structured output, on CPU, CUDA, Metal and Vulkan. Also serves MiniMax-H3 joint video+audio generation |
| parakeet.cpp | C++/GGML port of NVIDIA NeMo Parakeet ASR (tdt/ctc/rnnt/hybrid), with cache-aware streaming transcription |
| moss-transcribe.cpp | C++/GGML port of OpenMOSS MOSS-Transcribe-Diarize: joint long-form transcription, speaker diarization and timestamping in a single pass |
| moss-tts.cpp | C++/GGML port of the OpenMOSS MOSS-TTS family: text-to-speech (MOSS-TTS-Local v1.5, 48 kHz stereo) with reference-audio voice cloning, through the MOSS-Audio-Tokenizer neural codec |
| magpie-tts.cpp | C++/GGML port of NVIDIA's Magpie TTS Multilingual 357M: 22.05 kHz mono text-to-speech in 5 voices and 9+ languages, with the NanoCodec neural codec and tokenizer/G2P embedded in a single GGUF |
| ced.cpp | C++/GGML port of the CED audio-tagging models: sound-event classification (527-class AudioSet) over REST and the realtime API for live recognition |
| voice-detect.cpp | Speaker recognition and voice analysis (ECAPA-TDNN, WeSpeaker, ERes2Net, CAM++, wav2vec2 age/gender/emotion), replacing the Python speaker-recognition backend |
| voxtral-tts.c | Mistral Voxtral-4B-TTS text-to-speech in pure C: 20 preset voices across 9 languages, 24 kHz WAV output, no dependencies beyond libc |
| vibevoice.cpp | Native port of Microsoft VibeVoice for TTS (voice cloning) and long-form ASR with speaker diarization |
| rf-detr.cpp | Native RF-DETR object detection and instance segmentation |
| locate-anything.cpp | Open-vocabulary object detection and visual grounding (LocateAnything-3B) |
| depth-anything.cpp | Depth Anything 3 monocular metric depth + camera pose estimation |
| face-detect.cpp | Face detection, recognition, demographics and anti-spoofing (SCRFD/ArcFace, YuNet/SFace), replacing the Python insightface backend |
| free-splatter.cpp | Pose-free 3D reconstruction (FreeSplatter): turns a handful of plain photos into 3D Gaussians, no camera poses or GPU required |
| trellis2.cpp | C++/GGML port of Microsoft TRELLIS.2: single-image to textured 3D mesh (GLB with PBR materials) |
| gem-x.cpp | Live human motion capture with SOMA and SMPL pose streams (CPU/Vulkan) |
| kimodo.cpp | C++/GGML text-to-motion on CPU and Vulkan, exported as animated skeleton GLB |
| privacy-filter.cpp | Standalone GGML PII/NER token-classification engine powering LocalAI's PII redaction tier |
| LocalVQE | Joint acoustic echo cancellation, noise suppression, and dereverberation |
| local-store | Local-first vector database for embeddings (shipped in-tree) |
We also maintain apex-quant, a per-tensor, per-layer quantization recipe for Mixture-of-Experts models that exploits their structural sparsity to produce GGUFs matching or beating Q8_0 quality - and they run out of the box on stock llama.cpp.
Resources
- Documentation
- LLM fine-tuning guide
- Build from source
- Kubernetes installation
- Integrations & community projects
- Installation video walkthrough
- Blog: release write-ups, benchmarks and engineering notes
- Examples — including the realtime voice assistant demo (Go client for the Realtime API with tool calling)
Team
LocalAI is maintained by a small team of humans, together with the wider community of contributors.
- Ettore Di Giacinto — original author and project lead
- Richard Palethorpe — maintainer
A huge thank you to everyone who contributes code, reviews PRs, files issues, and helps users in Discord — LocalAI is a community-driven project and wouldn't exist without you. See the full contributors list.
Citation
If you utilize this repository, data in a downstream project, please consider citing it with:
@misc{localai,
author = {Ettore Di Giacinto},
title = {LocalAI: The free, Open source OpenAI alternative},
year = {2023},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/go-skynet/LocalAI}},
Sponsors
Do you find LocalAI useful?
Support the project by becoming a backer or sponsor. Your logo will show up here with a link to your website.
A huge thank you to our generous sponsors who support this project covering CI expenses, and our Sponsor list:
Past sponsors
Individual sponsors
A special thanks to individual sponsors, a full list is on GitHub and buymeacoffee. Special shout out to drikster80 for being generous. Thank you everyone!
License
LocalAI is a community-driven project created by Ettore Di Giacinto and maintained by the LocalAI team.
MIT - Author Ettore Di Giacinto mudler@localai.io
Acknowledgements
LocalAI couldn't have been built without the help of great software already available from the community. Thank you!
- llama.cpp
- https://github.com/tatsu-lab/stanford_alpaca
- https://github.com/cornelk/llama-go for the initial ideas
- https://github.com/antimatter15/alpaca.cpp
- https://github.com/EdVince/Stable-Diffusion-NCNN
- https://github.com/ggerganov/whisper.cpp
- https://github.com/rhasspy/piper
- exo for the MLX distributed auto-parallel sharding implementation
Contributors
This is a community project, a special thanks to our contributors!