Merge branch 'master' into feat-request-middleware

.github/workflows/image.yml

@@ -362,16 +362,16 @@ jobs:
             base-image: "ubuntu:22.04"
             skip-drivers: 'false'
             makeflags: "--jobs=4 --output-sync=target"
-          - build-type: 'cublas'
-            cuda-major-version: "12"
-            cuda-minor-version: "0"
-            platforms: 'linux/arm64'
-            tag-latest: 'false'
-            tag-suffix: '-nvidia-l4t-arm64-core'
-            latest-image: 'latest-nvidia-l4t-arm64-core'
-            ffmpeg: 'true'
-            image-type: 'core'
-            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
-            runs-on: 'arc-runner-set'
-            makeflags: "--jobs=4 --output-sync=target"
-            skip-drivers: 'true'
+          # - build-type: 'cublas'
+          #   cuda-major-version: "12"
+          #   cuda-minor-version: "0"
+          #   platforms: 'linux/arm64'
+          #   tag-latest: 'false'
+          #   tag-suffix: '-nvidia-l4t-arm64-core'
+          #   latest-image: 'latest-nvidia-l4t-arm64-core'
+          #   ffmpeg: 'true'
+          #   image-type: 'core'
+          #   base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+          #   runs-on: 'arc-runner-set'
+          #   makeflags: "--jobs=4 --output-sync=target"
+          #   skip-drivers: 'true'

Makefile

@@ -8,7 +8,7 @@ DETECT_LIBS?=true
 # llama.cpp versions
 GOLLAMA_REPO?=https://github.com/go-skynet/go-llama.cpp
 GOLLAMA_VERSION?=2b57a8ae43e4699d3dc5d1496a1ccd42922993be
-CPPLLAMA_VERSION?=ebdee9478ca7ba65497b9b96f7457698c6ee5115
+CPPLLAMA_VERSION?=d79d8f39b4da6deca4aea8bf130c6034c482b320
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggerganov/whisper.cpp

README.md

@@ -126,17 +126,18 @@ If you want to help and contribute, issues up for grabs: https://github.com/mudl
 
 ## 🚀 [Features](https://localai.io/features/)
 
-- 📖 [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 generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `transformers`, `vllm` ... [: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)
+- 🎨 [Image generation](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/)
+- 🔊 Voice activity detection (Silero-VAD support)
 - 🌍 Integrated WebUI!
 
 ## 💻 Usage

backend/cpp/llama/patches/01-llava.patch

@@ -1,13 +1,13 @@
 diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
-index 342042ff..224db9b5 100644
+index 3cd0d2fa..6c5e811a 100644
 --- a/examples/llava/clip.cpp
 +++ b/examples/llava/clip.cpp
-@@ -2419,7 +2419,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
-             struct ggml_tensor * patches = ggml_graph_get_tensor(gf, "patches");
-             int* patches_data = (int*)malloc(ggml_nbytes(patches));
-             for (int i = 0; i < num_patches; i++) {
--                patches_data[i] = i + 1;
-+                patches_data[i] = i;
-             }
-             ggml_backend_tensor_set(patches, patches_data, 0, ggml_nbytes(patches));
-             free(patches_data);
+@@ -2608,7 +2608,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
+                 struct ggml_tensor * patches = ggml_graph_get_tensor(gf, "patches");
+                 int* patches_data = (int*)malloc(ggml_nbytes(patches));
+                 for (int i = 0; i < num_patches; i++) {
+-                    patches_data[i] = i + 1;
++                    patches_data[i] = i;
+                 }
+                 ggml_backend_tensor_set(patches, patches_data, 0, ggml_nbytes(patches));
+                 free(patches_data);

docs/content/docs/reference/nvidia-l4t.md

@@ -0,0 +1,35 @@
+
++++
+disableToc = false
+title = "Running on Nvidia ARM64"
+weight = 27
++++
+
+LocalAI can be run on Nvidia ARM64 devices, such as the Jetson Nano, Jetson Xavier NX, and Jetson AGX Xavier. The following instructions will guide you through building the LocalAI container for Nvidia ARM64 devices.
+
+## Prerequisites
+
+- Docker engine installed (https://docs.docker.com/engine/install/ubuntu/)
+- Nvidia container toolkit installed (https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html#installing-with-ap)
+
+## Build the container
+
+Build the LocalAI container for Nvidia ARM64 devices using the following command:
+
+```bash
+git clone https://github.com/mudler/LocalAI
+
+cd LocalAI
+
+docker build --build-arg SKIP_DRIVERS=true --build-arg BUILD_TYPE=cublas --build-arg BASE_IMAGE=nvcr.io/nvidia/l4t-jetpack:r36.4.0 --build-arg IMAGE_TYPE=core -t localai-orin .
+```
+
+## Usage
+
+Run the LocalAI container on Nvidia ARM64 devices using the following command, where `/data/models` is the directory containing the models:
+
+```bash
+docker run -e DEBUG=true -p 8080:8080 -v /data/models:/build/models  -ti --restart=always --name local-ai --runtime nvidia --gpus all localai-orin
+```
+
+Note: `/data/models` is the directory containing the models. You can replace it with the directory containing your models.