[dropme

] quick CI check

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

.github/workflows/backend.yml

@@ -105,6 +105,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2404'
+          - build-type: 'cublas'
+            cuda-major-version: "12"
+            cuda-minor-version: "9"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-12-pocket-tts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:24.04"
+            skip-drivers: 'false'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2404'
           - build-type: 'cublas'
             cuda-major-version: "12"
             cuda-minor-version: "0"
@@ -340,6 +353,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2404'
+          - build-type: 'cublas'
+            cuda-major-version: "13"
+            cuda-minor-version: "0"
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-nvidia-cuda-13-pocket-tts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:24.04"
+            skip-drivers: 'false'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2404'
           - build-type: 'cublas'
             cuda-major-version: "13"
             cuda-minor-version: "0"
@@ -405,6 +431,19 @@ jobs:
             backend: "vibevoice"
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
+          - build-type: 'l4t'
+            cuda-major-version: "13"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-nvidia-l4t-cuda-13-arm64-pocket-tts'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: "ubuntu:24.04"
+            skip-drivers: 'false'
+            ubuntu-version: '2404'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
           - build-type: 'l4t'
             cuda-major-version: "13"
             cuda-minor-version: "0"
@@ -641,6 +680,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2404'
+          - build-type: 'hipblas'
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-rocm-hipblas-pocket-tts'
+            runs-on: 'arc-runner-set'
+            base-image: "rocm/dev-ubuntu-24.04:6.4.4"
+            skip-drivers: 'false'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2404'
           - build-type: 'hipblas'
             cuda-major-version: ""
             cuda-minor-version: ""
@@ -772,6 +824,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2204'
+          - build-type: 'l4t'
+            cuda-major-version: "12"
+            cuda-minor-version: "0"
+            platforms: 'linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-nvidia-l4t-pocket-tts'
+            runs-on: 'ubuntu-24.04-arm'
+            base-image: "nvcr.io/nvidia/l4t-jetpack:r36.4.0"
+            skip-drivers: 'true'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2204'
           - build-type: 'l4t'
             cuda-major-version: "12"
             cuda-minor-version: "0"
@@ -825,6 +890,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2404'
+          - build-type: 'intel'
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64'
+            tag-latest: 'auto'
+            tag-suffix: '-gpu-intel-pocket-tts'
+            runs-on: 'arc-runner-set'
+            base-image: "intel/oneapi-basekit:2025.3.0-0-devel-ubuntu24.04"
+            skip-drivers: 'false'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2404'
           - build-type: 'intel'
             cuda-major-version: ""
             cuda-minor-version: ""
@@ -1278,6 +1356,19 @@ jobs:
             dockerfile: "./backend/Dockerfile.python"
             context: "./"
             ubuntu-version: '2404'
+          - build-type: ''
+            cuda-major-version: ""
+            cuda-minor-version: ""
+            platforms: 'linux/amd64,linux/arm64'
+            tag-latest: 'auto'
+            tag-suffix: '-cpu-pocket-tts'
+            runs-on: 'ubuntu-latest'
+            base-image: "ubuntu:24.04"
+            skip-drivers: 'false'
+            backend: "pocket-tts"
+            dockerfile: "./backend/Dockerfile.python"
+            context: "./"
+            ubuntu-version: '2404'
   backend-jobs-darwin:
     uses: ./.github/workflows/backend_build_darwin.yml
     strategy:

.github/workflows/image-pr.yml

@@ -41,7 +41,7 @@
               platforms: 'linux/amd64'
               tag-latest: 'false'
               tag-suffix: '-gpu-nvidia-cuda-12'
-              runs-on: 'ubuntu-latest'
+              runs-on: 'bigger-runner'
               base-image: "ubuntu:24.04"
               makeflags: "--jobs=3 --output-sync=target"
               ubuntu-version: '2404'
@@ -51,7 +51,7 @@
               platforms: 'linux/amd64'
               tag-latest: 'false'
               tag-suffix: '-gpu-nvidia-cuda-13'
-              runs-on: 'ubuntu-latest'
+              runs-on: 'bigger-runner'
               base-image: "ubuntu:22.04"
               makeflags: "--jobs=3 --output-sync=target"
               ubuntu-version: '2404'
@@ -61,7 +61,7 @@
               tag-suffix: '-hipblas'
               base-image: "rocm/dev-ubuntu-24.04:6.4.4"
               grpc-base-image: "ubuntu:24.04"
-              runs-on: 'ubuntu-latest'
+              runs-on: 'bigger-runner'
               makeflags: "--jobs=3 --output-sync=target"
               ubuntu-version: '2404'
             - build-type: 'sycl'
@@ -70,14 +70,14 @@
               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'
+              runs-on: 'bigger-runner'
               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'
+              runs-on: 'bigger-runner'
               base-image: "ubuntu:24.04"
               makeflags: "--jobs=4 --output-sync=target"
               ubuntu-version: '2404'

.github/workflows/test-extra.yml

@@ -265,4 +265,23 @@ jobs:
       - 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
+          make --jobs=5 --output-sync=target -C backend/python/moonshine test
+  tests-pocket-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
+          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

Dockerfile

@@ -42,22 +42,22 @@ RUN <<EOT bash
             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" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
+            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
+            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
+            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
             mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.328.1 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.328.1 && \
+            mv 1.4.335.0 /opt/vulkan-sdk/ && \
+            cd /opt/vulkan-sdk/1.4.335.0 && \
             ./vulkansdk --no-deps --maxjobs \
                 vulkan-loader \
                 vulkan-validationlayers \
                 vulkan-extensionlayer \
                 vulkan-tools \
                 shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
             rm -rf /opt/vulkan-sdk
         fi
         if [ "arm64" = "$TARGETARCH" ]; then

Makefile

@@ -1,5 +1,5 @@
 # Disable parallel execution for backend builds
-.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/stablediffusion-ggml-darwin backends/vllm backends/moonshine
+.NOTPARALLEL: backends/diffusers backends/llama-cpp backends/piper backends/stablediffusion-ggml backends/whisper backends/faster-whisper backends/silero-vad backends/local-store backends/huggingface backends/rfdetr backends/kitten-tts backends/kokoro backends/chatterbox backends/llama-cpp-darwin backends/neutts build-darwin-python-backend build-darwin-go-backend backends/mlx backends/diffuser-darwin backends/mlx-vlm backends/mlx-audio backends/stablediffusion-ggml-darwin backends/vllm backends/moonshine backends/pocket-tts
 
 GOCMD=go
 GOTEST=$(GOCMD) test
@@ -9,7 +9,7 @@ LAUNCHER_BINARY_NAME=local-ai-launcher
 
 CUDA_MAJOR_VERSION?=13
 CUDA_MINOR_VERSION?=0
-UBUNTU_VERSION?=2204
+UBUNTU_VERSION?=2404
 UBUNTU_CODENAME?=noble
 
 GORELEASER?=
@@ -316,6 +316,7 @@ prepare-test-extra: protogen-python
 	$(MAKE) -C backend/python/vllm
 	$(MAKE) -C backend/python/vibevoice
 	$(MAKE) -C backend/python/moonshine
+	$(MAKE) -C backend/python/pocket-tts
 
 test-extra: prepare-test-extra
 	$(MAKE) -C backend/python/transformers test
@@ -324,6 +325,7 @@ test-extra: prepare-test-extra
 	$(MAKE) -C backend/python/vllm test
 	$(MAKE) -C backend/python/vibevoice test
 	$(MAKE) -C backend/python/moonshine test
+	$(MAKE) -C backend/python/pocket-tts test
 
 DOCKER_IMAGE?=local-ai
 DOCKER_AIO_IMAGE?=local-ai-aio
@@ -447,17 +449,16 @@ BACKEND_FASTER_WHISPER = faster-whisper|python|.|false|true
 BACKEND_COQUI = coqui|python|.|false|true
 BACKEND_BARK = bark|python|.|false|true
 BACKEND_EXLLAMA2 = exllama2|python|.|false|true
-
-# Python backends with ./backend context
-BACKEND_RFDETR = rfdetr|python|./backend|false|true
-BACKEND_KITTEN_TTS = kitten-tts|python|./backend|false|true
-BACKEND_NEUTTS = neutts|python|./backend|false|true
-BACKEND_KOKORO = kokoro|python|./backend|false|true
-BACKEND_VLLM = vllm|python|./backend|false|true
-BACKEND_DIFFUSERS = diffusers|python|./backend|--progress=plain|true
-BACKEND_CHATTERBOX = chatterbox|python|./backend|false|true
-BACKEND_VIBEVOICE = vibevoice|python|./backend|--progress=plain|true
-BACKEND_MOONSHINE = moonshine|python|./backend|false|true
+BACKEND_RFDETR = rfdetr|python|.|false|true
+BACKEND_KITTEN_TTS = kitten-tts|python|.|false|true
+BACKEND_NEUTTS = neutts|python|.|false|true
+BACKEND_KOKORO = kokoro|python|.|false|true
+BACKEND_VLLM = vllm|python|.|false|true
+BACKEND_DIFFUSERS = diffusers|python|.|--progress=plain|true
+BACKEND_CHATTERBOX = chatterbox|python|.|false|true
+BACKEND_VIBEVOICE = vibevoice|python|.|--progress=plain|true
+BACKEND_MOONSHINE = moonshine|python|.|false|true
+BACKEND_POCKET_TTS = pocket-tts|python|.|false|true
 
 # Helper function to build docker image for a backend
 # Usage: $(call docker-build-backend,BACKEND_NAME,DOCKERFILE_TYPE,BUILD_CONTEXT,PROGRESS_FLAG,NEEDS_BACKEND_ARG)
@@ -503,12 +504,13 @@ $(eval $(call generate-docker-build-target,$(BACKEND_DIFFUSERS)))
 $(eval $(call generate-docker-build-target,$(BACKEND_CHATTERBOX)))
 $(eval $(call generate-docker-build-target,$(BACKEND_VIBEVOICE)))
 $(eval $(call generate-docker-build-target,$(BACKEND_MOONSHINE)))
+$(eval $(call generate-docker-build-target,$(BACKEND_POCKET_TTS)))
 
 # Pattern rule for docker-save targets
 docker-save-%: backend-images
 	docker save local-ai-backend:$* -o backend-images/$*.tar
 
-docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-bark docker-build-chatterbox docker-build-vibevoice docker-build-exllama2 docker-build-moonshine
+docker-build-backends: docker-build-llama-cpp docker-build-rerankers docker-build-vllm docker-build-transformers docker-build-diffusers docker-build-kokoro docker-build-faster-whisper docker-build-coqui docker-build-bark docker-build-chatterbox docker-build-vibevoice docker-build-exllama2 docker-build-moonshine docker-build-pocket-tts
 
 ########################################################
 ### END Backends

README.md

@@ -111,6 +111,8 @@
 
 ## 💻 Quickstart
 
+> ⚠️ **Note:** The `install.sh` script is currently experiencing issues due to the heavy changes currently undergoing in LocalAI and may produce broken or misconfigured installations. Please use Docker installation (see below) or manual binary installation until [issue #8032](https://github.com/mudler/LocalAI/issues/8032) is resolved.
+
 Run the installer script:
 
 ```bash
@@ -128,7 +130,7 @@ For more installation options, see [Installer Options](https://localai.io/instal
 
 > Note: the DMGs are not signed by Apple as quarantined. See https://github.com/mudler/LocalAI/issues/6268 for a workaround, fix is tracked here: https://github.com/mudler/LocalAI/issues/6244
 
-Or run with docker:
+### Containers (Docker, podman, ...)
 
 > **💡 Docker Run vs Docker Start**
 > 
@@ -137,13 +139,13 @@ Or run with docker:
 > 
 > If you've already run LocalAI before and want to start it again, use: `docker start -i local-ai`
 
-### CPU only image:
+#### CPU only image:
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest
 ```
 
-### NVIDIA GPU Images:
+#### NVIDIA GPU Images:
 
 ```bash
 # CUDA 13.0
@@ -160,25 +162,25 @@ docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nv
 docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-nvidia-l4t-arm64-cuda-13
 ```
 
-### AMD GPU Images (ROCm):
+#### AMD GPU Images (ROCm):
 
 ```bash
 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 Images (oneAPI):
+#### Intel GPU Images (oneAPI):
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 --device=/dev/dri/card1 --device=/dev/dri/renderD128 localai/localai:latest-gpu-intel
 ```
 
-### Vulkan GPU Images:
+#### Vulkan GPU Images:
 
 ```bash
 docker run -ti --name local-ai -p 8080:8080 localai/localai:latest-gpu-vulkan
 ```
 
-### AIO Images (pre-downloaded models):
+#### AIO Images (pre-downloaded models):
 
 ```bash
 # CPU version
@@ -295,6 +297,7 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
 | **silero-vad** | Voice Activity Detection | CPU |
 | **neutts** | Text-to-speech with voice cloning | CUDA 12/13, ROCm, CPU |
 | **vibevoice** | Real-time TTS with voice cloning | CUDA 12/13, ROCm, Intel, CPU |
+| **pocket-tts** | Lightweight CPU-based TTS | CUDA 12/13, ROCm, Intel, CPU |
 
 ### Image & Video Generation
 | Backend | Description | Acceleration Support |
@@ -316,8 +319,8 @@ LocalAI supports a comprehensive range of AI backends with multiple acceleration
 |-------------------|-------------------|------------------|
 | **NVIDIA CUDA 12** | All CUDA-compatible backends | Nvidia hardware |
 | **NVIDIA CUDA 13** | All CUDA-compatible backends | Nvidia hardware |
-| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts, vibevoice | AMD Graphics |
-| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark, vibevoice | Intel Arc, Intel iGPUs |
+| **AMD ROCm** | llama.cpp, whisper, vllm, transformers, diffusers, rerankers, coqui, kokoro, bark, neutts, vibevoice, pocket-tts | AMD Graphics |
+| **Intel oneAPI** | llama.cpp, whisper, stablediffusion, vllm, transformers, diffusers, rfdetr, rerankers, exllama2, coqui, kokoro, bark, vibevoice, pocket-tts | Intel Arc, Intel iGPUs |
 | **Apple Metal** | llama.cpp, whisper, diffusers, MLX, MLX-VLM, bark-cpp | Apple M1/M2/M3+ |
 | **Vulkan** | llama.cpp, whisper, stablediffusion | Cross-platform GPUs |
 | **NVIDIA Jetson (CUDA 12)** | llama.cpp, whisper, stablediffusion, diffusers, rfdetr | ARM64 embedded AI (AGX Orin, etc.) |

backend/Dockerfile.golang

@@ -47,22 +47,22 @@ RUN <<EOT bash
             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" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
+            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
+            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
+            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
             mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.328.1 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.328.1 && \
+            mv 1.4.335.0 /opt/vulkan-sdk/ && \
+            cd /opt/vulkan-sdk/1.4.335.0 && \
             ./vulkansdk --no-deps --maxjobs \
                 vulkan-loader \
                 vulkan-validationlayers \
                 vulkan-extensionlayer \
                 vulkan-tools \
                 shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
             rm -rf /opt/vulkan-sdk
         fi
         if [ "arm64" = "$TARGETARCH" ]; then

backend/Dockerfile.llama-cpp

@@ -104,22 +104,22 @@ RUN <<EOT bash
             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" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
+            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
+            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
+            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
             mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.328.1 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.328.1 && \
+            mv 1.4.335.0 /opt/vulkan-sdk/ && \
+            cd /opt/vulkan-sdk/1.4.335.0 && \
             ./vulkansdk --no-deps --maxjobs \
                 vulkan-loader \
                 vulkan-validationlayers \
                 vulkan-extensionlayer \
                 vulkan-tools \
                 shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
             rm -rf /opt/vulkan-sdk
         fi
         if [ "arm64" = "$TARGETARCH" ]; then

backend/Dockerfile.python

@@ -61,22 +61,22 @@ RUN <<EOT bash
             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" = "$TARGETARCH" ]; then
-            wget "https://sdk.lunarg.com/sdk/download/1.4.328.1/linux/vulkansdk-linux-x86_64-1.4.328.1.tar.xz" && \
-            tar -xf vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
-            rm vulkansdk-linux-x86_64-1.4.328.1.tar.xz && \
+            wget "https://sdk.lunarg.com/sdk/download/1.4.335.0/linux/vulkansdk-linux-x86_64-1.4.335.0.tar.xz" && \
+            tar -xf vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
+            rm vulkansdk-linux-x86_64-1.4.335.0.tar.xz && \
             mkdir -p /opt/vulkan-sdk && \
-            mv 1.4.328.1 /opt/vulkan-sdk/ && \
-            cd /opt/vulkan-sdk/1.4.328.1 && \
+            mv 1.4.335.0 /opt/vulkan-sdk/ && \
+            cd /opt/vulkan-sdk/1.4.335.0 && \
             ./vulkansdk --no-deps --maxjobs \
                 vulkan-loader \
                 vulkan-validationlayers \
                 vulkan-extensionlayer \
                 vulkan-tools \
                 shaderc && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/bin/* /usr/bin/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/include/* /usr/include/ && \
-            cp -rfv /opt/vulkan-sdk/1.4.328.1/x86_64/share/* /usr/share/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/bin/* /usr/bin/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/lib/* /usr/lib/x86_64-linux-gnu/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/include/* /usr/include/ && \
+            cp -rfv /opt/vulkan-sdk/1.4.335.0/x86_64/share/* /usr/share/ && \
             rm -rf /opt/vulkan-sdk
         fi
         if [ "arm64" = "$TARGETARCH" ]; then

backend/cpp/llama-cpp/Makefile

@@ -1,5 +1,5 @@
 
-LLAMA_VERSION?=593da7fa49503b68f9f01700be9f508f1e528992
+LLAMA_VERSION?=785a71008573e2d84728fb0ba9e851d72d3f8fab
 LLAMA_REPO?=https://github.com/ggerganov/llama.cpp
 
 CMAKE_ARGS?=

backend/go/stablediffusion-ggml/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # stablediffusion.cpp (ggml)
 STABLEDIFFUSION_GGML_REPO?=https://github.com/leejet/stable-diffusion.cpp
-STABLEDIFFUSION_GGML_VERSION?=0e52afc6513cc2dea9a1a017afc4a008d5acf2b0
+STABLEDIFFUSION_GGML_VERSION?=7010bb4dff7bd55b03d35ef9772142c21699eba9
 
 CMAKE_ARGS+=-DGGML_MAX_NAME=128
 

backend/go/whisper/Makefile

@@ -8,7 +8,7 @@ JOBS?=$(shell nproc --ignore=1)
 
 # whisper.cpp version
 WHISPER_REPO?=https://github.com/ggml-org/whisper.cpp
-WHISPER_CPP_VERSION?=679bdb53dbcbfb3e42685f50c7ff367949fd4d48
+WHISPER_CPP_VERSION?=2eeeba56e9edd762b4b38467bab96c2517163158
 SO_TARGET?=libgowhisper.so
 
 CMAKE_ARGS+=-DBUILD_SHARED_LIBS=OFF

backend/index.yaml

@@ -428,6 +428,28 @@
     nvidia-l4t-cuda-12: "nvidia-l4t-vibevoice"
     nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-vibevoice"
   icon: https://avatars.githubusercontent.com/u/6154722?s=200&v=4
+- &pocket-tts
+  urls:
+    - https://github.com/kyutai-labs/pocket-tts
+  description: |
+    Pocket TTS is a lightweight text-to-speech model designed to run efficiently on CPUs.
+  tags:
+    - text-to-speech
+    - TTS
+  license: mit
+  name: "pocket-tts"
+  alias: "pocket-tts"
+  capabilities:
+    nvidia: "cuda12-pocket-tts"
+    intel: "intel-pocket-tts"
+    amd: "rocm-pocket-tts"
+    nvidia-l4t: "nvidia-l4t-pocket-tts"
+    default: "cpu-pocket-tts"
+    nvidia-cuda-13: "cuda13-pocket-tts"
+    nvidia-cuda-12: "cuda12-pocket-tts"
+    nvidia-l4t-cuda-12: "nvidia-l4t-pocket-tts"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-pocket-tts"
+  icon: https://avatars.githubusercontent.com/u/6154722?s=200&v=4
 - &piper
   name: "piper"
   uri: "quay.io/go-skynet/local-ai-backends:latest-piper"
@@ -1605,3 +1627,86 @@
   uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-vibevoice"
   mirrors:
     - localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-vibevoice
+## pocket-tts
+- !!merge <<: *pocket-tts
+  name: "pocket-tts-development"
+  capabilities:
+    nvidia: "cuda12-pocket-tts-development"
+    intel: "intel-pocket-tts-development"
+    amd: "rocm-pocket-tts-development"
+    nvidia-l4t: "nvidia-l4t-pocket-tts-development"
+    default: "cpu-pocket-tts-development"
+    nvidia-cuda-13: "cuda13-pocket-tts-development"
+    nvidia-cuda-12: "cuda12-pocket-tts-development"
+    nvidia-l4t-cuda-12: "nvidia-l4t-pocket-tts-development"
+    nvidia-l4t-cuda-13: "cuda13-nvidia-l4t-arm64-pocket-tts-development"
+- !!merge <<: *pocket-tts
+  name: "cpu-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-cpu-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-cpu-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cpu-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-cpu-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-cpu-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda12-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-12-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda12-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-12-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-12-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda13-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-nvidia-cuda-13-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda13-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-nvidia-cuda-13-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-gpu-nvidia-cuda-13-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "intel-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-intel-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "intel-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-intel-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-gpu-intel-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "rocm-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-gpu-rocm-hipblas-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "rocm-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-gpu-rocm-hipblas-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-gpu-rocm-hipblas-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "nvidia-l4t-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-nvidia-l4t-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "nvidia-l4t-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-nvidia-l4t-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda13-nvidia-l4t-arm64-pocket-tts"
+  uri: "quay.io/go-skynet/local-ai-backends:latest-nvidia-l4t-cuda-13-arm64-pocket-tts"
+  mirrors:
+    - localai/localai-backends:latest-nvidia-l4t-cuda-13-arm64-pocket-tts
+- !!merge <<: *pocket-tts
+  name: "cuda13-nvidia-l4t-arm64-pocket-tts-development"
+  uri: "quay.io/go-skynet/local-ai-backends:master-nvidia-l4t-cuda-13-arm64-pocket-tts"
+  mirrors:
+    - localai/localai-backends:master-nvidia-l4t-cuda-13-arm64-pocket-tts

backend/python/chatterbox/install.sh

@@ -17,4 +17,9 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
 fi
 EXTRA_PIP_INSTALL_FLAGS+=" --no-build-isolation"
 
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
+
 installRequirements

backend/python/chatterbox/requirements-install.txt

@@ -0,0 +1,5 @@
+# Build dependencies needed for packages installed from source (e.g., git dependencies)
+# When using --no-build-isolation, these must be installed in the venv first
+wheel
+setuptools
+packaging

backend/python/diffusers/backend.py

@@ -41,6 +41,14 @@ from optimum.quanto import freeze, qfloat8, quantize
 from transformers import T5EncoderModel
 from safetensors.torch import load_file
 
+# Import LTX-2 specific utilities
+try:
+    from diffusers.pipelines.ltx2.export_utils import encode_video as ltx2_encode_video
+    LTX2_AVAILABLE = True
+except ImportError:
+    LTX2_AVAILABLE = False
+    ltx2_encode_video = None
+
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
 COMPEL = os.environ.get("COMPEL", "0") == "1"
 XPU = os.environ.get("XPU", "0") == "1"
@@ -290,6 +298,20 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
                 pipe.enable_model_cpu_offload()
             return pipe
 
+        # LTX2ImageToVideoPipeline - needs img2vid flag, CPU offload, and special handling
+        if pipeline_type == "LTX2ImageToVideoPipeline":
+            self.img2vid = True
+            self.ltx2_pipeline = True
+            pipe = load_diffusers_pipeline(
+                class_name="LTX2ImageToVideoPipeline",
+                model_id=request.Model,
+                torch_dtype=torchType,
+                variant=variant
+            )
+            if not DISABLE_CPU_OFFLOAD:
+                pipe.enable_model_cpu_offload()
+            return pipe
+
         # ================================================================
         # Dynamic pipeline loading - the default path for most pipelines
         # Uses the dynamic loader to instantiate any pipeline by class name
@@ -404,6 +426,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             fromSingleFile = request.Model.startswith("http") or request.Model.startswith("/") or local
             self.img2vid = False
             self.txt2vid = False
+            self.ltx2_pipeline = False
 
             # Load pipeline using dynamic loader
             # Special cases that require custom initialization are handled first
@@ -686,7 +709,44 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             print(f"Generating video with {kwargs=}", file=sys.stderr)
 
             # Generate video frames based on pipeline type
-            if self.PipelineType == "WanPipeline":
+            if self.ltx2_pipeline or self.PipelineType == "LTX2ImageToVideoPipeline":
+                # LTX-2 image-to-video generation with audio
+                if not LTX2_AVAILABLE:
+                    return backend_pb2.Result(success=False, message="LTX-2 pipeline requires diffusers.pipelines.ltx2.export_utils")
+                
+                # LTX-2 uses 'image' parameter instead of 'start_image'
+                if request.start_image:
+                    image = load_image(request.start_image)
+                    kwargs["image"] = image
+                    # Remove start_image if it was added
+                    kwargs.pop("start_image", None)
+                
+                # LTX-2 uses 'frame_rate' instead of 'fps'
+                frame_rate = float(fps)
+                kwargs["frame_rate"] = frame_rate
+                
+                # LTX-2 requires output_type="np" and return_dict=False
+                kwargs["output_type"] = "np"
+                kwargs["return_dict"] = False
+                
+                # Generate video and audio
+                video, audio = self.pipe(**kwargs)
+                
+                # Convert video to uint8 format
+                video = (video * 255).round().astype("uint8")
+                video = torch.from_numpy(video)
+                
+                # Use LTX-2's encode_video function which handles audio
+                ltx2_encode_video(
+                    video[0],
+                    fps=frame_rate,
+                    audio=audio[0].float().cpu(),
+                    audio_sample_rate=self.pipe.vocoder.config.output_sampling_rate,
+                    output_path=request.dst,
+                )
+                
+                return backend_pb2.Result(message="Video generated successfully", success=True)
+            elif self.PipelineType == "WanPipeline":
                 # WAN2.2 text-to-video generation
                 output = self.pipe(**kwargs)
                 frames = output.frames[0]  # WAN2.2 returns frames in this format
@@ -727,7 +787,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             else:
                 return backend_pb2.Result(success=False, message=f"Pipeline {self.PipelineType} does not support video generation")
 
-            # Export video
+            # Export video (for non-LTX-2 pipelines)
             export_to_video(frames, request.dst, fps=fps)
             
             return backend_pb2.Result(message="Video generated successfully", success=True)

backend/python/diffusers/install.sh

@@ -16,6 +16,10 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
     EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
 fi
 
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
 # Use python 3.12 for l4t
 if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
   PYTHON_VERSION="3.12"

backend/python/kokoro/install.sh

@@ -16,4 +16,8 @@ if [ "x${BUILD_PROFILE}" == "xintel" ]; then
     EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
 fi
 
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
 installRequirements

backend/python/neutts/install.sh

@@ -26,6 +26,12 @@ fi
 
 EXTRA_PIP_INSTALL_FLAGS+=" --no-build-isolation"
 
+
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
+
 git clone https://github.com/neuphonic/neutts-air neutts-air
 
 cp -rfv neutts-air/neuttsair ./

backend/python/pocket-tts/Makefile

@@ -0,0 +1,23 @@
+.PHONY: pocket-tts
+pocket-tts:
+	bash install.sh
+
+.PHONY: run
+run: pocket-tts
+	@echo "Running pocket-tts..."
+	bash run.sh
+	@echo "pocket-tts run."
+
+.PHONY: test
+test: pocket-tts
+	@echo "Testing pocket-tts..."
+	bash test.sh
+	@echo "pocket-tts tested."
+
+.PHONY: protogen-clean
+protogen-clean:
+	$(RM) backend_pb2_grpc.py backend_pb2.py
+
+.PHONY: clean
+clean: protogen-clean
+	rm -rf venv __pycache__

backend/python/pocket-tts/backend.py

@@ -0,0 +1,255 @@
+#!/usr/bin/env python3
+"""
+This is an extra gRPC server of LocalAI for Pocket TTS
+"""
+from concurrent import futures
+import time
+import argparse
+import signal
+import sys
+import os
+import traceback
+import scipy.io.wavfile
+import backend_pb2
+import backend_pb2_grpc
+import torch
+from pocket_tts import TTSModel
+
+import grpc
+
+def is_float(s):
+    """Check if a string can be converted to float."""
+    try:
+        float(s)
+        return True
+    except ValueError:
+        return False
+
+def is_int(s):
+    """Check if a string can be converted to int."""
+    try:
+        int(s)
+        return True
+    except ValueError:
+        return False
+
+_ONE_DAY_IN_SECONDS = 60 * 60 * 24
+
+# If MAX_WORKERS are specified in the environment use it, otherwise default to 1
+MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
+
+# Implement the BackendServicer class with the service methods
+class BackendServicer(backend_pb2_grpc.BackendServicer):
+    """
+    BackendServicer is the class that implements the gRPC service
+    """
+    def Health(self, request, context):
+        return backend_pb2.Reply(message=bytes("OK", 'utf-8'))
+    
+    def LoadModel(self, request, context):
+        # Get device
+        if torch.cuda.is_available():
+            print("CUDA is available", file=sys.stderr)
+            device = "cuda"
+        else:
+            print("CUDA is not available", file=sys.stderr)
+            device = "cpu"
+        mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
+        if mps_available:
+            device = "mps"
+        if not torch.cuda.is_available() and request.CUDA:
+            return backend_pb2.Result(success=False, message="CUDA is not available")
+
+        # Normalize potential 'mpx' typo to 'mps'
+        if device == "mpx":
+            print("Note: device 'mpx' detected, treating it as 'mps'.", file=sys.stderr)
+            device = "mps"
+        
+        # Validate mps availability if requested
+        if device == "mps" and not torch.backends.mps.is_available():
+            print("Warning: MPS not available. Falling back to CPU.", file=sys.stderr)
+            device = "cpu"
+
+        self.device = device
+
+        options = request.Options
+
+        # empty dict
+        self.options = {}
+
+        # The options are a list of strings in this form optname:optvalue
+        # We are storing all the options in a dict so we can use it later when
+        # generating the audio
+        for opt in options:
+            if ":" not in opt:
+                continue
+            key, value = opt.split(":", 1)  # Split only on first colon
+            # if value is a number, convert it to the appropriate type
+            if is_float(value):
+                value = float(value)
+            elif is_int(value):
+                value = int(value)
+            elif value.lower() in ["true", "false"]:
+                value = value.lower() == "true"
+            self.options[key] = value
+
+        # Default voice for caching
+        self.default_voice_url = self.options.get("default_voice", None)
+        self._voice_cache = {}
+
+        try:
+            print("Loading Pocket TTS model", file=sys.stderr)
+            self.tts_model = TTSModel.load_model()
+            print(f"Model loaded successfully. Sample rate: {self.tts_model.sample_rate}", file=sys.stderr)
+
+            # Pre-load default voice if specified
+            if self.default_voice_url:
+                try:
+                    print(f"Pre-loading default voice: {self.default_voice_url}", file=sys.stderr)
+                    voice_state = self.tts_model.get_state_for_audio_prompt(self.default_voice_url)
+                    self._voice_cache[self.default_voice_url] = voice_state
+                    print("Default voice loaded successfully", file=sys.stderr)
+                except Exception as e:
+                    print(f"Warning: Failed to pre-load default voice: {e}", file=sys.stderr)
+
+        except Exception as err:
+            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
+        
+        return backend_pb2.Result(message="Model loaded successfully", success=True)
+
+    def _get_voice_state(self, voice_input):
+        """
+        Get voice state from cache or load it.
+        voice_input can be:
+        - HuggingFace URL (e.g., hf://kyutai/tts-voices/alba-mackenna/casual.wav)
+        - Local file path
+        - None (use default)
+        """
+        # Use default if no voice specified
+        if not voice_input:
+            voice_input = self.default_voice_url
+
+        if not voice_input:
+            return None
+
+        # Check cache first
+        if voice_input in self._voice_cache:
+            return self._voice_cache[voice_input]
+
+        # Load voice state
+        try:
+            print(f"Loading voice from: {voice_input}", file=sys.stderr)
+            voice_state = self.tts_model.get_state_for_audio_prompt(voice_input)
+            self._voice_cache[voice_input] = voice_state
+            return voice_state
+        except Exception as e:
+            print(f"Error loading voice from {voice_input}: {e}", file=sys.stderr)
+            return None
+
+    def TTS(self, request, context):
+        try:
+            # Determine voice input
+            # Priority: request.voice > AudioPath (from ModelOptions) > default
+            voice_input = None
+            
+            if request.voice:
+                voice_input = request.voice
+            elif hasattr(request, 'AudioPath') and request.AudioPath:
+                # Use AudioPath as voice file
+                if os.path.isabs(request.AudioPath):
+                    voice_input = request.AudioPath
+                elif hasattr(request, 'ModelFile') and request.ModelFile:
+                    model_file_base = os.path.dirname(request.ModelFile)
+                    voice_input = os.path.join(model_file_base, request.AudioPath)
+                elif hasattr(request, 'ModelPath') and request.ModelPath:
+                    voice_input = os.path.join(request.ModelPath, request.AudioPath)
+                else:
+                    voice_input = request.AudioPath
+
+            # Get voice state
+            voice_state = self._get_voice_state(voice_input)
+            if voice_state is None:
+                return backend_pb2.Result(
+                    success=False,
+                    message=f"Voice not found or failed to load: {voice_input}. Please provide a valid voice URL or file path."
+                )
+
+            # Prepare text
+            text = request.text.strip()
+
+            if not text:
+                return backend_pb2.Result(
+                    success=False,
+                    message="Text is empty"
+                )
+
+            print(f"Generating audio for text: {text[:50]}...", file=sys.stderr)
+
+            # Generate audio
+            audio = self.tts_model.generate_audio(voice_state, text)
+
+            # Audio is a 1D torch tensor containing PCM data
+            if audio is None or audio.numel() == 0:
+                return backend_pb2.Result(
+                    success=False,
+                    message="No audio generated"
+                )
+
+            # Save audio to file
+            output_path = request.dst
+            if not output_path:
+                output_path = "/tmp/pocket-tts-output.wav"
+
+            # Ensure output directory exists
+            output_dir = os.path.dirname(output_path)
+            if output_dir and not os.path.exists(output_dir):
+                os.makedirs(output_dir, exist_ok=True)
+
+            # Convert torch tensor to numpy and save
+            audio_numpy = audio.numpy()
+            scipy.io.wavfile.write(output_path, self.tts_model.sample_rate, audio_numpy)
+            print(f"Saved audio to {output_path}", file=sys.stderr)
+
+        except Exception as err:
+            print(f"Error in TTS: {err}", file=sys.stderr)
+            print(traceback.format_exc(), file=sys.stderr)
+            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
+        
+        return backend_pb2.Result(success=True)
+
+def serve(address):
+    server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS),
+        options=[
+            ('grpc.max_message_length', 50 * 1024 * 1024),  # 50MB
+            ('grpc.max_send_message_length', 50 * 1024 * 1024),  # 50MB
+            ('grpc.max_receive_message_length', 50 * 1024 * 1024),  # 50MB
+        ])
+    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
+    server.add_insecure_port(address)
+    server.start()
+    print("Server started. Listening on: " + address, file=sys.stderr)
+
+    # Define the signal handler function
+    def signal_handler(sig, frame):
+        print("Received termination signal. Shutting down...")
+        server.stop(0)
+        sys.exit(0)
+
+    # Set the signal handlers for SIGINT and SIGTERM
+    signal.signal(signal.SIGINT, signal_handler)
+    signal.signal(signal.SIGTERM, signal_handler)
+
+    try:
+        while True:
+            time.sleep(_ONE_DAY_IN_SECONDS)
+    except KeyboardInterrupt:
+        server.stop(0)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run the gRPC server.")
+    parser.add_argument(
+        "--addr", default="localhost:50051", help="The address to bind the server to."
+    )
+    args = parser.parse_args()
+
+    serve(args.addr)

backend/python/pocket-tts/install.sh

@@ -0,0 +1,30 @@
+#!/bin/bash
+set -e
+
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
+# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
+# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
+# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
+if [ "x${BUILD_PROFILE}" == "xintel" ]; then
+    EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
+fi
+
+# Use python 3.12 for l4t
+if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
+  PYTHON_VERSION="3.12"
+  PYTHON_PATCH="12"
+  PY_STANDALONE_TAG="20251120"
+fi
+
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
+installRequirements

backend/python/pocket-tts/protogen.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+set -e
+
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+python3 -m grpc_tools.protoc -I../.. -I./ --python_out=. --grpc_python_out=. backend.proto

backend/python/pocket-tts/requirements-cpu.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://download.pytorch.org/whl/cpu
+pocket-tts
+scipy
+torch

backend/python/pocket-tts/requirements-cublas12.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://download.pytorch.org/whl/cu121
+pocket-tts
+scipy
+torch

backend/python/pocket-tts/requirements-cublas13.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://download.pytorch.org/whl/cu130
+pocket-tts
+scipy
+torch

backend/python/pocket-tts/requirements-hipblas.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://download.pytorch.org/whl/rocm6.3
+pocket-tts
+scipy
+torch==2.7.1+rocm6.3

backend/python/pocket-tts/requirements-intel.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/
+pocket-tts
+scipy
+torch==2.5.1+cxx11.abi

backend/python/pocket-tts/requirements-l4t12.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://pypi.jetson-ai-lab.io/jp6/cu129/
+pocket-tts
+scipy
+torch

backend/python/pocket-tts/requirements-l4t13.txt

@@ -0,0 +1,4 @@
+--extra-index-url https://download.pytorch.org/whl/cu130
+pocket-tts
+scipy
+torch

backend/python/pocket-tts/requirements-mps.txt

@@ -0,0 +1,4 @@
+pocket-tts
+scipy
+torch==2.7.1
+torchvision==0.22.1

backend/python/pocket-tts/requirements.txt

@@ -0,0 +1,4 @@
+grpcio==1.71.0
+protobuf
+certifi
+packaging==24.1

backend/python/pocket-tts/run.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+startBackend $@

backend/python/pocket-tts/test.py

@@ -0,0 +1,141 @@
+"""
+A test script to test the gRPC service
+"""
+import unittest
+import subprocess
+import time
+import os
+import tempfile
+import backend_pb2
+import backend_pb2_grpc
+
+import grpc
+
+
+class TestBackendServicer(unittest.TestCase):
+    """
+    TestBackendServicer is the class that tests the gRPC service
+    """
+    def setUp(self):
+        """
+        This method sets up the gRPC service by starting the server
+        """
+        self.service = subprocess.Popen(["python3", "backend.py", "--addr", "localhost:50051"])
+        time.sleep(30)
+
+    def tearDown(self) -> None:
+        """
+        This method tears down the gRPC service by terminating the server
+        """
+        self.service.terminate()
+        self.service.wait()
+
+    def test_server_startup(self):
+        """
+        This method tests if the server starts up successfully
+        """
+        try:
+            self.setUp()
+            with grpc.insecure_channel("localhost:50051") as channel:
+                stub = backend_pb2_grpc.BackendStub(channel)
+                response = stub.Health(backend_pb2.HealthMessage())
+                self.assertEqual(response.message, b'OK')
+        except Exception as err:
+            print(err)
+            self.fail("Server failed to start")
+        finally:
+            self.tearDown()
+
+    def test_load_model(self):
+        """
+        This method tests if the model is loaded successfully
+        """
+        try:
+            self.setUp()
+            with grpc.insecure_channel("localhost:50051") as channel:
+                stub = backend_pb2_grpc.BackendStub(channel)
+                response = stub.LoadModel(backend_pb2.ModelOptions())
+                print(response)
+                self.assertTrue(response.success)
+                self.assertEqual(response.message, "Model loaded successfully")
+        except Exception as err:
+            print(err)
+            self.fail("LoadModel service failed")
+        finally:
+            self.tearDown()
+
+    def test_tts_with_hf_voice(self):
+        """
+        This method tests TTS generation with HuggingFace voice URL
+        """
+        try:
+            self.setUp()
+            with grpc.insecure_channel("localhost:50051") as channel:
+                stub = backend_pb2_grpc.BackendStub(channel)
+                # Load model
+                response = stub.LoadModel(backend_pb2.ModelOptions())
+                self.assertTrue(response.success)
+                
+                # Create temporary output file
+                with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file:
+                    output_path = tmp_file.name
+                
+                # Test TTS with HuggingFace voice URL
+                tts_request = backend_pb2.TTSRequest(
+                    text="Hello world, this is a test.",
+                    dst=output_path,
+                    voice="azelma"
+                )
+                tts_response = stub.TTS(tts_request)
+                self.assertTrue(tts_response.success)
+                
+                # Verify output file exists and is not empty
+                self.assertTrue(os.path.exists(output_path))
+                self.assertGreater(os.path.getsize(output_path), 0)
+                
+                # Cleanup
+                os.unlink(output_path)
+        except Exception as err:
+            print(err)
+            self.fail("TTS service failed")
+        finally:
+            self.tearDown()
+
+    def test_tts_with_default_voice(self):
+        """
+        This method tests TTS generation with default voice (via AudioPath in LoadModel)
+        """
+        try:
+            self.setUp()
+            with grpc.insecure_channel("localhost:50051") as channel:
+                stub = backend_pb2_grpc.BackendStub(channel)
+                # Load model with default voice
+                load_request = backend_pb2.ModelOptions(
+                    Options=["default_voice:azelma"]
+                )
+                response = stub.LoadModel(load_request)
+                self.assertTrue(response.success)
+                
+                # Create temporary output file
+                with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as tmp_file:
+                    output_path = tmp_file.name
+                
+                # Test TTS without specifying voice (should use default)
+                tts_request = backend_pb2.TTSRequest(
+                    text="Hello world, this is a test.",
+                    dst=output_path
+                )
+                tts_response = stub.TTS(tts_request)
+                self.assertTrue(tts_response.success)
+                
+                # Verify output file exists and is not empty
+                self.assertTrue(os.path.exists(output_path))
+                self.assertGreater(os.path.getsize(output_path), 0)
+                
+                # Cleanup
+                os.unlink(output_path)
+        except Exception as err:
+            print(err)
+            self.fail("TTS service with default voice failed")
+        finally:
+            self.tearDown()

backend/python/pocket-tts/test.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+set -e
+
+backend_dir=$(dirname $0)
+if [ -d $backend_dir/common ]; then
+    source $backend_dir/common/libbackend.sh
+else
+    source $backend_dir/../common/libbackend.sh
+fi
+
+runUnittests

backend/python/transformers/requirements-cpu.txt

@@ -6,4 +6,4 @@ transformers
 bitsandbytes
 outetts
 sentence-transformers==5.2.0
-protobuf==6.33.2
+protobuf==6.33.4

backend/python/transformers/requirements-cublas12.txt

@@ -6,4 +6,4 @@ transformers
 bitsandbytes
 outetts
 sentence-transformers==5.2.0
-protobuf==6.33.2
+protobuf==6.33.4

backend/python/transformers/requirements-cublas13.txt

@@ -6,4 +6,4 @@ transformers
 bitsandbytes
 outetts
 sentence-transformers==5.2.0
-protobuf==6.33.2
+protobuf==6.33.4

backend/python/transformers/requirements-hipblas.txt

@@ -8,4 +8,4 @@ bitsandbytes
 outetts
 bitsandbytes
 sentence-transformers==5.2.0
-protobuf==6.33.2
+protobuf==6.33.4

backend/python/transformers/requirements-intel.txt

@@ -10,4 +10,4 @@ intel-extension-for-transformers
 bitsandbytes
 outetts
 sentence-transformers==5.2.0
-protobuf==6.33.2
+protobuf==6.33.4

backend/python/transformers/requirements.txt

@@ -1,5 +1,5 @@
 grpcio==1.76.0
-protobuf==6.33.2
+protobuf==6.33.4
 certifi
 setuptools
 scipy==1.15.1

backend/python/vibevoice/install.sh

@@ -23,6 +23,10 @@ if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
   PY_STANDALONE_TAG="20251120"
 fi
 
+if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
+    USE_PIP=true
+fi
+
 installRequirements
 
 git clone https://github.com/microsoft/VibeVoice.git

core/cli/run.go

@@ -56,7 +56,7 @@ type RunCMD struct {
 	UseSubtleKeyComparison             bool     `env:"LOCALAI_SUBTLE_KEY_COMPARISON" default:"false" help:"If true, API Key validation comparisons will be performed using constant-time comparisons rather than simple equality. This trades off performance on each request for resiliancy against timing attacks." group:"hardening"`
 	DisableApiKeyRequirementForHttpGet bool     `env:"LOCALAI_DISABLE_API_KEY_REQUIREMENT_FOR_HTTP_GET" default:"false" help:"If true, a valid API key is not required to issue GET requests to portions of the web ui. This should only be enabled in secure testing environments" group:"hardening"`
 	DisableMetricsEndpoint             bool     `env:"LOCALAI_DISABLE_METRICS_ENDPOINT,DISABLE_METRICS_ENDPOINT" default:"false" help:"Disable the /metrics endpoint" group:"api"`
-	HttpGetExemptedEndpoints           []string `env:"LOCALAI_HTTP_GET_EXEMPTED_ENDPOINTS" default:"^/$,^/browse/?$,^/talk/?$,^/p2p/?$,^/chat/?$,^/text2image/?$,^/tts/?$,^/static/.*$,^/swagger.*$" help:"If LOCALAI_DISABLE_API_KEY_REQUIREMENT_FOR_HTTP_GET is overriden to true, this is the list of endpoints to exempt. Only adjust this in case of a security incident or as a result of a personal security posture review" group:"hardening"`
+	HttpGetExemptedEndpoints           []string `env:"LOCALAI_HTTP_GET_EXEMPTED_ENDPOINTS" default:"^/$,^/browse/?$,^/talk/?$,^/p2p/?$,^/chat/?$,^/image/?$,^/text2image/?$,^/tts/?$,^/static/.*$,^/swagger.*$" help:"If LOCALAI_DISABLE_API_KEY_REQUIREMENT_FOR_HTTP_GET is overriden to true, this is the list of endpoints to exempt. Only adjust this in case of a security incident or as a result of a personal security posture review" group:"hardening"`
 	Peer2Peer                          bool     `env:"LOCALAI_P2P,P2P" name:"p2p" default:"false" help:"Enable P2P mode" group:"p2p"`
 	Peer2PeerDHTInterval               int      `env:"LOCALAI_P2P_DHT_INTERVAL,P2P_DHT_INTERVAL" default:"360" name:"p2p-dht-interval" help:"Interval for DHT refresh (used during token generation)" group:"p2p"`
 	Peer2PeerOTPInterval               int      `env:"LOCALAI_P2P_OTP_INTERVAL,P2P_OTP_INTERVAL" default:"9000" name:"p2p-otp-interval" help:"Interval for OTP refresh (used during token generation)" group:"p2p"`

core/gallery/backend_types.go

@@ -63,6 +63,25 @@ func (m *GalleryBackend) IsMeta() bool {
 	return len(m.CapabilitiesMap) > 0 && m.URI == ""
 }
 
+// IsCompatibleWith checks if the backend is compatible with the current system capability.
+// For meta backends, it checks if any of the capabilities in the map match the system capability.
+// For concrete backends, it delegates to SystemState.IsBackendCompatible.
+func (m *GalleryBackend) IsCompatibleWith(systemState *system.SystemState) bool {
+	if systemState == nil {
+		return true
+	}
+
+	// Meta backends are compatible if the system capability matches one of the keys
+	if m.IsMeta() {
+		capability := systemState.Capability(m.CapabilitiesMap)
+		_, exists := m.CapabilitiesMap[capability]
+		return exists
+	}
+
+	// For concrete backends, delegate to the system package
+	return systemState.IsBackendCompatible(m.Name, m.URI)
+}
+
 func (m *GalleryBackend) SetInstalled(installed bool) {
 	m.Installed = installed
 }

core/gallery/backends_test.go

@@ -172,6 +172,252 @@ var _ = Describe("Gallery Backends", func() {
 			Expect(nilMetaBackend.IsMeta()).To(BeFalse())
 		})
 
+		It("should check IsCompatibleWith correctly for meta backends", func() {
+			metaBackend := &GalleryBackend{
+				Metadata: Metadata{
+					Name: "meta-backend",
+				},
+				CapabilitiesMap: map[string]string{
+					"nvidia":  "nvidia-backend",
+					"amd":     "amd-backend",
+					"default": "default-backend",
+				},
+			}
+
+			// Test with nil state - should be compatible
+			Expect(metaBackend.IsCompatibleWith(nil)).To(BeTrue())
+
+			// Test with NVIDIA system - should be compatible (has nvidia key)
+			nvidiaState := &system.SystemState{GPUVendor: "nvidia", VRAM: 8 * 1024 * 1024 * 1024}
+			Expect(metaBackend.IsCompatibleWith(nvidiaState)).To(BeTrue())
+
+			// Test with default (no GPU) - should be compatible (has default key)
+			defaultState := &system.SystemState{}
+			Expect(metaBackend.IsCompatibleWith(defaultState)).To(BeTrue())
+		})
+
+		Describe("IsCompatibleWith for concrete backends", func() {
+			Context("CPU backends", func() {
+				It("should be compatible on all systems", func() {
+					cpuBackend := &GalleryBackend{
+						Metadata: Metadata{
+							Name: "cpu-llama-cpp",
+						},
+						URI: "quay.io/go-skynet/local-ai-backends:latest-cpu-llama-cpp",
+					}
+					Expect(cpuBackend.IsCompatibleWith(&system.SystemState{})).To(BeTrue())
+					Expect(cpuBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Nvidia, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					Expect(cpuBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.AMD, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+				})
+			})
+
+			Context("Darwin/Metal backends", func() {
+				When("running on darwin", func() {
+					BeforeEach(func() {
+						if runtime.GOOS != "darwin" {
+							Skip("Skipping darwin-specific tests on non-darwin system")
+						}
+					})
+
+					It("should be compatible for MLX backend", func() {
+						mlxBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "mlx",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx",
+						}
+						Expect(mlxBackend.IsCompatibleWith(&system.SystemState{})).To(BeTrue())
+					})
+
+					It("should be compatible for metal-llama-cpp backend", func() {
+						metalBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "metal-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-llama-cpp",
+						}
+						Expect(metalBackend.IsCompatibleWith(&system.SystemState{})).To(BeTrue())
+					})
+				})
+
+				When("running on non-darwin", func() {
+					BeforeEach(func() {
+						if runtime.GOOS == "darwin" {
+							Skip("Skipping non-darwin-specific tests on darwin system")
+						}
+					})
+
+					It("should NOT be compatible for MLX backend", func() {
+						mlxBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "mlx",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-mlx",
+						}
+						Expect(mlxBackend.IsCompatibleWith(&system.SystemState{})).To(BeFalse())
+					})
+
+					It("should NOT be compatible for metal-llama-cpp backend", func() {
+						metalBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "metal-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-metal-darwin-arm64-llama-cpp",
+						}
+						Expect(metalBackend.IsCompatibleWith(&system.SystemState{})).To(BeFalse())
+					})
+				})
+			})
+
+			Context("NVIDIA/CUDA backends", func() {
+				When("running on non-darwin", func() {
+					BeforeEach(func() {
+						if runtime.GOOS == "darwin" {
+							Skip("Skipping CUDA tests on darwin system")
+						}
+					})
+
+					It("should NOT be compatible without nvidia GPU", func() {
+						cudaBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "cuda12-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-llama-cpp",
+						}
+						Expect(cudaBackend.IsCompatibleWith(&system.SystemState{})).To(BeFalse())
+						Expect(cudaBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.AMD, VRAM: 8 * 1024 * 1024 * 1024})).To(BeFalse())
+					})
+
+					It("should be compatible with nvidia GPU", func() {
+						cudaBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "cuda12-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-12-llama-cpp",
+						}
+						Expect(cudaBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Nvidia, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+
+					It("should be compatible with cuda13 backend on nvidia GPU", func() {
+						cuda13Backend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "cuda13-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-nvidia-cuda-13-llama-cpp",
+						}
+						Expect(cuda13Backend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Nvidia, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+				})
+			})
+
+			Context("AMD/ROCm backends", func() {
+				When("running on non-darwin", func() {
+					BeforeEach(func() {
+						if runtime.GOOS == "darwin" {
+							Skip("Skipping AMD/ROCm tests on darwin system")
+						}
+					})
+
+					It("should NOT be compatible without AMD GPU", func() {
+						rocmBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "rocm-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-llama-cpp",
+						}
+						Expect(rocmBackend.IsCompatibleWith(&system.SystemState{})).To(BeFalse())
+						Expect(rocmBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Nvidia, VRAM: 8 * 1024 * 1024 * 1024})).To(BeFalse())
+					})
+
+					It("should be compatible with AMD GPU", func() {
+						rocmBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "rocm-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-rocm-hipblas-llama-cpp",
+						}
+						Expect(rocmBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.AMD, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+
+					It("should be compatible with hipblas backend on AMD GPU", func() {
+						hipBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "hip-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-hip-llama-cpp",
+						}
+						Expect(hipBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.AMD, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+				})
+			})
+
+			Context("Intel/SYCL backends", func() {
+				When("running on non-darwin", func() {
+					BeforeEach(func() {
+						if runtime.GOOS == "darwin" {
+							Skip("Skipping Intel/SYCL tests on darwin system")
+						}
+					})
+
+					It("should NOT be compatible without Intel GPU", func() {
+						intelBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "intel-sycl-f16-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-llama-cpp",
+						}
+						Expect(intelBackend.IsCompatibleWith(&system.SystemState{})).To(BeFalse())
+						Expect(intelBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Nvidia, VRAM: 8 * 1024 * 1024 * 1024})).To(BeFalse())
+					})
+
+					It("should be compatible with Intel GPU", func() {
+						intelBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "intel-sycl-f16-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f16-llama-cpp",
+						}
+						Expect(intelBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Intel, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+
+					It("should be compatible with intel-sycl-f32 backend on Intel GPU", func() {
+						intelF32Backend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "intel-sycl-f32-llama-cpp",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-intel-sycl-f32-llama-cpp",
+						}
+						Expect(intelF32Backend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Intel, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+
+					It("should be compatible with intel-transformers backend on Intel GPU", func() {
+						intelTransformersBackend := &GalleryBackend{
+							Metadata: Metadata{
+								Name: "intel-transformers",
+							},
+							URI: "quay.io/go-skynet/local-ai-backends:latest-intel-transformers",
+						}
+						Expect(intelTransformersBackend.IsCompatibleWith(&system.SystemState{GPUVendor: system.Intel, VRAM: 8 * 1024 * 1024 * 1024})).To(BeTrue())
+					})
+				})
+			})
+
+			Context("Vulkan backends", func() {
+				It("should be compatible on CPU-only systems", func() {
+					// Vulkan backends don't have a specific GPU vendor requirement in the current logic
+					// They are compatible if no other GPU-specific pattern matches
+					vulkanBackend := &GalleryBackend{
+						Metadata: Metadata{
+							Name: "vulkan-llama-cpp",
+						},
+						URI: "quay.io/go-skynet/local-ai-backends:latest-gpu-vulkan-llama-cpp",
+					}
+					// Vulkan doesn't have vendor-specific filtering in current implementation
+					Expect(vulkanBackend.IsCompatibleWith(&system.SystemState{})).To(BeTrue())
+				})
+			})
+		})
+
 		It("should find best backend from meta based on system capabilities", func() {
 
 			metaBackend := &GalleryBackend{

core/gallery/gallery.go

@@ -226,6 +226,16 @@ func AvailableGalleryModels(galleries []config.Gallery, systemState *system.Syst
 
 // List available backends
 func AvailableBackends(galleries []config.Gallery, systemState *system.SystemState) (GalleryElements[*GalleryBackend], error) {
+	return availableBackendsWithFilter(galleries, systemState, true)
+}
+
+// AvailableBackendsUnfiltered returns all available backends without filtering by system capability.
+func AvailableBackendsUnfiltered(galleries []config.Gallery, systemState *system.SystemState) (GalleryElements[*GalleryBackend], error) {
+	return availableBackendsWithFilter(galleries, systemState, false)
+}
+
+// availableBackendsWithFilter is a helper function that lists available backends with optional filtering.
+func availableBackendsWithFilter(galleries []config.Gallery, systemState *system.SystemState, filterByCapability bool) (GalleryElements[*GalleryBackend], error) {
 	var backends []*GalleryBackend
 
 	systemBackends, err := ListSystemBackends(systemState)
@@ -241,7 +251,17 @@ func AvailableBackends(galleries []config.Gallery, systemState *system.SystemSta
 		if err != nil {
 			return nil, err
 		}
-		backends = append(backends, galleryBackends...)
+
+		// Filter backends by system capability if requested
+		if filterByCapability {
+			for _, backend := range galleryBackends {
+				if backend.IsCompatibleWith(systemState) {
+					backends = append(backends, backend)
+				}
+			}
+		} else {
+			backends = append(backends, galleryBackends...)
+		}
 	}
 
 	return backends, nil

core/http/app.go

@@ -108,7 +108,15 @@ func API(application *application.Application) (*echo.Echo, error) {
 			req := c.Request()
 			res := c.Response()
 			err := next(c)
-			xlog.Info("HTTP request", "method", req.Method, "path", req.URL.Path, "status", res.Status)
+
+			// Fix for #7989: Reduce log verbosity of Web UI polling
+			// If the path is /api/operations and the request was successful (200),
+			// we log it at DEBUG level (hidden by default) instead of INFO.
+			if req.URL.Path == "/api/operations" && res.Status == 200 {
+				xlog.Debug("HTTP request", "method", req.Method, "path", req.URL.Path, "status", res.Status)
+			} else {
+				xlog.Info("HTTP request", "method", req.Method, "path", req.URL.Path, "status", res.Status)
+			}
 			return err
 		}
 	})
@@ -205,6 +213,7 @@ func API(application *application.Application) (*echo.Echo, error) {
 
 	routes.RegisterLocalAIRoutes(e, requestExtractor, application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.GalleryService(), opcache, application.TemplatesEvaluator(), application)
 	routes.RegisterOpenAIRoutes(e, requestExtractor, application)
+	routes.RegisterAnthropicRoutes(e, requestExtractor, application)
 	if !application.ApplicationConfig().DisableWebUI {
 		routes.RegisterUIAPIRoutes(e, application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.GalleryService(), opcache, application)
 		routes.RegisterUIRoutes(e, application.ModelConfigLoader(), application.ModelLoader(), application.ApplicationConfig(), application.GalleryService())

core/http/endpoints/anthropic/messages.go

@@ -0,0 +1,537 @@
+package anthropic
+
+import (
+	"encoding/json"
+	"fmt"
+
+	"github.com/google/uuid"
+	"github.com/labstack/echo/v4"
+	"github.com/mudler/LocalAI/core/backend"
+	"github.com/mudler/LocalAI/core/config"
+	"github.com/mudler/LocalAI/core/http/middleware"
+	"github.com/mudler/LocalAI/core/schema"
+	"github.com/mudler/LocalAI/core/templates"
+	"github.com/mudler/LocalAI/pkg/functions"
+	"github.com/mudler/LocalAI/pkg/model"
+	"github.com/mudler/xlog"
+)
+
+// MessagesEndpoint is the Anthropic Messages API endpoint
+// https://docs.anthropic.com/claude/reference/messages_post
+// @Summary Generate a message response for the given messages and model.
+// @Param request body schema.AnthropicRequest true "query params"
+// @Success 200 {object} schema.AnthropicResponse "Response"
+// @Router /v1/messages [post]
+func MessagesEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator *templates.Evaluator, appConfig *config.ApplicationConfig) echo.HandlerFunc {
+	return func(c echo.Context) error {
+		id := uuid.New().String()
+
+		input, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.AnthropicRequest)
+		if !ok || input.Model == "" {
+			return sendAnthropicError(c, 400, "invalid_request_error", "model is required")
+		}
+
+		cfg, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
+		if !ok || cfg == nil {
+			return sendAnthropicError(c, 400, "invalid_request_error", "model configuration not found")
+		}
+
+		if input.MaxTokens <= 0 {
+			return sendAnthropicError(c, 400, "invalid_request_error", "max_tokens is required and must be greater than 0")
+		}
+
+		xlog.Debug("Anthropic Messages endpoint configuration read", "config", cfg)
+
+		// Convert Anthropic messages to OpenAI format for internal processing
+		openAIMessages := convertAnthropicToOpenAIMessages(input)
+
+		// Convert Anthropic tools to internal Functions format
+		funcs, shouldUseFn := convertAnthropicTools(input, cfg)
+
+		// Create an OpenAI-compatible request for internal processing
+		openAIReq := &schema.OpenAIRequest{
+			PredictionOptions: schema.PredictionOptions{
+				BasicModelRequest: schema.BasicModelRequest{Model: input.Model},
+				Temperature:       input.Temperature,
+				TopK:              input.TopK,
+				TopP:              input.TopP,
+				Maxtokens:         &input.MaxTokens,
+			},
+			Messages: openAIMessages,
+			Stream:   input.Stream,
+			Context:  input.Context,
+			Cancel:   input.Cancel,
+		}
+
+		// Set stop sequences
+		if len(input.StopSequences) > 0 {
+			openAIReq.Stop = input.StopSequences
+		}
+
+		// Merge config settings
+		if input.Temperature != nil {
+			cfg.Temperature = input.Temperature
+		}
+		if input.TopK != nil {
+			cfg.TopK = input.TopK
+		}
+		if input.TopP != nil {
+			cfg.TopP = input.TopP
+		}
+		cfg.Maxtokens = &input.MaxTokens
+		if len(input.StopSequences) > 0 {
+			cfg.StopWords = append(cfg.StopWords, input.StopSequences...)
+		}
+
+		// Template the prompt with tools if available
+		predInput := evaluator.TemplateMessages(*openAIReq, openAIReq.Messages, cfg, funcs, shouldUseFn)
+		xlog.Debug("Anthropic Messages - Prompt (after templating)", "prompt", predInput)
+
+		if input.Stream {
+			return handleAnthropicStream(c, id, input, cfg, ml, predInput, openAIReq, funcs, shouldUseFn)
+		}
+
+		return handleAnthropicNonStream(c, id, input, cfg, ml, predInput, openAIReq, funcs, shouldUseFn)
+	}
+}
+
+func handleAnthropicNonStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string, openAIReq *schema.OpenAIRequest, funcs functions.Functions, shouldUseFn bool) error {
+	images := []string{}
+	for _, m := range openAIReq.Messages {
+		images = append(images, m.StringImages...)
+	}
+
+	predFunc, err := backend.ModelInference(
+		input.Context, predInput, openAIReq.Messages, images, nil, nil, ml, cfg, nil, nil, nil, "", "", nil, nil, nil)
+	if err != nil {
+		xlog.Error("Anthropic model inference failed", "error", err)
+		return sendAnthropicError(c, 500, "api_error", fmt.Sprintf("model inference failed: %v", err))
+	}
+
+	prediction, err := predFunc()
+	if err != nil {
+		xlog.Error("Anthropic prediction failed", "error", err)
+		return sendAnthropicError(c, 500, "api_error", fmt.Sprintf("prediction failed: %v", err))
+	}
+
+	result := backend.Finetune(*cfg, predInput, prediction.Response)
+	
+	// Check if the result contains tool calls
+	toolCalls := functions.ParseFunctionCall(result, cfg.FunctionsConfig)
+	
+	var contentBlocks []schema.AnthropicContentBlock
+	var stopReason string
+	
+	if shouldUseFn && len(toolCalls) > 0 {
+		// Model wants to use tools
+		stopReason = "tool_use"
+		for _, tc := range toolCalls {
+			// Parse arguments as JSON
+			var inputArgs map[string]interface{}
+			if err := json.Unmarshal([]byte(tc.Arguments), &inputArgs); err != nil {
+				xlog.Warn("Failed to parse tool call arguments as JSON", "error", err, "args", tc.Arguments)
+				inputArgs = map[string]interface{}{"raw": tc.Arguments}
+			}
+			
+			contentBlocks = append(contentBlocks, schema.AnthropicContentBlock{
+				Type:  "tool_use",
+				ID:    fmt.Sprintf("toolu_%s_%d", id, len(contentBlocks)),
+				Name:  tc.Name,
+				Input: inputArgs,
+			})
+		}
+		
+		// Add any text content before the tool calls
+		textContent := functions.ParseTextContent(result, cfg.FunctionsConfig)
+		if textContent != "" {
+			// Prepend text block
+			contentBlocks = append([]schema.AnthropicContentBlock{{Type: "text", Text: textContent}}, contentBlocks...)
+		}
+	} else {
+		// Normal text response
+		stopReason = "end_turn"
+		contentBlocks = []schema.AnthropicContentBlock{
+			{Type: "text", Text: result},
+		}
+	}
+
+	resp := &schema.AnthropicResponse{
+		ID:         fmt.Sprintf("msg_%s", id),
+		Type:       "message",
+		Role:       "assistant",
+		Model:      input.Model,
+		StopReason: &stopReason,
+		Content:    contentBlocks,
+		Usage: schema.AnthropicUsage{
+			InputTokens:  prediction.Usage.Prompt,
+			OutputTokens: prediction.Usage.Completion,
+		},
+	}
+
+	if respData, err := json.Marshal(resp); err == nil {
+		xlog.Debug("Anthropic Response", "response", string(respData))
+	}
+
+	return c.JSON(200, resp)
+}
+
+func handleAnthropicStream(c echo.Context, id string, input *schema.AnthropicRequest, cfg *config.ModelConfig, ml *model.ModelLoader, predInput string, openAIReq *schema.OpenAIRequest, funcs functions.Functions, shouldUseFn bool) error {
+	c.Response().Header().Set("Content-Type", "text/event-stream")
+	c.Response().Header().Set("Cache-Control", "no-cache")
+	c.Response().Header().Set("Connection", "keep-alive")
+
+	// Create OpenAI messages for inference
+	openAIMessages := openAIReq.Messages
+
+	images := []string{}
+	for _, m := range openAIMessages {
+		images = append(images, m.StringImages...)
+	}
+
+	// Send message_start event
+	messageStart := schema.AnthropicStreamEvent{
+		Type: "message_start",
+		Message: &schema.AnthropicStreamMessage{
+			ID:      fmt.Sprintf("msg_%s", id),
+			Type:    "message",
+			Role:    "assistant",
+			Content: []schema.AnthropicContentBlock{},
+			Model:   input.Model,
+			Usage:   schema.AnthropicUsage{InputTokens: 0, OutputTokens: 0},
+		},
+	}
+	sendAnthropicSSE(c, messageStart)
+
+	// Track accumulated content for tool call detection
+	accumulatedContent := ""
+	currentBlockIndex := 0
+	inToolCall := false
+	toolCallsEmitted := 0
+	
+	// Send initial content_block_start event
+	contentBlockStart := schema.AnthropicStreamEvent{
+		Type:         "content_block_start",
+		Index:        currentBlockIndex,
+		ContentBlock: &schema.AnthropicContentBlock{Type: "text", Text: ""},
+	}
+	sendAnthropicSSE(c, contentBlockStart)
+
+	// Stream content deltas
+	tokenCallback := func(token string, usage backend.TokenUsage) bool {
+		accumulatedContent += token
+		
+		// If we're using functions, try to detect tool calls incrementally
+		if shouldUseFn {
+			cleanedResult := functions.CleanupLLMResult(accumulatedContent, cfg.FunctionsConfig)
+			
+			// Try parsing for tool calls
+			toolCalls := functions.ParseFunctionCall(cleanedResult, cfg.FunctionsConfig)
+			
+			// If we detected new tool calls and haven't emitted them yet
+			if len(toolCalls) > toolCallsEmitted {
+				// Stop the current text block if we were in one
+				if !inToolCall && currentBlockIndex == 0 {
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_stop",
+						Index: currentBlockIndex,
+					})
+					currentBlockIndex++
+					inToolCall = true
+				}
+				
+				// Emit new tool calls
+				for i := toolCallsEmitted; i < len(toolCalls); i++ {
+					tc := toolCalls[i]
+					
+					// Send content_block_start for tool_use
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_start",
+						Index: currentBlockIndex,
+						ContentBlock: &schema.AnthropicContentBlock{
+							Type: "tool_use",
+							ID:   fmt.Sprintf("toolu_%s_%d", id, i),
+							Name: tc.Name,
+						},
+					})
+					
+					// Send input_json_delta with the arguments
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_delta",
+						Index: currentBlockIndex,
+						Delta: &schema.AnthropicStreamDelta{
+							Type:        "input_json_delta",
+							PartialJSON: tc.Arguments,
+						},
+					})
+					
+					// Send content_block_stop
+					sendAnthropicSSE(c, schema.AnthropicStreamEvent{
+						Type:  "content_block_stop",
+						Index: currentBlockIndex,
+					})
+					
+					currentBlockIndex++
+				}
+				toolCallsEmitted = len(toolCalls)
+				return true
+			}
+		}
+		
+		// Send regular text delta if not in tool call mode
+		if !inToolCall {
+			delta := schema.AnthropicStreamEvent{
+				Type:  "content_block_delta",
+				Index: 0,
+				Delta: &schema.AnthropicStreamDelta{
+					Type: "text_delta",
+					Text: token,
+				},
+			}
+			sendAnthropicSSE(c, delta)
+		}
+		return true
+	}
+
+	predFunc, err := backend.ModelInference(
+		input.Context, predInput, openAIMessages, images, nil, nil, ml, cfg, nil, nil, tokenCallback, "", "", nil, nil, nil)
+	if err != nil {
+		xlog.Error("Anthropic stream model inference failed", "error", err)
+		return sendAnthropicError(c, 500, "api_error", fmt.Sprintf("model inference failed: %v", err))
+	}
+
+	prediction, err := predFunc()
+	if err != nil {
+		xlog.Error("Anthropic stream prediction failed", "error", err)
+		return sendAnthropicError(c, 500, "api_error", fmt.Sprintf("prediction failed: %v", err))
+	}
+
+	// Send content_block_stop event for last block if we didn't close it yet
+	if !inToolCall {
+		contentBlockStop := schema.AnthropicStreamEvent{
+			Type:  "content_block_stop",
+			Index: 0,
+		}
+		sendAnthropicSSE(c, contentBlockStop)
+	}
+
+	// Determine stop reason
+	stopReason := "end_turn"
+	if toolCallsEmitted > 0 {
+		stopReason = "tool_use"
+	}
+
+	// Send message_delta event with stop_reason
+	messageDelta := schema.AnthropicStreamEvent{
+		Type: "message_delta",
+		Delta: &schema.AnthropicStreamDelta{
+			StopReason: &stopReason,
+		},
+		Usage: &schema.AnthropicUsage{
+			OutputTokens: prediction.Usage.Completion,
+		},
+	}
+	sendAnthropicSSE(c, messageDelta)
+
+	// Send message_stop event
+	messageStop := schema.AnthropicStreamEvent{
+		Type: "message_stop",
+	}
+	sendAnthropicSSE(c, messageStop)
+
+	return nil
+}
+
+func sendAnthropicSSE(c echo.Context, event schema.AnthropicStreamEvent) {
+	data, err := json.Marshal(event)
+	if err != nil {
+		xlog.Error("Failed to marshal SSE event", "error", err)
+		return
+	}
+	fmt.Fprintf(c.Response().Writer, "event: %s\ndata: %s\n\n", event.Type, string(data))
+	c.Response().Flush()
+}
+
+func sendAnthropicError(c echo.Context, statusCode int, errorType, message string) error {
+	resp := schema.AnthropicErrorResponse{
+		Type: "error",
+		Error: schema.AnthropicError{
+			Type:    errorType,
+			Message: message,
+		},
+	}
+	return c.JSON(statusCode, resp)
+}
+
+func convertAnthropicToOpenAIMessages(input *schema.AnthropicRequest) []schema.Message {
+	var messages []schema.Message
+
+	// Add system message if present
+	if input.System != "" {
+		messages = append(messages, schema.Message{
+			Role:          "system",
+			StringContent: input.System,
+			Content:       input.System,
+		})
+	}
+
+	// Convert Anthropic messages to OpenAI format
+	for _, msg := range input.Messages {
+		openAIMsg := schema.Message{
+			Role: msg.Role,
+		}
+
+		// Handle content (can be string or array of content blocks)
+		switch content := msg.Content.(type) {
+		case string:
+			openAIMsg.StringContent = content
+			openAIMsg.Content = content
+		case []interface{}:
+			// Handle array of content blocks
+			var textContent string
+			var stringImages []string
+			var toolCalls []schema.ToolCall
+			toolCallIndex := 0
+
+			for _, block := range content {
+				if blockMap, ok := block.(map[string]interface{}); ok {
+					blockType, _ := blockMap["type"].(string)
+					switch blockType {
+					case "text":
+						if text, ok := blockMap["text"].(string); ok {
+							textContent += text
+						}
+					case "image":
+						// Handle image content
+						if source, ok := blockMap["source"].(map[string]interface{}); ok {
+							if sourceType, ok := source["type"].(string); ok && sourceType == "base64" {
+								if data, ok := source["data"].(string); ok {
+									mediaType, _ := source["media_type"].(string)
+									// Format as data URI
+									dataURI := fmt.Sprintf("data:%s;base64,%s", mediaType, data)
+									stringImages = append(stringImages, dataURI)
+								}
+							}
+						}
+					case "tool_use":
+						// Convert tool_use to ToolCall format
+						toolID, _ := blockMap["id"].(string)
+						toolName, _ := blockMap["name"].(string)
+						toolInput := blockMap["input"]
+						
+						// Serialize input to JSON string
+						inputJSON, err := json.Marshal(toolInput)
+						if err != nil {
+							xlog.Warn("Failed to marshal tool input", "error", err)
+							inputJSON = []byte("{}")
+						}
+						
+						toolCalls = append(toolCalls, schema.ToolCall{
+							Index: toolCallIndex,
+							ID:    toolID,
+							Type:  "function",
+							FunctionCall: schema.FunctionCall{
+								Name:      toolName,
+								Arguments: string(inputJSON),
+							},
+						})
+						toolCallIndex++
+					case "tool_result":
+						// Convert tool_result to a message with role "tool"
+						// This is handled by creating a separate message after this block
+						// For now, we'll add it as text content
+						toolUseID, _ := blockMap["tool_use_id"].(string)
+						isError := false
+						if isErrorPtr, ok := blockMap["is_error"].(*bool); ok && isErrorPtr != nil {
+							isError = *isErrorPtr
+						}
+						
+						var resultText string
+						if resultContent, ok := blockMap["content"]; ok {
+							switch rc := resultContent.(type) {
+							case string:
+								resultText = rc
+							case []interface{}:
+								// Array of content blocks
+								for _, cb := range rc {
+									if cbMap, ok := cb.(map[string]interface{}); ok {
+										if cbMap["type"] == "text" {
+											if text, ok := cbMap["text"].(string); ok {
+												resultText += text
+											}
+										}
+									}
+								}
+							}
+						}
+						
+						// Add tool result as a tool role message
+						// We need to handle this differently - create a new message
+						if msg.Role == "user" {
+							// Store tool result info for creating separate message
+							prefix := ""
+							if isError {
+								prefix = "Error: "
+							}
+							textContent += fmt.Sprintf("\n[Tool Result for %s]: %s%s", toolUseID, prefix, resultText)
+						}
+					}
+				}
+			}
+			openAIMsg.StringContent = textContent
+			openAIMsg.Content = textContent
+			openAIMsg.StringImages = stringImages
+			
+			// Add tool calls if present
+			if len(toolCalls) > 0 {
+				openAIMsg.ToolCalls = toolCalls
+			}
+		}
+
+		messages = append(messages, openAIMsg)
+	}
+
+	return messages
+}
+
+// convertAnthropicTools converts Anthropic tools to internal Functions format
+func convertAnthropicTools(input *schema.AnthropicRequest, cfg *config.ModelConfig) (functions.Functions, bool) {
+	if len(input.Tools) == 0 {
+		return nil, false
+	}
+	
+	var funcs functions.Functions
+	for _, tool := range input.Tools {
+		f := functions.Function{
+			Name:        tool.Name,
+			Description: tool.Description,
+			Parameters:  tool.InputSchema,
+		}
+		funcs = append(funcs, f)
+	}
+	
+	// Handle tool_choice
+	if input.ToolChoice != nil {
+		switch tc := input.ToolChoice.(type) {
+		case string:
+			// "auto", "any", or "none"
+			if tc == "any" {
+				// Force the model to use one of the tools
+				cfg.SetFunctionCallString("required")
+			} else if tc == "none" {
+				// Don't use tools
+				return nil, false
+			}
+			// "auto" is the default - let model decide
+		case map[string]interface{}:
+			// Specific tool selection: {"type": "tool", "name": "tool_name"}
+			if tcType, ok := tc["type"].(string); ok && tcType == "tool" {
+				if name, ok := tc["name"].(string); ok {
+					// Force specific tool
+					cfg.SetFunctionCallString(name)
+				}
+			}
+		}
+	}
+	
+	return funcs, len(funcs) > 0 && cfg.ShouldUseFunctions()
+}

core/http/endpoints/openai/chat.go

@@ -3,6 +3,7 @@ package openai
 import (
 	"encoding/json"
 	"fmt"
+	"strings"
 	"time"
 
 	"github.com/google/uuid"
@@ -34,11 +35,54 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 			Created: created,
 			Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
 			Choices: []schema.Choice{{Delta: &schema.Message{Role: "assistant"}, Index: 0, FinishReason: nil}},
-			Object:  "chat.completion.chunk",
 		}
 		responses <- initialMessage
 
+		// Track accumulated content for reasoning extraction
+		accumulatedContent := ""
+		lastEmittedReasoning := ""
+		lastEmittedCleanedContent := ""
+
 		_, _, err := ComputeChoices(req, s, config, cl, startupOptions, loader, func(s string, c *[]schema.Choice) {}, func(s string, tokenUsage backend.TokenUsage) bool {
+			accumulatedContent += s
+			// Extract reasoning from accumulated content
+			currentReasoning, cleanedContent := functions.ExtractReasoning(accumulatedContent)
+
+			// Calculate new reasoning delta (what we haven't emitted yet)
+			var reasoningDelta *string
+			if currentReasoning != lastEmittedReasoning {
+				// Extract only the new part
+				if len(currentReasoning) > len(lastEmittedReasoning) && strings.HasPrefix(currentReasoning, lastEmittedReasoning) {
+					newReasoning := currentReasoning[len(lastEmittedReasoning):]
+					reasoningDelta = &newReasoning
+					lastEmittedReasoning = currentReasoning
+				} else if currentReasoning != "" {
+					// If reasoning changed in a non-append way, emit the full current reasoning
+					reasoningDelta = &currentReasoning
+					lastEmittedReasoning = currentReasoning
+				}
+			}
+
+			// Calculate content delta from cleaned content
+			var deltaContent string
+			if len(cleanedContent) > len(lastEmittedCleanedContent) && strings.HasPrefix(cleanedContent, lastEmittedCleanedContent) {
+				deltaContent = cleanedContent[len(lastEmittedCleanedContent):]
+				lastEmittedCleanedContent = cleanedContent
+			} else if cleanedContent != lastEmittedCleanedContent {
+				// If cleaned content changed but not in a simple append, extract delta from cleaned content
+				// This handles cases where thinking tags are removed mid-stream
+				if lastEmittedCleanedContent == "" {
+					deltaContent = cleanedContent
+					lastEmittedCleanedContent = cleanedContent
+				} else {
+					// Content changed in non-append way, use the new cleaned content
+					deltaContent = cleanedContent
+					lastEmittedCleanedContent = cleanedContent
+				}
+			}
+			// Only emit content if there's actual content (not just thinking tags)
+			// If deltaContent is empty, we still emit the response but with empty content
+
 			usage := schema.OpenAIUsage{
 				PromptTokens:     tokenUsage.Prompt,
 				CompletionTokens: tokenUsage.Completion,
@@ -49,11 +93,20 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 				usage.TimingPromptProcessing = tokenUsage.TimingPromptProcessing
 			}
 
+			delta := &schema.Message{}
+			// Only include content if there's actual content (not just thinking tags)
+			if deltaContent != "" {
+				delta.Content = &deltaContent
+			}
+			if reasoningDelta != nil && *reasoningDelta != "" {
+				delta.Reasoning = reasoningDelta
+			}
+
 			resp := schema.OpenAIResponse{
 				ID:      id,
 				Created: created,
 				Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
-				Choices: []schema.Choice{{Delta: &schema.Message{Content: &s}, Index: 0, FinishReason: nil}},
+				Choices: []schema.Choice{{Delta: delta, Index: 0, FinishReason: nil}},
 				Object:  "chat.completion.chunk",
 				Usage:   usage,
 			}
@@ -176,6 +229,10 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 		if err != nil {
 			return err
 		}
+		// Extract reasoning before processing tool calls
+		reasoning, cleanedResult := functions.ExtractReasoning(result)
+		result = cleanedResult
+
 		textContentToReturn = functions.ParseTextContent(result, config.FunctionsConfig)
 		result = functions.CleanupLLMResult(result, config.FunctionsConfig)
 		functionResults := functions.ParseFunctionCall(result, config.FunctionsConfig)
@@ -208,11 +265,20 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 				usage.TimingPromptProcessing = tokenUsage.TimingPromptProcessing
 			}
 
+			var deltaReasoning *string
+			if reasoning != "" {
+				deltaReasoning = &reasoning
+			}
+			delta := &schema.Message{Content: &result}
+			if deltaReasoning != nil {
+				delta.Reasoning = deltaReasoning
+			}
+
 			resp := schema.OpenAIResponse{
 				ID:      id,
 				Created: created,
 				Model:   req.Model, // we have to return what the user sent here, due to OpenAI spec.
-				Choices: []schema.Choice{{Delta: &schema.Message{Content: &result}, Index: 0, FinishReason: nil}},
+				Choices: []schema.Choice{{Delta: delta, Index: 0, FinishReason: nil}},
 				Object:  "chat.completion.chunk",
 				Usage:   usage,
 			}
@@ -553,10 +619,18 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 		default:
 
 			tokenCallback := func(s string, c *[]schema.Choice) {
+				// Extract reasoning from the response
+				reasoning, cleanedS := functions.ExtractReasoning(s)
+				s = cleanedS
+
 				if !shouldUseFn {
 					// no function is called, just reply and use stop as finish reason
 					stopReason := FinishReasonStop
-					*c = append(*c, schema.Choice{FinishReason: &stopReason, Index: 0, Message: &schema.Message{Role: "assistant", Content: &s}})
+					message := &schema.Message{Role: "assistant", Content: &s}
+					if reasoning != "" {
+						message.Reasoning = &reasoning
+					}
+					*c = append(*c, schema.Choice{FinishReason: &stopReason, Index: 0, Message: message})
 					return
 				}
 
@@ -575,9 +649,13 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 					}
 
 					stopReason := FinishReasonStop
+					message := &schema.Message{Role: "assistant", Content: &result}
+					if reasoning != "" {
+						message.Reasoning = &reasoning
+					}
 					*c = append(*c, schema.Choice{
 						FinishReason: &stopReason,
-						Message:      &schema.Message{Role: "assistant", Content: &result}})
+						Message:      message})
 				default:
 					toolCallsReason := FinishReasonToolCalls
 					toolChoice := schema.Choice{
@@ -586,6 +664,9 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 							Role: "assistant",
 						},
 					}
+					if reasoning != "" {
+						toolChoice.Message.Reasoning = &reasoning
+					}
 
 					for _, ss := range results {
 						name, args := ss.Name, ss.Arguments
@@ -606,16 +687,20 @@ func ChatEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, evaluator
 						} else {
 							// otherwise we return more choices directly (deprecated)
 							functionCallReason := FinishReasonFunctionCall
+							message := &schema.Message{
+								Role:    "assistant",
+								Content: &textContentToReturn,
+								FunctionCall: map[string]interface{}{
+									"name":      name,
+									"arguments": args,
+								},
+							}
+							if reasoning != "" {
+								message.Reasoning = &reasoning
+							}
 							*c = append(*c, schema.Choice{
 								FinishReason: &functionCallReason,
-								Message: &schema.Message{
-									Role:    "assistant",
-									Content: &textContentToReturn,
-									FunctionCall: map[string]interface{}{
-										"name":      name,
-										"arguments": args,
-									},
-								},
+								Message:      message,
 							})
 						}
 					}

core/http/routes/anthropic.go

@@ -0,0 +1,108 @@
+package routes
+
+import (
+	"context"
+	"fmt"
+	"net/http"
+
+	"github.com/google/uuid"
+	"github.com/labstack/echo/v4"
+	"github.com/mudler/LocalAI/core/application"
+	"github.com/mudler/LocalAI/core/config"
+	"github.com/mudler/LocalAI/core/http/endpoints/anthropic"
+	"github.com/mudler/LocalAI/core/http/middleware"
+	"github.com/mudler/LocalAI/core/schema"
+	"github.com/mudler/xlog"
+)
+
+func RegisterAnthropicRoutes(app *echo.Echo,
+	re *middleware.RequestExtractor,
+	application *application.Application) {
+
+	// Anthropic Messages API endpoint
+	messagesHandler := anthropic.MessagesEndpoint(
+		application.ModelConfigLoader(),
+		application.ModelLoader(),
+		application.TemplatesEvaluator(),
+		application.ApplicationConfig(),
+	)
+
+	messagesMiddleware := []echo.MiddlewareFunc{
+		middleware.TraceMiddleware(application),
+		re.BuildFilteredFirstAvailableDefaultModel(config.BuildUsecaseFilterFn(config.FLAG_CHAT)),
+		re.SetModelAndConfig(func() schema.LocalAIRequest { return new(schema.AnthropicRequest) }),
+		setAnthropicRequestContext(application.ApplicationConfig()),
+	}
+
+	// Main Anthropic endpoint
+	app.POST("/v1/messages", messagesHandler, messagesMiddleware...)
+
+	// Also support without version prefix for compatibility
+	app.POST("/messages", messagesHandler, messagesMiddleware...)
+}
+
+// setAnthropicRequestContext sets up the context and cancel function for Anthropic requests
+func setAnthropicRequestContext(appConfig *config.ApplicationConfig) echo.MiddlewareFunc {
+	return func(next echo.HandlerFunc) echo.HandlerFunc {
+		return func(c echo.Context) error {
+			input, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.AnthropicRequest)
+			if !ok || input.Model == "" {
+				return echo.NewHTTPError(http.StatusBadRequest, "model is required")
+			}
+
+			cfg, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig)
+			if !ok || cfg == nil {
+				return echo.NewHTTPError(http.StatusBadRequest, "model configuration not found")
+			}
+
+			// Extract or generate the correlation ID
+			// Anthropic uses x-request-id header
+			correlationID := c.Request().Header.Get("x-request-id")
+			if correlationID == "" {
+				correlationID = uuid.New().String()
+			}
+			c.Response().Header().Set("x-request-id", correlationID)
+
+			// Set up context with cancellation
+			reqCtx := c.Request().Context()
+			c1, cancel := context.WithCancel(appConfig.Context)
+
+			// Cancel when request context is cancelled (client disconnects)
+			go func() {
+				select {
+				case <-reqCtx.Done():
+					cancel()
+				case <-c1.Done():
+					// Already cancelled
+				}
+			}()
+
+			// Add the correlation ID to the new context
+			ctxWithCorrelationID := context.WithValue(c1, middleware.CorrelationIDKey, correlationID)
+
+			input.Context = ctxWithCorrelationID
+			input.Cancel = cancel
+
+			if cfg.Model == "" {
+				xlog.Debug("replacing empty cfg.Model with input value", "input.Model", input.Model)
+				cfg.Model = input.Model
+			}
+
+			c.Set(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST, input)
+			c.Set(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG, cfg)
+
+			// Log the Anthropic API version if provided
+			anthropicVersion := c.Request().Header.Get("anthropic-version")
+			if anthropicVersion != "" {
+				xlog.Debug("Anthropic API version", "version", anthropicVersion)
+			}
+
+			// Validate max_tokens is provided
+			if input.MaxTokens <= 0 {
+				return echo.NewHTTPError(http.StatusBadRequest, fmt.Sprintf("max_tokens is required and must be greater than 0"))
+			}
+
+			return next(c)
+		}
+	}
+}

core/http/routes/ui.go

@@ -219,7 +219,7 @@ func RegisterUIRoutes(app *echo.Echo,
 		return c.Render(200, "views/chat", summary)
 	})
 
-	app.GET("/text2image/:model", func(c echo.Context) error {
+	app.GET("/image/:model", func(c echo.Context) error {
 		modelConfigs := cl.GetAllModelsConfigs()
 		modelsWithoutConfig, _ := services.ListModels(cl, ml, config.NoFilterFn, services.LOOSE_ONLY)
 
@@ -233,10 +233,10 @@ func RegisterUIRoutes(app *echo.Echo,
 		}
 
 		// Render index
-		return c.Render(200, "views/text2image", summary)
+		return c.Render(200, "views/image", summary)
 	})
 
-	app.GET("/text2image", func(c echo.Context) error {
+	app.GET("/image", func(c echo.Context) error {
 		modelConfigs := cl.GetAllModelsConfigs()
 		modelsWithoutConfig, _ := services.ListModels(cl, ml, config.NoFilterFn, services.LOOSE_ONLY)
 
@@ -266,7 +266,7 @@ func RegisterUIRoutes(app *echo.Echo,
 		}
 
 		// Render index
-		return c.Render(200, "views/text2image", summary)
+		return c.Render(200, "views/image", summary)
 	})
 
 	app.GET("/tts/:model", func(c echo.Context) error {
@@ -318,6 +318,56 @@ func RegisterUIRoutes(app *echo.Echo,
 		return c.Render(200, "views/tts", summary)
 	})
 
+	app.GET("/video/:model", func(c echo.Context) error {
+		modelConfigs := cl.GetAllModelsConfigs()
+		modelsWithoutConfig, _ := services.ListModels(cl, ml, config.NoFilterFn, services.LOOSE_ONLY)
+
+		summary := map[string]interface{}{
+			"Title":               "LocalAI - Generate videos with " + c.Param("model"),
+			"BaseURL":             middleware.BaseURL(c),
+			"ModelsConfig":        modelConfigs,
+			"ModelsWithoutConfig": modelsWithoutConfig,
+			"Model":               c.Param("model"),
+			"Version":             internal.PrintableVersion(),
+		}
+
+		// Render index
+		return c.Render(200, "views/video", summary)
+	})
+
+	app.GET("/video", func(c echo.Context) error {
+		modelConfigs := cl.GetAllModelsConfigs()
+		modelsWithoutConfig, _ := services.ListModels(cl, ml, config.NoFilterFn, services.LOOSE_ONLY)
+
+		if len(modelConfigs)+len(modelsWithoutConfig) == 0 {
+			// If no model is available redirect to the index which suggests how to install models
+			return c.Redirect(302, middleware.BaseURL(c))
+		}
+
+		modelThatCanBeUsed := ""
+		title := "LocalAI - Generate videos"
+
+		for _, b := range modelConfigs {
+			if b.HasUsecases(config.FLAG_VIDEO) {
+				modelThatCanBeUsed = b.Name
+				title = "LocalAI - Generate videos with " + modelThatCanBeUsed
+				break
+			}
+		}
+
+		summary := map[string]interface{}{
+			"Title":               title,
+			"BaseURL":             middleware.BaseURL(c),
+			"ModelsConfig":        modelConfigs,
+			"ModelsWithoutConfig": modelsWithoutConfig,
+			"Model":               modelThatCanBeUsed,
+			"Version":             internal.PrintableVersion(),
+		}
+
+		// Render index
+		return c.Render(200, "views/video", summary)
+	})
+
 	// Traces UI
 	app.GET("/traces", func(c echo.Context) error {
 		summary := map[string]interface{}{

core/http/routes/ui_api.go

@@ -617,6 +617,12 @@ func RegisterUIAPIRoutes(app *echo.Echo, cl *config.ModelConfigLoader, ml *model
 			installedBackendsCount = len(installedBackends)
 		}
 
+		// Get the detected system capability
+		detectedCapability := ""
+		if appConfig.SystemState != nil {
+			detectedCapability = appConfig.SystemState.DetectedCapability()
+		}
+
 		return c.JSON(200, map[string]interface{}{
 			"backends":           backendsJSON,
 			"repositories":       appConfig.BackendGalleries,
@@ -629,6 +635,7 @@ func RegisterUIAPIRoutes(app *echo.Echo, cl *config.ModelConfigLoader, ml *model
 			"totalPages":         totalPages,
 			"prevPage":           prevPage,
 			"nextPage":           nextPage,
+			"systemCapability":   detectedCapability,
 		})
 	})
 

core/http/static/chat.js

@@ -1368,6 +1368,7 @@ async function promptGPT(systemPrompt, input) {
     let lastAssistantMessageIndex = -1;
     let lastThinkingMessageIndex = -1;
     let lastThinkingScrollTime = 0;
+    let hasReasoningFromAPI = false; // Track if we're receiving reasoning from API (skip tag-based detection)
     const THINKING_SCROLL_THROTTLE = 200; // Throttle scrolling to every 200ms
 
     try {
@@ -1401,19 +1402,24 @@ async function promptGPT(systemPrompt, input) {
               // Handle different event types
               switch (eventData.type) {
                 case "reasoning":
+                  hasReasoningFromAPI = true; // Mark that we're receiving reasoning from API
                   if (eventData.content) {
-                    // Insert reasoning before assistant message if it exists
+                    const currentChat = chatStore.getChat(chatId);
+                    if (!currentChat) break; // Chat was deleted
+                    const isMCPMode = currentChat.mcpMode || false;
+                    const shouldExpand = !isMCPMode; // Expanded in non-MCP mode, collapsed in MCP mode
+                    // Insert thinking before assistant message if it exists (always use "thinking" role)
                     if (lastAssistantMessageIndex >= 0 && targetHistory[lastAssistantMessageIndex]?.role === "assistant") {
                       targetHistory.splice(lastAssistantMessageIndex, 0, {
-                        role: "reasoning",
+                        role: "thinking",
                         content: eventData.content,
                         html: DOMPurify.sanitize(marked.parse(eventData.content)),
                         image: [],
                         audio: [],
-                        expanded: false // Reasoning is always collapsed
+                        expanded: shouldExpand
                       });
                       lastAssistantMessageIndex++; // Adjust index since we inserted
-                      // Scroll smoothly after adding reasoning
+                      // Scroll smoothly after adding thinking
                       setTimeout(() => {
                         const chatContainer = document.getElementById('chat');
                         if (chatContainer) {
@@ -1425,7 +1431,7 @@ async function promptGPT(systemPrompt, input) {
                       }, 100);
                     } else {
                       // No assistant message yet, just add normally
-                      chatStore.add("reasoning", eventData.content, null, null, chatId);
+                      chatStore.add("thinking", eventData.content, null, null, chatId);
                     }
                   }
                   break;
@@ -1491,14 +1497,17 @@ async function promptGPT(systemPrompt, input) {
                     // Only update display if this is the active chat (interval will handle it)
                     // Don't call updateTokensPerSecond here to avoid unnecessary updates
                     
-                    // Check for thinking tags in the chunk (incremental detection)
-                    if (contentChunk.includes("<thinking>") || contentChunk.includes("<think>")) {
-                      isThinking = true;
-                      thinkingContent = "";
-                      lastThinkingMessageIndex = -1;
-                    }
-                    
-                    if (contentChunk.includes("</thinking>") || contentChunk.includes("</think>")) {
+                    // Only check for thinking tags if we're NOT receiving reasoning from API
+                    // This prevents duplicate thinking/reasoning messages
+                    if (!hasReasoningFromAPI) {
+                      // Check for thinking tags in the chunk (incremental detection)
+                      if (contentChunk.includes("<thinking>") || contentChunk.includes("<think>")) {
+                        isThinking = true;
+                        thinkingContent = "";
+                        lastThinkingMessageIndex = -1;
+                      }
+                      
+                      if (contentChunk.includes("</thinking>") || contentChunk.includes("</think>")) {
                       isThinking = false;
                       // When closing tag is detected, process the accumulated thinking content
                       if (thinkingContent.trim()) {
@@ -1552,10 +1561,11 @@ async function promptGPT(systemPrompt, input) {
                         }
                         thinkingContent = "";
                       }
+                      }
                     }
                     
-                    // Handle content based on thinking state
-                    if (isThinking) {
+                    // Handle content based on thinking state (only if not receiving reasoning from API)
+                    if (!hasReasoningFromAPI && isThinking) {
                       thinkingContent += contentChunk;
                       const currentChat = chatStore.getChat(chatId);
                       if (!currentChat) break; // Chat was deleted
@@ -1637,7 +1647,10 @@ async function promptGPT(systemPrompt, input) {
           
           // Process any thinking tags that might be in the accumulated content
           // This handles cases where tags are split across chunks
-          const { regularContent: processedRegular, thinkingContent: processedThinking } = processThinkingTags(regularContent);
+          // Only process if we're NOT receiving reasoning from API (to avoid duplicates)
+          const { regularContent: processedRegular, thinkingContent: processedThinking } = hasReasoningFromAPI
+            ? { regularContent: regularContent, thinkingContent: "" }
+            : processThinkingTags(regularContent);
           
           // Update or create assistant message with processed regular content
           const currentChat = chatStore.getChat(chatId);
@@ -1645,10 +1658,10 @@ async function promptGPT(systemPrompt, input) {
           const request = activeRequests.get(chatId);
           const requestModel = request?.model || null;
           if (lastAssistantMessageIndex === -1) {
-            if (processedRegular && processedRegular.trim()) {
-              chatStore.add("assistant", processedRegular, null, null, chatId, requestModel);
-              lastAssistantMessageIndex = targetHistory.length - 1;
-            }
+            // Create assistant message if we have any content (even if empty string after processing)
+            // This ensures the message is created and can be updated with more content later
+            chatStore.add("assistant", processedRegular || "", null, null, chatId, requestModel);
+            lastAssistantMessageIndex = targetHistory.length - 1;
           } else {
             const lastMessage = targetHistory[lastAssistantMessageIndex];
             if (lastMessage && lastMessage.role === "assistant") {
@@ -1686,7 +1699,10 @@ async function promptGPT(systemPrompt, input) {
       if (assistantContentBuffer.length > 0) {
         const regularContent = assistantContentBuffer.join("");
         // Process any remaining thinking tags that might be in the buffer
-        const { regularContent: processedRegular, thinkingContent: processedThinking } = processThinkingTags(regularContent);
+        // Only process if we're NOT receiving reasoning from API (to avoid duplicates)
+        const { regularContent: processedRegular, thinkingContent: processedThinking } = hasReasoningFromAPI
+          ? { regularContent: regularContent, thinkingContent: "" }
+          : processThinkingTags(regularContent);
         
         const currentChat = chatStore.getChat(chatId);
         if (!currentChat) {
@@ -1719,23 +1735,26 @@ async function promptGPT(systemPrompt, input) {
         }
         
         // Then update or create assistant message
+        // Always create/update assistant message if we have any content
         if (lastAssistantMessageIndex !== -1) {
           const lastMessage = targetHistory[lastAssistantMessageIndex];
           if (lastMessage && lastMessage.role === "assistant") {
             lastMessage.content = (lastMessage.content || "") + (processedRegular || "");
             lastMessage.html = DOMPurify.sanitize(marked.parse(lastMessage.content));
           }
-        } else if (processedRegular && processedRegular.trim()) {
+        } else {
+          // Create assistant message (even if empty, so it can be updated with more content)
           const request = activeRequests.get(chatId);
           const requestModel = request?.model || null;
-          chatStore.add("assistant", processedRegular, null, null, chatId, requestModel);
+          chatStore.add("assistant", processedRegular || "", null, null, chatId, requestModel);
           lastAssistantMessageIndex = targetHistory.length - 1;
         }
       }
       
       // Final thinking content flush if any data remains (from incremental detection)
+      // Only process if we're NOT receiving reasoning from API (to avoid duplicates)
       const finalChat = chatStore.getChat(chatId);
-      if (finalChat && thinkingContent.trim() && lastThinkingMessageIndex === -1) {
+      if (finalChat && !hasReasoningFromAPI && thinkingContent.trim() && lastThinkingMessageIndex === -1) {
         const finalHistory = finalChat.history;
         // Extract thinking content if tags are present
         const thinkingMatch = thinkingContent.match(/<(?:thinking|redacted_reasoning)>(.*?)<\/(?:thinking|redacted_reasoning)>/s);
@@ -1891,9 +1910,13 @@ async function promptGPT(systemPrompt, input) {
     let buffer = "";
     let contentBuffer = [];
     let thinkingContent = "";
+    let reasoningContent = ""; // Track reasoning from API reasoning field
     let isThinking = false;
     let lastThinkingMessageIndex = -1;
+    let lastReasoningMessageIndex = -1; // Track reasoning message separately
+    let lastAssistantMessageIndex = -1; // Track assistant message for reasoning placement
     let lastThinkingScrollTime = 0;
+    let hasReasoningFromAPI = false; // Track if we're receiving reasoning from API (skip tag-based detection)
     const THINKING_SCROLL_THROTTLE = 200; // Throttle scrolling to every 200ms
 
     try {
@@ -1929,30 +1952,100 @@ async function promptGPT(systemPrompt, input) {
                 chatStore.updateTokenUsage(jsonData.usage, chatId);
               }
               
-              const token = jsonData.choices[0].delta.content;
+              const token = jsonData.choices?.[0]?.delta?.content;
+              const reasoningDelta = jsonData.choices?.[0]?.delta?.reasoning;
 
-              if (token) {
-                // Check for thinking tags
-                if (token.includes("<thinking>") || token.includes("<think>")) {
-                  isThinking = true;
-                  thinkingContent = "";
-                  lastThinkingMessageIndex = -1;
+              // Handle reasoning from API reasoning field - always use "thinking" role
+              if (reasoningDelta && reasoningDelta.trim() !== "") {
+                hasReasoningFromAPI = true; // Mark that we're receiving reasoning from API
+                reasoningContent += reasoningDelta;
+                const currentChat = chatStore.getChat(chatId);
+                if (!currentChat) {
+                  // Chat was deleted, skip this line
                   return;
                 }
-                if (token.includes("</thinking>") || token.includes("</think>")) {
-                  isThinking = false;
-                  if (thinkingContent.trim()) {
-                    // Only add the final thinking message if we don't already have one
-                    if (lastThinkingMessageIndex === -1) {
-                      chatStore.add("thinking", thinkingContent, null, null, chatId);
+                const isMCPMode = currentChat.mcpMode || false;
+                const shouldExpand = !isMCPMode; // Expanded in non-MCP mode, collapsed in MCP mode
+                
+                // Only create/update thinking message if we have actual content
+                if (reasoningContent.trim() !== "") {
+                  // Update or create thinking message (always use "thinking" role, not "reasoning")
+                  if (lastReasoningMessageIndex === -1) {
+                    // Find the last assistant message index to insert thinking before it
+                    const targetHistory = currentChat.history;
+                    const assistantIndex = targetHistory.length - 1;
+                    if (assistantIndex >= 0 && targetHistory[assistantIndex]?.role === "assistant") {
+                      // Insert thinking before assistant message
+                      targetHistory.splice(assistantIndex, 0, {
+                        role: "thinking",
+                        content: reasoningContent,
+                        html: DOMPurify.sanitize(marked.parse(reasoningContent)),
+                        image: [],
+                        audio: [],
+                        expanded: shouldExpand
+                      });
+                      lastReasoningMessageIndex = assistantIndex;
+                      lastAssistantMessageIndex = assistantIndex + 1; // Adjust for inserted thinking
+                    } else {
+                      // No assistant message yet, just add normally
+                      chatStore.add("thinking", reasoningContent, null, null, chatId);
+                      lastReasoningMessageIndex = currentChat.history.length - 1;
+                    }
+                  } else {
+                    // Update existing thinking message
+                    const targetHistory = currentChat.history;
+                    if (lastReasoningMessageIndex >= 0 && lastReasoningMessageIndex < targetHistory.length) {
+                      const thinkingMessage = targetHistory[lastReasoningMessageIndex];
+                      if (thinkingMessage && thinkingMessage.role === "thinking") {
+                        thinkingMessage.content = reasoningContent;
+                        thinkingMessage.html = DOMPurify.sanitize(marked.parse(reasoningContent));
+                      }
                     }
                   }
-                  return;
                 }
+                
+                // Scroll when reasoning is updated (throttled)
+                const now = Date.now();
+                if (now - lastThinkingScrollTime > THINKING_SCROLL_THROTTLE) {
+                  lastThinkingScrollTime = now;
+                  setTimeout(() => {
+                    const chatContainer = document.getElementById('chat');
+                    if (chatContainer) {
+                      chatContainer.scrollTo({
+                        top: chatContainer.scrollHeight,
+                        behavior: 'smooth'
+                      });
+                    }
+                    scrollThinkingBoxToBottom();
+                  }, 100);
+                }
+              }
 
-                // Handle content based on thinking state
-                if (isThinking) {
-                  thinkingContent += token;
+              if (token && token.trim() !== "") {
+                // Only check for thinking tags if we're NOT receiving reasoning from API
+                // This prevents duplicate thinking/reasoning messages
+                if (!hasReasoningFromAPI) {
+                  // Check for thinking tags (legacy support - models that output tags directly)
+                  if (token.includes("<thinking>") || token.includes("<think>")) {
+                    isThinking = true;
+                    thinkingContent = "";
+                    lastThinkingMessageIndex = -1;
+                    return;
+                  }
+                  if (token.includes("</thinking>") || token.includes("</think>")) {
+                    isThinking = false;
+                    if (thinkingContent.trim()) {
+                      // Only add the final thinking message if we don't already have one
+                      if (lastThinkingMessageIndex === -1) {
+                        chatStore.add("thinking", thinkingContent, null, null, chatId);
+                      }
+                    }
+                    return;
+                  }
+
+                  // Handle content based on thinking state
+                  if (isThinking) {
+                    thinkingContent += token;
                   // Count tokens for rate calculation (per chat)
                   const request = activeRequests.get(chatId);
                   if (request) {
@@ -1995,7 +2088,42 @@ async function promptGPT(systemPrompt, input) {
                     }, 100);
                   }
                 } else {
+                  // Not in thinking state, add to content buffer
                   contentBuffer.push(token);
+                  // Track assistant message index for reasoning placement
+                  if (lastAssistantMessageIndex === -1) {
+                    const currentChat = chatStore.getChat(chatId);
+                    if (currentChat) {
+                      const targetHistory = currentChat.history;
+                      // Find or create assistant message index
+                      for (let i = targetHistory.length - 1; i >= 0; i--) {
+                        if (targetHistory[i].role === "assistant") {
+                          lastAssistantMessageIndex = i;
+                          break;
+                        }
+                      }
+                      // If no assistant message yet, it will be created when we flush contentBuffer
+                    }
+                  }
+                }
+                } else {
+                  // Receiving reasoning from API, just add token to content buffer
+                  contentBuffer.push(token);
+                  // Track assistant message index for reasoning placement
+                  if (lastAssistantMessageIndex === -1) {
+                    const currentChat = chatStore.getChat(chatId);
+                    if (currentChat) {
+                      const targetHistory = currentChat.history;
+                      // Find or create assistant message index
+                      for (let i = targetHistory.length - 1; i >= 0; i--) {
+                        if (targetHistory[i].role === "assistant") {
+                          lastAssistantMessageIndex = i;
+                          break;
+                        }
+                      }
+                      // If no assistant message yet, it will be created when we flush contentBuffer
+                    }
+                  }
                 }
               }
             } catch (error) {
@@ -2007,6 +2135,17 @@ async function promptGPT(systemPrompt, input) {
         // Efficiently update the chat in batch
         if (contentBuffer.length > 0) {
           addToChat(contentBuffer.join(""));
+          // Update assistant message index after adding content
+          const currentChat = chatStore.getChat(chatId);
+          if (currentChat) {
+            const targetHistory = currentChat.history;
+            for (let i = targetHistory.length - 1; i >= 0; i--) {
+              if (targetHistory[i].role === "assistant") {
+                lastAssistantMessageIndex = i;
+                break;
+              }
+            }
+          }
           contentBuffer = [];
           // Scroll when assistant content is updated (this will also show thinking messages above)
           setTimeout(() => {
@@ -2025,7 +2164,30 @@ async function promptGPT(systemPrompt, input) {
       if (contentBuffer.length > 0) {
         addToChat(contentBuffer.join(""));
       }
+      
+      // Final reasoning flush if any data remains - always use "thinking" role
       const finalChat = chatStore.getChat(chatId);
+      if (finalChat && reasoningContent.trim() && lastReasoningMessageIndex === -1) {
+        const isMCPMode = finalChat.mcpMode || false;
+        const shouldExpand = !isMCPMode;
+        const targetHistory = finalChat.history;
+        // Find assistant message to insert before
+        const assistantIndex = targetHistory.length - 1;
+        if (assistantIndex >= 0 && targetHistory[assistantIndex]?.role === "assistant") {
+          targetHistory.splice(assistantIndex, 0, {
+            role: "thinking",
+            content: reasoningContent,
+            html: DOMPurify.sanitize(marked.parse(reasoningContent)),
+            image: [],
+            audio: [],
+            expanded: shouldExpand
+          });
+        } else {
+          chatStore.add("thinking", reasoningContent, null, null, chatId);
+        }
+      }
+      
+      // Final thinking content flush (legacy tag-based thinking)
       if (finalChat && thinkingContent.trim() && lastThinkingMessageIndex === -1) {
         chatStore.add("thinking", thinkingContent, null, null, chatId);
       }

core/http/static/video.js

@@ -0,0 +1,300 @@
+// Helper function to convert file to base64
+function fileToBase64(file) {
+  return new Promise((resolve, reject) => {
+    const reader = new FileReader();
+    reader.onload = () => {
+      // Remove data:image/...;base64, prefix if present
+      const base64 = reader.result.split(',')[1] || reader.result;
+      resolve(base64);
+    };
+    reader.onerror = reject;
+    reader.readAsDataURL(file);
+  });
+}
+
+function genVideo(event) {
+  event.preventDefault();
+  promptVideo();
+}
+
+async function promptVideo() {
+  const loader = document.getElementById("loader");
+  const input = document.getElementById("input");
+  const generateBtn = document.getElementById("generate-btn");
+  const resultDiv = document.getElementById("result");
+  const resultPlaceholder = document.getElementById("result-placeholder");
+
+  // Show loader and disable form
+  loader.classList.remove("hidden");
+  if (resultPlaceholder) {
+    resultPlaceholder.style.display = "none";
+  }
+  input.disabled = true;
+  generateBtn.disabled = true;
+
+  // Store the prompt for later restoration
+  const prompt = input.value.trim();
+  if (!prompt) {
+    alert("Please enter a prompt");
+    loader.classList.add("hidden");
+    if (resultPlaceholder) {
+      resultPlaceholder.style.display = "flex";
+    }
+    input.disabled = false;
+    generateBtn.disabled = false;
+    return;
+  }
+
+  // Collect all form values
+  const model = document.getElementById("video-model").value;
+  const size = document.getElementById("video-size").value;
+  const negativePrompt = document.getElementById("negative-prompt").value.trim();
+  
+  // Parse size into width and height
+  const sizeParts = size.split("x");
+  let width = 512;
+  let height = 512;
+  if (sizeParts.length === 2) {
+    width = parseInt(sizeParts[0]) || 512;
+    height = parseInt(sizeParts[1]) || 512;
+  }
+
+  // Video-specific parameters
+  const secondsInput = document.getElementById("video-seconds").value.trim();
+  const seconds = secondsInput ? secondsInput : undefined;
+  const fpsInput = document.getElementById("video-fps").value.trim();
+  const fps = fpsInput ? parseInt(fpsInput) : 16;
+  const framesInput = document.getElementById("video-frames").value.trim();
+  const numFrames = framesInput ? parseInt(framesInput) : undefined;
+
+  // Advanced parameters
+  const stepInput = document.getElementById("video-steps").value.trim();
+  const step = stepInput ? parseInt(stepInput) : undefined;
+  const seedInput = document.getElementById("video-seed").value.trim();
+  const seed = seedInput ? parseInt(seedInput) : undefined;
+  const cfgScaleInput = document.getElementById("video-cfg-scale").value.trim();
+  const cfgScale = cfgScaleInput ? parseFloat(cfgScaleInput) : undefined;
+
+  // Prepare request body
+  const requestBody = {
+    model: model,
+    prompt: prompt,
+    width: width,
+    height: height,
+    fps: fps,
+  };
+
+  if (negativePrompt) {
+    requestBody.negative_prompt = negativePrompt;
+  }
+
+  if (seconds !== undefined) {
+    requestBody.seconds = seconds;
+  }
+
+  if (numFrames !== undefined) {
+    requestBody.num_frames = numFrames;
+  }
+
+  if (step !== undefined) {
+    requestBody.step = step;
+  }
+
+  if (seed !== undefined) {
+    requestBody.seed = seed;
+  }
+
+  if (cfgScale !== undefined) {
+    requestBody.cfg_scale = cfgScale;
+  }
+
+  // Handle file inputs
+  try {
+    // Start image (for img2video)
+    const startImageInput = document.getElementById("start-image");
+    if (startImageInput.files.length > 0) {
+      const base64 = await fileToBase64(startImageInput.files[0]);
+      requestBody.start_image = base64;
+    }
+
+    // End image
+    const endImageInput = document.getElementById("end-image");
+    if (endImageInput.files.length > 0) {
+      const base64 = await fileToBase64(endImageInput.files[0]);
+      requestBody.end_image = base64;
+    }
+  } catch (error) {
+    console.error("Error processing image files:", error);
+    resultDiv.innerHTML = '<p class="text-xs text-red-500 p-2">Error processing image files: ' + error.message + '</p>';
+    loader.classList.add("hidden");
+    if (resultPlaceholder) {
+      resultPlaceholder.style.display = "none";
+    }
+    input.disabled = false;
+    generateBtn.disabled = false;
+    return;
+  }
+
+  // Make API request
+  try {
+    const response = await fetch("v1/videos/generations", {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+      },
+      body: JSON.stringify(requestBody),
+    });
+
+    const json = await response.json();
+
+    if (json.error) {
+      // Display error
+      resultDiv.innerHTML = '<p class="text-xs text-red-500 p-2">Error: ' + json.error.message + '</p>';
+      loader.classList.add("hidden");
+      if (resultPlaceholder) {
+        resultPlaceholder.style.display = "none";
+      }
+      input.disabled = false;
+      generateBtn.disabled = false;
+      return;
+    }
+
+    // Clear result div and hide placeholder
+    resultDiv.innerHTML = '';
+    if (resultPlaceholder) {
+      resultPlaceholder.style.display = "none";
+    }
+
+    // Display generated video
+    if (json.data && json.data.length > 0) {
+      json.data.forEach((item, index) => {
+        const videoContainer = document.createElement("div");
+        videoContainer.className = "flex flex-col";
+
+        // Create video element
+        const video = document.createElement("video");
+        video.controls = true;
+        video.className = "w-full h-auto rounded-lg";
+        video.preload = "metadata";
+        
+        if (item.url) {
+          video.src = item.url;
+        } else if (item.b64_json) {
+          video.src = "data:video/mp4;base64," + item.b64_json;
+        } else {
+          return; // Skip invalid items
+        }
+        
+        videoContainer.appendChild(video);
+
+        // Create caption container
+        const captionDiv = document.createElement("div");
+        captionDiv.className = "mt-2 p-2 bg-[var(--color-bg-secondary)] rounded-lg text-xs";
+
+        // Prompt caption
+        const promptCaption = document.createElement("p");
+        promptCaption.className = "text-[var(--color-text-primary)] mb-1.5 break-words";
+        promptCaption.innerHTML = '<strong>Prompt:</strong> ' + escapeHtml(prompt);
+        captionDiv.appendChild(promptCaption);
+
+        // Negative prompt if provided
+        if (negativePrompt) {
+          const negativeCaption = document.createElement("p");
+          negativeCaption.className = "text-[var(--color-text-secondary)] mb-1.5 break-words";
+          negativeCaption.innerHTML = '<strong>Negative Prompt:</strong> ' + escapeHtml(negativePrompt);
+          captionDiv.appendChild(negativeCaption);
+        }
+
+        // Generation details
+        const detailsDiv = document.createElement("div");
+        detailsDiv.className = "flex flex-wrap gap-3 text-[10px] text-[var(--color-text-secondary)] mt-1.5";
+        detailsDiv.innerHTML = `
+          <span><strong>Size:</strong> ${width}x${height}</span>
+          ${fps ? `<span><strong>FPS:</strong> ${fps}</span>` : ''}
+          ${numFrames !== undefined ? `<span><strong>Frames:</strong> ${numFrames}</span>` : ''}
+          ${seconds !== undefined ? `<span><strong>Duration:</strong> ${seconds}s</span>` : ''}
+          ${step !== undefined ? `<span><strong>Steps:</strong> ${step}</span>` : ''}
+          ${seed !== undefined ? `<span><strong>Seed:</strong> ${seed}</span>` : ''}
+          ${cfgScale !== undefined ? `<span><strong>CFG Scale:</strong> ${cfgScale}</span>` : ''}
+        `;
+        captionDiv.appendChild(detailsDiv);
+
+        // Copy prompt button
+        const copyBtn = document.createElement("button");
+        copyBtn.className = "mt-1.5 px-2 py-0.5 text-[10px] bg-[var(--color-primary)] text-white rounded hover:opacity-80";
+        copyBtn.innerHTML = '<i class="fas fa-copy mr-1"></i>Copy Prompt';
+        copyBtn.onclick = () => {
+          navigator.clipboard.writeText(prompt).then(() => {
+            copyBtn.innerHTML = '<i class="fas fa-check mr-1"></i>Copied!';
+            setTimeout(() => {
+              copyBtn.innerHTML = '<i class="fas fa-copy mr-1"></i>Copy Prompt';
+            }, 2000);
+          });
+        };
+        captionDiv.appendChild(copyBtn);
+
+        videoContainer.appendChild(captionDiv);
+        resultDiv.appendChild(videoContainer);
+      });
+      // Hide placeholder when videos are displayed
+      if (resultPlaceholder) {
+        resultPlaceholder.style.display = "none";
+      }
+    } else {
+      resultDiv.innerHTML = '<p class="text-xs text-[var(--color-text-secondary)] p-2">No videos were generated.</p>';
+      if (resultPlaceholder) {
+        resultPlaceholder.style.display = "none";
+      }
+    }
+
+  } catch (error) {
+    console.error("Error generating video:", error);
+    resultDiv.innerHTML = '<p class="text-xs text-red-500 p-2">Error: ' + error.message + '</p>';
+    if (resultPlaceholder) {
+      resultPlaceholder.style.display = "none";
+    }
+  } finally {
+    // Hide loader and re-enable form
+    loader.classList.add("hidden");
+    input.disabled = false;
+    generateBtn.disabled = false;
+    input.focus();
+  }
+}
+
+// Helper function to escape HTML
+function escapeHtml(text) {
+  const div = document.createElement("div");
+  div.textContent = text;
+  return div.innerHTML;
+}
+
+// Initialize
+document.addEventListener("DOMContentLoaded", function() {
+  const input = document.getElementById("input");
+  const form = document.getElementById("genvideo");
+
+  if (input) {
+    input.focus();
+  }
+
+  if (form) {
+    form.addEventListener("submit", genVideo);
+  }
+
+  // Handle Enter key press in the prompt input (but allow Shift+Enter for new lines)
+  if (input) {
+    input.addEventListener("keydown", function(event) {
+      if (event.key === "Enter" && !event.shiftKey) {
+        event.preventDefault();
+        genVideo(event);
+      }
+    });
+  }
+
+  // Hide loader initially
+  const loader = document.getElementById("loader");
+  if (loader) {
+    loader.classList.add("hidden");
+  }
+});

core/http/views/backends.html

@@ -54,6 +54,11 @@
                         <span class="font-semibold text-cyan-300" x-text="installedBackends"></span>
                         <span class="text-[#94A3B8] ml-1">installed</span>
                     </a>
+                    <div class="flex items-center bg-[#101827] rounded-lg px-4 py-2 border border-[#38BDF8]/30">
+                        <i class="fas fa-microchip text-[#38BDF8] mr-2"></i>
+                        <span class="text-[#94A3B8] mr-1">Capability:</span>
+                        <span class="font-semibold text-[#38BDF8]" x-text="systemCapability"></span>
+                    </div>
                     <a href="https://localai.io/backends/" target="_blank" class="btn-primary">
                         <i class="fas fa-info-circle mr-2"></i>
                         <span>Documentation</span>
@@ -588,6 +593,7 @@ function backendsGallery() {
         totalPages: 1,
         availableBackends: 0,
         installedBackends: 0,
+        systemCapability: '',
         selectedBackend: null,
         jobProgress: {},
         notifications: [],
@@ -683,6 +689,7 @@ function backendsGallery() {
                 this.totalPages = data.totalPages || 1;
                 this.availableBackends = data.availableBackends || 0;
                 this.installedBackends = data.installedBackends || 0;
+                this.systemCapability = data.systemCapability || 'default';
             } catch (error) {
                 console.error('Error fetching backends:', error);
             } finally {

core/http/views/chat.html

@@ -41,7 +41,7 @@ SOFTWARE.
     __chatContextSize = {{ .ContextSize }};
     {{ end }}
 
-    // Store gallery configs for header icon display
+    // Store gallery configs for header icon display and model info modal
     window.__galleryConfigs = {};
     {{ $allGalleryConfigs:=.GalleryConfig }}
     {{ range $modelName, $galleryConfig := $allGalleryConfigs }}
@@ -49,6 +49,16 @@ SOFTWARE.
     {{ if $galleryConfig.Icon }}
     window.__galleryConfigs["{{$modelName}}"].Icon = "{{$galleryConfig.Icon}}";
     {{ end }}
+    {{ if $galleryConfig.Description }}
+    window.__galleryConfigs["{{$modelName}}"].Description = {{ printf "%q" $galleryConfig.Description }};
+    {{ end }}
+    {{ if $galleryConfig.URLs }}
+    window.__galleryConfigs["{{$modelName}}"].URLs = [
+      {{ range $idx, $url := $galleryConfig.URLs }}
+      {{ if $idx }},{{ end }}{{ printf "%q" $url }}
+      {{ end }}
+    ];
+    {{ end }}
     {{ end }}
 
     // Function to initialize store
@@ -326,10 +336,10 @@ SOFTWARE.
                 c += DOMPurify.sanitize(marked.parse(line));
               });
             }
-            // Set expanded state: thinking is expanded by default in non-MCP mode, collapsed in MCP mode
-            // Reasoning, tool_call, and tool_result are always collapsed by default
+            // Set expanded state: thinking and reasoning are expanded by default in non-MCP mode, collapsed in MCP mode
+            // tool_call and tool_result are always collapsed by default
             const isMCPMode = chat.mcpMode || false;
-            const shouldExpand = (role === "thinking" && !isMCPMode) || false;
+            const shouldExpand = ((role === "thinking" || role === "reasoning") && !isMCPMode) || false;
             chat.history.push({ role, content, html: c, image, audio, expanded: shouldExpand, model: messageModel });
             
             // Auto-name chat from first user message
@@ -497,6 +507,11 @@ SOFTWARE.
       activeChat.model = modelName;
       activeChat.updatedAt = Date.now();
       
+      // Update model info modal with new model
+      if (window.updateModelInfoModal) {
+        window.updateModelInfoModal(modelName);
+      }
+      
       // Get context size from data attribute
       let contextSize = null;
       if (selectedOption.dataset.contextSize) {
@@ -536,18 +551,23 @@ SOFTWARE.
       }
       
       // Update model selector to reflect the change (ensure it stays in sync)
+      // Note: We don't dispatch a change event here to avoid infinite loop
+      // The selector is already updated via user interaction or programmatic change
       const modelSelector = document.getElementById('modelSelector');
       if (modelSelector) {
         // Find and select the option matching the model
         const optionValue = 'chat/' + modelName;
         for (let i = 0; i < modelSelector.options.length; i++) {
           if (modelSelector.options[i].value === optionValue) {
-            modelSelector.selectedIndex = i;
+            // Only update if it's different to avoid unnecessary updates
+            if (modelSelector.selectedIndex !== i) {
+              modelSelector.selectedIndex = i;
+            }
             break;
           }
         }
-        // Trigger Alpine reactivity by dispatching change event
-        modelSelector.dispatchEvent(new Event('change', { bubbles: true }));
+        // Don't dispatch change event here - it would cause infinite recursion
+        // The selector is already in sync with the model
       }
       
       // Trigger MCP availability check in Alpine component
@@ -603,27 +623,52 @@ SOFTWARE.
             <div class="flex items-center justify-between gap-2">
               <label class="text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide flex-shrink-0">Model</label>
               <div class="flex items-center gap-1 flex-shrink-0">
-                {{ if $model }}
-                {{ $galleryConfig:= index $allGalleryConfigs $model}}
-                {{ if $galleryConfig }}
-                <button 
-                  data-twe-ripple-init 
-                  data-twe-ripple-color="light" 
-                  class="text-[var(--color-text-secondary)] hover:text-[var(--color-primary)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
-                  data-modal-target="model-info-modal" 
-                  data-modal-toggle="model-info-modal"
-                  title="Model Information">
-                  <i class="fas fa-info-circle"></i>
-                </button>
-                {{ end }}
-                {{ end }}
-                {{ if $model }}
-                <a href="/models/edit/{{$model}}" 
-                   class="text-[var(--color-text-secondary)] hover:text-[var(--color-warning)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
-                   title="Edit Model Configuration">
-                  <i class="fas fa-edit"></i>
-                </a>
-                {{ end }}
+                <!-- Info button - reactive to active chat model -->
+                <template x-if="$store.chat.activeChat() && $store.chat.activeChat().model && window.__galleryConfigs && window.__galleryConfigs[$store.chat.activeChat().model]">
+                  <button 
+                    data-twe-ripple-init 
+                    data-twe-ripple-color="light" 
+                    class="text-[var(--color-text-secondary)] hover:text-[var(--color-primary)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
+                    data-modal-target="model-info-modal" 
+                    data-modal-toggle="model-info-modal"
+                    :data-model-name="$store.chat.activeChat().model"
+                    @click="if (window.updateModelInfoModal) { window.updateModelInfoModal($store.chat.activeChat().model, true); }"
+                    title="Model Information">
+                    <i class="fas fa-info-circle"></i>
+                  </button>
+                </template>
+                <!-- Fallback info button for initial model from server -->
+                <template x-if="(!$store.chat.activeChat() || !$store.chat.activeChat().model) && window.__galleryConfigs && window.__galleryConfigs['{{$model}}']">
+                  <button 
+                    data-twe-ripple-init 
+                    data-twe-ripple-color="light" 
+                    class="text-[var(--color-text-secondary)] hover:text-[var(--color-primary)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
+                    data-modal-target="model-info-modal" 
+                    data-modal-toggle="model-info-modal"
+                    data-model-name="{{$model}}"
+                    @click="if (window.updateModelInfoModal) { window.updateModelInfoModal('{{$model}}', true); }"
+                    title="Model Information">
+                    <i class="fas fa-info-circle"></i>
+                  </button>
+                </template>
+                <!-- Edit button - reactive to active chat model -->
+                <template x-if="$store.chat.activeChat() && $store.chat.activeChat().model">
+                  <a :href="'/models/edit/' + $store.chat.activeChat().model" 
+                     class="text-[var(--color-text-secondary)] hover:text-[var(--color-warning)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
+                     title="Edit Model Configuration">
+                    <i class="fas fa-edit"></i>
+                  </a>
+                </template>
+                <!-- Fallback edit button for initial model from server -->
+                <template x-if="!$store.chat.activeChat() || !$store.chat.activeChat().model">
+                  {{ if $model }}
+                  <a href="/models/edit/{{$model}}" 
+                     class="text-[var(--color-text-secondary)] hover:text-[var(--color-warning)] transition-colors text-xs p-1 rounded hover:bg-[var(--color-bg-primary)]" 
+                     title="Edit Model Configuration">
+                    <i class="fas fa-edit"></i>
+                  </a>
+                  {{ end }}
+                </template>
               </div>
             </div>
             <select
@@ -1488,17 +1533,14 @@ SOFTWARE.
       </div>
     </div>
 
-    <!-- Modal moved outside of sidebar to appear in center of page -->
-    {{ if $model }}
-    {{ $galleryConfig:= index $allGalleryConfigs $model}}
-    {{ if $galleryConfig }}
-    <div id="model-info-modal" tabindex="-1" aria-hidden="true" class="hidden overflow-y-auto overflow-x-hidden fixed top-0 right-0 left-0 z-50 flex justify-center items-center w-full md:inset-0 h-[calc(100%-1rem)] max-h-full">
+    <!-- Modal moved outside of sidebar to appear in center of page - Always available, content updated dynamically -->
+    <div id="model-info-modal" tabindex="-1" aria-hidden="true" class="hidden overflow-y-auto overflow-x-hidden fixed top-0 right-0 left-0 z-50 flex justify-center items-center w-full h-full md:inset-0 max-h-full" style="padding: 1rem;">
       <div class="relative p-4 w-full max-w-2xl max-h-full">
         <div class="relative p-4 w-full max-w-2xl max-h-full bg-white rounded-lg shadow dark:bg-gray-700">
           <!-- Header -->
           <div class="flex items-center justify-between p-4 md:p-5 border-b rounded-t dark:border-gray-600">
-            <h3 class="text-xl font-semibold text-gray-900 dark:text-white">{{ $model }}</h3>
-            <button class="text-gray-400 bg-transparent hover:bg-gray-200 hover:text-gray-900 rounded-lg text-sm w-8 h-8 ms-auto inline-flex justify-center items-center dark:hover:bg-gray-600 dark:hover:text-white" data-modal-hide="model-info-modal">
+            <h3 id="model-info-modal-title" class="text-xl font-semibold text-gray-900 dark:text-white">{{ if $model }}{{ $model }}{{ end }}</h3>
+            <button class="text-gray-400 bg-transparent hover:bg-gray-200 hover:text-gray-900 rounded-lg text-sm w-8 h-8 ms-auto inline-flex justify-center items-center dark:hover:bg-gray-600 dark:hover:text-white" data-modal-hide="model-info-modal" @click="if (window.closeModelInfoModal) { window.closeModelInfoModal(); }">
               <svg class="w-3 h-3" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 14 14">
                 <path stroke="currentColor" stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="m1 1 6 6m0 0 6 6M7 7l6-6M7 7l-6 6"/>
               </svg>
@@ -1509,29 +1551,24 @@ SOFTWARE.
           <!-- Body -->
           <div class="p-4 md:p-5 space-y-4">
             <div class="flex justify-center items-center">
-              {{ if $galleryConfig.Icon }}<img class="lazy rounded-t-lg max-h-48 max-w-96 object-cover mt-3 entered loaded" src="{{$galleryConfig.Icon}}" loading="lazy"/>{{end}}
+              <img id="model-info-modal-icon" class="lazy rounded-t-lg max-h-48 max-w-96 object-cover mt-3 entered loaded" style="display: none;" loading="lazy"/>
             </div>
-            <div id="model-info-description" class="text-base leading-relaxed text-gray-500 dark:text-gray-400 break-words max-w-full">{{ $galleryConfig.Description }}</div>
+            <div id="model-info-description" class="text-base leading-relaxed text-gray-500 dark:text-gray-400 break-words max-w-full"></div>
             <hr>
             <p class="text-sm font-semibold text-gray-900 dark:text-white">Links</p>
-            <ul>
-              {{range $galleryConfig.URLs}}
-              <li><a href="{{ . }}" target="_blank">{{ . }}</a></li>
-              {{end}}
+            <ul id="model-info-links">
             </ul>
           </div>
 
           <!-- Footer -->
           <div class="flex items-center p-4 md:p-5 border-t border-gray-200 rounded-b dark:border-gray-600">
-            <button data-modal-hide="model-info-modal" class="py-2.5 px-5 ms-3 text-sm font-medium text-gray-900 focus:outline-none bg-white rounded-lg border border-gray-200 hover:bg-gray-100 hover:text-blue-700 focus:z-10 focus:ring-4 focus:ring-gray-100 dark:focus:ring-gray-700 dark:bg-gray-800 dark:text-gray-400 dark:border-gray-600 dark:hover:text-white dark:hover:bg-gray-700">
+            <button data-modal-hide="model-info-modal" class="py-2.5 px-5 ms-3 text-sm font-medium text-gray-900 focus:outline-none bg-white rounded-lg border border-gray-200 hover:bg-gray-100 hover:text-blue-700 focus:z-10 focus:ring-4 focus:ring-gray-100 dark:focus:ring-gray-700 dark:bg-gray-800 dark:text-gray-400 dark:border-gray-600 dark:hover:text-white dark:hover:bg-gray-700" @click="if (window.closeModelInfoModal) { window.closeModelInfoModal(); }">
               Close
             </button>
           </div>
         </div>
       </div>
     </div>
-    {{ end }}
-    {{ end }}
 
     <!-- Alpine store initialization and utilities -->
     <script>
@@ -1742,10 +1779,20 @@ SOFTWARE.
         });
 
         // Also listen for click events on modal toggle buttons
-        document.querySelectorAll('[data-modal-toggle="model-info-modal"]').forEach(button => {
-          button.addEventListener('click', () => {
+        // Use event delegation to handle dynamically created buttons
+        document.addEventListener('click', (e) => {
+          const button = e.target.closest('[data-modal-toggle="model-info-modal"]');
+          if (button) {
+            // Update modal with current model before showing
+            if (window.Alpine && window.Alpine.store("chat")) {
+              const activeChat = window.Alpine.store("chat").activeChat();
+              const modelName = activeChat ? activeChat.model : (button.dataset.modelName || (document.getElementById("chat-model") ? document.getElementById("chat-model").value : null));
+              if (modelName && window.updateModelInfoModal) {
+                window.updateModelInfoModal(modelName, true);
+              }
+            }
             setTimeout(processMarkdown, 300);
-          });
+          }
         });
 
         // Process on initial load if libraries are ready
@@ -1786,12 +1833,176 @@ SOFTWARE.
         syncModelSelectorOnLoad();
       }
 
+      // Function to update model info modal with current model
+      // Set openModal to true to actually open the modal, false to just update content
+      window.updateModelInfoModal = function(modelName, openModal = false) {
+        if (!modelName) {
+          return;
+        }
+        if (!window.__galleryConfigs) {
+          return;
+        }
+        
+        const galleryConfig = window.__galleryConfigs[modelName];
+        // Check if galleryConfig exists and has at least one property
+        if (!galleryConfig || Object.keys(galleryConfig).length === 0) {
+          // Still update the modal title even if no config, so user can see which model they clicked
+          const titleEl = document.getElementById('model-info-modal-title');
+          if (titleEl) {
+            titleEl.textContent = modelName;
+          }
+          // Show message that no info is available
+          const descEl = document.getElementById('model-info-description');
+          if (descEl) {
+            descEl.textContent = 'No additional information available for this model.';
+          }
+          const linksEl = document.getElementById('model-info-links');
+          if (linksEl) {
+            linksEl.innerHTML = '';
+          }
+          const iconEl = document.getElementById('model-info-modal-icon');
+          if (iconEl) {
+            iconEl.style.display = 'none';
+          }
+          // Only open the modal if explicitly requested
+          if (openModal) {
+            const modalElement = document.getElementById('model-info-modal');
+            if (modalElement) {
+              modalElement.classList.remove('hidden');
+              modalElement.setAttribute('aria-hidden', 'false');
+              // Add backdrop
+              let backdrop = document.querySelector('.modal-backdrop');
+              if (!backdrop) {
+                backdrop = document.createElement('div');
+                backdrop.className = 'modal-backdrop fixed inset-0 bg-gray-900 bg-opacity-50 dark:bg-opacity-80 z-40';
+                document.body.appendChild(backdrop);
+                backdrop.addEventListener('click', () => {
+                  closeModelInfoModal();
+                });
+              }
+            }
+          }
+          return;
+        }
+        
+        // Update modal title
+        const titleEl = document.getElementById('model-info-modal-title');
+        if (titleEl) {
+          titleEl.textContent = modelName;
+        }
+        
+        // Update icon
+        const iconEl = document.getElementById('model-info-modal-icon');
+        if (iconEl) {
+          if (galleryConfig.Icon) {
+            iconEl.src = galleryConfig.Icon;
+            iconEl.style.display = 'block';
+          } else {
+            iconEl.style.display = 'none';
+          }
+        }
+        
+        // Update description
+        const descEl = document.getElementById('model-info-description');
+        if (descEl) {
+          descEl.textContent = galleryConfig.Description || 'No description available.';
+        }
+        
+        // Update links
+        const linksEl = document.getElementById('model-info-links');
+        if (linksEl && galleryConfig.URLs && Array.isArray(galleryConfig.URLs) && galleryConfig.URLs.length > 0) {
+          linksEl.innerHTML = '';
+          galleryConfig.URLs.forEach(url => {
+            const li = document.createElement('li');
+            const a = document.createElement('a');
+            a.href = url;
+            a.target = '_blank';
+            a.textContent = url;
+            li.appendChild(a);
+            linksEl.appendChild(li);
+          });
+        } else if (linksEl) {
+          linksEl.innerHTML = '<li>No links available</li>';
+        }
+        
+        // Only open the modal if explicitly requested
+        if (openModal) {
+          const modalElement = document.getElementById('model-info-modal');
+          if (modalElement) {
+            // Ensure positioning classes are present (they might have been removed)
+            if (!modalElement.classList.contains('flex')) {
+              modalElement.classList.add('flex');
+            }
+            if (!modalElement.classList.contains('justify-center')) {
+              modalElement.classList.add('justify-center');
+            }
+            if (!modalElement.classList.contains('items-center')) {
+              modalElement.classList.add('items-center');
+            }
+            // Ensure fixed positioning
+            if (!modalElement.classList.contains('fixed')) {
+              modalElement.classList.add('fixed');
+            }
+            // Ensure full width and height
+            if (!modalElement.classList.contains('w-full')) {
+              modalElement.classList.add('w-full');
+            }
+            if (!modalElement.classList.contains('h-full')) {
+              modalElement.classList.add('h-full');
+            }
+            // Ensure padding is set
+            if (!modalElement.style.padding) {
+              modalElement.style.padding = '1rem';
+            }
+            // Remove hidden class if present
+            modalElement.classList.remove('hidden');
+            // Set aria-hidden to false
+            modalElement.setAttribute('aria-hidden', 'false');
+            // Add backdrop if needed
+            let backdrop = document.querySelector('.modal-backdrop');
+            if (!backdrop) {
+              backdrop = document.createElement('div');
+              backdrop.className = 'modal-backdrop fixed inset-0 bg-gray-900 bg-opacity-50 dark:bg-opacity-80 z-40';
+              document.body.appendChild(backdrop);
+              backdrop.addEventListener('click', () => {
+                window.closeModelInfoModal();
+              });
+            }
+          }
+        }
+      };
+      
+      // Function to close the model info modal
+      window.closeModelInfoModal = function() {
+        const modalElement = document.getElementById('model-info-modal');
+        if (modalElement) {
+          modalElement.classList.add('hidden');
+          modalElement.setAttribute('aria-hidden', 'true');
+        }
+        const backdrop = document.querySelector('.modal-backdrop');
+        if (backdrop) {
+          backdrop.remove();
+        }
+      };
+
       // Also sync after Alpine initializes (in case it runs after DOMContentLoaded)
+      function initializeModelInfo() {
+        syncModelSelectorOnLoad();
+        // Initialize model info modal content with current model (but don't open it)
+        if (window.updateModelInfoModal && window.Alpine && window.Alpine.store("chat")) {
+          const activeChat = window.Alpine.store("chat").activeChat();
+          const modelName = activeChat ? activeChat.model : (document.getElementById("chat-model") ? document.getElementById("chat-model").value : null);
+          if (modelName) {
+            window.updateModelInfoModal(modelName, false); // false = don't open, just update content
+          }
+        }
+      }
+      
       if (window.Alpine) {
-        Alpine.nextTick(syncModelSelectorOnLoad);
+        Alpine.nextTick(initializeModelInfo);
       } else {
         document.addEventListener('alpine:init', () => {
-          Alpine.nextTick(syncModelSelectorOnLoad);
+          Alpine.nextTick(initializeModelInfo);
         });
       }
     </script>

core/http/views/image.html

@@ -28,19 +28,19 @@
                               {{ $cfg := . }}
                               {{ range .KnownUsecaseStrings }}
                                 {{ if eq . "FLAG_IMAGE" }}
-                                    <option value="text2image/{{$cfg.Name}}" {{ if eq $cfg.Name $model }} selected {{end}} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{$cfg.Name}}</option>
+                                    <option value="image/{{$cfg.Name}}" {{ if eq $cfg.Name $model }} selected {{end}} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{$cfg.Name}}</option>
                                 {{ end }}
                               {{ end }}
                             {{ end }}
                             {{ range .ModelsWithoutConfig }}
-                                <option value="text2image/{{.}}" {{ if eq . $model }} selected {{ end }} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{.}}</option>
+                                <option value="image/{{.}}" {{ if eq . $model }} selected {{ end }} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{.}}</option>
                             {{end}}
                         </select>
                     </div>
                     
                     <div class="relative">
                         <input id="image-model" type="hidden" value="{{.Model}}">
-                        <form id="genimage" action="text2image/{{.Model}}" method="get">
+                        <form id="genimage" action="image/{{.Model}}" method="get">
                             <!-- Basic Settings -->
                             <div class="space-y-2">
                                 <!-- Prompt -->
@@ -326,4 +326,4 @@
 </script>
 
 </body>
-</html>
+</html>

core/http/views/manage.html

@@ -315,7 +315,7 @@
                                     </a>
                                     {{ end }}
                                     {{ if eq . "FLAG_IMAGE" }}
-                                    <a href="text2image/{{$backendCfg.Name}}" class="inline-flex items-center px-1.5 py-0.5 rounded text-[10px] font-medium bg-[var(--color-success)]/10 text-green-300 hover:bg-[var(--color-success)]/20 transition-colors" title="Image">
+                                    <a href="image/{{$backendCfg.Name}}" class="inline-flex items-center px-1.5 py-0.5 rounded text-[10px] font-medium bg-[var(--color-success)]/10 text-green-300 hover:bg-[var(--color-success)]/20 transition-colors" title="Image">
                                         <i class="fas fa-image text-[8px] mr-1"></i>Image
                                     </a>
                                     {{ end }}

core/http/views/partials/navbar.html

@@ -25,7 +25,7 @@
                 <a href="chat/" class="text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] px-2 py-2 rounded-lg transition duration-300 ease-in-out hover:bg-[var(--color-bg-secondary)] flex items-center group text-sm">
                     <i class="fa-solid fa-comments text-[var(--color-primary)] mr-1.5 text-sm group-hover:scale-110 transition-transform"></i>Chat
                 </a>
-                <a href="text2image/" class="text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] px-2 py-2 rounded-lg transition duration-300 ease-in-out hover:bg-[var(--color-bg-secondary)] flex items-center group text-sm">
+                <a href="image/" class="text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] px-2 py-2 rounded-lg transition duration-300 ease-in-out hover:bg-[var(--color-bg-secondary)] flex items-center group text-sm">
                     <i class="fas fa-image text-[var(--color-primary)] mr-1.5 text-sm group-hover:scale-110 transition-transform"></i>Images
                 </a>
                 <a href="tts/" class="text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] px-2 py-2 rounded-lg transition duration-300 ease-in-out hover:bg-[var(--color-bg-secondary)] flex items-center group text-sm">
@@ -85,7 +85,7 @@
                 <a href="chat/" class="block text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] px-3 py-2 rounded-lg transition duration-300 ease-in-out flex items-center text-sm">
                     <i class="fa-solid fa-comments text-[var(--color-primary)] mr-3 w-5 text-center text-sm"></i>Chat
                 </a>
-                <a href="text2image/" class="block text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] px-3 py-2 rounded-lg transition duration-300 ease-in-out flex items-center text-sm">
+                <a href="image/" class="block text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] px-3 py-2 rounded-lg transition duration-300 ease-in-out flex items-center text-sm">
                     <i class="fas fa-image text-[var(--color-primary)] mr-3 w-5 text-center text-sm"></i>Images
                 </a>
                 <a href="tts/" class="block text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] px-3 py-2 rounded-lg transition duration-300 ease-in-out flex items-center text-sm">

core/http/views/video.html

@@ -0,0 +1,315 @@
+<!DOCTYPE html>
+<html lang="en">
+{{template "views/partials/head" .}}
+<script defer src="static/video.js"></script>
+
+<body class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)] flex flex-col h-screen">
+<div class="flex flex-col flex-1 overflow-hidden">
+   
+    {{template "views/partials/navbar" .}}
+    <div class="flex flex-1 overflow-hidden">
+        <!-- Two Column Layout: Settings on Left, Preview on Right -->
+        <div class="flex flex-col lg:flex-row flex-1 gap-4 p-4 overflow-hidden">
+            <!-- Left Column: Generation Settings -->
+            <div class="flex-shrink-0 lg:w-1/4 flex flex-col min-h-0">
+                <div class="card p-3 space-y-3 overflow-y-auto flex-1">
+                    <!-- Model Selection - Compact -->
+                    <div class="space-y-1.5">
+                        <div class="flex items-center justify-between gap-2">
+                            <label class="text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide flex-shrink-0">Model</label>
+                        </div>
+                        <select x-data="{ link : '' }" x-model="link" x-init="$watch('link', value => window.location = link)" 
+                            id="model-select"
+                            class="input w-full p-1.5 text-xs"
+                        >	
+                            <option value="" disabled class="text-[var(--color-text-secondary)]">Select a model</option>
+                            {{ $model:=.Model}}
+                            {{ range .ModelsConfig }}
+                              {{ $cfg := . }}
+                              {{ range .KnownUsecaseStrings }}
+                                {{ if eq . "FLAG_VIDEO" }}
+                                    <option value="video/{{$cfg.Name}}" {{ if eq $cfg.Name $model }} selected {{end}} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{$cfg.Name}}</option>
+                                {{ end }}
+                              {{ end }}
+                            {{ end }}
+                            {{ range .ModelsWithoutConfig }}
+                                <option value="video/{{.}}" {{ if eq . $model }} selected {{ end }} class="bg-[var(--color-bg-primary)] text-[var(--color-text-primary)]">{{.}}</option>
+                            {{end}}
+                        </select>
+                    </div>
+                    
+                    <div class="relative">
+                        <input id="video-model" type="hidden" value="{{.Model}}">
+                        <form id="genvideo" action="video/{{.Model}}" method="get">
+                            <!-- Basic Settings -->
+                            <div class="space-y-2">
+                                <!-- Prompt -->
+                                <div class="space-y-1">
+                                    <label for="input" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-magic mr-1.5 text-[var(--color-primary)]"></i>Prompt
+                                    </label>
+                                    <textarea
+                                        id="input"
+                                        name="input"
+                                        placeholder="Describe the video you want to generate..."
+                                        autocomplete="off"
+                                        rows="3"
+                                        class="input w-full p-1.5 text-xs resize-y"
+                                        required
+                                    ></textarea>
+                                </div>
+
+                                <!-- Negative Prompt -->
+                                <div class="space-y-1">
+                                    <label for="negative-prompt" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-ban mr-1.5 text-[var(--color-primary)]"></i>Negative Prompt
+                                    </label>
+                                    <textarea
+                                        id="negative-prompt"
+                                        name="negative-prompt"
+                                        placeholder="Things to avoid in the video..."
+                                        rows="2"
+                                        class="input w-full p-1.5 text-xs resize-y"
+                                    ></textarea>
+                                </div>
+
+                                <!-- Size Selection with Presets -->
+                                <div class="space-y-1">
+                                    <label for="video-size" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-expand-arrows-alt mr-1.5 text-[var(--color-primary)]"></i>Video Size
+                                    </label>
+                                    <div class="flex flex-wrap gap-1.5 mb-1.5">
+                                        <button type="button" class="size-preset px-2 py-0.5 text-[10px] rounded border border-[var(--color-border)] hover:bg-[var(--color-bg-secondary)]" data-size="256x256">256×256</button>
+                                        <button type="button" class="size-preset px-2 py-0.5 text-[10px] rounded border border-[var(--color-border)] hover:bg-[var(--color-bg-secondary)]" data-size="512x512">512×512</button>
+                                        <button type="button" class="size-preset px-2 py-0.5 text-[10px] rounded border border-[var(--color-border)] hover:bg-[var(--color-bg-secondary)]" data-size="768x768">768×768</button>
+                                        <button type="button" class="size-preset px-2 py-0.5 text-[10px] rounded border border-[var(--color-border)] hover:bg-[var(--color-bg-secondary)]" data-size="1024x1024">1024×1024</button>
+                                    </div>
+                                    <input
+                                        type="text"
+                                        id="video-size"
+                                        value="512x512"
+                                        placeholder="e.g., 256x256, 512x512, 1024x1024"
+                                        class="input p-1.5 text-xs w-full"
+                                    />
+                                </div>
+
+                                <!-- Video Duration / FPS / Frames -->
+                                <div class="space-y-1">
+                                    <label for="video-seconds" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-clock mr-1.5 text-[var(--color-primary)]"></i>Duration (seconds)
+                                    </label>
+                                    <input
+                                        type="number"
+                                        id="video-seconds"
+                                        name="seconds"
+                                        min="1"
+                                        max="60"
+                                        placeholder="Leave empty for default"
+                                        class="input p-1.5 text-xs w-full"
+                                    />
+                                </div>
+
+                                <div class="space-y-1">
+                                    <label for="video-fps" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-film mr-1.5 text-[var(--color-primary)]"></i>FPS
+                                    </label>
+                                    <input
+                                        type="number"
+                                        id="video-fps"
+                                        name="fps"
+                                        min="1"
+                                        max="60"
+                                        value="16"
+                                        placeholder="Frames per second"
+                                        class="input p-1.5 text-xs w-full"
+                                    />
+                                </div>
+
+                                <div class="space-y-1">
+                                    <label for="video-frames" class="block text-xs font-medium text-[var(--color-text-secondary)] uppercase tracking-wide">
+                                        <i class="fas fa-images mr-1.5 text-[var(--color-primary)]"></i>Number of Frames
+                                    </label>
+                                    <input
+                                        type="number"
+                                        id="video-frames"
+                                        name="num_frames"
+                                        min="1"
+                                        max="500"
+                                        placeholder="Leave empty for default"
+                                        class="input p-1.5 text-xs w-full"
+                                    />
+                                </div>
+                            </div>
+
+                            <!-- Advanced Settings (Collapsible) -->
+                            <div class="space-y-2">
+                                <button type="button" id="advanced-toggle" class="w-full flex items-center justify-between px-2 py-1.5 text-xs rounded text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] transition-colors">
+                                    <span><i class="fa-solid fa-sliders mr-1.5 text-[var(--color-primary)]"></i> Advanced Settings</span>
+                                    <i class="fas fa-chevron-down text-[10px]" id="advanced-chevron"></i>
+                                </button>
+                                <div id="advanced-settings" class="hidden p-2 bg-[var(--color-bg-secondary)] border border-[var(--color-primary-border)]/20 rounded pl-4 border-l-2 border-[var(--color-bg-secondary)] space-y-2">
+                                    <!-- Steps -->
+                                    <div class="space-y-1">
+                                        <label for="video-steps" class="block text-xs text-[var(--color-text-secondary)]">
+                                            <i class="fas fa-step-forward mr-1.5 text-[var(--color-primary)]"></i>Steps
+                                        </label>
+                                        <input
+                                            type="number"
+                                            id="video-steps"
+                                            name="step"
+                                            min="1"
+                                            max="100"
+                                            placeholder="Leave empty for default"
+                                            class="input p-1.5 text-xs w-full"
+                                        />
+                                    </div>
+
+                                    <!-- Seed -->
+                                    <div class="space-y-1">
+                                        <label for="video-seed" class="block text-xs text-[var(--color-text-secondary)]">
+                                            <i class="fas fa-seedling mr-1.5 text-[var(--color-primary)]"></i>Seed
+                                        </label>
+                                        <input
+                                            type="number"
+                                            id="video-seed"
+                                            name="seed"
+                                            min="0"
+                                            placeholder="Leave empty for random"
+                                            class="input p-1.5 text-xs w-full"
+                                        />
+                                    </div>
+
+                                    <!-- CFG Scale -->
+                                    <div class="space-y-1">
+                                        <label for="video-cfg-scale" class="block text-xs text-[var(--color-text-secondary)]">
+                                            <i class="fas fa-sliders-h mr-1.5 text-[var(--color-primary)]"></i>CFG Scale
+                                        </label>
+                                        <input
+                                            type="number"
+                                            id="video-cfg-scale"
+                                            name="cfg_scale"
+                                            min="0"
+                                            max="20"
+                                            step="0.1"
+                                            placeholder="Leave empty for default"
+                                            class="input p-1.5 text-xs w-full"
+                                        />
+                                    </div>
+                                </div>
+                            </div>
+
+                            <!-- Image Inputs (Collapsible) -->
+                            <div class="space-y-2">
+                                <button type="button" id="image-inputs-toggle" class="w-full flex items-center justify-between px-2 py-1.5 text-xs rounded text-[var(--color-text-secondary)] hover:text-[var(--color-text-primary)] hover:bg-[var(--color-bg-secondary)] transition-colors">
+                                    <span><i class="fa-solid fa-image mr-1.5 text-[var(--color-primary)]"></i> Image Inputs</span>
+                                    <i class="fas fa-chevron-down text-[10px]" id="image-inputs-chevron"></i>
+                                </button>
+                                <div id="image-inputs-settings" class="hidden p-2 bg-[var(--color-bg-secondary)] border border-[var(--color-primary-border)]/20 rounded pl-4 border-l-2 border-[var(--color-bg-secondary)] space-y-2">
+                                    <!-- Start Image (img2video) -->
+                                    <div class="space-y-1">
+                                        <label for="start-image" class="block text-xs text-[var(--color-text-secondary)]">
+                                            <i class="fas fa-play-circle mr-1.5 text-[var(--color-primary)]"></i>Start Image (img2video)
+                                        </label>
+                                        <input
+                                            type="file"
+                                            id="start-image"
+                                            name="start_image"
+                                            accept="image/*"
+                                            class="input p-1.5 text-xs w-full"
+                                        />
+                                    </div>
+
+                                    <!-- End Image -->
+                                    <div class="space-y-1">
+                                        <label for="end-image" class="block text-xs text-[var(--color-text-secondary)]">
+                                            <i class="fas fa-stop-circle mr-1.5 text-[var(--color-primary)]"></i>End Image
+                                        </label>
+                                        <input
+                                            type="file"
+                                            id="end-image"
+                                            name="end_image"
+                                            accept="image/*"
+                                            class="input p-1.5 text-xs w-full"
+                                        />
+                                    </div>
+                                </div>
+                            </div>
+                            
+                            <!-- Submit Button -->
+                            <div>
+                                <button
+                                    type="submit"
+                                    id="generate-btn"
+                                    class="w-full px-2 py-1.5 text-xs rounded text-[var(--color-bg-primary)] bg-[var(--color-primary)] hover:bg-[var(--color-primary)]/90 transition-colors font-medium"
+                                >
+                                    <i class="fas fa-video mr-1.5"></i>Generate Video
+                                </button>
+                            </div>
+                        </form>
+                    </div>
+                </div>
+            </div>
+
+            <!-- Right Column: Video Preview -->
+            <div class="flex-grow lg:w-3/4 flex flex-col min-h-0">
+                <div class="relative flex-1 min-h-0 overflow-y-auto">
+                    <!-- Loading Animation -->
+                    <div id="loader" class="hidden absolute inset-0 flex items-center justify-center bg-[var(--color-bg-primary)]/80 rounded-xl z-10">
+                        <div class="text-center">
+                            <svg class="animate-spin h-10 w-10 text-[var(--color-primary)] mx-auto mb-3" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24">
+                                <circle class="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" stroke-width="4"></circle>
+                                <path class="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
+                            </svg>
+                            <p class="text-xs text-[var(--color-text-secondary)]">Generating video...</p>
+                        </div>
+                    </div>
+                    <!-- Placeholder when no videos -->
+                    <div id="result-placeholder" class="min-h-[400px] flex items-center justify-center flex-shrink-0">
+                        <p class="text-xs text-[var(--color-text-secondary)] italic text-center">Your generated videos will appear here</p>
+                    </div>
+                    <!-- Results container -->
+                    <div id="result" class="grid grid-cols-1 gap-4 pb-4"></div>
+                </div>
+            </div>
+        </div>
+    </div>
+
+</div>
+
+<script>
+    // Collapsible sections
+    document.getElementById('advanced-toggle').addEventListener('click', function() {
+        const settings = document.getElementById('advanced-settings');
+        const chevron = document.getElementById('advanced-chevron');
+        settings.classList.toggle('hidden');
+        chevron.classList.toggle('fa-chevron-down');
+        chevron.classList.toggle('fa-chevron-up');
+    });
+
+    document.getElementById('image-inputs-toggle').addEventListener('click', function() {
+        const settings = document.getElementById('image-inputs-settings');
+        const chevron = document.getElementById('image-inputs-chevron');
+        settings.classList.toggle('hidden');
+        chevron.classList.toggle('fa-chevron-down');
+        chevron.classList.toggle('fa-chevron-up');
+    });
+
+    // Size preset buttons
+    document.querySelectorAll('.size-preset').forEach(button => {
+        button.addEventListener('click', function() {
+            const size = this.getAttribute('data-size');
+            document.getElementById('video-size').value = size;
+            // Update active state
+            document.querySelectorAll('.size-preset').forEach(btn => {
+                btn.classList.remove('bg-[var(--color-primary)]', 'text-white');
+            });
+            this.classList.add('bg-[var(--color-primary)]', 'text-white');
+        });
+    });
+
+    // Set initial active size preset
+    document.querySelector('.size-preset[data-size="512x512"]').classList.add('bg-[var(--color-primary)]', 'text-white');
+</script>
+
+</body>
+</html>

core/schema/anthropic.go

@@ -0,0 +1,176 @@
+package schema
+
+import (
+	"context"
+	"encoding/json"
+)
+
+// AnthropicRequest represents a request to the Anthropic Messages API
+// https://docs.anthropic.com/claude/reference/messages_post
+type AnthropicRequest struct {
+	Model         string             `json:"model"`
+	Messages      []AnthropicMessage `json:"messages"`
+	MaxTokens     int                `json:"max_tokens"`
+	Metadata      map[string]string  `json:"metadata,omitempty"`
+	StopSequences []string           `json:"stop_sequences,omitempty"`
+	Stream        bool               `json:"stream,omitempty"`
+	System        string             `json:"system,omitempty"`
+	Temperature   *float64           `json:"temperature,omitempty"`
+	TopK          *int               `json:"top_k,omitempty"`
+	TopP          *float64           `json:"top_p,omitempty"`
+	Tools         []AnthropicTool    `json:"tools,omitempty"`
+	ToolChoice    interface{}        `json:"tool_choice,omitempty"`
+
+	// Internal fields for request handling
+	Context context.Context    `json:"-"`
+	Cancel  context.CancelFunc `json:"-"`
+}
+
+// ModelName implements the LocalAIRequest interface
+func (ar *AnthropicRequest) ModelName(s *string) string {
+	if s != nil {
+		ar.Model = *s
+	}
+	return ar.Model
+}
+
+// AnthropicTool represents a tool definition in the Anthropic format
+type AnthropicTool struct {
+	Name        string                 `json:"name"`
+	Description string                 `json:"description,omitempty"`
+	InputSchema map[string]interface{} `json:"input_schema"`
+}
+
+// AnthropicMessage represents a message in the Anthropic format
+type AnthropicMessage struct {
+	Role    string      `json:"role"`
+	Content interface{} `json:"content"`
+}
+
+// AnthropicContentBlock represents a content block in an Anthropic message
+type AnthropicContentBlock struct {
+	Type       string                 `json:"type"`
+	Text       string                 `json:"text,omitempty"`
+	Source     *AnthropicImageSource  `json:"source,omitempty"`
+	ID         string                 `json:"id,omitempty"`
+	Name       string                 `json:"name,omitempty"`
+	Input      map[string]interface{} `json:"input,omitempty"`
+	ToolUseID  string                 `json:"tool_use_id,omitempty"`
+	Content    interface{}            `json:"content,omitempty"`
+	IsError    *bool                  `json:"is_error,omitempty"`
+}
+
+// AnthropicImageSource represents an image source in Anthropic format
+type AnthropicImageSource struct {
+	Type      string `json:"type"`
+	MediaType string `json:"media_type"`
+	Data      string `json:"data"`
+}
+
+// AnthropicResponse represents a response from the Anthropic Messages API
+type AnthropicResponse struct {
+	ID           string                  `json:"id"`
+	Type         string                  `json:"type"`
+	Role         string                  `json:"role"`
+	Content      []AnthropicContentBlock `json:"content"`
+	Model        string                  `json:"model"`
+	StopReason   *string                 `json:"stop_reason"`
+	StopSequence *string                 `json:"stop_sequence,omitempty"`
+	Usage        AnthropicUsage          `json:"usage"`
+}
+
+// AnthropicUsage represents token usage in Anthropic format
+type AnthropicUsage struct {
+	InputTokens  int `json:"input_tokens"`
+	OutputTokens int `json:"output_tokens"`
+}
+
+// AnthropicStreamEvent represents a streaming event from the Anthropic API
+type AnthropicStreamEvent struct {
+	Type         string                  `json:"type"`
+	Index        int                     `json:"index,omitempty"`
+	ContentBlock *AnthropicContentBlock  `json:"content_block,omitempty"`
+	Delta        *AnthropicStreamDelta   `json:"delta,omitempty"`
+	Message      *AnthropicStreamMessage `json:"message,omitempty"`
+	Usage        *AnthropicUsage         `json:"usage,omitempty"`
+}
+
+// AnthropicStreamDelta represents the delta in a streaming response
+type AnthropicStreamDelta struct {
+	Type         string  `json:"type,omitempty"`
+	Text         string  `json:"text,omitempty"`
+	PartialJSON  string  `json:"partial_json,omitempty"`
+	StopReason   *string `json:"stop_reason,omitempty"`
+	StopSequence *string `json:"stop_sequence,omitempty"`
+}
+
+// AnthropicStreamMessage represents the message object in streaming events
+type AnthropicStreamMessage struct {
+	ID           string                  `json:"id"`
+	Type         string                  `json:"type"`
+	Role         string                  `json:"role"`
+	Content      []AnthropicContentBlock `json:"content"`
+	Model        string                  `json:"model"`
+	StopReason   *string                 `json:"stop_reason"`
+	StopSequence *string                 `json:"stop_sequence,omitempty"`
+	Usage        AnthropicUsage          `json:"usage"`
+}
+
+// AnthropicErrorResponse represents an error response from the Anthropic API
+type AnthropicErrorResponse struct {
+	Type  string         `json:"type"`
+	Error AnthropicError `json:"error"`
+}
+
+// AnthropicError represents an error in the Anthropic format
+type AnthropicError struct {
+	Type    string `json:"type"`
+	Message string `json:"message"`
+}
+
+// GetStringContent extracts the string content from an AnthropicMessage
+// Content can be either a string or an array of content blocks
+func (m *AnthropicMessage) GetStringContent() string {
+	switch content := m.Content.(type) {
+	case string:
+		return content
+	case []interface{}:
+		var result string
+		for _, block := range content {
+			if blockMap, ok := block.(map[string]interface{}); ok {
+				if blockMap["type"] == "text" {
+					if text, ok := blockMap["text"].(string); ok {
+						result += text
+					}
+				}
+			}
+		}
+		return result
+	}
+	return ""
+}
+
+// GetContentBlocks extracts content blocks from an AnthropicMessage
+func (m *AnthropicMessage) GetContentBlocks() []AnthropicContentBlock {
+	switch content := m.Content.(type) {
+	case string:
+		return []AnthropicContentBlock{{Type: "text", Text: content}}
+	case []interface{}:
+		var blocks []AnthropicContentBlock
+		for _, block := range content {
+			if blockMap, ok := block.(map[string]interface{}); ok {
+				cb := AnthropicContentBlock{}
+				data, err := json.Marshal(blockMap)
+				if err != nil {
+					continue
+				}
+				if err := json.Unmarshal(data, &cb); err != nil {
+					continue
+				}
+				blocks = append(blocks, cb)
+			}
+		}
+		return blocks
+	}
+	return nil
+}

core/schema/anthropic_test.go

@@ -0,0 +1,216 @@
+package schema_test
+
+import (
+	"encoding/json"
+
+	"github.com/mudler/LocalAI/core/schema"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+var _ = Describe("Anthropic Schema", func() {
+	Describe("AnthropicRequest", func() {
+		It("should unmarshal a valid request", func() {
+			jsonData := `{
+				"model": "claude-3-sonnet-20240229",
+				"max_tokens": 1024,
+				"messages": [
+					{"role": "user", "content": "Hello, world!"}
+				],
+				"system": "You are a helpful assistant.",
+				"temperature": 0.7
+			}`
+
+			var req schema.AnthropicRequest
+			err := json.Unmarshal([]byte(jsonData), &req)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(req.Model).To(Equal("claude-3-sonnet-20240229"))
+			Expect(req.MaxTokens).To(Equal(1024))
+			Expect(len(req.Messages)).To(Equal(1))
+			Expect(req.System).To(Equal("You are a helpful assistant."))
+			Expect(*req.Temperature).To(Equal(0.7))
+		})
+
+		It("should unmarshal a request with tools", func() {
+			jsonData := `{
+				"model": "claude-3-sonnet-20240229",
+				"max_tokens": 1024,
+				"messages": [
+					{"role": "user", "content": "What's the weather?"}
+				],
+				"tools": [
+					{
+						"name": "get_weather",
+						"description": "Get the current weather",
+						"input_schema": {
+							"type": "object",
+							"properties": {
+								"location": {"type": "string"}
+							}
+						}
+					}
+				],
+				"tool_choice": {"type": "tool", "name": "get_weather"}
+			}`
+
+			var req schema.AnthropicRequest
+			err := json.Unmarshal([]byte(jsonData), &req)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(req.Tools)).To(Equal(1))
+			Expect(req.Tools[0].Name).To(Equal("get_weather"))
+			Expect(req.Tools[0].Description).To(Equal("Get the current weather"))
+			Expect(req.ToolChoice).ToNot(BeNil())
+		})
+
+		It("should implement LocalAIRequest interface", func() {
+			req := &schema.AnthropicRequest{Model: "test-model"}
+			Expect(req.ModelName(nil)).To(Equal("test-model"))
+
+			newModel := "new-model"
+			Expect(req.ModelName(&newModel)).To(Equal("new-model"))
+			Expect(req.Model).To(Equal("new-model"))
+		})
+	})
+
+	Describe("AnthropicMessage", func() {
+		It("should get string content from string content", func() {
+			msg := schema.AnthropicMessage{
+				Role:    "user",
+				Content: "Hello, world!",
+			}
+			Expect(msg.GetStringContent()).To(Equal("Hello, world!"))
+		})
+
+		It("should get string content from array content", func() {
+			msg := schema.AnthropicMessage{
+				Role: "user",
+				Content: []interface{}{
+					map[string]interface{}{"type": "text", "text": "Hello, "},
+					map[string]interface{}{"type": "text", "text": "world!"},
+				},
+			}
+			Expect(msg.GetStringContent()).To(Equal("Hello, world!"))
+		})
+
+		It("should get content blocks from string content", func() {
+			msg := schema.AnthropicMessage{
+				Role:    "user",
+				Content: "Hello, world!",
+			}
+			blocks := msg.GetContentBlocks()
+			Expect(len(blocks)).To(Equal(1))
+			Expect(blocks[0].Type).To(Equal("text"))
+			Expect(blocks[0].Text).To(Equal("Hello, world!"))
+		})
+
+		It("should get content blocks from array content", func() {
+			msg := schema.AnthropicMessage{
+				Role: "user",
+				Content: []interface{}{
+					map[string]interface{}{"type": "text", "text": "Hello"},
+					map[string]interface{}{"type": "image", "source": map[string]interface{}{"type": "base64", "data": "abc123"}},
+				},
+			}
+			blocks := msg.GetContentBlocks()
+			Expect(len(blocks)).To(Equal(2))
+			Expect(blocks[0].Type).To(Equal("text"))
+			Expect(blocks[0].Text).To(Equal("Hello"))
+		})
+	})
+
+	Describe("AnthropicResponse", func() {
+		It("should marshal a valid response", func() {
+			stopReason := "end_turn"
+			resp := schema.AnthropicResponse{
+				ID:         "msg_123",
+				Type:       "message",
+				Role:       "assistant",
+				Model:      "claude-3-sonnet-20240229",
+				StopReason: &stopReason,
+				Content: []schema.AnthropicContentBlock{
+					{Type: "text", Text: "Hello!"},
+				},
+				Usage: schema.AnthropicUsage{
+					InputTokens:  10,
+					OutputTokens: 5,
+				},
+			}
+
+			data, err := json.Marshal(resp)
+			Expect(err).ToNot(HaveOccurred())
+
+			var result map[string]interface{}
+			err = json.Unmarshal(data, &result)
+			Expect(err).ToNot(HaveOccurred())
+
+			Expect(result["id"]).To(Equal("msg_123"))
+			Expect(result["type"]).To(Equal("message"))
+			Expect(result["role"]).To(Equal("assistant"))
+			Expect(result["stop_reason"]).To(Equal("end_turn"))
+		})
+
+		It("should marshal a response with tool use", func() {
+			stopReason := "tool_use"
+			resp := schema.AnthropicResponse{
+				ID:         "msg_123",
+				Type:       "message",
+				Role:       "assistant",
+				Model:      "claude-3-sonnet-20240229",
+				StopReason: &stopReason,
+				Content: []schema.AnthropicContentBlock{
+					{
+						Type: "tool_use",
+						ID:   "toolu_123",
+						Name: "get_weather",
+						Input: map[string]interface{}{
+							"location": "San Francisco",
+						},
+					},
+				},
+				Usage: schema.AnthropicUsage{
+					InputTokens:  10,
+					OutputTokens: 5,
+				},
+			}
+
+			data, err := json.Marshal(resp)
+			Expect(err).ToNot(HaveOccurred())
+
+			var result map[string]interface{}
+			err = json.Unmarshal(data, &result)
+			Expect(err).ToNot(HaveOccurred())
+
+			Expect(result["stop_reason"]).To(Equal("tool_use"))
+			content := result["content"].([]interface{})
+			Expect(len(content)).To(Equal(1))
+			toolUse := content[0].(map[string]interface{})
+			Expect(toolUse["type"]).To(Equal("tool_use"))
+			Expect(toolUse["id"]).To(Equal("toolu_123"))
+			Expect(toolUse["name"]).To(Equal("get_weather"))
+		})
+	})
+
+	Describe("AnthropicErrorResponse", func() {
+		It("should marshal an error response", func() {
+			resp := schema.AnthropicErrorResponse{
+				Type: "error",
+				Error: schema.AnthropicError{
+					Type:    "invalid_request_error",
+					Message: "max_tokens is required",
+				},
+			}
+
+			data, err := json.Marshal(resp)
+			Expect(err).ToNot(HaveOccurred())
+
+			var result map[string]interface{}
+			err = json.Unmarshal(data, &result)
+			Expect(err).ToNot(HaveOccurred())
+
+			Expect(result["type"]).To(Equal("error"))
+			errorObj := result["error"].(map[string]interface{})
+			Expect(errorObj["type"]).To(Equal("invalid_request_error"))
+			Expect(errorObj["message"]).To(Equal("max_tokens is required"))
+		})
+	})
+})

core/schema/message.go

@@ -27,6 +27,9 @@ type Message struct {
 	FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
 
 	ToolCalls []ToolCall `json:"tool_calls,omitempty" yaml:"tool_call,omitempty"`
+
+	// Reasoning content extracted from <thinking>...</thinking> tags
+	Reasoning *string `json:"reasoning,omitempty" yaml:"reasoning,omitempty"`
 }
 
 type ToolCall struct {
@@ -78,8 +81,8 @@ func (messages Messages) ToProto() []*proto.Message {
 			}
 		}
 
-		// Note: tool_call_id and reasoning_content are not in schema.Message yet
-		// They may need to be added to schema.Message if needed in the future
+		// Note: tool_call_id is not in schema.Message yet
+		// Reasoning field is now available in schema.Message but not yet in proto.Message
 	}
 	return protoMessages
 }

docs/content/features/text-to-audio.md

@@ -164,6 +164,57 @@ curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
    }' | aplay
 ```
 
+### Pocket TTS
+
+[Pocket TTS](https://github.com/kyutai-labs/pocket-tts) is a lightweight text-to-speech model designed to run efficiently on CPUs. It supports voice cloning through HuggingFace voice URLs or local audio files.
+
+#### Setup
+
+Install the `pocket-tts` model in the Model gallery or run `local-ai run models install pocket-tts`.
+
+#### Usage
+
+Use the tts endpoint by specifying the pocket-tts backend:
+
+```
+curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
+     "model": "pocket-tts",
+     "input":"Hello world, this is a test."
+   }' | aplay
+```
+
+#### Voice cloning
+
+Pocket TTS supports voice cloning through built-in voice names, HuggingFace URLs, or local audio files. You can configure a model with a specific voice:
+
+```yaml
+name: pocket-tts
+backend: pocket-tts
+tts:
+  voice: "azelma"  # Built-in voice name
+  # Or use HuggingFace URL: "hf://kyutai/tts-voices/alba-mackenna/casual.wav"
+  # Or use local file path: "path/to/voice.wav"
+  # Available built-in voices: alba, marius, javert, jean, fantine, cosette, eponine, azelma
+```
+
+You can also pre-load a default voice for faster first generation:
+
+```yaml
+name: pocket-tts
+backend: pocket-tts
+options:
+  - "default_voice:azelma"  # Pre-load this voice when model loads
+```
+
+Then you can use the model:
+
+```
+curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
+     "model": "pocket-tts",
+     "input":"Hello world, this is a test."
+   }' | aplay
+```
+
 ### Vall-E-X
 
 [VALL-E-X](https://github.com/Plachtaa/VALL-E-X) is an open source implementation of Microsoft's VALL-E X zero-shot TTS model.

docs/content/installation/_index.en.md

@@ -20,7 +20,7 @@ Choose the installation method that best suits your needs:
 
 1. **[Docker](docker/)** ⭐ **Recommended** - Works on all platforms, easiest setup
 2. **[macOS](macos/)** - Download and install the DMG application
-3. **[Linux](linux/)** - Install on Linux using the one-liner script or binaries
+3. **[Linux](linux/)** - Install on Linux using binaries (install.sh script currently has issues - see [issue #8032](https://github.com/mudler/LocalAI/issues/8032))
 4. **[Kubernetes](kubernetes/)** - Deploy LocalAI on Kubernetes clusters
 5. **[Build from Source](build/)** - Build LocalAI from source code
 
@@ -36,6 +36,6 @@ This will start LocalAI. The API will be available at `http://localhost:8080`. F
 
 For other platforms:
 - **macOS**: Download the [DMG](macos/)
-- **Linux**: Use the `curl https://localai.io/install.sh | sh` [one-liner](linux/)
+- **Linux**: See the [Linux installation guide](linux/) for installation options. **Note:** The `install.sh` script is currently experiencing issues - see [issue #8032](https://github.com/mudler/LocalAI/issues/8032) for details.
 
 For detailed instructions, see the [Docker installation guide](docker/).

docs/content/installation/linux.md

@@ -6,7 +6,11 @@ url: '/installation/linux/'
 ---
 
 
-## One-Line Installer (Recommended)
+## One-Line Installer
+
+{{% notice warning %}}
+**The `install.sh` script is currently experiencing issues and may produce broken or misconfigured installations. Please use alternative installation methods (Docker or manual binary installation) until [issue #8032](https://github.com/mudler/LocalAI/issues/8032) is resolved.**
+{{% /notice %}}
 
 The fastest way to install LocalAI on Linux is with the installation script:
 

docs/content/reference/cli-reference.md

@@ -97,7 +97,7 @@ For more information on VRAM management, see [VRAM and Memory Management]({{%rel
 | `--opaque-errors` | `false` | If true, all error responses are replaced with blank 500 errors. This is intended only for hardening against information leaks and is normally not recommended | `$LOCALAI_OPAQUE_ERRORS` |
 | `--use-subtle-key-comparison` | `false` | If true, API Key validation comparisons will be performed using constant-time comparisons rather than simple equality. This trades off performance on each request for resilience against timing attacks | `$LOCALAI_SUBTLE_KEY_COMPARISON` |
 | `--disable-api-key-requirement-for-http-get` | `false` | If true, a valid API key is not required to issue GET requests to portions of the web UI. This should only be enabled in secure testing environments | `$LOCALAI_DISABLE_API_KEY_REQUIREMENT_FOR_HTTP_GET` |
-| `--http-get-exempted-endpoints` | `^/$,^/browse/?$,^/talk/?$,^/p2p/?$,^/chat/?$,^/text2image/?$,^/tts/?$,^/static/.*$,^/swagger.*$` | If `--disable-api-key-requirement-for-http-get` is overridden to true, this is the list of endpoints to exempt. Only adjust this in case of a security incident or as a result of a personal security posture review | `$LOCALAI_HTTP_GET_EXEMPTED_ENDPOINTS` |
+| `--http-get-exempted-endpoints` | `^/$,^/browse/?$,^/talk/?$,^/p2p/?$,^/chat/?$,^/image/?$,^/text2image/?$,^/tts/?$,^/static/.*$,^/swagger.*$` | If `--disable-api-key-requirement-for-http-get` is overridden to true, this is the list of endpoints to exempt. Only adjust this in case of a security incident or as a result of a personal security posture review | `$LOCALAI_HTTP_GET_EXEMPTED_ENDPOINTS` |
 
 ## P2P Flags
 

docs/content/reference/compatibility-table.md

@@ -42,6 +42,7 @@ LocalAI will attempt to automatically load models which are not explicitly confi
 | [silero-vad](https://github.com/snakers4/silero-vad) with [Golang bindings](https://github.com/streamer45/silero-vad-go) | Silero VAD    | no                       | Voice Activity Detection    | no                               | no                   | CPU |
 | [neutts](https://github.com/neuphonic/neuttsair) | NeuTTSAir    | no                       | Text-to-speech with voice cloning    | no                               | no                   | CUDA 12/13, ROCm, CPU |
 | [vibevoice](https://github.com/microsoft/VibeVoice) | VibeVoice-Realtime    | no                       | Real-time text-to-speech with voice cloning    | no                               | no                   | CUDA 12/13, ROCm, Intel, CPU |
+| [pocket-tts](https://github.com/kyutai-labs/pocket-tts) | Pocket TTS    | no                       | Lightweight CPU-based text-to-speech with voice cloning    | no                               | no                   | CUDA 12/13, ROCm, Intel, CPU |
 | [mlx-audio](https://github.com/Blaizzy/mlx-audio) | MLX | no                       | Text-tospeech    | no                               | no                   | Metal (Apple Silicon) |
 
 ## Image & Video Generation

gallery/index.yaml

@@ -1,4 +1,56 @@
 ---
+- name: "qwen3-vl-reranker-8b"
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  urls:
+    - https://huggingface.co/mradermacher/Qwen3-VL-Reranker-8B-GGUF
+  description: |
+    **Model Name:** Qwen3-VL-Reranker-8B
+    **Base Model:** Qwen/Qwen3-VL-Reranker-8B
+
+    **Description:**
+    A high-performance multimodal reranking model for state-of-the-art cross-modal search. It supports 30+ languages and handles text, images, screenshots, videos, and mixed modalities. With 8B parameters and a 32K context length, it refines retrieval results by combining embedding vectors with precise relevance scores. Optimized for efficiency, it supports quantized versions (e.g., Q8_0, Q4_K_M) and is ideal for applications requiring accurate multimodal content matching.
+
+    **Key Features:**
+      - **Multimodal**: Text, images, videos, and mixed content.
+      - **Language Support**: 30+ languages.
+      - **Quantization**: Available in Q8_0 (best quality), Q4_K_M (fast, recommended), and lower-precision options.
+      - **Performance**: Outperforms base models in retrieval tasks (e.g., JinaVDR, ViDoRe v3).
+      - **Use Case**: Enhances search pipelines by refining embeddings with precise relevance scores.
+
+    **Downloads:**
+      - [GGUF Files](https://huggingface.co/mradermacher/Qwen3-VL-Reranker-8B-GGUF) (e.g., `Qwen3-VL-Reranker-8B.Q8_0.gguf`).
+
+    **Usage:**
+      - Requires `transformers`, `qwen-vl-utils`, and `torch`.
+      - Example: `from scripts.qwen3_vl_reranker import Qwen3VLReranker; model = Qwen3VLReranker(...)`
+
+    **Citation:**
+    @article{qwen3vlembedding, ...}
+
+    This description emphasizes its capabilities, efficiency, and versatility for multimodal search tasks.
+  overrides:
+    parameters:
+      model: llama-cpp/models/Qwen3-VL-Reranker-8B.Q4_K_M.gguf
+    name: Qwen3-VL-Reranker-8B-GGUF
+    backend: llama-cpp
+    template:
+      use_tokenizer_template: true
+    known_usecases:
+      - chat
+    function:
+      grammar:
+        disable: true
+    mmproj: llama-cpp/mmproj/Qwen3-VL-Reranker-8B.mmproj-f16.gguf
+    description: Imported from https://huggingface.co/mradermacher/Qwen3-VL-Reranker-8B-GGUF
+    options:
+      - use_jinja:true
+  files:
+    - filename: llama-cpp/models/Qwen3-VL-Reranker-8B.Q4_K_M.gguf
+      sha256: f73e62ea68abf741c3e713af823cfb4d2fd2ca35c8b68277b87b4b3d8570b66d
+      uri: https://huggingface.co/mradermacher/Qwen3-VL-Reranker-8B-GGUF/resolve/main/Qwen3-VL-Reranker-8B.Q4_K_M.gguf
+    - filename: llama-cpp/mmproj/Qwen3-VL-Reranker-8B.mmproj-f16.gguf
+      sha256: 15cd9bd4882dae771344f0ac204fce07de91b47c1438ada3861dfc817403c31e
+      uri: https://huggingface.co/mradermacher/Qwen3-VL-Reranker-8B-GGUF/resolve/main/Qwen3-VL-Reranker-8B.mmproj-f16.gguf
 - name: "liquidai.lfm2-2.6b-transcript"
   url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
   urls:
@@ -426,6 +478,16 @@
     - filename: voices/streaming_model/en-Davis_man.pt
       uri: https://raw.githubusercontent.com/microsoft/VibeVoice/main/demo/voices/streaming_model/en-Davis_man.pt
       sha256: 67561d63bfa2153616e4c02fd967007c182593fc53738a6ad94bf5f84e8832ac
+- &pocket-tts
+  url: "github:mudler/LocalAI/gallery/pocket-tts.yaml@master"
+  icon: https://avatars.githubusercontent.com/u/6154722?s=200&v=4
+  license: mit
+  tags:
+    - text-to-speech
+    - TTS
+  name: "pocket-tts"
+  urls:
+    - https://github.com/kyutai-labs/pocket-tts
 - &qwen3vl
   url: "github:mudler/LocalAI/gallery/qwen3.yaml@master"
   icon: https://cdn-avatars.huggingface.co/v1/production/uploads/620760a26e3b7210c2ff1943/-s1gyJfvbE1RgO5iBeNOi.png
@@ -1185,6 +1247,63 @@
       cuda: true
       pipeline_type: QwenImageEditPipeline
       enable_parameters: num_inference_steps,image
+- &ltx2
+  name: "ltx-2"
+  url: "github:mudler/LocalAI/gallery/virtual.yaml@master"
+  urls:
+    - https://huggingface.co/Lightricks/LTX-2
+  license: ltx-2-community-license-agreement
+  tags:
+    - diffusers
+    - gpu
+    - image-to-video
+    - video-generation
+    - audio-video
+  description: |
+    **LTX-2** is a DiT-based audio-video foundation model designed to generate synchronized video and audio within a single model. It brings together the core building blocks of modern video generation, with open weights and a focus on practical, local execution.
+
+    **Key Features:**
+    - **Joint Audio-Video Generation**: Generates synchronized video and audio in a single model
+    - **Image-to-Video**: Converts static images into dynamic videos with matching audio
+    - **High Quality**: Produces realistic video with natural motion and synchronized audio
+    - **Open Weights**: Available under the LTX-2 Community License Agreement
+
+    **Model Details:**
+    - **Model Type**: Diffusion-based audio-video foundation model
+    - **Architecture**: DiT (Diffusion Transformer) based
+    - **Developed by**: Lightricks
+    - **Paper**: [LTX-2: Efficient Joint Audio-Visual Foundation Model](https://arxiv.org/abs/2601.03233)
+
+    **Usage Tips:**
+    - Width & height settings must be divisible by 32
+    - Frame count must be divisible by 8 + 1 (e.g., 9, 17, 25, 33, 41, 49, 57, 65, 73, 81, 89, 97, 105, 113, 121)
+    - Recommended settings: width=768, height=512, num_frames=121, frame_rate=24.0
+    - For best results, use detailed prompts describing motion and scene dynamics
+
+    **Limitations:**
+    - This model is not intended or able to provide factual information
+    - Prompt following is heavily influenced by the prompting-style
+    - When generating audio without speech, the audio may be of lower quality
+
+    **Citation:**
+    ```bibtex
+    @article{hacohen2025ltx2,
+      title={LTX-2: Efficient Joint Audio-Visual Foundation Model},
+      author={HaCohen, Yoav and Brazowski, Benny and Chiprut, Nisan and others},
+      journal={arXiv preprint arXiv:2601.03233},
+      year={2025}
+    }
+    ```
+  overrides:
+    backend: diffusers
+    low_vram: true
+    parameters:
+      model: Lightricks/LTX-2
+    diffusers:
+      cuda: true
+      pipeline_type: LTX2ImageToVideoPipeline
+    options:
+      - torch_dtype:bf16
 - &gptoss
   name: "gpt-oss-20b"
   url: "github:mudler/LocalAI/gallery/harmony.yaml@master"

gallery/pocket-tts.yaml

@@ -0,0 +1,34 @@
+---
+name: localai
+
+config_file: |-
+    name: pocket-tts
+    backend: pocket-tts
+    description: |
+      Pocket TTS is a lightweight text-to-speech model designed to run efficiently on CPUs.
+      This model supports voice cloning through HuggingFace voice URLs or local audio files.
+
+    parameters:
+      model: ""
+
+    # TTS configuration
+    tts:
+      # Voice selection - can be:
+      # 1. Built-in voice name (e.g., "alba", "marius", "javert", "jean", "fantine", "cosette", "eponine", "azelma")
+      # 2. HuggingFace URL (e.g., "hf://kyutai/tts-voices/alba-mackenna/casual.wav")
+      # 3. Local file path (relative to model directory or absolute)
+      # voice: "azelma"
+      # Alternative: use audio_path to specify a voice file directly
+      # audio_path: "hf://kyutai/tts-voices/alba-mackenna/casual.wav"
+
+    known_usecases:
+      - tts
+
+    # Backend-specific options
+    # These are passed as "key:value" strings to the backend
+    options:
+      # Default voice to pre-load (optional)
+      # Can be a voice name or HuggingFace URL
+      # If set, this voice will be loaded when the model loads for faster first generation
+      - "default_voice:azelma"
+      # - "default_voice:hf://kyutai/tts-voices/alba-mackenna/casual.wav"

go.mod

@@ -6,9 +6,10 @@ toolchain go1.24.5
 
 require (
 	dario.cat/mergo v1.0.2
-	fyne.io/fyne/v2 v2.7.1
+	fyne.io/fyne/v2 v2.7.2
 	github.com/Masterminds/sprig/v3 v3.3.0
 	github.com/alecthomas/kong v1.13.0
+	github.com/anthropics/anthropic-sdk-go v1.19.0
 	github.com/charmbracelet/glamour v0.10.0
 	github.com/containerd/containerd v1.7.30
 	github.com/ebitengine/purego v0.9.1
@@ -19,7 +20,7 @@ require (
 	github.com/gofrs/flock v0.13.0
 	github.com/google/go-containerregistry v0.20.7
 	github.com/google/uuid v1.6.0
-	github.com/gpustack/gguf-parser-go v0.22.1
+	github.com/gpustack/gguf-parser-go v0.23.1
 	github.com/hpcloud/tail v1.0.0
 	github.com/ipfs/go-log v1.0.5
 	github.com/jaypipes/ghw v0.21.2
@@ -33,11 +34,11 @@ require (
 	github.com/modelcontextprotocol/go-sdk v1.2.0
 	github.com/mudler/cogito v0.7.2
 	github.com/mudler/edgevpn v0.31.1
-	github.com/mudler/go-processmanager v0.0.0-20240820160718-8b802d3ecf82
+	github.com/mudler/go-processmanager v0.1.0
 	github.com/mudler/memory v0.0.0-20251216220809-d1256471a6c2
 	github.com/mudler/xlog v0.0.5
-	github.com/onsi/ginkgo/v2 v2.27.3
-	github.com/onsi/gomega v1.38.3
+	github.com/onsi/ginkgo/v2 v2.27.5
+	github.com/onsi/gomega v1.39.0
 	github.com/otiai10/copy v1.14.1
 	github.com/otiai10/openaigo v1.7.0
 	github.com/phayes/freeport v0.0.0-20220201140144-74d24b5ae9f5
@@ -67,12 +68,16 @@ require (
 	github.com/ghodss/yaml v1.0.0 // indirect
 	github.com/labstack/gommon v0.4.2 // indirect
 	github.com/swaggo/files/v2 v2.0.2 // indirect
+	github.com/tidwall/gjson v1.18.0 // indirect
+	github.com/tidwall/match v1.1.1 // indirect
+	github.com/tidwall/pretty v1.2.1 // indirect
+	github.com/tidwall/sjson v1.2.5 // indirect
 	github.com/valyala/fasttemplate v1.2.2 // indirect
 	google.golang.org/protobuf v1.36.10 // indirect
 )
 
 require (
-	fyne.io/systray v1.11.1-0.20250603113521-ca66a66d8b58 // indirect
+	fyne.io/systray v1.12.0 // indirect
 	github.com/BurntSushi/toml v1.5.0 // indirect
 	github.com/charmbracelet/colorprofile v0.2.3-0.20250311203215-f60798e515dc // indirect
 	github.com/charmbracelet/lipgloss v1.1.1-0.20250404203927-76690c660834 // indirect
@@ -319,7 +324,7 @@ require (
 	golang.org/x/exp v0.0.0-20250606033433-dcc06ee1d476 // indirect
 	golang.org/x/mod v0.30.0 // indirect
 	golang.org/x/sync v0.19.0 // indirect
-	golang.org/x/sys v0.39.0 // indirect
+	golang.org/x/sys v0.40.0 // indirect
 	golang.org/x/term v0.38.0 // indirect
 	golang.org/x/text v0.32.0 // indirect
 	golang.org/x/tools v0.39.0 // indirect

go.sum

@@ -8,10 +8,10 @@ dmitri.shuralyov.com/app/changes v0.0.0-20180602232624-0a106ad413e3/go.mod h1:Yl
 dmitri.shuralyov.com/html/belt v0.0.0-20180602232347-f7d459c86be0/go.mod h1:JLBrvjyP0v+ecvNYvCpyZgu5/xkfAUhi6wJj28eUfSU=
 dmitri.shuralyov.com/service/change v0.0.0-20181023043359-a85b471d5412/go.mod h1:a1inKt/atXimZ4Mv927x+r7UpyzRUf4emIoiiSC2TN4=
 dmitri.shuralyov.com/state v0.0.0-20180228185332-28bcc343414c/go.mod h1:0PRwlb0D6DFvNNtx+9ybjezNCa8XF0xaYcETyp6rHWU=
-fyne.io/fyne/v2 v2.7.1 h1:ja7rNHWWEooha4XBIZNnPP8tVFwmTfwMJdpZmLxm2Zc=
-fyne.io/fyne/v2 v2.7.1/go.mod h1:xClVlrhxl7D+LT+BWYmcrW4Nf+dJTvkhnPgji7spAwE=
-fyne.io/systray v1.11.1-0.20250603113521-ca66a66d8b58 h1:eA5/u2XRd8OUkoMqEv3IBlFYSruNlXD8bRHDiqm0VNI=
-fyne.io/systray v1.11.1-0.20250603113521-ca66a66d8b58/go.mod h1:RVwqP9nYMo7h5zViCBHri2FgjXF7H2cub7MAq4NSoLs=
+fyne.io/fyne/v2 v2.7.2 h1:XiNpWkn0PzX43ZCjbb0QYGg1RCxVbugwfVgikWZBCMw=
+fyne.io/fyne/v2 v2.7.2/go.mod h1:PXbqY3mQmJV3J1NRUR2VbVgUUx3vgvhuFJxyjRK/4Ug=
+fyne.io/systray v1.12.0 h1:CA1Kk0e2zwFlxtc02L3QFSiIbxJ/P0n582YrZHT7aTM=
+fyne.io/systray v1.12.0/go.mod h1:RVwqP9nYMo7h5zViCBHri2FgjXF7H2cub7MAq4NSoLs=
 git.apache.org/thrift.git v0.0.0-20180902110319-2566ecd5d999/go.mod h1:fPE2ZNJGynbRyZ4dJvy6G277gSllfV2HJqblrnkyeyg=
 github.com/AdaLogics/go-fuzz-headers v0.0.0-20240806141605-e8a1dd7889d6 h1:He8afgbRMd7mFxO99hRNu+6tazq8nFF9lIwo9JFroBk=
 github.com/AdaLogics/go-fuzz-headers v0.0.0-20240806141605-e8a1dd7889d6/go.mod h1:8o94RPi1/7XTJvwPpRSzSUedZrtlirdB3r9Z20bi2f8=
@@ -44,6 +44,8 @@ github.com/andybalholm/brotli v1.0.1/go.mod h1:loMXtMfwqflxFJPmdbJO0a3KNoPuLBgiu
 github.com/andybalholm/brotli v1.2.0 h1:ukwgCxwYrmACq68yiUqwIWnGY0cTPox/M94sVwToPjQ=
 github.com/andybalholm/brotli v1.2.0/go.mod h1:rzTDkvFWvIrjDXZHkuS16NPggd91W3kUSvPlQ1pLaKY=
 github.com/anmitsu/go-shlex v0.0.0-20161002113705-648efa622239/go.mod h1:2FmKhYUyUczH0OGQWaF5ceTx0UBShxjsH6f8oGKYe2c=
+github.com/anthropics/anthropic-sdk-go v1.19.0 h1:mO6E+ffSzLRvR/YUH9KJC0uGw0uV8GjISIuzem//3KE=
+github.com/anthropics/anthropic-sdk-go v1.19.0/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
 github.com/aymanbagabas/go-osc52/v2 v2.0.1 h1:HwpRHbFMcZLEVr42D4p7XBqjyuxQH5SMiErDT4WkJ2k=
 github.com/aymanbagabas/go-osc52/v2 v2.0.1/go.mod h1:uYgXzlJ7ZpABp8OJ+exZzJJhRNQ2ASbcXHWsFqH8hp8=
 github.com/aymanbagabas/go-udiff v0.2.0 h1:TK0fH4MteXUDspT88n8CKzvK0X9O2xu9yQjWpi6yML8=
@@ -290,8 +292,8 @@ github.com/gorilla/css v1.0.1 h1:ntNaBIghp6JmvWnxbZKANoLyuXTPZ4cAMlo6RyhlbO8=
 github.com/gorilla/css v1.0.1/go.mod h1:BvnYkspnSzMmwRK+b8/xgNPLiIuNZr6vbZBTPQ2A3b0=
 github.com/gorilla/websocket v1.5.3 h1:saDtZ6Pbx/0u+bgYQ3q96pZgCzfhKXGPqt7kZ72aNNg=
 github.com/gorilla/websocket v1.5.3/go.mod h1:YR8l580nyteQvAITg2hZ9XVh4b55+EU/adAjf1fMHhE=
-github.com/gpustack/gguf-parser-go v0.22.1 h1:FRnEDWqT0Rcplr/R9ctCRSN2+3DhVsf6dnR5/i9JA4E=
-github.com/gpustack/gguf-parser-go v0.22.1/go.mod h1:y4TwTtDqFWTK+xvprOjRUh+dowgU2TKCX37vRKvGiZ0=
+github.com/gpustack/gguf-parser-go v0.23.1 h1:0U7DOrsi7ryx2L/dlMy+BSQ5bJV4AuMEIgGBs4RK46A=
+github.com/gpustack/gguf-parser-go v0.23.1/go.mod h1:y4TwTtDqFWTK+xvprOjRUh+dowgU2TKCX37vRKvGiZ0=
 github.com/gregjones/httpcache v0.0.0-20180305231024-9cad4c3443a7/go.mod h1:FecbI9+v66THATjSRHfNgh1IVFe/9kFxbXtjV0ctIMA=
 github.com/grpc-ecosystem/grpc-gateway v1.5.0/go.mod h1:RSKVYQBd5MCa4OVpNdGskqpgL2+G+NZTnrVHpWWfpdw=
 github.com/grpc-ecosystem/grpc-gateway v1.16.0 h1:gmcG1KaJ57LophUzW0Hy8NmPhnMZb4M0+kPpLofRdBo=
@@ -511,8 +513,8 @@ github.com/mudler/edgevpn v0.31.1 h1:7qegiDWd0kAg6ljhNHxqvp8hbo/6BbzSdbb7/2WZfiY
 github.com/mudler/edgevpn v0.31.1/go.mod h1:ftV5B0nKFzm4R8vR80UYnCb2nf7lxCRgAALxUEEgCf8=
 github.com/mudler/go-piper v0.0.0-20241023091659-2494246fd9fc h1:RxwneJl1VgvikiX28EkpdAyL4yQVnJMrbquKospjHyA=
 github.com/mudler/go-piper v0.0.0-20241023091659-2494246fd9fc/go.mod h1:O7SwdSWMilAWhBZMK9N9Y/oBDyMMzshE3ju8Xkexwig=
-github.com/mudler/go-processmanager v0.0.0-20240820160718-8b802d3ecf82 h1:FVT07EI8njvsD4tC2Hw8Xhactp5AWhsQWD4oTeQuSAU=
-github.com/mudler/go-processmanager v0.0.0-20240820160718-8b802d3ecf82/go.mod h1:Urp7LG5jylKoDq0663qeBh0pINGcRl35nXdKx82PSoU=
+github.com/mudler/go-processmanager v0.1.0 h1:fcSKgF9U/a1Z7KofAFeZnke5YseadCI5GqL9oT0LS3E=
+github.com/mudler/go-processmanager v0.1.0/go.mod h1:h6kmHUZeafr+k5hRYpGLMzJFH4hItHffgpRo2QIkP+o=
 github.com/mudler/memory v0.0.0-20251216220809-d1256471a6c2 h1:+WHsL/j6EWOMUiMVIOJNKOwSKiQt/qDPc9fePCf87fA=
 github.com/mudler/memory v0.0.0-20251216220809-d1256471a6c2/go.mod h1:EA8Ashhd56o32qN7ouPKFSRUs/Z+LrRCF4v6R2Oarm8=
 github.com/mudler/water v0.0.0-20250808092830-dd90dcf09025 h1:WFLP5FHInarYGXi6B/Ze204x7Xy6q/I4nCZnWEyPHK0=
@@ -559,10 +561,10 @@ github.com/nxadm/tail v1.4.8 h1:nPr65rt6Y5JFSKQO7qToXr7pePgD6Gwiw05lkbyAQTE=
 github.com/nxadm/tail v1.4.8/go.mod h1:+ncqLTQzXmGhMZNUePPaPqPvBxHAIsmXswZKocGu+AU=
 github.com/onsi/ginkgo v1.16.5 h1:8xi0RTUf59SOSfEtZMvwTvXYMzG4gV23XVHOZiXNtnE=
 github.com/onsi/ginkgo v1.16.5/go.mod h1:+E8gABHa3K6zRBolWtd+ROzc/U5bkGt0FwiG042wbpU=
-github.com/onsi/ginkgo/v2 v2.27.3 h1:ICsZJ8JoYafeXFFlFAG75a7CxMsJHwgKwtO+82SE9L8=
-github.com/onsi/ginkgo/v2 v2.27.3/go.mod h1:ArE1D/XhNXBXCBkKOLkbsb2c81dQHCRcF5zwn/ykDRo=
-github.com/onsi/gomega v1.38.3 h1:eTX+W6dobAYfFeGC2PV6RwXRu/MyT+cQguijutvkpSM=
-github.com/onsi/gomega v1.38.3/go.mod h1:ZCU1pkQcXDO5Sl9/VVEGlDyp+zm0m1cmeG5TOzLgdh4=
+github.com/onsi/ginkgo/v2 v2.27.5 h1:ZeVgZMx2PDMdJm/+w5fE/OyG6ILo1Y3e+QX4zSR0zTE=
+github.com/onsi/ginkgo/v2 v2.27.5/go.mod h1:ArE1D/XhNXBXCBkKOLkbsb2c81dQHCRcF5zwn/ykDRo=
+github.com/onsi/gomega v1.39.0 h1:y2ROC3hKFmQZJNFeGAMeHZKkjBL65mIZcvrLQBF9k6Q=
+github.com/onsi/gomega v1.39.0/go.mod h1:ZCU1pkQcXDO5Sl9/VVEGlDyp+zm0m1cmeG5TOzLgdh4=
 github.com/opencontainers/go-digest v1.0.0 h1:apOUWs51W5PlhuyGyz9FCeeBIOUDA/6nW8Oi/yOhh5U=
 github.com/opencontainers/go-digest v1.0.0/go.mod h1:0JzlMkj0TRzQZfJkVvzbP0HBR3IKzErnv2BNG4W4MAM=
 github.com/opencontainers/image-spec v1.1.1 h1:y0fUlFfIZhPF1W537XOLg0/fcx6zcHCJwooC2xJA040=
@@ -762,10 +764,12 @@ github.com/swaggo/swag v1.16.6/go.mod h1:ngP2etMK5a0P3QBizic5MEwpRmluJZPHjXcMoj4
 github.com/tarm/serial v0.0.0-20180830185346-98f6abe2eb07/go.mod h1:kDXzergiv9cbyO7IOYJZWg1U88JhDg3PB6klq9Hg2pA=
 github.com/testcontainers/testcontainers-go v0.40.0 h1:pSdJYLOVgLE8YdUY2FHQ1Fxu+aMnb6JfVz1mxk7OeMU=
 github.com/testcontainers/testcontainers-go v0.40.0/go.mod h1:FSXV5KQtX2HAMlm7U3APNyLkkap35zNLxukw9oBi/MY=
+github.com/tidwall/gjson v1.14.2/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
 github.com/tidwall/gjson v1.18.0 h1:FIDeeyB800efLX89e5a8Y0BNH+LOngJyGrIWxG2FKQY=
 github.com/tidwall/gjson v1.18.0/go.mod h1:/wbyibRr2FHMks5tjHJ5F8dMZh3AcwJEMf5vlfC0lxk=
 github.com/tidwall/match v1.1.1 h1:+Ho715JplO36QYgwN9PGYNhgZvoUSc9X2c80KVTi+GA=
 github.com/tidwall/match v1.1.1/go.mod h1:eRSPERbgtNPcGhD8UCthc6PmLEQXEWd3PRB5JTxsfmM=
+github.com/tidwall/pretty v1.2.0/go.mod h1:ITEVvHYasfjBbM0u2Pg8T2nJnzm8xPwvNhhsoaGGjNU=
 github.com/tidwall/pretty v1.2.1 h1:qjsOFOWWQl+N3RsoF5/ssm1pHmJJwhjlSbZ51I6wMl4=
 github.com/tidwall/pretty v1.2.1/go.mod h1:ITEVvHYasfjBbM0u2Pg8T2nJnzm8xPwvNhhsoaGGjNU=
 github.com/tidwall/sjson v1.2.5 h1:kLy8mja+1c9jlljvWTlSazM7cKDRfJuR/bOJhcY5NcY=
@@ -974,8 +978,8 @@ golang.org/x/sys v0.8.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.10.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.11.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.16.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
-golang.org/x/sys v0.39.0 h1:CvCKL8MeisomCi6qNZ+wbb0DN9E5AATixKsvNtMoMFk=
-golang.org/x/sys v0.39.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
+golang.org/x/sys v0.40.0 h1:DBZZqJ2Rkml6QMQsZywtnjnnGvHza6BTfYFWY9kjEWQ=
+golang.org/x/sys v0.40.0/go.mod h1:OgkHotnGiDImocRcuBABYBEXf8A9a87e/uXjp9XT3ks=
 golang.org/x/telemetry v0.0.0-20251111182119-bc8e575c7b54 h1:E2/AqCUMZGgd73TQkxUMcMla25GB9i/5HOdLr+uH7Vo=
 golang.org/x/telemetry v0.0.0-20251111182119-bc8e575c7b54/go.mod h1:hKdjCMrbv9skySur+Nek8Hd0uJ0GuxJIoIX2payrIdQ=
 golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=

pkg/functions/parse.go

@@ -1492,7 +1492,7 @@ func ParseFunctionCall(llmresult string, functionConfig FunctionsConfig) []FuncC
 	results := []FuncCallResults{}
 	llmResults := []string{}
 
-	returnResult := func(results []string) (result []FuncCallResults, e error) {
+	extractJSON := func(results []string) (result []FuncCallResults, e error) {
 		// As we have to change the result before processing, we can't stream the answer token-by-token (yet?)
 		result = make([]FuncCallResults, 0)
 
@@ -1593,7 +1593,7 @@ func ParseFunctionCall(llmresult string, functionConfig FunctionsConfig) []FuncC
 		if len(llmResults) == 0 {
 			llmResults = append(llmResults, llmresult)
 		}
-		results, _ = returnResult(llmResults)
+		results, _ = extractJSON(llmResults)
 	}
 
 	// Determine which XML format to use (if any)
@@ -1632,8 +1632,16 @@ func ParseFunctionCall(llmresult string, functionConfig FunctionsConfig) []FuncC
 		// But skip if JSONRegexMatch or ResponseRegex was used (they already extracted the content)
 		xmlResults, err := ParseXML(llmresult, xmlFormat)
 		if err == nil && len(xmlResults) > 0 {
-			xlog.Debug("Found additional XML tool calls alongside JSON", "xml_count", len(xmlResults))
-			results = append(results, xmlResults...)
+			// Check if JSON is inside XML tags, if so, skip it
+			for _, result := range xmlResults {
+				jsonResults, _ := extractJSON([]string{result.Name})
+				if len(jsonResults) > 0 {
+					xlog.Debug("Found valid JSON inside XML tags, skipping XML parsing", "json_count", len(jsonResults))
+				} else {
+					xlog.Debug("Found additional XML tool calls alongside JSON", "xml_count", len(xmlResults))
+					results = append(results, xmlResults...)
+				}
+			}
 		}
 	}
 

pkg/functions/parse_test.go

@@ -820,6 +820,23 @@ Final text`
 			Expect(results[0].Name).To(Equal("first"))
 			Expect(results[1].Name).To(Equal("second"))
 		})
+
+		It("should not duplicate parse JSON inside tool_call tags", func() {
+			// This test reproduces a bug where JSON inside <tool_call> tags
+			// gets parsed twice: once as JSON (correctly) and once as XML (incorrectly)
+			// The XML parser should not run when JSON parsing already found valid results
+			input := `<tool_call>
+{"name": "get_current_weather", "arguments": {"location": "Beijing", "unit": "celsius"}}
+</tool_call>`
+
+			results := ParseFunctionCall(input, functionConfig)
+			// Should only have 1 result, not 2 (one correct + one malformed)
+			Expect(results).To(HaveLen(1), "Should not create duplicate entries when JSON is inside XML tags")
+			Expect(results[0].Name).To(Equal("get_current_weather"))
+			Expect(results[0].Arguments).To(Equal(`{"location":"Beijing","unit":"celsius"}`))
+			// Verify the name is not the entire JSON object (which would indicate malformed XML parsing)
+			Expect(results[0].Name).NotTo(ContainSubstring(`{"name"`), "Function name should not contain JSON object")
+		})
 	})
 
 	Context("Iterative Parser (ChatMsgParser)", func() {

pkg/functions/reasoning.go

@@ -0,0 +1,114 @@
+package functions
+
+import (
+	"strings"
+)
+
+// ExtractReasoning extracts reasoning content from thinking tags and returns
+// both the extracted reasoning and the cleaned content (with tags removed).
+// It handles <thinking>...</thinking> and <think>...</think> tags.
+// Multiple reasoning blocks are concatenated with newlines.
+func ExtractReasoning(content string) (reasoning string, cleanedContent string) {
+	if content == "" {
+		return "", content
+	}
+
+	var reasoningParts []string
+	var cleanedParts []string
+	remaining := content
+
+	// Define tag pairs to look for
+	tagPairs := []struct {
+		start string
+		end   string
+	}{
+		{"<thinking>", "</thinking>"},
+		{"<think>", "</think>"},
+	}
+
+	// Track the last position we've processed
+	lastPos := 0
+
+	for {
+		// Find the earliest tag start
+		earliestStart := -1
+		earliestEnd := -1
+		isUnclosed := false
+		var matchedTag struct {
+			start string
+			end   string
+		}
+
+		for _, tagPair := range tagPairs {
+			startIdx := strings.Index(remaining[lastPos:], tagPair.start)
+			if startIdx == -1 {
+				continue
+			}
+			startIdx += lastPos
+
+			// Find the corresponding end tag
+			endIdx := strings.Index(remaining[startIdx+len(tagPair.start):], tagPair.end)
+			if endIdx == -1 {
+				// Unclosed tag - extract what we have
+				if earliestStart == -1 || startIdx < earliestStart {
+					earliestStart = startIdx
+					earliestEnd = len(remaining)
+					isUnclosed = true
+					matchedTag = tagPair
+				}
+				continue
+			}
+			endIdx += startIdx + len(tagPair.start)
+
+			// Found a complete tag pair
+			if earliestStart == -1 || startIdx < earliestStart {
+				earliestStart = startIdx
+				earliestEnd = endIdx + len(tagPair.end)
+				isUnclosed = false
+				matchedTag = tagPair
+			}
+		}
+
+		if earliestStart == -1 {
+			// No more tags found, add remaining content
+			if lastPos < len(remaining) {
+				cleanedParts = append(cleanedParts, remaining[lastPos:])
+			}
+			break
+		}
+
+		// Add content before the tag
+		if earliestStart > lastPos {
+			cleanedParts = append(cleanedParts, remaining[lastPos:earliestStart])
+		}
+
+		// Extract reasoning content
+		reasoningStart := earliestStart + len(matchedTag.start)
+		// For unclosed tags, earliestEnd is already at the end of the string
+		// For closed tags, earliestEnd points to after the closing tag, so we subtract the end tag length
+		var reasoningEnd int
+		if isUnclosed {
+			// Unclosed tag - extract everything to the end
+			reasoningEnd = len(remaining)
+		} else {
+			// Closed tag - exclude the end tag
+			reasoningEnd = earliestEnd - len(matchedTag.end)
+		}
+		if reasoningEnd > reasoningStart {
+			reasoningContent := strings.TrimSpace(remaining[reasoningStart:reasoningEnd])
+			if reasoningContent != "" {
+				reasoningParts = append(reasoningParts, reasoningContent)
+			}
+		}
+
+		// Move past this tag
+		lastPos = earliestEnd
+	}
+
+	// Combine reasoning parts
+	reasoning = strings.Join(reasoningParts, "\n\n")
+	// Combine cleaned content parts
+	cleanedContent = strings.Join(cleanedParts, "")
+
+	return reasoning, cleanedContent
+}

pkg/functions/reasoning_test.go

@@ -0,0 +1,261 @@
+package functions_test
+
+import (
+	"strings"
+
+	. "github.com/mudler/LocalAI/pkg/functions"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+var _ = Describe("ExtractReasoning", func() {
+	Context("when content has no reasoning tags", func() {
+		It("should return empty reasoning and original content", func() {
+			content := "This is regular content without any tags."
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal(content))
+		})
+
+		It("should handle empty string", func() {
+			content := ""
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(BeEmpty())
+		})
+
+		It("should handle content with only whitespace", func() {
+			content := "   \n\t  "
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal(content))
+		})
+	})
+
+	Context("when content has <thinking> tags", func() {
+		It("should extract reasoning from single thinking block", func() {
+			content := "Some text <thinking>This is my reasoning</thinking> More text"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("This is my reasoning"))
+			Expect(cleaned).To(Equal("Some text  More text"))
+		})
+
+		It("should extract reasoning and preserve surrounding content", func() {
+			content := "Before <thinking>Reasoning here</thinking> After"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Reasoning here"))
+			Expect(cleaned).To(Equal("Before  After"))
+		})
+
+		It("should handle thinking block at the start", func() {
+			content := "<thinking>Start reasoning</thinking> Regular content"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Start reasoning"))
+			Expect(cleaned).To(Equal(" Regular content"))
+		})
+
+		It("should handle thinking block at the end", func() {
+			content := "Regular content <thinking>End reasoning</thinking>"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("End reasoning"))
+			Expect(cleaned).To(Equal("Regular content "))
+		})
+
+		It("should handle only thinking block", func() {
+			content := "<thinking>Only reasoning</thinking>"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Only reasoning"))
+			Expect(cleaned).To(BeEmpty())
+		})
+
+		It("should trim whitespace from reasoning content", func() {
+			content := "Text <thinking>  \n  Reasoning with spaces  \n  </thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Reasoning with spaces"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+	})
+
+	Context("when content has <think> tags", func() {
+		It("should extract reasoning from redacted_reasoning block", func() {
+			content := "Text <think>Redacted reasoning</think> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Redacted reasoning"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+
+		It("should handle redacted_reasoning with multiline content", func() {
+			content := "Before <think>Line 1\nLine 2\nLine 3</think> After"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Line 1\nLine 2\nLine 3"))
+			Expect(cleaned).To(Equal("Before  After"))
+		})
+
+		It("should handle redacted_reasoning with complex content", func() {
+			content := "Start <think>Complex reasoning\nwith\nmultiple\nlines</think> End"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Complex reasoning\nwith\nmultiple\nlines"))
+			Expect(cleaned).To(Equal("Start  End"))
+		})
+	})
+
+	Context("when content has multiple reasoning blocks", func() {
+		It("should concatenate multiple thinking blocks with newlines", func() {
+			content := "Text <thinking>First</thinking> Middle <thinking>Second</thinking> End"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("First\n\nSecond"))
+			Expect(cleaned).To(Equal("Text  Middle  End"))
+		})
+
+		It("should handle multiple different tag types", func() {
+			content := "A <thinking>One</thinking> B <think>Two</think> C <think>Three</think> D"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(ContainSubstring("One"))
+			Expect(reasoning).To(ContainSubstring("Two"))
+			Expect(reasoning).To(ContainSubstring("Three"))
+			Expect(cleaned).To(Equal("A  B  C  D"))
+		})
+
+		It("should handle nested tags correctly (extracts first match)", func() {
+			content := "Text <thinking>Outer <think>Inner</think></thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			// Should extract the outer thinking block
+			Expect(reasoning).To(ContainSubstring("Outer"))
+			Expect(reasoning).To(ContainSubstring("Inner"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+	})
+
+	Context("when content has unclosed reasoning tags", func() {
+		It("should extract unclosed thinking block", func() {
+			content := "Text <thinking>Unclosed reasoning"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Unclosed reasoning"))
+			Expect(cleaned).To(Equal("Text "))
+		})
+
+		It("should extract unclosed think block", func() {
+			content := "Before <think>Incomplete"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Incomplete"))
+			Expect(cleaned).To(Equal("Before "))
+		})
+
+		It("should extract unclosed redacted_reasoning block", func() {
+			content := "Start <think>Partial reasoning content"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Partial reasoning content"))
+			Expect(cleaned).To(Equal("Start "))
+		})
+
+		It("should handle unclosed tag at the end", func() {
+			content := "Regular content <thinking>Unclosed at end"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Unclosed at end"))
+			Expect(cleaned).To(Equal("Regular content "))
+		})
+	})
+
+	Context("when content has empty reasoning blocks", func() {
+		It("should ignore empty thinking block", func() {
+			content := "Text <thinking></thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+
+		It("should ignore thinking block with only whitespace", func() {
+			content := "Text <thinking>   \n\t  </thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+	})
+
+	Context("when content has reasoning tags with special characters", func() {
+		It("should handle reasoning with newlines", func() {
+			content := "Before <thinking>Line 1\nLine 2\nLine 3</thinking> After"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Line 1\nLine 2\nLine 3"))
+			Expect(cleaned).To(Equal("Before  After"))
+		})
+
+		It("should handle reasoning with code blocks", func() {
+			content := "Text <thinking>Reasoning with ```code``` blocks</thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Reasoning with ```code``` blocks"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+
+		It("should handle reasoning with JSON", func() {
+			content := "Before <think>{\"key\": \"value\"}</think> After"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("{\"key\": \"value\"}"))
+			Expect(cleaned).To(Equal("Before  After"))
+		})
+
+		It("should handle reasoning with HTML-like content", func() {
+			content := "Text <thinking>Reasoning with <tags> inside</thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Reasoning with <tags> inside"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+	})
+
+	Context("when content has reasoning mixed with regular content", func() {
+		It("should preserve content order correctly", func() {
+			content := "Start <thinking>Reasoning</thinking> Middle <think>More reasoning</think> End"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(ContainSubstring("Reasoning"))
+			Expect(reasoning).To(ContainSubstring("More reasoning"))
+			Expect(cleaned).To(Equal("Start  Middle  End"))
+		})
+
+		It("should handle reasoning in the middle of a sentence", func() {
+			content := "This is a <thinking>reasoning</thinking> sentence."
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("reasoning"))
+			Expect(cleaned).To(Equal("This is a  sentence."))
+		})
+	})
+
+	Context("edge cases", func() {
+		It("should handle content with only opening tag", func() {
+			content := "<thinking>"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal(""))
+		})
+
+		It("should handle content with only closing tag", func() {
+			content := "</thinking>"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(BeEmpty())
+			Expect(cleaned).To(Equal("</thinking>"))
+		})
+
+		It("should handle mismatched tags", func() {
+			content := "<thinking>Content</think>"
+			reasoning, cleaned := ExtractReasoning(content)
+			// Should extract unclosed thinking block
+			Expect(reasoning).To(ContainSubstring("Content"))
+			Expect(cleaned).To(Equal(""))
+		})
+
+		It("should handle very long reasoning content", func() {
+			longReasoning := strings.Repeat("This is reasoning content. ", 100)
+			content := "Text <thinking>" + longReasoning + "</thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			// TrimSpace is applied, so we need to account for that
+			Expect(reasoning).To(Equal(strings.TrimSpace(longReasoning)))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+
+		It("should handle reasoning with unicode characters", func() {
+			content := "Text <thinking>Reasoning with 中文 and emoji 🧠</thinking> More"
+			reasoning, cleaned := ExtractReasoning(content)
+			Expect(reasoning).To(Equal("Reasoning with 中文 and emoji 🧠"))
+			Expect(cleaned).To(Equal("Text  More"))
+		})
+	})
+})

pkg/model/process.go

@@ -24,8 +24,6 @@ func (ml *ModelLoader) deleteProcess(s string) error {
 		return fmt.Errorf("model %s not found", s)
 	}
 
-	defer delete(ml.models, s)
-
 	retries := 1
 	for model.GRPC(false, ml.wd).IsBusy() {
 		xlog.Debug("Model busy. Waiting.", "model", s)
@@ -48,6 +46,7 @@ func (ml *ModelLoader) deleteProcess(s string) error {
 	if process == nil {
 		xlog.Error("No process", "model", s)
 		// Nothing to do as there is no process
+		delete(ml.models, s)
 		return nil
 	}
 
@@ -56,6 +55,10 @@ func (ml *ModelLoader) deleteProcess(s string) error {
 		xlog.Error("(deleteProcess) error while deleting process", "error", err, "model", s)
 	}
 
+	if err == nil {
+		delete(ml.models, s)
+	}
+
 	return err
 }
 

pkg/system/capabilities.go

@@ -12,15 +12,17 @@ import (
 )
 
 const (
+	// Public constants - used by tests and external packages
+	Nvidia = "nvidia"
+	AMD    = "amd"
+	Intel  = "intel"
+
+	// Private constants - only used within this package
 	defaultCapability = "default"
 	nvidiaL4T         = "nvidia-l4t"
 	darwinX86         = "darwin-x86"
 	metal             = "metal"
-	nvidia            = "nvidia"
-
-	amd    = "amd"
-	intel  = "intel"
-	vulkan = "vulkan"
+	vulkan            = "vulkan"
 
 	nvidiaCuda13    = "nvidia-cuda-13"
 	nvidiaCuda12    = "nvidia-cuda-12"
@@ -30,6 +32,16 @@ const (
 	capabilityEnv        = "LOCALAI_FORCE_META_BACKEND_CAPABILITY"
 	capabilityRunFileEnv = "LOCALAI_FORCE_META_BACKEND_CAPABILITY_RUN_FILE"
 	defaultRunFile       = "/run/localai/capability"
+
+	// Backend detection tokens (private)
+	backendTokenDarwin = "darwin"
+	backendTokenMLX    = "mlx"
+	backendTokenMetal  = "metal"
+	backendTokenL4T    = "l4t"
+	backendTokenCUDA   = "cuda"
+	backendTokenROCM   = "rocm"
+	backendTokenHIP    = "hip"
+	backendTokenSYCL   = "sycl"
 )
 
 var (
@@ -96,7 +108,7 @@ func (s *SystemState) getSystemCapabilities() string {
 
 	// If arm64 on linux and a nvidia gpu is detected, we will return nvidia-l4t
 	if runtime.GOOS == "linux" && runtime.GOARCH == "arm64" {
-		if s.GPUVendor == nvidia {
+		if s.GPUVendor == Nvidia {
 			xlog.Info("Using nvidia-l4t capability (arm64 on linux)", "env", capabilityEnv)
 			if cuda13DirExists {
 				return nvidiaL4TCuda13
@@ -131,7 +143,6 @@ func (s *SystemState) getSystemCapabilities() string {
 	return s.GPUVendor
 }
 
-
 // BackendPreferenceTokens returns a list of substrings that represent the preferred
 // backend implementation order for the current system capability. Callers can use
 // these tokens to select the most appropriate concrete backend among multiple
@@ -139,19 +150,76 @@ func (s *SystemState) getSystemCapabilities() string {
 func (s *SystemState) BackendPreferenceTokens() []string {
 	capStr := strings.ToLower(s.getSystemCapabilities())
 	switch {
-	case strings.HasPrefix(capStr, nvidia):
-		return []string{"cuda", "vulkan", "cpu"}
-	case strings.HasPrefix(capStr, amd):
-		return []string{"rocm", "hip", "vulkan", "cpu"}
-	case strings.HasPrefix(capStr, intel):
-		return []string{"sycl", intel, "cpu"}
+	case strings.HasPrefix(capStr, Nvidia):
+		return []string{backendTokenCUDA, vulkan, "cpu"}
+	case strings.HasPrefix(capStr, AMD):
+		return []string{backendTokenROCM, backendTokenHIP, vulkan, "cpu"}
+	case strings.HasPrefix(capStr, Intel):
+		return []string{backendTokenSYCL, Intel, "cpu"}
 	case strings.HasPrefix(capStr, metal):
-		return []string{"metal", "cpu"}
+		return []string{backendTokenMetal, "cpu"}
 	case strings.HasPrefix(capStr, darwinX86):
 		return []string{"darwin-x86", "cpu"}
 	case strings.HasPrefix(capStr, vulkan):
-		return []string{"vulkan", "cpu"}
+		return []string{vulkan, "cpu"}
 	default:
 		return []string{"cpu"}
 	}
 }
+
+// DetectedCapability returns the detected system capability string.
+// This can be used by the UI to display what capability was detected.
+func (s *SystemState) DetectedCapability() string {
+	return s.getSystemCapabilities()
+}
+
+// IsBackendCompatible checks if a backend (identified by name and URI) is compatible
+// with the current system capability. This function uses getSystemCapabilities to ensure
+// consistency with capability detection (including VRAM checks, environment overrides, etc.).
+func (s *SystemState) IsBackendCompatible(name, uri string) bool {
+	combined := strings.ToLower(name + " " + uri)
+	capability := s.getSystemCapabilities()
+
+	// Check for darwin/macOS-specific backends (mlx, metal, darwin)
+	isDarwinBackend := strings.Contains(combined, backendTokenDarwin) ||
+		strings.Contains(combined, backendTokenMLX) ||
+		strings.Contains(combined, backendTokenMetal)
+	if isDarwinBackend {
+		// Darwin backends require the system to be running on darwin with metal or darwin-x86 capability
+		return capability == metal || capability == darwinX86
+	}
+
+	// Check for NVIDIA L4T-specific backends (arm64 Linux with NVIDIA GPU)
+	// This must be checked before the general NVIDIA check as L4T backends
+	// may also contain "cuda" or "nvidia" in their names
+	isL4TBackend := strings.Contains(combined, backendTokenL4T)
+	if isL4TBackend {
+		return strings.HasPrefix(capability, nvidiaL4T)
+	}
+
+	// Check for NVIDIA/CUDA-specific backends (non-L4T)
+	isNvidiaBackend := strings.Contains(combined, backendTokenCUDA) ||
+		strings.Contains(combined, Nvidia)
+	if isNvidiaBackend {
+		// NVIDIA backends are compatible with nvidia, nvidia-cuda-12, nvidia-cuda-13, and l4t capabilities
+		return strings.HasPrefix(capability, Nvidia)
+	}
+
+	// Check for AMD/ROCm-specific backends
+	isAMDBackend := strings.Contains(combined, backendTokenROCM) ||
+		strings.Contains(combined, backendTokenHIP) ||
+		strings.Contains(combined, AMD)
+	if isAMDBackend {
+		return capability == AMD
+	}
+
+	// Check for Intel/SYCL-specific backends
+	isIntelBackend := strings.Contains(combined, backendTokenSYCL) ||
+		strings.Contains(combined, Intel)
+	if isIntelBackend {
+		return capability == Intel
+	}
+
+	// CPU backends are always compatible
+	return true
+}

scripts/build/package-gpu-libs.sh

@@ -148,10 +148,10 @@ package_cuda_libs() {
     done
 
     # Copy CUDA target directory for runtime compilation support
-    if [ -d "/usr/local/cuda/targets" ]; then
-        mkdir -p "$TARGET_LIB_DIR/../cuda"
-        cp -arfL /usr/local/cuda/targets "$TARGET_LIB_DIR/../cuda/" 2>/dev/null || true
-    fi
+    # if [ -d "/usr/local/cuda/targets" ]; then
+    #     mkdir -p "$TARGET_LIB_DIR/../cuda"
+    #     cp -arfL /usr/local/cuda/targets "$TARGET_LIB_DIR/../cuda/" 2>/dev/null || true
+    # fi
 
     echo "CUDA libraries packaged successfully"
 }

swagger/docs.go

@@ -1198,6 +1198,30 @@ const docTemplate = `{
                 }
             }
         },
+        "/v1/messages": {
+            "post": {
+                "summary": "Generate a message response for the given messages and model.",
+                "parameters": [
+                    {
+                        "description": "query params",
+                        "name": "request",
+                        "in": "body",
+                        "required": true,
+                        "schema": {
+                            "$ref": "#/definitions/schema.AnthropicRequest"
+                        }
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "schema": {
+                            "$ref": "#/definitions/schema.AnthropicResponse"
+                        }
+                    }
+                }
+            }
+        },
         "/v1/models": {
             "get": {
                 "summary": "List and describe the various models available in the API.",
@@ -1739,6 +1763,169 @@ const docTemplate = `{
                 }
             }
         },
+        "schema.AnthropicContentBlock": {
+            "type": "object",
+            "properties": {
+                "content": {},
+                "id": {
+                    "type": "string"
+                },
+                "input": {
+                    "type": "object",
+                    "additionalProperties": true
+                },
+                "is_error": {
+                    "type": "boolean"
+                },
+                "name": {
+                    "type": "string"
+                },
+                "source": {
+                    "$ref": "#/definitions/schema.AnthropicImageSource"
+                },
+                "text": {
+                    "type": "string"
+                },
+                "tool_use_id": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicImageSource": {
+            "type": "object",
+            "properties": {
+                "data": {
+                    "type": "string"
+                },
+                "media_type": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicMessage": {
+            "type": "object",
+            "properties": {
+                "content": {},
+                "role": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicRequest": {
+            "type": "object",
+            "properties": {
+                "max_tokens": {
+                    "type": "integer"
+                },
+                "messages": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicMessage"
+                    }
+                },
+                "metadata": {
+                    "type": "object",
+                    "additionalProperties": {
+                        "type": "string"
+                    }
+                },
+                "model": {
+                    "type": "string"
+                },
+                "stop_sequences": {
+                    "type": "array",
+                    "items": {
+                        "type": "string"
+                    }
+                },
+                "stream": {
+                    "type": "boolean"
+                },
+                "system": {
+                    "type": "string"
+                },
+                "temperature": {
+                    "type": "number"
+                },
+                "tool_choice": {},
+                "tools": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicTool"
+                    }
+                },
+                "top_k": {
+                    "type": "integer"
+                },
+                "top_p": {
+                    "type": "number"
+                }
+            }
+        },
+        "schema.AnthropicResponse": {
+            "type": "object",
+            "properties": {
+                "content": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicContentBlock"
+                    }
+                },
+                "id": {
+                    "type": "string"
+                },
+                "model": {
+                    "type": "string"
+                },
+                "role": {
+                    "type": "string"
+                },
+                "stop_reason": {
+                    "type": "string"
+                },
+                "stop_sequence": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                },
+                "usage": {
+                    "$ref": "#/definitions/schema.AnthropicUsage"
+                }
+            }
+        },
+        "schema.AnthropicTool": {
+            "type": "object",
+            "properties": {
+                "description": {
+                    "type": "string"
+                },
+                "input_schema": {
+                    "type": "object",
+                    "additionalProperties": true
+                },
+                "name": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicUsage": {
+            "type": "object",
+            "properties": {
+                "input_tokens": {
+                    "type": "integer"
+                },
+                "output_tokens": {
+                    "type": "integer"
+                }
+            }
+        },
         "schema.BackendMonitorRequest": {
             "type": "object",
             "properties": {
@@ -2229,6 +2416,10 @@ const docTemplate = `{
                     "description": "The message name (used for tools calls)",
                     "type": "string"
                 },
+                "reasoning": {
+                    "description": "Reasoning content extracted from \u003cthinking\u003e...\u003c/thinking\u003e tags",
+                    "type": "string"
+                },
                 "role": {
                     "description": "The message role",
                     "type": "string"

swagger/swagger.json

@@ -1191,6 +1191,30 @@
                 }
             }
         },
+        "/v1/messages": {
+            "post": {
+                "summary": "Generate a message response for the given messages and model.",
+                "parameters": [
+                    {
+                        "description": "query params",
+                        "name": "request",
+                        "in": "body",
+                        "required": true,
+                        "schema": {
+                            "$ref": "#/definitions/schema.AnthropicRequest"
+                        }
+                    }
+                ],
+                "responses": {
+                    "200": {
+                        "description": "Response",
+                        "schema": {
+                            "$ref": "#/definitions/schema.AnthropicResponse"
+                        }
+                    }
+                }
+            }
+        },
         "/v1/models": {
             "get": {
                 "summary": "List and describe the various models available in the API.",
@@ -1732,6 +1756,169 @@
                 }
             }
         },
+        "schema.AnthropicContentBlock": {
+            "type": "object",
+            "properties": {
+                "content": {},
+                "id": {
+                    "type": "string"
+                },
+                "input": {
+                    "type": "object",
+                    "additionalProperties": true
+                },
+                "is_error": {
+                    "type": "boolean"
+                },
+                "name": {
+                    "type": "string"
+                },
+                "source": {
+                    "$ref": "#/definitions/schema.AnthropicImageSource"
+                },
+                "text": {
+                    "type": "string"
+                },
+                "tool_use_id": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicImageSource": {
+            "type": "object",
+            "properties": {
+                "data": {
+                    "type": "string"
+                },
+                "media_type": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicMessage": {
+            "type": "object",
+            "properties": {
+                "content": {},
+                "role": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicRequest": {
+            "type": "object",
+            "properties": {
+                "max_tokens": {
+                    "type": "integer"
+                },
+                "messages": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicMessage"
+                    }
+                },
+                "metadata": {
+                    "type": "object",
+                    "additionalProperties": {
+                        "type": "string"
+                    }
+                },
+                "model": {
+                    "type": "string"
+                },
+                "stop_sequences": {
+                    "type": "array",
+                    "items": {
+                        "type": "string"
+                    }
+                },
+                "stream": {
+                    "type": "boolean"
+                },
+                "system": {
+                    "type": "string"
+                },
+                "temperature": {
+                    "type": "number"
+                },
+                "tool_choice": {},
+                "tools": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicTool"
+                    }
+                },
+                "top_k": {
+                    "type": "integer"
+                },
+                "top_p": {
+                    "type": "number"
+                }
+            }
+        },
+        "schema.AnthropicResponse": {
+            "type": "object",
+            "properties": {
+                "content": {
+                    "type": "array",
+                    "items": {
+                        "$ref": "#/definitions/schema.AnthropicContentBlock"
+                    }
+                },
+                "id": {
+                    "type": "string"
+                },
+                "model": {
+                    "type": "string"
+                },
+                "role": {
+                    "type": "string"
+                },
+                "stop_reason": {
+                    "type": "string"
+                },
+                "stop_sequence": {
+                    "type": "string"
+                },
+                "type": {
+                    "type": "string"
+                },
+                "usage": {
+                    "$ref": "#/definitions/schema.AnthropicUsage"
+                }
+            }
+        },
+        "schema.AnthropicTool": {
+            "type": "object",
+            "properties": {
+                "description": {
+                    "type": "string"
+                },
+                "input_schema": {
+                    "type": "object",
+                    "additionalProperties": true
+                },
+                "name": {
+                    "type": "string"
+                }
+            }
+        },
+        "schema.AnthropicUsage": {
+            "type": "object",
+            "properties": {
+                "input_tokens": {
+                    "type": "integer"
+                },
+                "output_tokens": {
+                    "type": "integer"
+                }
+            }
+        },
         "schema.BackendMonitorRequest": {
             "type": "object",
             "properties": {
@@ -2222,6 +2409,10 @@
                     "description": "The message name (used for tools calls)",
                     "type": "string"
                 },
+                "reasoning": {
+                    "description": "Reasoning content extracted from \u003cthinking\u003e...\u003c/thinking\u003e tags",
+                    "type": "string"
+                },
                 "role": {
                     "description": "The message role",
                     "type": "string"

swagger/swagger.yaml

@@ -239,6 +239,114 @@ definitions:
       start:
         type: number
     type: object
+  schema.AnthropicContentBlock:
+    properties:
+      content: {}
+      id:
+        type: string
+      input:
+        additionalProperties: true
+        type: object
+      is_error:
+        type: boolean
+      name:
+        type: string
+      source:
+        $ref: '#/definitions/schema.AnthropicImageSource'
+      text:
+        type: string
+      tool_use_id:
+        type: string
+      type:
+        type: string
+    type: object
+  schema.AnthropicImageSource:
+    properties:
+      data:
+        type: string
+      media_type:
+        type: string
+      type:
+        type: string
+    type: object
+  schema.AnthropicMessage:
+    properties:
+      content: {}
+      role:
+        type: string
+    type: object
+  schema.AnthropicRequest:
+    properties:
+      max_tokens:
+        type: integer
+      messages:
+        items:
+          $ref: '#/definitions/schema.AnthropicMessage'
+        type: array
+      metadata:
+        additionalProperties:
+          type: string
+        type: object
+      model:
+        type: string
+      stop_sequences:
+        items:
+          type: string
+        type: array
+      stream:
+        type: boolean
+      system:
+        type: string
+      temperature:
+        type: number
+      tool_choice: {}
+      tools:
+        items:
+          $ref: '#/definitions/schema.AnthropicTool'
+        type: array
+      top_k:
+        type: integer
+      top_p:
+        type: number
+    type: object
+  schema.AnthropicResponse:
+    properties:
+      content:
+        items:
+          $ref: '#/definitions/schema.AnthropicContentBlock'
+        type: array
+      id:
+        type: string
+      model:
+        type: string
+      role:
+        type: string
+      stop_reason:
+        type: string
+      stop_sequence:
+        type: string
+      type:
+        type: string
+      usage:
+        $ref: '#/definitions/schema.AnthropicUsage'
+    type: object
+  schema.AnthropicTool:
+    properties:
+      description:
+        type: string
+      input_schema:
+        additionalProperties: true
+        type: object
+      name:
+        type: string
+    type: object
+  schema.AnthropicUsage:
+    properties:
+      input_tokens:
+        type: integer
+      output_tokens:
+        type: integer
+    type: object
   schema.BackendMonitorRequest:
     properties:
       model:
@@ -573,6 +681,9 @@ definitions:
       name:
         description: The message name (used for tools calls)
         type: string
+      reasoning:
+        description: Reasoning content extracted from <thinking>...</thinking> tags
+        type: string
       role:
         description: The message role
         type: string
@@ -1813,6 +1924,21 @@ paths:
           schema:
             $ref: '#/definitions/schema.OpenAIResponse'
       summary: Stream MCP chat completions with reasoning, tool calls, and results
+  /v1/messages:
+    post:
+      parameters:
+      - description: query params
+        in: body
+        name: request
+        required: true
+        schema:
+          $ref: '#/definitions/schema.AnthropicRequest'
+      responses:
+        "200":
+          description: Response
+          schema:
+            $ref: '#/definitions/schema.AnthropicResponse'
+      summary: Generate a message response for the given messages and model.
   /v1/models:
     get:
       responses:

tests/e2e/e2e_anthropic_test.go

@@ -0,0 +1,375 @@
+package e2e_test
+
+import (
+	"context"
+
+	"github.com/anthropics/anthropic-sdk-go"
+	"github.com/anthropics/anthropic-sdk-go/option"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+var _ = Describe("Anthropic API E2E test", func() {
+	var client anthropic.Client
+
+	Context("API with Anthropic SDK", func() {
+		BeforeEach(func() {
+			// Create Anthropic client pointing to LocalAI
+			client = anthropic.NewClient(
+				option.WithBaseURL(localAIURL),
+				option.WithAPIKey("test-api-key"), // LocalAI doesn't require a real API key
+			)
+
+			// Wait for API to be ready by attempting a simple request
+			Eventually(func() error {
+				_, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 10,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Hi")),
+					},
+				})
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+
+		Context("Non-streaming responses", func() {
+			It("generates a response for a simple message", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("How much is 2+2? Reply with just the number.")),
+					},
+				})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+				// Role is a constant type that defaults to "assistant"
+				Expect(string(message.Role)).To(Equal("assistant"))
+				Expect(message.StopReason).To(Equal(anthropic.MessageStopReasonEndTurn))
+				Expect(string(message.Type)).To(Equal("message"))
+
+				// Check that content contains text block with expected answer
+				Expect(len(message.Content)).To(BeNumerically(">=", 1))
+				textBlock := message.Content[0]
+				Expect(string(textBlock.Type)).To(Equal("text"))
+				Expect(textBlock.Text).To(Or(ContainSubstring("4"), ContainSubstring("four")))
+			})
+
+			It("handles system prompts", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					System: []anthropic.TextBlockParam{
+						{Text: "You are a helpful assistant. Always respond in uppercase letters."},
+					},
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Say hello")),
+					},
+				})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+				Expect(len(message.Content)).To(BeNumerically(">=", 1))
+			})
+
+			It("returns usage information", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 100,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Hello")),
+					},
+				})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Usage.InputTokens).To(BeNumerically(">", 0))
+				Expect(message.Usage.OutputTokens).To(BeNumerically(">", 0))
+			})
+		})
+
+		Context("Streaming responses", func() {
+			It("streams tokens for a simple message", func() {
+				stream := client.Messages.NewStreaming(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Count from 1 to 5")),
+					},
+				})
+
+				message := anthropic.Message{}
+				eventCount := 0
+				hasContentDelta := false
+
+				for stream.Next() {
+					event := stream.Current()
+					err := message.Accumulate(event)
+					Expect(err).ToNot(HaveOccurred())
+					eventCount++
+
+					// Check for content block delta events
+					switch event.AsAny().(type) {
+					case anthropic.ContentBlockDeltaEvent:
+						hasContentDelta = true
+					}
+				}
+
+				Expect(stream.Err()).ToNot(HaveOccurred())
+				Expect(eventCount).To(BeNumerically(">", 0))
+				Expect(hasContentDelta).To(BeTrue())
+
+				// Check accumulated message
+				Expect(message.Content).ToNot(BeEmpty())
+				// Role is a constant type that defaults to "assistant"
+				Expect(string(message.Role)).To(Equal("assistant"))
+			})
+
+			It("streams with system prompt", func() {
+				stream := client.Messages.NewStreaming(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					System: []anthropic.TextBlockParam{
+						{Text: "You are a helpful assistant."},
+					},
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Say hello")),
+					},
+				})
+
+				message := anthropic.Message{}
+				for stream.Next() {
+					event := stream.Current()
+					err := message.Accumulate(event)
+					Expect(err).ToNot(HaveOccurred())
+				}
+
+				Expect(stream.Err()).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+			})
+		})
+
+		Context("Tool calling", func() {
+			It("handles tool calls in non-streaming mode", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather like in San Francisco?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather in a given location"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type":        "string",
+										"description": "The city and state, e.g. San Francisco, CA",
+									},
+								},
+								"required": []string{"location"},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+
+				// The model must use tools - find the tool use in the response
+				hasToolUse := false
+				for _, block := range message.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						hasToolUse = true
+						Expect(block.Name).To(Equal("get_weather"))
+						Expect(block.ID).ToNot(BeEmpty())
+						// Verify that input contains location
+						inputMap, ok := block.Input.(map[string]interface{})
+						Expect(ok).To(BeTrue())
+						_, hasLocation := inputMap["location"]
+						Expect(hasLocation).To(BeTrue())
+					}
+				}
+
+				// Model must have called the tool
+				Expect(hasToolUse).To(BeTrue(), "Model should have called the get_weather tool")
+				Expect(message.StopReason).To(Equal(anthropic.MessageStopReasonToolUse))
+			})
+
+			It("handles tool_choice parameter", func() {
+				message, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("Tell me about the weather")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type": "string",
+									},
+								},
+							}),
+						},
+					},
+					ToolChoice: anthropic.F[anthropic.ToolChoiceUnionParam](
+						anthropic.ToolChoiceAutoParam{
+							Type: anthropic.F(anthropic.ToolChoiceAutoTypeAuto),
+						},
+					),
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(message.Content).ToNot(BeEmpty())
+			})
+
+			It("handles tool results in messages", func() {
+				// First, make a request that should trigger a tool call
+				firstMessage, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather in SF?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{"type": "string"},
+								},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+
+				// Find the tool use block - model must call the tool
+				var toolUseID string
+				var toolUseName string
+				for _, block := range firstMessage.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						toolUseID = block.ID
+						toolUseName = block.Name
+						break
+					}
+				}
+
+				// Model must have called the tool
+				Expect(toolUseID).ToNot(BeEmpty(), "Model should have called the get_weather tool")
+
+				// Send back a tool result and verify it's handled correctly
+				secondMessage, err := client.Messages.New(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather in SF?")),
+						anthropic.NewAssistantMessage(firstMessage.Content...),
+						anthropic.NewUserMessage(
+							anthropic.NewToolResultBlock(toolUseID, "Sunny, 72°F", false),
+						),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        toolUseName,
+							Description: anthropic.F("Get weather"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{"type": "string"},
+								},
+							}),
+						},
+					},
+				})
+
+				Expect(err).ToNot(HaveOccurred())
+				Expect(secondMessage.Content).ToNot(BeEmpty())
+			})
+
+			It("handles tool calls in streaming mode", func() {
+				stream := client.Messages.NewStreaming(context.TODO(), anthropic.MessageNewParams{
+					Model:     "gpt-4",
+					MaxTokens: 1024,
+					Messages: []anthropic.MessageParam{
+						anthropic.NewUserMessage(anthropic.NewTextBlock("What's the weather like in San Francisco?")),
+					},
+					Tools: []anthropic.ToolParam{
+						{
+							Name:        "get_weather",
+							Description: anthropic.F("Get the current weather in a given location"),
+							InputSchema: anthropic.F(map[string]interface{}{
+								"type": "object",
+								"properties": map[string]interface{}{
+									"location": map[string]interface{}{
+										"type":        "string",
+										"description": "The city and state, e.g. San Francisco, CA",
+									},
+								},
+								"required": []string{"location"},
+							}),
+						},
+					},
+				})
+
+				message := anthropic.Message{}
+				eventCount := 0
+				hasToolUseBlock := false
+				hasContentBlockStart := false
+				hasContentBlockDelta := false
+				hasContentBlockStop := false
+
+				for stream.Next() {
+					event := stream.Current()
+					err := message.Accumulate(event)
+					Expect(err).ToNot(HaveOccurred())
+					eventCount++
+
+					// Check for different event types related to tool use
+					switch e := event.AsAny().(type) {
+					case anthropic.ContentBlockStartEvent:
+						hasContentBlockStart = true
+						if e.ContentBlock.Type == anthropic.ContentBlockTypeToolUse {
+							hasToolUseBlock = true
+						}
+					case anthropic.ContentBlockDeltaEvent:
+						hasContentBlockDelta = true
+					case anthropic.ContentBlockStopEvent:
+						hasContentBlockStop = true
+					}
+				}
+
+				Expect(stream.Err()).ToNot(HaveOccurred())
+				Expect(eventCount).To(BeNumerically(">", 0))
+
+				// Verify streaming events were emitted
+				Expect(hasContentBlockStart).To(BeTrue(), "Should have content_block_start event")
+				Expect(hasContentBlockDelta).To(BeTrue(), "Should have content_block_delta event")
+				Expect(hasContentBlockStop).To(BeTrue(), "Should have content_block_stop event")
+
+				// Check accumulated message has tool use
+				Expect(message.Content).ToNot(BeEmpty())
+				
+				// Model must have called the tool
+				foundToolUse := false
+				for _, block := range message.Content {
+					if block.Type == anthropic.ContentBlockTypeToolUse {
+						foundToolUse = true
+						Expect(block.Name).To(Equal("get_weather"))
+						Expect(block.ID).ToNot(BeEmpty())
+					}
+				}
+				Expect(foundToolUse).To(BeTrue(), "Model should have called the get_weather tool in streaming mode")
+				Expect(message.StopReason).To(Equal(anthropic.MessageStopReasonToolUse))
+			})
+		})
+	})
+})