docs: add more icon support

docs: add docker compose generator
2026-07-24 04:39:02 +03:00 · 2026-04-21 22:23:09 +08:00 · 2026-04-21 20:59:16 +08:00
426 changed files with 3449 additions and 16251 deletions
@@ -26,7 +26,7 @@ _Please read the [contributing guidelines](https://github.com/blakeblackshear/fr

 - This PR fixes or closes issue: fixes #
 - This PR is related to issue:
- Link to discussion with maintainers (**required** for any large or "planned" features):
+- Link to discussion with maintainers (**required** for large/pinned features):

 ## For new features

@@ -13,7 +13,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Check PR description against template
-        uses: actions/github-script@v9
+        uses: actions/github-script@v7
        with:
          script: |
            const maintainers = ['blakeblackshear', 'NickM-27', 'hawkeye217', 'dependabot[bot]', 'weblate'];
@@ -72,7 +72,7 @@ jobs:
        run: npm run e2e
        working-directory: ./web
      - name: Upload test artifacts
-        uses: actions/upload-artifact@v7
+        uses: actions/upload-artifact@v4
        if: failure()
        with:
          name: playwright-report
@@ -18,9 +18,9 @@ jobs:
          close-issue-message: ""
          days-before-stale: 30
          days-before-close: 3
-          exempt-draft-pr: false
-          exempt-issue-labels: "planned,security"
-          exempt-pr-labels: "planned,security,dependencies"
+          exempt-draft-pr: true
+          exempt-issue-labels: "pinned,security"
+          exempt-pr-labels: "pinned,security,dependencies"
          operations-per-run: 120
      - name: Print outputs
        env:
@@ -10,14 +10,11 @@ If you've found a bug and want to fix it, go for it. Link to the relevant issue

 ### New features

-A pull request is more than just code — it's a request for the maintainers to review, integrate, and support the change long-term. We're selective about what we take on, and prioritize changes that align with the project's direction and can be responsibly maintained in the long term.
+Every new feature adds scope that the maintainers must test, maintain, and support long-term. Before writing code for a new feature:

-**Large or highly-requested features** raise the bar even higher. Popularity signals demand, but it doesn't pre-approve any particular implementation. The bigger the change, the higher the long-term cost, and the more important it is that we're aligned on scope and approach before any code is written. A large PR that lands without prior discussion is unlikely to be merged as-is, no matter how well it's implemented.
-
-Before writing code for a new feature:
-
-1. **Check for existing discussion.** Search [feature requests](https://github.com/blakeblackshear/frigate/issues) and [discussions](https://github.com/blakeblackshear/frigate/discussions) to see if it's been proposed or discussed. Feature requests tagged with "planned" are on our radar — we plan to get to them, but we don't maintain a public roadmap or timeline. Check in with us first if you have interest in contributing to one.
+1. **Check for existing discussion.** Search [feature requests](https://github.com/blakeblackshear/frigate/issues) and [discussions](https://github.com/blakeblackshear/frigate/discussions) to see if it's been proposed or discussed. Pinned feature requests are on our radar — we plan to get to them, but we don't maintain a public roadmap or timeline. Check in with us first if you have interest in contributing to one.
 2. **Start a discussion or feature request first.** This helps ensure your idea aligns with Frigate's direction before you invest time building it. Community interest in a feature request helps us gauge demand, though a great idea is a great idea even without a crowd behind it.
+3. **Be open to "no".** We try to be thoughtful about what we take on, and sometimes that means saying no to good code if the feature isn't the right fit for the project. These calls are sometimes subjective, and we won't always get them right. We're happy to discuss and reconsider.

 ## AI usage policy

@@ -42,8 +39,6 @@ We're not trying to gatekeep how you write code. Use whatever tools make you pro

 Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term — often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.

-One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated — where the author can't explain the design, debug issues independently, or engage substantively in design discussions — doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
-
 ## Pull request guidelines

 ### Before submitting
@@ -87,43 +87,43 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
    # intel packages use zst compression so we need to update dpkg
    apt-get install -y dpkg

-    # use intel apt repo for libmfx1 (legacy QSV, pre-Gen12)
+    # use intel apt intel packages
    wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg
    echo "deb [arch=amd64 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | tee /etc/apt/sources.list.d/intel-gpu-jammy.list
    apt-get -qq update
-
    # intel-media-va-driver-non-free is built from source in the
    # intel-media-driver Dockerfile stage for Battlemage (Xe2) support
    apt-get -qq install --no-install-recommends --no-install-suggests -y \
-        libmfx1
-    rm -f /usr/share/keyrings/intel-graphics.gpg
-    rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list
+        libmfx1 libmfxgen1 libvpl2

-    # upgrade libva2, oneVPL runtime, and libvpl2 from trixie for Battlemage support
-    echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list
-    apt-get -qq update
-    apt-get -qq install -y -t trixie libva2 libva-drm2 libzstd1
-    apt-get -qq install -y -t trixie libmfx-gen1.2 libvpl2
-    rm -f /etc/apt/sources.list.d/trixie.list
-    apt-get -qq update
    apt-get -qq install -y ocl-icd-libopencl1

    # install libtbb12 for NPU support
    apt-get -qq install -y libtbb12

-    # install legacy and standard intel compute packages
+    rm -f /usr/share/keyrings/intel-graphics.gpg
+    rm -f /etc/apt/sources.list.d/intel-gpu-jammy.list
+
+    # install legacy and standard intel icd and level-zero-gpu
    # see https://github.com/intel/compute-runtime/blob/master/LEGACY_PLATFORMS.md for more info
+    # newer intel packages (gmmlib 22.9+, igc 2.32+) require libstdc++ >= 13.1 and libzstd >= 1.5.5
+    echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list
+    apt-get -qq update
+    apt-get -qq install -y -t trixie libstdc++6 libzstd1
+    rm -f /etc/apt/sources.list.d/trixie.list
+    apt-get -qq update
+
    # needed core package
    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libigdgmm12_22.9.0_amd64.deb
    dpkg -i libigdgmm12_22.9.0_amd64.deb
    rm libigdgmm12_22.9.0_amd64.deb

-    # legacy compute-runtime packages
+    # legacy packages
    wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-opencl-icd-legacy1_24.35.30872.36_amd64.deb
    wget https://github.com/intel/compute-runtime/releases/download/24.35.30872.36/intel-level-zero-gpu-legacy1_1.5.30872.36_amd64.deb
    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-opencl_1.0.17537.24_amd64.deb
    wget https://github.com/intel/intel-graphics-compiler/releases/download/igc-1.0.17537.24/intel-igc-core_1.0.17537.24_amd64.deb
-    # standard compute-runtime packages
+    # standard packages
    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/intel-opencl-icd_26.14.37833.4-0_amd64.deb
    wget https://github.com/intel/compute-runtime/releases/download/26.14.37833.4/libze-intel-gpu1_26.14.37833.4-0_amd64.deb
    wget https://github.com/intel/intel-graphics-compiler/releases/download/v2.32.7/intel-igc-opencl-2_2.32.7+21184_amd64.deb
@@ -137,10 +137,6 @@ if [[ "${TARGETARCH}" == "amd64" ]]; then
    dpkg -i *.deb
    rm *.deb
    apt-get -qq install -f -y
-
-    # Battlemage uses the xe kernel driver, but the VA-API driver is still iHD.
-    # The oneVPL runtime may look for a driver named after the kernel module.
-    ln -sf /usr/lib/x86_64-linux-gnu/dri/iHD_drv_video.so /usr/lib/x86_64-linux-gnu/dri/xe_drv_video.so
 fi

 if [[ "${TARGETARCH}" == "arm64" ]]; then
@@ -11,7 +11,7 @@ joserfc == 1.2.*
 cryptography == 44.0.*
 pathvalidate == 3.3.*
 markupsafe == 3.0.*
-python-multipart == 0.0.26
+python-multipart == 0.0.20
 # Classification Model Training
 tensorflow == 2.19.* ; platform_machine == 'aarch64'
 tensorflow-cpu == 2.19.* ; platform_machine == 'x86_64'
@@ -42,7 +42,7 @@ opencv-python-headless == 4.11.0.*
 opencv-contrib-python == 4.11.0.*
 scipy == 1.16.*
 # OpenVino & ONNX
-openvino == 2025.4.*
+openvino == 2025.3.*
 onnxruntime == 1.22.*
 # Embeddings
 transformers == 4.45.*
@@ -13,7 +13,7 @@ ARG ROCM

 RUN apt update -qq && \
    apt install -y wget gpg && \
-    wget -O rocm.deb https://repo.radeon.com/amdgpu-install/7.2.3/ubuntu/jammy/amdgpu-install_7.2.3.70203-1_all.deb && \
+    wget -O rocm.deb https://repo.radeon.com/amdgpu-install/7.2/ubuntu/jammy/amdgpu-install_7.2.70200-1_all.deb && \
    apt install -y ./rocm.deb && \
    apt update && \
    apt install -qq -y rocm
@@ -32,14 +32,11 @@ RUN echo /opt/rocm/lib|tee /opt/rocm-dist/etc/ld.so.conf.d/rocm.conf
 FROM deps AS deps-prelim

 COPY docker/rocm/debian-backports.sources /etc/apt/sources.list.d/debian-backports.sources
-# install_deps.sh upgraded libstdc++6 from trixie for Battlemage; the matching
-# -dev package must also come from trixie or apt refuses to satisfy it.
-RUN echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list && \
-    apt-get update && \
+RUN apt-get update && \
    apt-get install -y libnuma1 && \
    apt-get install -qq -y -t bookworm-backports mesa-va-drivers mesa-vulkan-drivers && \
-    apt-get install -qq -y -t trixie libstdc++-14-dev && \
-    rm -f /etc/apt/sources.list.d/trixie.list && \
+    # Install C++ standard library headers for HIPRTC kernel compilation fallback
+    apt-get install -qq -y libstdc++-12-dev && \
    rm -rf /var/lib/apt/lists/*

 WORKDIR /opt/frigate
@@ -78,10 +75,6 @@ ENV MIGRAPHX_DISABLE_MIOPEN_FUSION=1
 ENV MIGRAPHX_DISABLE_SCHEDULE_PASS=1
 ENV MIGRAPHX_DISABLE_REDUCE_FUSION=1
 ENV MIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS=1
-ENV MIOPEN_CUSTOM_CACHE_DIR=/config/model_cache/migraphx
-ENV MIOPEN_USER_DB_PATH=/config/model_cache/migraphx
-ENV AMD_COMGR_CACHE=1
-ENV AMD_COMGR_CACHE_DIR=/config/model_cache/migraphx

 COPY --from=rocm-dist / /

@@ -1 +1 @@
-onnxruntime-migraphx @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v7.2.3-1/onnxruntime_migraphx-1.24.4-cp311-cp311-linux_x86_64.whl
+onnxruntime-migraphx @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v7.2.0/onnxruntime_migraphx-1.23.1-cp311-cp311-linux_x86_64.whl
@@ -1,5 +1,5 @@
 variable "ROCM" {
-  default = "7.2.3"
+  default = "7.2.0"
 }
 variable "HSA_OVERRIDE_GFX_VERSION" {
  default = ""
@@ -19,7 +19,7 @@ Face recognition requires a one-time internet connection to download detection a

 ### Face Detection

-When running a Frigate+ model (or any custom model that natively detects faces) should ensure that `face` is added to the [list of objects to track](../plus/index.md#available-label-types) either globally or for a specific camera. This will allow face detection to run at the same time as object detection and be more efficient.
+When running a Frigate+ model (or any custom model that natively detects faces) should ensure that `face` is added to the [list of objects to track](../plus/#available-label-types) either globally or for a specific camera. This will allow face detection to run at the same time as object detection and be more efficient.

 When running a default COCO model or another model that does not include `face` as a detectable label, face detection will run via CV2 using a lightweight DNN model that runs on the CPU. In this case, you should _not_ define `face` in your list of objects to track.

@@ -171,7 +171,7 @@ When choosing images to include in the face training set it is recommended to al
 - If it is difficult to make out details in a persons face it will not be helpful in training.
 - Avoid images with extreme under/over-exposure.
 - Avoid blurry / pixelated images.
- Avoid training on infrared (gray-scale). The models are trained on color images and will not be able to extract features from gray-scale images.
+- Avoid training on infrared (gray-scale). The models are trained on color images and will be able to extract features from gray-scale images.
 - Using images of people wearing hats / sunglasses may confuse the model.
 - Do not upload too many similar images at the same time, it is recommended to train no more than 4-6 similar images for each person to avoid over-fitting.

@@ -201,7 +201,7 @@ Cloud Generative AI providers require an active internet connection to send imag

 ### Ollama Cloud

-Ollama also supports [cloud models](https://ollama.com/cloud), where model inference is performed in the cloud. You can connect directly to Ollama Cloud by setting `base_url` to `https://ollama.com` and providing an API key. Alternatively, you can run Ollama locally and use a cloud model name so your local instance forwards requests to the cloud. For more details, see the Ollama cloud model [docs](https://docs.ollama.com/cloud).
+Ollama also supports [cloud models](https://ollama.com/cloud), where your local Ollama instance handles requests from Frigate, but model inference is performed in the cloud. Set up Ollama locally, sign in with your Ollama account, and specify the cloud model name in your Frigate config. For more details, see the Ollama cloud model [docs](https://docs.ollama.com/cloud).

 #### Configuration

@@ -210,8 +210,7 @@ Ollama also supports [cloud models](https://ollama.com/cloud), where model infer

 1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
   - Set **Provider** to `ollama`
-   - Set **Base URL** to your local Ollama address (e.g., `http://localhost:11434`) or `https://ollama.com` for direct cloud inference
-   - Set **API key** if required by your endpoint (e.g., when using `https://ollama.com`)
+   - Set **Base URL** to your local Ollama address (e.g., `http://localhost:11434`)
   - Set **Model** to the cloud model name

 </TabItem>
@@ -224,16 +223,6 @@ genai:
  model: cloud-model-name
 ```

-or when using Ollama Cloud directly
-
-```yaml
-genai:
-  provider: ollama
-  base_url: https://ollama.com
-  model: cloud-model-name
-  api_key: your-api-key
-```
-
 </TabItem>
 </ConfigTabs>

@@ -136,32 +136,90 @@ ffmpeg:
 </TabItem>
 </ConfigTabs>

-### Configuring Intel GPU Stats
+### Configuring Intel GPU Stats in Docker

-Frigate reads Intel GPU utilization directly from the kernel's per-client DRM usage counters exposed at `/proc/<pid>/fdinfo/<fd>`. This requires:
+Additional configuration is needed for the Docker container to be able to access the `intel_gpu_top` command for GPU stats. There are two options:

- Linux kernel **5.19 or newer** for the `i915` driver, or any release of the `xe` driver.
- Frigate running with permission to read other processes' fdinfo. Running as root inside the container (the default) satisfies this; non-root setups may need `CAP_SYS_PTRACE`.
+1. Run the container as privileged.
+2. Add the `CAP_PERFMON` capability (note: you might need to set the `perf_event_paranoid` low enough to allow access to the performance event system.)

-No `intel_gpu_top` binary, `CAP_PERFMON`, privileged mode, or `perf_event_paranoid` tuning is required.
+#### Run as privileged

-#### Stats for SR-IOV or specific devices
+This method works, but it gives more permissions to the container than are actually needed.

-If the host has more than one Intel GPU (e.g. an iGPU plus a discrete GPU, or SR-IOV virtual functions), pin stats collection to a specific device by setting `intel_gpu_device` to either its PCI bus address or a DRM card/render-node path:
+##### Docker Compose - Privileged
+
+```yaml
+services:
+  frigate:
+    ...
+    image: ghcr.io/blakeblackshear/frigate:stable
+    # highlight-next-line
+    privileged: true
+```
+
+##### Docker Run CLI - Privileged
+
+```bash {4}
+docker run -d \
+  --name frigate \
+  ...
+  --privileged \
+  ghcr.io/blakeblackshear/frigate:stable
+```
+
+#### CAP_PERFMON
+
+Only recent versions of Docker support the `CAP_PERFMON` capability. You can test to see if yours supports it by running: `docker run --cap-add=CAP_PERFMON hello-world`
+
+##### Docker Compose - CAP_PERFMON
+
+```yaml {5,6}
+services:
+  frigate:
+    ...
+    image: ghcr.io/blakeblackshear/frigate:stable
+    cap_add:
+      - CAP_PERFMON
+```
+
+##### Docker Run CLI - CAP_PERFMON
+
+```bash {4}
+docker run -d \
+  --name frigate \
+  ...
+  --cap-add=CAP_PERFMON \
+  ghcr.io/blakeblackshear/frigate:stable
+```
+
+#### perf_event_paranoid
+
+_Note: This setting must be changed for the entire system._
+
+For more information on the various values across different distributions, see https://askubuntu.com/questions/1400874/what-does-perf-paranoia-level-four-do.
+
+Depending on your OS and kernel configuration, you may need to change the `/proc/sys/kernel/perf_event_paranoid` kernel tunable. You can test the change by running `sudo sh -c 'echo 2 >/proc/sys/kernel/perf_event_paranoid'` which will persist until a reboot. Make it permanent by running `sudo sh -c 'echo kernel.perf_event_paranoid=2 >> /etc/sysctl.d/local.conf'`
+
+#### Stats for SR-IOV or other devices
+
+When using virtualized GPUs via SR-IOV, you need to specify the device path to use to gather stats from `intel_gpu_top`. This example may work for some systems using SR-IOV:

 ```yaml
 telemetry:
  stats:
-    intel_gpu_device: "0000:00:02.0"
+    intel_gpu_device: "sriov"
 ```

+For other virtualized GPUs, try specifying the direct path to the device instead:
+
 ```yaml
 telemetry:
  stats:
-    intel_gpu_device: "/dev/dri/card1"
+    intel_gpu_device: "drm:/dev/dri/card0"
 ```

-When passing a device path, make sure the device is also passed through to the container.
+If you are passing in a device path, make sure you've passed the device through to the container.

 ## AMD-based CPUs

@@ -72,7 +72,7 @@ This does not affect using hardware for accelerating other tasks such as [semant

 # Officially Supported Detectors

-Frigate provides a number of builtin detector types. By default, Frigate will use a single OpenVINO detector running on the CPU. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
+Frigate provides a number of builtin detector types. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.

 ## Edge TPU Detector

@@ -494,7 +494,7 @@ detectors:
 | [YOLO-NAS](#yolo-nas)                 | ✅  | ✅  |                                                              |
 | [MobileNet v2](#ssdlite-mobilenet-v2) | ✅  | ✅  | Fast and lightweight model, less accurate than larger models |
 | [YOLOX](#yolox)                       | ✅  | ?   |                                                              |
-| [D-FINE / DEIMv2](#d-fine--deimv2)    | ❌  | ❌  |                                                              |
+| [D-FINE](#d-fine)                     | ❌  | ❌  |                                                              |

 #### SSDLite MobileNet v2

@@ -710,13 +710,13 @@ model:

 </details>

-#### D-FINE / DEIMv2
+#### D-FINE

-[D-FINE](https://github.com/Peterande/D-FINE) and [DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) are DETR based models that share the same ONNX input/output format. The ONNX exported models are supported, but not included by default. See the models section for downloading [D-FINE](#downloading-d-fine-model) or [DEIMv2](#downloading-deimv2-model) for use in Frigate.
+[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.

 :::warning

-Currently D-FINE / DEIMv2 models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
+Currently D-FINE models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model

 :::

@@ -766,31 +766,6 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl

 </details>

-<details>
-  <summary>DEIMv2 Setup & Config</summary>
-
-After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
-
-```yaml
-detectors:
-  ov:
-    type: openvino
-    device: CPU
-
-model:
-  model_type: dfine
-  width: 640
-  height: 640
-  input_tensor: nchw
-  input_dtype: float
-  path: /config/model_cache/deimv2_hgnetv2_n.onnx
-  labelmap_path: /labelmap/coco-80.txt
-```
-
-Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
-
-</details>
-
 ## Apple Silicon detector

 The NPU in Apple Silicon can't be accessed from within a container, so the [Apple Silicon detector client](https://github.com/frigate-nvr/apple-silicon-detector) must first be setup. It is recommended to use the Frigate docker image with `-standard-arm64` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-standard-arm64`.
@@ -972,7 +947,7 @@ The AMD GPU kernel is known problematic especially when converting models to mxr

 See [ONNX supported models](#supported-models) for supported models, there are some caveats:

- D-FINE / DEIMv2 models are not supported
+- D-FINE models are not supported
 - YOLO-NAS models are known to not run well on integrated GPUs

 ## ONNX
@@ -1022,13 +997,13 @@ detectors:

 ### ONNX Supported Models

-| Model                                | Nvidia GPU | AMD GPU | Notes                                               |
-| ------------------------------------ | ---------- | ------- | --------------------------------------------------- |
-| [YOLOv9](#yolo-v3-v4-v7-v9-2)        | ✅         | ✅      | Supports CUDA Graphs for optimal Nvidia performance |
-| [RF-DETR](#rf-detr)                  | ✅         | ⚠️      | Supports CUDA Graphs for optimal Nvidia performance |
-| [YOLO-NAS](#yolo-nas-1)              | ⚠️         | ⚠️      | Not supported by CUDA Graphs                        |
-| [YOLOX](#yolox-1)                    | ✅         | ✅      | Supports CUDA Graphs for optimal Nvidia performance |
-| [D-FINE / DEIMv2](#d-fine--deimv2-1) | ⚠️         | ❌      | Not supported by CUDA Graphs                        |
+| Model                         | Nvidia GPU | AMD GPU | Notes                                               |
+| ----------------------------- | ---------- | ------- | --------------------------------------------------- |
+| [YOLOv9](#yolo-v3-v4-v7-v9-2) | ✅         | ✅      | Supports CUDA Graphs for optimal Nvidia performance |
+| [RF-DETR](#rf-detr)           | ✅         | ❌      | Supports CUDA Graphs for optimal Nvidia performance |
+| [YOLO-NAS](#yolo-nas-1)       | ⚠️         | ⚠️      | Not supported by CUDA Graphs                        |
+| [YOLOX](#yolox-1)             | ✅         | ✅      | Supports CUDA Graphs for optimal Nvidia performance |
+| [D-FINE](#d-fine)             | ⚠️         | ❌      | Not supported by CUDA Graphs                        |

 There is no default model provided, the following formats are supported:

@@ -1240,9 +1215,9 @@ model:

 </details>

-#### D-FINE / DEIMv2
+#### D-FINE

-[D-FINE](https://github.com/Peterande/D-FINE) and [DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) are DETR based models that share the same ONNX input/output format. The ONNX exported models are supported, but not included by default. See the models section for downloading [D-FINE](#downloading-d-fine-model) or [DEIMv2](#downloading-deimv2-model) for use in Frigate.
+[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.

 <details>
  <summary>D-FINE Setup & Config</summary>
@@ -1287,28 +1262,6 @@ model:

 </details>

-<details>
-  <summary>DEIMv2 Setup & Config</summary>
-
-After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
-
-```yaml
-detectors:
-  onnx:
-    type: onnx
-
-model:
-  model_type: dfine
-  width: 640
-  height: 640
-  input_tensor: nchw
-  input_dtype: float
-  path: /config/model_cache/deimv2_hgnetv2_n.onnx
-  labelmap_path: /labelmap/coco-80.txt
-```
-
-</details>
-
 Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.

 ## CPU Detector (not recommended)
@@ -1452,7 +1405,7 @@ MemryX `.dfp` models are automatically downloaded at runtime, if enabled, to the

 #### YOLO-NAS

-The [YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) model included in this detector is downloaded from the [Models Section](#downloading-yolo-nas-model) and compiled to DFP with [mx_nc](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage).
+The [YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) model included in this detector is downloaded from the [Models Section](#downloading-yolo-nas-model) and compiled to DFP with [mx_nc](https://developer.memryx.com/tools/neural_compiler.html#usage).

 **Note:** The default model for the MemryX detector is YOLO-NAS 320x320.

@@ -1506,7 +1459,7 @@ model:

 #### YOLOv9

-The YOLOv9s model included in this detector is downloaded from [the original GitHub](https://github.com/WongKinYiu/yolov9) like in the [Models Section](#yolov9-1) and compiled to DFP with [mx_nc](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage).
+The YOLOv9s model included in this detector is downloaded from [the original GitHub](https://github.com/WongKinYiu/yolov9) like in the [Models Section](#yolov9-1) and compiled to DFP with [mx_nc](https://developer.memryx.com/tools/neural_compiler.html#usage).

 ##### Configuration

@@ -1648,39 +1601,19 @@ model:

 #### Using a Custom Model

-To use your own custom model, first compile it into a [.dfp](https://developer.memryx.com/2p1/specs/files.html#dataflow-program) file, which is the format used by MemryX.
+To use your own model:

-#### Compile the Model
+1.  Package your compiled model into a `.zip` file.

-Custom models must be compiled using **MemryX SDK 2.1**.
+2.  The `.zip` must contain the compiled `.dfp` file.

-Before compiling your model, install the MemryX Neural Compiler tools from the
-[Install Tools](https://developer.memryx.com/2p1/get_started/install_tools.html) page on the **host**.
+3.  Depending on the model, the compiler may also generate a cropped post-processing network. If present, it will be named with the suffix `_post.onnx`.

-> **Note:** It is recommended to compile the model on the host machine, or on another separate machine, rather than inside the Frigate Docker container. Installing the compiler inside Docker may conflict with container packages. It is recommended to create a Python virtual environment and install the compiler there.
+4.  Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.

-Once the SDK 2.1 environment is set up, follow the
-[MemryX Compiler](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage) documentation to compile your model.
+5.  Update the `labelmap_path` to match your custom model's labels.

-Example:
-
-```bash
-mx_nc -m yolonas.onnx -c 4 --autocrop -v --dfp_fname yolonas.dfp
-```
-
-For detailed instructions on compiling models, refer to the [MemryX Compiler](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage) docs and [Tutorials](https://developer.memryx.com/2p1/tutorials/tutorials.html).
-
-#### Package the Compiled Model
-
-1. Package your compiled model into a `.zip` file.
-
-2. The `.zip` file must contain the compiled `.dfp` file.
-
-3. Depending on the model, the compiler may also generate a cropped post-processing network. If present, it will be named with the suffix `_post.onnx`.
-
-4. Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.
-
-5. Update `labelmap_path` to match your custom model's labels.
+For detailed instructions on compiling models, refer to the [MemryX Compiler](https://developer.memryx.com/tools/neural_compiler.html#usage) docs and [Tutorials](https://developer.memryx.com/tutorials/tutorials.html).

 ```yaml
 # The detector automatically selects the default model if nothing is provided in the config.
@@ -2341,49 +2274,6 @@ COPY --from=build /dfine/output/dfine_${MODEL_SIZE}_obj2coco.onnx /dfine-${MODEL
 EOF
 ```

-### Downloading DEIMv2 Model
-
-[DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) can be exported as ONNX by running the command below. Pretrained weights are available on Hugging Face for two backbone families:
-
- **HGNetv2** (smaller/faster): `atto`, `femto`, `pico`, `n`
- **DINOv3** (larger/more accurate): `s`, `m`, `l`, `x`
-
-Set `BACKBONE` and `MODEL_SIZE` in the first line to match your desired variant. Hugging Face model names use uppercase (e.g. `HGNetv2_N`, `DINOv3_S`), while config files use lowercase (e.g. `hgnetv2_n`, `dinov3_s`).
-
-```sh
-docker build . --rm --build-arg BACKBONE=hgnetv2 --build-arg MODEL_SIZE=n --output . -f- <<'EOF'
-FROM python:3.11-slim AS build
-RUN apt-get update && apt-get install --no-install-recommends -y git libgl1 libglib2.0-0 && rm -rf /var/lib/apt/lists/*
-COPY --from=ghcr.io/astral-sh/uv:0.8.0 /uv /bin/
-WORKDIR /deimv2
-RUN git clone https://github.com/Intellindust-AI-Lab/DEIMv2.git .
-# Install CPU-only PyTorch first to avoid pulling CUDA variant
-RUN uv pip install --no-cache --system torch torchvision --index-url https://download.pytorch.org/whl/cpu
-RUN uv pip install --no-cache --system -r requirements.txt
-RUN uv pip install --no-cache --system onnx safetensors huggingface_hub
-RUN mkdir -p output
-ARG BACKBONE
-ARG MODEL_SIZE
-# Download from Hugging Face and convert safetensors to pth
-RUN python3 -c "\
-from huggingface_hub import hf_hub_download; \
-from safetensors.torch import load_file; \
-import torch; \
-backbone = '${BACKBONE}'.replace('hgnetv2','HGNetv2').replace('dinov3','DINOv3'); \
-size = '${MODEL_SIZE}'.upper(); \
-st = load_file(hf_hub_download('Intellindust/DEIMv2_' + backbone + '_' + size + '_COCO', 'model.safetensors')); \
-torch.save({'model': st}, 'output/deimv2.pth')"
-RUN sed -i "s/data = torch.rand(2/data = torch.rand(1/" tools/deployment/export_onnx.py
-# HuggingFace safetensors omits frozen constants that the model constructor initializes
-RUN sed -i "s/cfg.model.load_state_dict(state)/cfg.model.load_state_dict(state, strict=False)/" tools/deployment/export_onnx.py
-RUN python3 tools/deployment/export_onnx.py -c configs/deimv2/deimv2_${BACKBONE}_${MODEL_SIZE}_coco.yml -r output/deimv2.pth
-FROM scratch
-ARG BACKBONE
-ARG MODEL_SIZE
-COPY --from=build /deimv2/output/deimv2.onnx /deimv2_${BACKBONE}_${MODEL_SIZE}.onnx
-EOF
-```
-
 ### Downloading RF-DETR Model

 RF-DETR can be exported as ONNX by running the command below. You can copy and paste the whole thing to your terminal and execute, altering `MODEL_SIZE=Nano` in the first line to `Nano`, `Small`, or `Medium` size.
@@ -195,7 +195,7 @@ Pre and post capture footage is included in the **recording timeline**, visible

 ## Will Frigate delete old recordings if my storage runs out?

-If there is less than an hour left of storage, the oldest hour of recordings will be deleted and a message will be printed in the Frigate logs. This emergency cleanup deletes the oldest recordings first regardless of retention settings to reclaim space as quickly as possible.
+As of Frigate 0.12 if there is less than an hour left of storage, the oldest 2 hours of recordings will be deleted.

 ## Configuring Recording Retention

@@ -236,7 +236,7 @@ Enabling arbitrary exec sources allows execution of arbitrary commands through g

 ## Advanced Restream Configurations

-The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-exec) source in go2rtc can be used for custom ffmpeg commands and other applications. An example is below:
+The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-exec) source in go2rtc can be used for custom ffmpeg commands. An example is below:

 :::warning

@@ -244,11 +244,16 @@ The `exec:`, `echo:`, and `expr:` sources are disabled by default for security.

 :::

-NOTE: RTSP output will need to be passed with two curly braces `{{output}}`, whereas pipe output must be passed without curly braces.
+:::warning
+
+The `exec:`, `echo:`, and `expr:` sources are disabled by default for security. You must set `GO2RTC_ALLOW_ARBITRARY_EXEC=true` to use them. See [Security: Restricted Stream Sources](#security-restricted-stream-sources) for more information.
+
+:::
+
+NOTE: The output will need to be passed with two curly braces `{{output}}`

 ```yaml
 go2rtc:
  streams:
    stream1: exec:ffmpeg -hide_banner -re -stream_loop -1 -i /media/BigBuckBunny.mp4 -c copy -rtsp_transport tcp -f rtsp {{output}}
-    stream2: exec:rpicam-vid -t 0 --libav-format h264 -o -
 ```
@@ -223,11 +223,10 @@ Apple Silicon can not run within a container, so a ZMQ proxy is utilized to comm

 With the [ROCm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many discrete AMD GPUs.

-| Name           | YOLOv9 Inference Time       | YOLO-NAS Inference Time   | RF-DETR Inference Time |
-| -------------- | --------------------------- | ------------------------- | ---------------------- |
-| AMD 780M       | t-320: ~ 14 ms s-320: 20 ms | 320: ~ 25 ms 640: ~ 50 ms |                        |
-| AMD 8700G      |                             | 320: ~ 20 ms 640: ~ 40 ms |                        |
-| AMD 9060XT 16G | t-320: ~ 4 ms  s-320: 5 ms  | 320: ~ 6 ms               | Nano-320: ~ 90 ms      |
+| Name      | YOLOv9 Inference Time       | YOLO-NAS Inference Time   |
+| --------- | --------------------------- | ------------------------- |
+| AMD 780M  | t-320: ~ 14 ms s-320: 20 ms | 320: ~ 25 ms 640: ~ 50 ms |
+| AMD 8700G |                             | 320: ~ 20 ms 640: ~ 40 ms |

 ## Community Supported Detectors

@@ -5,14 +5,13 @@ title: Installation

 import ShmCalculator from '@site/src/components/ShmCalculator'
 import DockerComposeGenerator from '@site/src/components/DockerComposeGenerator'
-import Tabs from '@theme/Tabs';
-import TabItem from '@theme/TabItem';
+

 Frigate is a Docker container that can be run on any Docker host including as a [Home Assistant App](https://www.home-assistant.io/apps/). Note that the Home Assistant App is **not** the same thing as the integration. The [integration](/integrations/home-assistant) is required to integrate Frigate into Home Assistant, whether you are running Frigate as a standalone Docker container or as a Home Assistant App.

 :::tip

-If you already have Frigate installed as a Home Assistant App, check out the [getting started guide](../guides/getting_started.md#configuring-frigate) to configure Frigate.
+If you already have Frigate installed as a Home Assistant App, check out the [getting started guide](../guides/getting_started#configuring-frigate) to configure Frigate.

 :::

@@ -74,6 +73,13 @@ Users of the Snapcraft build of Docker cannot use storage locations outside your

 :::

+### Docker Compose Generator
+
+Generate a Frigate Docker Compose configuration based on your hardware and requirements.
+
+<DockerComposeGenerator/>
+
+
 ### Calculating required shm-size

 Frigate utilizes shared memory to store frames during processing. The default `shm-size` provided by Docker is **64MB**.
@@ -289,7 +295,7 @@ The MemryX MX3 Accelerator is available in the M.2 2280 form factor (like an NVM

 #### Installation

-To get started with MX3 hardware setup for your system, refer to the [Hardware Setup Guide](https://developer.memryx.com/2p1/get_started/install_hardware.html).
+To get started with MX3 hardware setup for your system, refer to the [Hardware Setup Guide](https://developer.memryx.com/get_started/hardware_setup.html).

 Then follow these steps for installing the correct driver/runtime configuration:

@@ -298,12 +304,6 @@ Then follow these steps for installing the correct driver/runtime configuration:
 3. Run the script with `./user_installation.sh`
 4. **Restart your computer** to complete driver installation.

-:::warning
-
-For manual setup, use **MemryX SDK 2.1** only. Other SDK versions are not supported for this setup. See the [SDK 2.1 documentation](https://developer.memryx.com/2p1/index.html)
-
-:::
-
 #### Setup

 To set up Frigate, follow the default installation instructions, for example: `ghcr.io/blakeblackshear/frigate:stable`
@@ -477,16 +477,6 @@ Finally, configure [hardware object detection](/configuration/object_detectors#a

 Running through Docker with Docker Compose is the recommended install method.

-<Tabs>
-  <TabItem value="domestic" label="Docker Compose Generator" default>
-
-Generate a Frigate Docker Compose configuration based on your hardware and requirements.
-
-<DockerComposeGenerator/>
-
-
-  </TabItem>
-  <TabItem value="original" label="Example Docker Compose File">
 ```yaml
 services:
  frigate:
@@ -520,10 +510,6 @@ services:
    environment:
      FRIGATE_RTSP_PASSWORD: "password"
 ```
-  </TabItem>
-</Tabs>
-
-**Docker CLI**

 If you can't use Docker Compose, you can run the container with something similar to this:

@@ -192,7 +192,7 @@ cameras:

 ### Step 4: Configure detectors

-By default, Frigate will use a single OpenVINO detector running on the CPU.
+By default, Frigate will use a single CPU detector.

 In many cases, the integrated graphics on Intel CPUs provides sufficient performance for typical Frigate setups. If you have an Intel processor, you can follow the configuration below.

@@ -39,10 +39,6 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht

 [Frigate telegram](https://github.com/OldTyT/frigate-telegram) makes it possible to send events from Frigate to Telegram. Events are sent as a message with a text description, video, and thumbnail.

-## [kiosk-monitor](https://github.com/extremeshok/kiosk-monitor)
-
-[kiosk-monitor](https://github.com/extremeshok/kiosk-monitor) is a Raspberry Pi watchdog that runs Chromium fullscreen on a Frigate dashboard (optionally with VLC on a second monitor for an RTSP camera stream), auto-restarts on frozen screens or unreachable URLs, and ships a Birdseye-aware Chromium helper that auto-sizes the grid to the display.
-
 ## [Periscope](https://github.com/maksz42/periscope)

 [Periscope](https://github.com/maksz42/periscope) is a lightweight Android app that turns old devices into live viewers for Frigate. It works on Android 2.2 and above, including Android TV. It supports authentication and HTTPS.
@@ -111,16 +111,26 @@ TCP ensures that all data packets arrive in the correct order. This is crucial f

 You can still configure Frigate to use UDP by using ffmpeg input args or the preset `preset-rtsp-udp`. See the [ffmpeg presets](/configuration/ffmpeg_presets) documentation.

-### Frigate is slow to start up with a "probing detect stream" message in the logs
+### Frigate hangs on startup with a "probing detect stream" message in the logs

-When `detect.width` and `detect.height` are not set, Frigate probes each camera's detect stream on startup (and when saving the config) to auto-detect its resolution. For RTSP streams Frigate probes with ffprobe and automatically retries over TCP if UDP doesn't respond, with a 5 second timeout per attempt. A camera that cannot be reached over either transport will add up to ~10 seconds to startup before Frigate falls through with default dimensions, which may show up as width `0` and height `0` in Camera Probe Info under System Metrics.
+On startup, Frigate probes each camera's detect stream with OpenCV to auto-detect its resolution. OpenCV's FFmpeg backend may attempt RTSP over UDP during this probe regardless of the `-rtsp_transport tcp` in your `input_args` or preset. For cameras that do not respond to UDP (common on some Reolink models and others behind firewalls that block UDP), the probe can hang indefinitely and block Frigate from finishing startup, or it can return zeroed-out dimensions that show up as width `0` and height `0` in Camera Probe Info under System Metrics.

-To skip the probe entirely and make startup instant, set `detect.width` and `detect.height` explicitly in your camera config:
+There are two ways to avoid this:

-```yaml
-cameras:
-  my_camera:
-    detect:
-      width: 1280
-      height: 720
-```
+1. Set `detect.width` and `detect.height` explicitly in your camera config. When both are set, Frigate skips the auto-detect probe entirely:
+
+   ```yaml
+   cameras:
+     my_camera:
+       detect:
+         width: 1280
+         height: 720
+   ```
+
+2. Force OpenCV's FFmpeg backend to use TCP for RTSP by setting the environment variable on your Frigate container:
+
+   ```
+   OPENCV_FFMPEG_CAPTURE_OPTIONS=rtsp_transport;tcp
+   ```
+
+   This is a process-wide setting and applies to all cameras. If you have any cameras that require `preset-rtsp-udp`, use option 1 instead.
@@ -367,12 +367,12 @@
      }
    },
    "node_modules/@babel/code-frame": {
-      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
-      "integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
+      "version": "7.27.1",
+      "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz",
+      "integrity": "sha512-cjQ7ZlQ0Mv3b47hABuTevyTuYN4i+loJKGeV9flcCgIK37cCXRh+L1bd3iBHlynerhQ7BhCkn2BPbQUL+rGqFg==",
      "license": "MIT",
      "dependencies": {
-        "@babel/helper-validator-identifier": "^7.28.5",
+        "@babel/helper-validator-identifier": "^7.27.1",
        "js-tokens": "^4.0.0",
        "picocolors": "^1.1.1"
      },
@@ -429,13 +429,13 @@
      }
    },
    "node_modules/@babel/generator": {
-      "version": "7.29.1",
-      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.29.1.tgz",
-      "integrity": "sha512-qsaF+9Qcm2Qv8SRIMMscAvG4O3lJ0F1GuMo5HR/Bp02LopNgnZBC/EkbevHFeGs4ls/oPz9v+Bsmzbkbe+0dUw==",
+      "version": "7.28.5",
+      "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.28.5.tgz",
+      "integrity": "sha512-3EwLFhZ38J4VyIP6WNtt2kUdW9dokXA9Cr4IVIFHuCpZ3H8/YFOl5JjZHisrn1fATPBmKKqXzDFvh9fUwHz6CQ==",
      "license": "MIT",
      "dependencies": {
-        "@babel/parser": "^7.29.0",
-        "@babel/types": "^7.29.0",
+        "@babel/parser": "^7.28.5",
+        "@babel/types": "^7.28.5",
        "@jridgewell/gen-mapping": "^0.3.12",
        "@jridgewell/trace-mapping": "^0.3.28",
        "jsesc": "^3.0.2"
@@ -576,27 +576,27 @@
      }
    },
    "node_modules/@babel/helper-module-imports": {
-      "version": "7.28.6",
-      "resolved": "https://registry.npmjs.org/@babel/helper-module-imports/-/helper-module-imports-7.28.6.tgz",
-      "integrity": "sha512-l5XkZK7r7wa9LucGw9LwZyyCUscb4x37JWTPz7swwFE/0FMQAGpiWUZn8u9DzkSBWEcK25jmvubfpw2dnAMdbw==",
+      "version": "7.27.1",
+      "resolved": "https://registry.npmjs.org/@babel/helper-module-imports/-/helper-module-imports-7.27.1.tgz",
+      "integrity": "sha512-0gSFWUPNXNopqtIPQvlD5WgXYI5GY2kP2cCvoT8kczjbfcfuIljTbcWrulD1CIPIX2gt1wghbDy08yE1p+/r3w==",
      "license": "MIT",
      "dependencies": {
-        "@babel/traverse": "^7.28.6",
-        "@babel/types": "^7.28.6"
+        "@babel/traverse": "^7.27.1",
+        "@babel/types": "^7.27.1"
      },
      "engines": {
        "node": ">=6.9.0"
      }
    },
    "node_modules/@babel/helper-module-transforms": {
-      "version": "7.28.6",
-      "resolved": "https://registry.npmjs.org/@babel/helper-module-transforms/-/helper-module-transforms-7.28.6.tgz",
-      "integrity": "sha512-67oXFAYr2cDLDVGLXTEABjdBJZ6drElUSI7WKp70NrpyISso3plG9SAGEF6y7zbha/wOzUByWWTJvEDVNIUGcA==",
+      "version": "7.28.3",
+      "resolved": "https://registry.npmjs.org/@babel/helper-module-transforms/-/helper-module-transforms-7.28.3.tgz",
+      "integrity": "sha512-gytXUbs8k2sXS9PnQptz5o0QnpLL51SwASIORY6XaBKF88nsOT0Zw9szLqlSGQDP/4TljBAD5y98p2U1fqkdsw==",
      "license": "MIT",
      "dependencies": {
-        "@babel/helper-module-imports": "^7.28.6",
-        "@babel/helper-validator-identifier": "^7.28.5",
-        "@babel/traverse": "^7.28.6"
+        "@babel/helper-module-imports": "^7.27.1",
+        "@babel/helper-validator-identifier": "^7.27.1",
+        "@babel/traverse": "^7.28.3"
      },
      "engines": {
        "node": ">=6.9.0"
@@ -618,9 +618,9 @@
      }
    },
    "node_modules/@babel/helper-plugin-utils": {
-      "version": "7.28.6",
-      "resolved": "https://registry.npmjs.org/@babel/helper-plugin-utils/-/helper-plugin-utils-7.28.6.tgz",
-      "integrity": "sha512-S9gzZ/bz83GRysI7gAD4wPT/AI3uCnY+9xn+Mx/KPs2JwHJIz1W8PZkg2cqyt3RNOBM8ejcXhV6y8Og7ly/Dug==",
+      "version": "7.27.1",
+      "resolved": "https://registry.npmjs.org/@babel/helper-plugin-utils/-/helper-plugin-utils-7.27.1.tgz",
+      "integrity": "sha512-1gn1Up5YXka3YYAHGKpbideQ5Yjf1tDa9qYcgysz+cNCXukyLl6DjPXhD3VRwSb8c0J9tA4b2+rHEZtc6R0tlw==",
      "license": "MIT",
      "engines": {
        "node": ">=6.9.0"
@@ -728,12 +728,12 @@
      }
    },
    "node_modules/@babel/parser": {
-      "version": "7.29.3",
-      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.29.3.tgz",
-      "integrity": "sha512-b3ctpQwp+PROvU/cttc4OYl4MzfJUWy6FZg+PMXfzmt/+39iHVF0sDfqay8TQM3JA2EUOyKcFZt75jWriQijsA==",
+      "version": "7.28.5",
+      "resolved": "https://registry.npmjs.org/@babel/parser/-/parser-7.28.5.tgz",
+      "integrity": "sha512-KKBU1VGYR7ORr3At5HAtUQ+TV3SzRCXmA/8OdDZiLDBIZxVyzXuztPjfLd3BV1PRAQGCMWWSHYhL0F8d5uHBDQ==",
      "license": "MIT",
      "dependencies": {
-        "@babel/types": "^7.29.0"
+        "@babel/types": "^7.28.5"
      },
      "bin": {
        "parser": "bin/babel-parser.js"
@@ -1318,15 +1318,15 @@
      }
    },
    "node_modules/@babel/plugin-transform-modules-systemjs": {
-      "version": "7.29.4",
-      "resolved": "https://registry.npmjs.org/@babel/plugin-transform-modules-systemjs/-/plugin-transform-modules-systemjs-7.29.4.tgz",
-      "integrity": "sha512-N7QmZ0xRZfjHOfZeQLJjwgX2zS9pdGHSVl/cjSGlo4dXMqvurfxXDMKY4RqEKzPozV78VMcd0lxyG13mlbKc4w==",
+      "version": "7.28.5",
+      "resolved": "https://registry.npmjs.org/@babel/plugin-transform-modules-systemjs/-/plugin-transform-modules-systemjs-7.28.5.tgz",
+      "integrity": "sha512-vn5Jma98LCOeBy/KpeQhXcV2WZgaRUtjwQmjoBuLNlOmkg0fB5pdvYVeWRYI69wWKwK2cD1QbMiUQnoujWvrew==",
      "license": "MIT",
      "dependencies": {
-        "@babel/helper-module-transforms": "^7.28.6",
-        "@babel/helper-plugin-utils": "^7.28.6",
+        "@babel/helper-module-transforms": "^7.28.3",
+        "@babel/helper-plugin-utils": "^7.27.1",
        "@babel/helper-validator-identifier": "^7.28.5",
-        "@babel/traverse": "^7.29.0"
+        "@babel/traverse": "^7.28.5"
      },
      "engines": {
        "node": ">=6.9.0"
@@ -2022,31 +2022,31 @@
      }
    },
    "node_modules/@babel/template": {
-      "version": "7.28.6",
-      "resolved": "https://registry.npmjs.org/@babel/template/-/template-7.28.6.tgz",
-      "integrity": "sha512-YA6Ma2KsCdGb+WC6UpBVFJGXL58MDA6oyONbjyF/+5sBgxY/dwkhLogbMT2GXXyU84/IhRw/2D1Os1B/giz+BQ==",
+      "version": "7.27.2",
+      "resolved": "https://registry.npmjs.org/@babel/template/-/template-7.27.2.tgz",
+      "integrity": "sha512-LPDZ85aEJyYSd18/DkjNh4/y1ntkE5KwUHWTiqgRxruuZL2F1yuHligVHLvcHY2vMHXttKFpJn6LwfI7cw7ODw==",
      "license": "MIT",
      "dependencies": {
-        "@babel/code-frame": "^7.28.6",
-        "@babel/parser": "^7.28.6",
-        "@babel/types": "^7.28.6"
+        "@babel/code-frame": "^7.27.1",
+        "@babel/parser": "^7.27.2",
+        "@babel/types": "^7.27.1"
      },
      "engines": {
        "node": ">=6.9.0"
      }
    },
    "node_modules/@babel/traverse": {
-      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/traverse/-/traverse-7.29.0.tgz",
-      "integrity": "sha512-4HPiQr0X7+waHfyXPZpWPfWL/J7dcN1mx9gL6WdQVMbPnF3+ZhSMs8tCxN7oHddJE9fhNE7+lxdnlyemKfJRuA==",
+      "version": "7.28.5",
+      "resolved": "https://registry.npmjs.org/@babel/traverse/-/traverse-7.28.5.tgz",
+      "integrity": "sha512-TCCj4t55U90khlYkVV/0TfkJkAkUg3jZFA3Neb7unZT8CPok7iiRfaX0F+WnqWqt7OxhOn0uBKXCw4lbL8W0aQ==",
      "license": "MIT",
      "dependencies": {
-        "@babel/code-frame": "^7.29.0",
-        "@babel/generator": "^7.29.0",
+        "@babel/code-frame": "^7.27.1",
+        "@babel/generator": "^7.28.5",
        "@babel/helper-globals": "^7.28.0",
-        "@babel/parser": "^7.29.0",
-        "@babel/template": "^7.28.6",
-        "@babel/types": "^7.29.0",
+        "@babel/parser": "^7.28.5",
+        "@babel/template": "^7.27.2",
+        "@babel/types": "^7.28.5",
        "debug": "^4.3.1"
      },
      "engines": {
@@ -2054,9 +2054,9 @@
      }
    },
    "node_modules/@babel/types": {
-      "version": "7.29.0",
-      "resolved": "https://registry.npmjs.org/@babel/types/-/types-7.29.0.tgz",
-      "integrity": "sha512-LwdZHpScM4Qz8Xw2iKSzS+cfglZzJGvofQICy7W7v4caru4EaAmyUuO6BGrbyQ2mYV11W0U8j5mBhd14dd3B0A==",
+      "version": "7.28.5",
+      "resolved": "https://registry.npmjs.org/@babel/types/-/types-7.28.5.tgz",
+      "integrity": "sha512-qQ5m48eI/MFLQ5PxQj4PFaprjyCTLI37ElWMmNs0K8Lk3dVeOdNpB3ks8jc7yM5CDmVC73eMVk/trk3fgmrUpA==",
      "license": "MIT",
      "dependencies": {
        "@babel/helper-string-parser": "^7.27.1",
@@ -10904,9 +10904,9 @@
      "license": "MIT"
    },
    "node_modules/express/node_modules/path-to-regexp": {
-      "version": "0.1.13",
-      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.13.tgz",
-      "integrity": "sha512-A/AGNMFN3c8bOlvV9RreMdrv7jsmF9XIfDeCd87+I8RNg6s78BhJxMu69NEMHBSJFxKidViTEdruRwEk/WIKqA==",
+      "version": "0.1.12",
+      "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.12.tgz",
+      "integrity": "sha512-RA1GjUVMnvYFxuqovrEqZoxxW5NUZqbwKtYz/Tt7nXerk0LbLblQmrsgdeOxV5SFHf0UDggjS/bSeOZwt1pmEQ==",
      "license": "MIT"
    },
    "node_modules/express/node_modules/range-parser": {
@@ -32,12 +32,12 @@ function renderHelpText(text: string): React.ReactNode {
 export default function DockerComposeGenerator() {
  const {
    deviceId, device, hardwareEnabled,
-    portEnabled,
+    portEnabled, port5000Confirmed,
    nvidiaGpuCount, nvidiaGpuDeviceId,
    configPath, mediaPath, rtspPassword, timezone, shmSize,
    shmSizeError, gpuDeviceIdError, configPathError, mediaPathError,
    hasAnyHardware, generatedYaml,
-    selectDevice, toggleHardware, togglePort,
+    selectDevice, toggleHardware, togglePort, setPort5000Confirmed,
    handleShmSizeChange, handleConfigPathChange, handleMediaPathChange,
    handleNvidiaGpuCountChange, handleNvidiaGpuDeviceIdChange,
    setRtspPassword, setTimezone, isHardwareDisabled,
@@ -82,7 +82,9 @@ export default function DockerComposeGenerator() {

        <PortConfigSection
          portEnabled={portEnabled}
+          port5000Confirmed={port5000Confirmed}
          onTogglePort={togglePort}
+          onConfirm5000={setPort5000Confirmed}
        />

        <OtherOptions
@@ -42,7 +42,7 @@ function HardwareCheckbox({
 export default function HardwareOptions({ deviceId, hardwareEnabled, onToggle, isDisabled }: Props) {
  return (
    <div className={styles.formSection}>
-      <h4>Generic Hardware Devices</h4>
+      <h4>Generic Hardware Acceleration</h4>
      {deviceId !== "stable" && (
        <p className={styles.helpText}>
          Some options have been auto-configured based on your device type.
@@ -16,8 +16,6 @@ export default function NvidiaGpuConfig({
  onGpuCountChange,
  onGpuDeviceIdChange,
 }: Props) {
-  const showDeviceId = gpuCount !== "";
-
  return (
    <div className={styles.nvidiaConfig}>
      <div className={styles.formGroup}>
@@ -27,15 +25,16 @@ export default function NvidiaGpuConfig({
        <input
          id="dcg-gpu-count"
          type="text"
-          inputMode="numeric"
-          pattern="[0-9]*"
          className={styles.input}
          value={gpuCount}
-          placeholder="all"
-          onChange={(e) => onGpuCountChange(e.target.value.replace(/\D/g, ""))}
+          placeholder="1 or all"
+          onChange={(e) => onGpuCountChange(e.target.value)}
        />
+        <p className={styles.helpText}>
+          Enter a number (e.g. 1, 2, 3) or &quot;all&quot; to use all GPUs
+        </p>
      </div>
-      {showDeviceId && (
+      {gpuCount !== "all" && (
        <div className={styles.formGroup}>
          <label htmlFor="dcg-gpu-device-id" className={styles.label}>
            GPU device IDs (required, comma-separated):
@@ -1,24 +1,7 @@
-import React, { useMemo } from "react";
+import React from "react";
 import CodeInline from "@theme/CodeInline";
 import styles from "../styles.module.css";

-const AUTO_TIMEZONE_VALUE = "__auto__";
-
-function getTimezoneList(): string[] {
-  if (typeof Intl !== "undefined") {
-    const intl = Intl as typeof Intl & {
-      supportedValuesOf?: (key: string) => string[];
-    };
-    const supported = intl.supportedValuesOf?.("timeZone");
-    if (supported && supported.length > 0) {
-      return [...supported].sort();
-    }
-  }
-
-  const fallback = Intl.DateTimeFormat().resolvedOptions().timeZone;
-  return fallback ? [fallback] : ["UTC"];
-}
-
 interface Props {
  rtspPassword: string;
  timezone: string;
@@ -38,38 +21,41 @@ export default function OtherOptions({
  onTimezoneChange,
  onShmSizeChange,
 }: Props) {
-  const timezones = useMemo(() => getTimezoneList(), []);
-  const systemTimezone =
-    Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC";
-  const selectedValue = timezone || AUTO_TIMEZONE_VALUE;
-
  return (
    <div className={styles.formSection}>
      <h4>Other Options</h4>
      <div className={styles.formGrid}>
+        <div className={styles.formGroup}>
+          <label htmlFor="dcg-rtsp-password" className={styles.label}>
+            RTSP password:
+          </label>
+          <input
+            id="dcg-rtsp-password"
+            type="text"
+            className={styles.input}
+            value={rtspPassword}
+            placeholder="password"
+            onChange={(e) => onRtspPasswordChange(e.target.value)}
+          />
+          <p className={styles.helpText}>
+            Used as{" "}
+            <CodeInline>{"{FRIGATE_RTSP_PASSWORD}"}</CodeInline>{" "}
+            in the config file to reference camera stream passwords. This is NOT
+            the Frigate login password.
+          </p>
+        </div>
        <div className={styles.formGroup}>
          <label htmlFor="dcg-timezone" className={styles.label}>
            Timezone:
          </label>
-          <select
+          <input
            id="dcg-timezone"
-            className={`${styles.input} ${styles.select}`}
-            value={selectedValue}
-            onChange={(e) =>
-              onTimezoneChange(
-                e.target.value === AUTO_TIMEZONE_VALUE ? "" : e.target.value
-              )
-            }
-          >
-            <option value={AUTO_TIMEZONE_VALUE}>
-              Use browser timezone ({systemTimezone})
-            </option>
-            {timezones.map((tz) => (
-              <option key={tz} value={tz}>
-                {tz}
-              </option>
-            ))}
-          </select>
+            type="text"
+            className={styles.input}
+            value={timezone}
+            placeholder={Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC"}
+            onChange={(e) => onTimezoneChange(e.target.value)}
+          />
        </div>
        <div className={styles.formGroup}>
          <label htmlFor="dcg-shm-size" className={styles.label}>
@@ -97,25 +83,6 @@ export default function OtherOptions({
            </p>
          )}
        </div>
-        <div className={styles.formGroup}>
-          <label htmlFor="dcg-rtsp-password" className={styles.label}>
-            RTSP password:
-          </label>
-          <input
-            id="dcg-rtsp-password"
-            type="text"
-            className={styles.input}
-            value={rtspPassword}
-            placeholder="password"
-            onChange={(e) => onRtspPasswordChange(e.target.value)}
-          />
-          <p className={styles.helpText}>
-            Optional. You can specify{" "}
-            <CodeInline>{"{FRIGATE_RTSP_PASSWORD}"}</CodeInline>{" "}
-            in the config file to reference camera stream passwords. This is NOT
-            the Frigate login password.
-          </p>
-        </div>
      </div>
    </div>
  );
@@ -1,71 +1,125 @@
 import React from "react";
 import Admonition from "@theme/Admonition";
 import { ports } from "../config";
+import { useCooldown } from "../hooks/useCooldown";
 import styles from "../styles.module.css";

 interface Props {
  portEnabled: Record<string, boolean>;
+  port5000Confirmed: boolean;
  onTogglePort: (portId: string) => void;
+  onConfirm5000: (confirmed: boolean) => void;
 }

-function PortItem({
-  port,
-  enabled,
+function Port5000Confirmation({
+  portEnabled,
+  confirmed,
  onToggle,
+  onConfirm,
 }: {
-  port: typeof ports[number];
-  enabled: boolean;
+  portEnabled: boolean;
+  confirmed: boolean;
  onToggle: () => void;
+  onConfirm: (confirmed: boolean) => void;
 }) {
-  const showWarning = port.warningContent && (
-    port.warningWhen === "checked" ? enabled :
-    port.warningWhen === "unchecked" ? !enabled : enabled
-  );
+  const { remaining, start, stop } = useCooldown(10);
+
+  React.useEffect(() => {
+    if (portEnabled) {
+      start();
+    } else {
+      stop();
+      onConfirm(false);
+    }
+    return stop;
+  }, [portEnabled]);

  return (
-    <div className={styles.hardwareItem}>
-      <label className={`${styles.checkboxLabel} ${port.locked ? styles.checkboxDisabled : ""}`}>
-        <input
-          type="checkbox"
-          checked={enabled}
-          onChange={onToggle}
-          disabled={port.locked}
-        />
-        <span>
-          {port.locked && "🔒 "}
-          Port {port.host}
-          {port.protocol !== "tcp" && `/${port.protocol}`}
-        </span>
-      </label>
-      {port.description && (
-        <div className={styles.hardwareDescription}>{port.description}</div>
-      )}
-      {showWarning && (
-        <Admonition type={port.warningType || "warning"}>
-          {port.warningContent}
+    <div className={styles.portSection}>
+      {portEnabled && (
+        <Admonition type="danger">
+          <p>
+            Exposing port 5000 allows <strong>unauthenticated access</strong> to
+            your Frigate instance. Anyone on your network (or the internet if you
+            have a public IP) could access it without credentials.
+          </p>
+          <p>
+            This may lead to <strong>unauthorized access</strong>,{" "}
+            <strong>privacy leaks</strong>, or further attacks. Ensure you have
+            proper firewall rules or VPN in place.
+          </p>
+          <label
+            className={`${styles.checkboxLabel} ${remaining > 0 ? styles.checkboxDisabled : ""}`}
+          >
+            <input
+              type="checkbox"
+              checked={confirmed}
+              onChange={(e) => onConfirm(e.target.checked)}
+              disabled={remaining > 0}
+            />
+            <span>
+              I understand the risk and confirm enabling port 5000
+              {remaining > 0 && ` (${remaining}s)`}
+            </span>
+          </label>
        </Admonition>
      )}
+      <label className={styles.checkboxLabel}>
+        <input
+          type="checkbox"
+          checked={portEnabled}
+          onChange={onToggle}
+        />
+        <span>Port 5000 (unauthenticated access)</span>
+        <span className={styles.warningBadge}>⚠️ Expose carefully</span>
+      </label>
    </div>
  );
 }

 export default function PortConfigSection({
  portEnabled,
+  port5000Confirmed,
  onTogglePort,
+  onConfirm5000,
 }: Props) {
  return (
    <div className={styles.formSection}>
      <h4>Port Configuration</h4>
+
+      {/* All ports except 5000 */}
      <div className={styles.checkboxGrid}>
-        {ports.map((port) => (
-          <PortItem
-            key={port.id}
-            port={port}
-            enabled={!!portEnabled[port.id]}
-            onToggle={() => onTogglePort(port.id)}
-          />
-        ))}
+        {ports
+          .filter((p) => p.id !== "5000")
+          .map((port) => (
+            <div key={port.id} className={styles.hardwareItem}>
+              <label className={`${styles.checkboxLabel} ${port.locked ? styles.checkboxDisabled : ""}`}>
+                <input
+                  type="checkbox"
+                  checked={!!portEnabled[port.id]}
+                  onChange={() => onTogglePort(port.id)}
+                  disabled={port.locked}
+                />
+                <span>
+                  {port.locked && "🔒 "}
+                  Port {port.host}
+                  {port.protocol !== "tcp" && `/${port.protocol}`}
+                </span>
+              </label>
+              {port.description && (
+                <div className={styles.hardwareDescription}>{port.description}</div>
+              )}
+            </div>
+          ))}
      </div>
+
+      {/* Port 5000 with special warning — placed last */}
+      <Port5000Confirmation
+        portEnabled={!!portEnabled["5000"]}
+        confirmed={port5000Confirmed}
+        onToggle={() => onTogglePort("5000")}
+        onConfirm={onConfirm5000}
+      />
    </div>
  );
 }
@@ -24,7 +24,7 @@ export default function StoragePaths({
      <div className={styles.formGrid}>
        <div className={styles.formGroup}>
          <label htmlFor="dcg-config-path" className={styles.label}>
-            Config / DB / model cache directory (on your host):
+            Config / DB / model cache directory:
          </label>
          <input
            id="dcg-config-path"
@@ -43,7 +43,7 @@ export default function StoragePaths({
        </div>
        <div className={styles.formGroup}>
          <label htmlFor="dcg-media-path" className={styles.label}>
-            Recording storage directory (on your host):
+            Recording storage directory:
          </label>
          <input
            id="dcg-media-path"
@@ -12,7 +12,7 @@ devices:
  - id: "intel"
    name: "Intel Device"
    description: "Intel GPU / NPU"
-    icon: '<svg xmlns="http://www.w3.org/2000/svg" width="41" height="25" viewBox="0 0 51 20" fill="none"><g clip-path="url(#clip0_5432_16259)"><path d="M4.2299 0.667969H0.605469V4.27284H4.2299V0.667969Z"fill="#00C7FD"></path><path d="M4.13917 19.4491V6.4536H0.695312V19.4363H4.13917V19.4491ZM26.9434 19.5774V16.3959C26.4404 16.3959 26.0147 16.3702 25.7052 16.3189C25.344 16.2676 25.0732 16.1393 24.8926 15.9597C24.712 15.7801 24.5959 15.5235 24.5314 15.1771C24.4798 14.8564 24.454 14.4331 24.454 13.9199V9.39138H26.9434V6.4536H24.454V1.39908H21.0102V13.9584C21.0102 15.0232 21.1005 15.9212 21.2811 16.6396C21.4616 17.3452 21.7712 17.9225 22.1968 18.3587C22.6225 18.7948 23.19 19.1027 23.8736 19.2952C24.5701 19.4876 25.4472 19.5774 26.492 19.5774H26.9434ZM46.6521 19.4491V0.398438H43.2082V19.4491H46.6521ZM17.6953 7.73647C16.7408 6.71018 15.3994 6.19703 13.6968 6.19703C12.8713 6.19703 12.1103 6.3638 11.4396 6.69735C10.756 7.03089 10.1885 7.49273 9.72414 8.08285L9.54357 8.3266V8.10851V6.4536H6.15131V19.4363H9.56936V12.5216V12.9963C9.56936 12.9193 9.56936 12.8423 9.56936 12.7653C9.60806 11.5466 9.90472 10.6486 10.4722 10.0713C11.0785 9.45553 11.8137 9.14764 12.6521 9.14764C13.6452 9.14764 14.4062 9.45553 14.9093 10.0456C15.3994 10.6358 15.6574 11.4696 15.6574 12.5344V12.5729V19.4363H19.127V12.0726C19.1399 10.2252 18.6498 8.76277 17.6953 7.73647ZM41.4282 12.9321C41.4282 11.9956 41.2606 11.1233 40.9381 10.3022C40.6028 9.49401 40.1384 8.7756 39.558 8.15982C38.9647 7.54404 38.2553 7.06938 37.4298 6.723C36.6043 6.37663 35.6885 6.20986 34.6953 6.20986C33.7537 6.20986 32.8638 6.38946 32.0383 6.73583C31.2128 7.09504 30.4905 7.5697 29.8842 8.17265C29.278 8.7756 28.7879 9.49401 28.4396 10.3151C28.0785 11.1361 27.9108 12.0213 27.9108 12.9578C27.9108 13.8943 28.0785 14.7795 28.4138 15.6005C28.7492 16.4215 29.2264 17.1399 29.8197 17.7429C30.4131 18.3458 31.1483 18.8333 31.9996 19.1797C32.8509 19.5389 33.7924 19.7185 34.7985 19.7185C37.7135 19.7185 39.5193 18.3972 40.6027 17.1656L38.1263 15.2926C37.6103 15.9084 36.3721 16.7422 34.8243 16.7422C33.8569 16.7422 33.0572 16.5242 32.451 16.0752C31.8448 15.639 31.432 15.0232 31.2128 14.2663L31.1741 14.1508H41.4282V12.9321ZM31.1999 11.739C31.1999 10.7897 32.2962 9.13481 34.6566 9.12198C37.017 9.12198 38.1263 10.7769 38.1263 11.7262L31.1999 11.739ZM50.5732 17.807C50.5087 17.6531 50.4184 17.5248 50.3023 17.4093C50.1862 17.2939 50.0572 17.2041 49.9024 17.1399C49.7477 17.0758 49.58 17.0373 49.4123 17.0373C49.2317 17.0373 49.077 17.0758 48.9222 17.1399C48.7674 17.2041 48.6384 17.2939 48.5223 17.4093C48.4062 17.5248 48.316 17.6531 48.2515 17.807C48.187 17.961 48.1483 18.1278 48.1483 18.2945C48.1483 18.4741 48.187 18.6281 48.2515 18.782C48.316 18.936 48.4062 19.0642 48.5223 19.1797C48.6384 19.2952 48.7674 19.385 48.9222 19.4491C49.077 19.5133 49.2446 19.5517 49.4123 19.5517C49.5929 19.5517 49.7477 19.5133 49.9024 19.4491C50.0572 19.385 50.1862 19.2952 50.3023 19.1797C50.4184 19.0642 50.5087 18.936 50.5732 18.782C50.6377 18.6281 50.6763 18.4613 50.6763 18.2945C50.6763 18.1278 50.6377 17.961 50.5732 17.807ZM50.3668 18.705C50.3152 18.8333 50.2378 18.9488 50.1475 19.0386C50.0572 19.1284 49.9411 19.2054 49.8122 19.2567C49.6832 19.308 49.5542 19.3337 49.3994 19.3337C49.2575 19.3337 49.1157 19.308 48.9867 19.2567C48.8577 19.2054 48.7416 19.1284 48.6513 19.0386C48.561 18.9488 48.4836 18.8333 48.432 18.705C48.3804 18.5768 48.3546 18.4485 48.3546 18.2945C48.3546 18.1534 48.3804 18.0123 48.432 17.884C48.4836 17.7557 48.561 17.6403 48.6513 17.5505C48.7416 17.4607 48.8577 17.3837 48.9867 17.3324C49.1157 17.2811 49.2446 17.2554 49.3994 17.2554C49.5413 17.2554 49.6832 17.2811 49.8122 17.3324C49.9411 17.3837 50.0572 17.4607 50.1475 17.5505C50.2378 17.6403 50.3152 17.7557 50.3668 17.884C50.4184 18.0123 50.4442 18.1406 50.4442 18.2945C50.4442 18.4485 50.4184 18.5768 50.3668 18.705ZM49.6445 18.41C49.7477 18.3972 49.8251 18.3587 49.8895 18.2945C49.954 18.2304 49.9927 18.1406 49.9927 18.0123C49.9927 17.8712 49.954 17.7685 49.8638 17.6916C49.7864 17.6146 49.6445 17.5761 49.4768 17.5761H48.9093V19.0258H49.1801V18.4356H49.3736L49.7348 19.0258H50.0185L49.6445 18.41ZM49.5026 18.1919C49.4639 18.1919 49.4252 18.1919 49.3736 18.1919H49.1801V17.7814H49.3736C49.4123 17.7814 49.451 17.7814 49.5026 17.7814C49.5413 17.7814 49.58 17.7942 49.6187 17.807C49.6574 17.8199 49.6832 17.8455 49.6961 17.8712C49.7219 17.8968 49.7219 17.9353 49.7219 17.9866C49.7219 18.0379 49.709 18.0764 49.6961 18.1021C49.6703 18.1278 49.6445 18.1534 49.6187 18.1662C49.58 18.1791 49.5413 18.1919 49.5026 18.1919Z"fill="currentColor"></path></g><defs><clipPath id="clip0_5432_16259"><rect width="51"height="20"fill="white"></rect></clipPath></defs></svg>'
+    icon: '<svg xmlns="http://www.w3.org/2000/svg"width="41" height="25" viewBox="0 0 50 12" fill="none" "viewBox="0 0 51 20"fill="none"><g clip-path="url(#clip0_5432_16259)"><path d="M4.2299 0.667969H0.605469V4.27284H4.2299V0.667969Z"fill="#00C7FD"></path><path d="M4.13917 19.4491V6.4536H0.695312V19.4363H4.13917V19.4491ZM26.9434 19.5774V16.3959C26.4404 16.3959 26.0147 16.3702 25.7052 16.3189C25.344 16.2676 25.0732 16.1393 24.8926 15.9597C24.712 15.7801 24.5959 15.5235 24.5314 15.1771C24.4798 14.8564 24.454 14.4331 24.454 13.9199V9.39138H26.9434V6.4536H24.454V1.39908H21.0102V13.9584C21.0102 15.0232 21.1005 15.9212 21.2811 16.6396C21.4616 17.3452 21.7712 17.9225 22.1968 18.3587C22.6225 18.7948 23.19 19.1027 23.8736 19.2952C24.5701 19.4876 25.4472 19.5774 26.492 19.5774H26.9434ZM46.6521 19.4491V0.398438H43.2082V19.4491H46.6521ZM17.6953 7.73647C16.7408 6.71018 15.3994 6.19703 13.6968 6.19703C12.8713 6.19703 12.1103 6.3638 11.4396 6.69735C10.756 7.03089 10.1885 7.49273 9.72414 8.08285L9.54357 8.3266V8.10851V6.4536H6.15131V19.4363H9.56936V12.5216V12.9963C9.56936 12.9193 9.56936 12.8423 9.56936 12.7653C9.60806 11.5466 9.90472 10.6486 10.4722 10.0713C11.0785 9.45553 11.8137 9.14764 12.6521 9.14764C13.6452 9.14764 14.4062 9.45553 14.9093 10.0456C15.3994 10.6358 15.6574 11.4696 15.6574 12.5344V12.5729V19.4363H19.127V12.0726C19.1399 10.2252 18.6498 8.76277 17.6953 7.73647ZM41.4282 12.9321C41.4282 11.9956 41.2606 11.1233 40.9381 10.3022C40.6028 9.49401 40.1384 8.7756 39.558 8.15982C38.9647 7.54404 38.2553 7.06938 37.4298 6.723C36.6043 6.37663 35.6885 6.20986 34.6953 6.20986C33.7537 6.20986 32.8638 6.38946 32.0383 6.73583C31.2128 7.09504 30.4905 7.5697 29.8842 8.17265C29.278 8.7756 28.7879 9.49401 28.4396 10.3151C28.0785 11.1361 27.9108 12.0213 27.9108 12.9578C27.9108 13.8943 28.0785 14.7795 28.4138 15.6005C28.7492 16.4215 29.2264 17.1399 29.8197 17.7429C30.4131 18.3458 31.1483 18.8333 31.9996 19.1797C32.8509 19.5389 33.7924 19.7185 34.7985 19.7185C37.7135 19.7185 39.5193 18.3972 40.6027 17.1656L38.1263 15.2926C37.6103 15.9084 36.3721 16.7422 34.8243 16.7422C33.8569 16.7422 33.0572 16.5242 32.451 16.0752C31.8448 15.639 31.432 15.0232 31.2128 14.2663L31.1741 14.1508H41.4282V12.9321ZM31.1999 11.739C31.1999 10.7897 32.2962 9.13481 34.6566 9.12198C37.017 9.12198 38.1263 10.7769 38.1263 11.7262L31.1999 11.739ZM50.5732 17.807C50.5087 17.6531 50.4184 17.5248 50.3023 17.4093C50.1862 17.2939 50.0572 17.2041 49.9024 17.1399C49.7477 17.0758 49.58 17.0373 49.4123 17.0373C49.2317 17.0373 49.077 17.0758 48.9222 17.1399C48.7674 17.2041 48.6384 17.2939 48.5223 17.4093C48.4062 17.5248 48.316 17.6531 48.2515 17.807C48.187 17.961 48.1483 18.1278 48.1483 18.2945C48.1483 18.4741 48.187 18.6281 48.2515 18.782C48.316 18.936 48.4062 19.0642 48.5223 19.1797C48.6384 19.2952 48.7674 19.385 48.9222 19.4491C49.077 19.5133 49.2446 19.5517 49.4123 19.5517C49.5929 19.5517 49.7477 19.5133 49.9024 19.4491C50.0572 19.385 50.1862 19.2952 50.3023 19.1797C50.4184 19.0642 50.5087 18.936 50.5732 18.782C50.6377 18.6281 50.6763 18.4613 50.6763 18.2945C50.6763 18.1278 50.6377 17.961 50.5732 17.807ZM50.3668 18.705C50.3152 18.8333 50.2378 18.9488 50.1475 19.0386C50.0572 19.1284 49.9411 19.2054 49.8122 19.2567C49.6832 19.308 49.5542 19.3337 49.3994 19.3337C49.2575 19.3337 49.1157 19.308 48.9867 19.2567C48.8577 19.2054 48.7416 19.1284 48.6513 19.0386C48.561 18.9488 48.4836 18.8333 48.432 18.705C48.3804 18.5768 48.3546 18.4485 48.3546 18.2945C48.3546 18.1534 48.3804 18.0123 48.432 17.884C48.4836 17.7557 48.561 17.6403 48.6513 17.5505C48.7416 17.4607 48.8577 17.3837 48.9867 17.3324C49.1157 17.2811 49.2446 17.2554 49.3994 17.2554C49.5413 17.2554 49.6832 17.2811 49.8122 17.3324C49.9411 17.3837 50.0572 17.4607 50.1475 17.5505C50.2378 17.6403 50.3152 17.7557 50.3668 17.884C50.4184 18.0123 50.4442 18.1406 50.4442 18.2945C50.4442 18.4485 50.4184 18.5768 50.3668 18.705ZM49.6445 18.41C49.7477 18.3972 49.8251 18.3587 49.8895 18.2945C49.954 18.2304 49.9927 18.1406 49.9927 18.0123C49.9927 17.8712 49.954 17.7685 49.8638 17.6916C49.7864 17.6146 49.6445 17.5761 49.4768 17.5761H48.9093V19.0258H49.1801V18.4356H49.3736L49.7348 19.0258H50.0185L49.6445 18.41ZM49.5026 18.1919C49.4639 18.1919 49.4252 18.1919 49.3736 18.1919H49.1801V17.7814H49.3736C49.4123 17.7814 49.451 17.7814 49.5026 17.7814C49.5413 17.7814 49.58 17.7942 49.6187 17.807C49.6574 17.8199 49.6832 17.8455 49.6961 17.8712C49.7219 17.8968 49.7219 17.9353 49.7219 17.9866C49.7219 18.0379 49.709 18.0764 49.6961 18.1021C49.6703 18.1278 49.6445 18.1534 49.6187 18.1662C49.58 18.1791 49.5413 18.1919 49.5026 18.1919Z"fill="currentColor"></path></g><defs><clipPath id="clip0_5432_16259"><rect width="51"height="20"fill="white"></rect></clipPath></defs></svg>'
    imageTag: "stable"
    autoHardware:
      - "gpu"
@@ -104,7 +104,7 @@ devices:
    imageTagSuffix: "-standard-arm64"
    autoHardware:
      - "video11"
-    helpText: "Raspberry Pi automatically configures the video11 device (RPi 4) and uses the arm64 image."
+    helpText: "Raspberry Pi automatically configures the Video11 device and uses the arm64 image."
    helpType: "info"

  - id: "stable-rk"
@@ -172,7 +172,7 @@ hardware:
        comment: "PCIe Coral — follow driver instructions at https://github.com/jnicolson/gasket-builder"

  - id: "gpu"
-    label: "Intel/AMD GPU (/dev/dri)"
+    label: "GPU Acceleration (/dev/dri)"
    description: "Pass through /dev/dri for GPU hardware acceleration (Intel/AMD)."
    disabledWhen:
      - "stable-tensorrt-jp6"
@@ -180,7 +180,7 @@ hardware:
    devices:
      - host: "/dev/dri"
        container: "/dev/dri"
-        comment: "Intel/AMD GPU hardware acceleration"
+        comment: "GPU hardware acceleration"

  - id: "intelNpu"
    label: "Intel NPU (/dev/accel)"
@@ -198,7 +198,7 @@ hardware:

  - id: "hailo"
    label: "Hailo NPU (/dev/hailo0)"
-    description: "Pass through /dev/hailo0 for Hailo-8 / Hailo-8L NPU acceleration. You also need to [install the driver](#hailo-8)."
+    description: "Pass through /dev/hailo0 for Hailo-8 / Hailo-8L NPU acceleration."
    disabledWhen:
      - "apple-silicon"
      - "stable-synaptics"
@@ -208,7 +208,7 @@ hardware:

  - id: "memryx"
    label: "MemryX MX3 (/dev/memx0)"
-    description: "Pass through /dev/memx0 for MemryX MX3 NPU acceleration. You also need to [install the driver](#memryx-mx3)."
+    description: "Pass through /dev/memx0 for MemryX MX3 NPU acceleration."
    disabledWhen:
      - "apple-silicon"
      - "stable-synaptics"
@@ -242,7 +242,7 @@ hardware:
        comment: "AXERA libraries"

  - id: "video11"
-    label: "Raspberry Pi (/dev/video11)"
+    label: "Raspberry Pi Video11"
    description: "Pass through /dev/video11 for Raspberry Pi 4B hardware acceleration."
    disabledWhen:
      - "stable-tensorrt"
@@ -265,14 +265,25 @@ ports:
    protocol: "tcp"
    description: "Authenticated UI and API access (default HTTPS)"
    defaultEnabled: true
-    warningContent: "This is the access port for Frigate. Closing it means you will no longer be able to access the instance."
-    warningWhen: "unchecked"
+    locked: true
+
+  - id: "5000"
+    host: 5000
+    container: 5000
+    protocol: "tcp"
+    description: "Unauthenticated Web UI port (not recommended)"
+    defaultEnabled: false
+    requiresConfirmation: true
+    warningType: "danger"
+    warningContent: "Exposing port 5000 allows **unauthenticated access** to your Frigate instance. Anyone on your network (or the internet if you have a public IP) could access it without any credentials. This may lead to **unauthorized access**, **privacy leaks**, or further attacks. Ensure you have proper firewall rules or VPN in place before enabling this."
+    confirmationLabel: "I understand the risk and confirm enabling port 5000"
+    cooldownSeconds: 10

  - id: "8554"
    host: 8554
    container: 8554
    protocol: "tcp"
-    description: "Access RTSP feeds from go2rtc"
+    description: "RTSP feeds"
    defaultEnabled: true

  - id: "8555-tcp"
@@ -293,5 +304,5 @@ ports:
    host: 1984
    container: 1984
    protocol: "tcp"
-    description: "Go2RTC Web UI"
-    defaultEnabled: false
+    description: "Go2RTC Web UIport"
+    defaultEnabled: false
@@ -145,10 +145,14 @@ export interface PortConfig {
  defaultEnabled: boolean;
  /** Whether this port is locked (always enabled, cannot be toggled off) */
  locked?: boolean;
+  /** Whether this port requires a confirmation step before enabling */
+  requiresConfirmation?: boolean;
  /** Admonition type for the warning */
  warningType?: "warning" | "danger";
  /** Warning content (markdown) */
  warningContent?: string;
-  /** When to show the warning: when the port is checked or unchecked */
-  warningWhen?: "checked" | "unchecked";
+  /** Confirmation checkbox label */
+  confirmationLabel?: string;
+  /** Cooldown in seconds before the confirmation checkbox becomes available */
+  cooldownSeconds?: number;
 }
@@ -15,7 +15,7 @@ export interface GeneratorInput {
  enabledPorts: string[];
  configPath: string;
  mediaPath: string;
-  rtspPassword?: string;
+  rtspPassword: string;
  timezone: string;
  shmSize: string;
  nvidiaGpuCount?: string;
@@ -99,7 +99,7 @@ function buildPorts(enabledPorts: string[]): string[] {
 function buildEnvironment(
  device: DeviceConfig,
  hwEnv: Record<string, string>,
-  rtspPassword: string | undefined,
+  rtspPassword: string,
  timezone: string
 ): string[] {
  const allEnv: Record<string, string> = {
@@ -107,15 +107,11 @@ function buildEnvironment(
    ...(device.env ?? {}),
  };

-  const lines: string[] = ["    environment:"];
-
-  if (rtspPassword) {
-    lines.push(
-      `      FRIGATE_RTSP_PASSWORD: "${rtspPassword}" # RTSP password — change to your own`
-    );
-  }
-
-  lines.push(`      TZ: "${timezone}" # Timezone`);
+  const lines: string[] = [
+    "    environment:",
+    `      FRIGATE_RTSP_PASSWORD: "${rtspPassword}" # RTSP password — change to your own`,
+    `      TZ: "${timezone}" # Timezone`,
+  ];

  for (const [key, value] of Object.entries(allEnv)) {
    lines.push(`      ${key}: "${value}"`);
@@ -127,7 +123,7 @@ function buildEnvironment(
 function buildDeploy(device: DeviceConfig, input: GeneratorInput): string[] {
  if (device.id === "stable-tensorrt") {
    const count = input.nvidiaGpuCount || "all";
-    const isAll = count === "all";
+    const isAll = count.toLowerCase() === "all";
    const deviceId = input.nvidiaGpuDeviceId?.trim();

    if (isAll) {
@@ -29,12 +29,15 @@ export function useConfigGenerator() {
    return initial;
  });

-  const [nvidiaGpuCount, setNvidiaGpuCount] = useState("");
+  const [port5000Confirmed, setPort5000Confirmed] = useState(false);
+  const [nvidiaGpuCount, setNvidiaGpuCount] = useState("all");
  const [nvidiaGpuDeviceId, setNvidiaGpuDeviceId] = useState("");
  const [configPath, setConfigPath] = useState("");
  const [mediaPath, setMediaPath] = useState("");
-  const [rtspPassword, setRtspPassword] = useState("");
-  const [timezone, setTimezone] = useState("");
+  const [rtspPassword, setRtspPassword] = useState("password");
+  const [timezone, setTimezone] = useState(
+    () => Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC"
+  );
  const [shmSize, setShmSize] = useState("512mb");
  const [shmSizeError, setShmSizeError] = useState(false);
  const [gpuDeviceIdError, setGpuDeviceIdError] = useState(false);
@@ -54,7 +57,7 @@ export function useConfigGenerator() {
      }
      return next;
    });
-    setNvidiaGpuCount("");
+    setNvidiaGpuCount("all");
    setNvidiaGpuDeviceId("");
    setGpuDeviceIdError(false);
  }, []);
@@ -66,7 +69,13 @@ export function useConfigGenerator() {
  const togglePort = useCallback((portId: string) => {
    const port = portMap.get(portId);
    if (port?.locked) return;
-    setPortEnabled((prev) => ({ ...prev, [portId]: !prev[portId] }));
+    setPortEnabled((prev) => {
+      const next = { ...prev, [portId]: !prev[portId] };
+      if (portId === "5000" && !next[portId]) {
+        setPort5000Confirmed(false);
+      }
+      return next;
+    });
  }, []);

  const isHardwareDisabled = useCallback(
@@ -119,13 +128,15 @@ export function useConfigGenerator() {
  );

  const handleNvidiaGpuCountChange = useCallback((value: string) => {
-    // Only allow digits
-    setNvidiaGpuCount(value);
-    if (value === "") {
-      setNvidiaGpuDeviceId("");
-      setGpuDeviceIdError(false);
-    } else {
-      setGpuDeviceIdError(false);
+    const lower = value.trim().toLowerCase();
+    if (lower === "all" || lower === "" || /^[0-9]+$/.test(lower)) {
+      setNvidiaGpuCount(lower || "all");
+      if (lower === "all") {
+        setNvidiaGpuDeviceId("");
+        setGpuDeviceIdError(false);
+      } else if (/^[0-9]+$/.test(lower)) {
+        setGpuDeviceIdError(false);
+      }
    }
  }, []);

@@ -138,6 +149,7 @@ export function useConfigGenerator() {
    const lines: string[] = [];
    for (const [id, enabled] of Object.entries(portEnabled)) {
      if (!enabled) continue;
+      if (id === "5000" && !port5000Confirmed) continue;
      const p = portMap.get(id);
      if (!p) continue;
      const proto = p.protocol && p.protocol !== "tcp" ? `/${p.protocol}` : "";
@@ -145,7 +157,7 @@ export function useConfigGenerator() {
      lines.push(`      - "${p.host}:${p.container}${proto}"${comment}`);
    }
    return lines;
-  }, [portEnabled]);
+  }, [portEnabled, port5000Confirmed]);

  const selectedHardwareIds = useMemo(() => {
    return Object.entries(hardwareEnabled)
@@ -166,7 +178,7 @@ export function useConfigGenerator() {
      enabledPorts: enabledPortLines,
      configPath: configPath || "/path/to/your/config",
      mediaPath: mediaPath || "/path/to/your/storage",
-      rtspPassword,
+      rtspPassword: rtspPassword || "password",
      timezone: timezone || Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC",
      shmSize: shmSize || "512mb",
      nvidiaGpuCount,
@@ -183,11 +195,11 @@ export function useConfigGenerator() {

  return {
    deviceId, device, hardwareEnabled, portEnabled,
-    nvidiaGpuCount, nvidiaGpuDeviceId,
+    port5000Confirmed, nvidiaGpuCount, nvidiaGpuDeviceId,
    configPath, mediaPath, rtspPassword, timezone, shmSize,
    shmSizeError, gpuDeviceIdError, configPathError, mediaPathError,
    hasAnyHardware, generatedYaml,
-    selectDevice, toggleHardware, togglePort,
+    selectDevice, toggleHardware, togglePort, setPort5000Confirmed,
    handleShmSizeChange, handleConfigPathChange, handleMediaPathChange,
    handleNvidiaGpuCountChange, handleNvidiaGpuDeviceIdChange,
    setRtspPassword, setTimezone, isHardwareDisabled,
@@ -0,0 +1,42 @@
+import { useState, useEffect, useCallback, useRef } from "react";
+
+/**
+ * Hook for a countdown timer (e.g. cooldown before confirming port 5000).
+ */
+export function useCooldown(initialSeconds: number) {
+  const [remaining, setRemaining] = useState(0);
+  const timerRef = useRef<ReturnType<typeof setInterval> | null>(null);
+
+  const start = useCallback(() => {
+    // Clear any existing timer
+    if (timerRef.current) clearInterval(timerRef.current);
+    setRemaining(initialSeconds);
+    timerRef.current = setInterval(() => {
+      setRemaining((prev) => {
+        if (prev <= 1) {
+          if (timerRef.current) clearInterval(timerRef.current);
+          timerRef.current = null;
+          return 0;
+        }
+        return prev - 1;
+      });
+    }, 1000);
+  }, [initialSeconds]);
+
+  const stop = useCallback(() => {
+    if (timerRef.current) {
+      clearInterval(timerRef.current);
+      timerRef.current = null;
+    }
+    setRemaining(0);
+  }, []);
+
+  // Cleanup on unmount
+  useEffect(() => {
+    return () => {
+      if (timerRef.current) clearInterval(timerRef.current);
+    };
+  }, []);
+
+  return { remaining, start, stop };
+}
@@ -103,25 +103,6 @@
  }
 }

-/* --- Select dropdown --- */
-
-.select {
-  cursor: pointer;
-  appearance: none;
-  -moz-appearance: none;
-  -webkit-appearance: none;
-  background: var(--ifm-background-color)
-    url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='12' height='12' viewBox='0 0 12 12'%3E%3Cpath fill='%23666' d='M6 8L1 3h10z'/%3E%3C/svg%3E")
-    no-repeat right 0.75rem center / 12px 12px;
-  padding-right: 2rem;
-}
-
-[data-theme="light"] .select {
-  background: #fff
-    url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='12' height='12' viewBox='0 0 12 12'%3E%3Cpath fill='%23555' d='M6 8L1 3h10z'/%3E%3C/svg%3E")
-    no-repeat right 0.75rem center / 12px 12px;
-}
-
 .helpText {
  margin: 0.5rem 0 0 0;
  font-size: 0.85rem;
@@ -5997,10 +5997,7 @@ paths:
      tags:
        - App
      summary: Start debug replay
-      description:
-        Start a debug replay session from camera recordings. Returns
-        immediately while clip generation runs as a background job; subscribe
-        to the 'debug_replay' job_state WS topic to track progress.
+      description: Start a debug replay session from camera recordings.
      operationId: start_debug_replay_debug_replay_start_post
      requestBody:
        required: true
@@ -6009,16 +6006,12 @@ paths:
            schema:
              $ref: "#/components/schemas/DebugReplayStartBody"
      responses:
-        "202":
+        "200":
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DebugReplayStartResponse"
-        "400":
-          description: Invalid camera, time range, or no recordings
-        "409":
-          description: A replay session is already active
        "422":
          description: Validation Error
          content:
@@ -6279,14 +6272,10 @@ components:
        replay_camera:
          type: string
          title: Replay Camera
-        job_id:
-          type: string
-          title: Job Id
      type: object
      required:
        - success
        - replay_camera
-        - job_id
      title: DebugReplayStartResponse
      description: Response for starting a debug replay session.
    DebugReplayStatusResponse:
@@ -146,13 +146,8 @@ def config(request: Request):
        for name, detector in config_obj.detectors.items()
    }

-    # remove environment_vars for non-admin users
-    if request.headers.get("remote-role") != "admin":
-        config.pop("environment_vars", None)
-
-    # remove mqtt credentials
+    # remove the mqtt password
    config["mqtt"].pop("password", None)
-    config["mqtt"].pop("user", None)

    # remove the proxy secret
    config["proxy"].pop("auth_secret", None)
@@ -499,40 +494,6 @@ def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
        )


-def _restore_masked_camera_paths(config_data: dict, config: FrigateConfig) -> None:
-    """Substitute incoming `*:*` masked credentials with the in-memory ones.
-
-    The /config response masks ffmpeg input credentials, so the settings UI
-    sends the masked path back when sibling fields (e.g. hwaccel_args) are
-    edited.  Without this we'd write `rtsp://*:*@host` into YAML and lose
-    the real credentials.  Mutates `config_data` in place.
-    """
-    cameras = config_data.get("cameras")
-    if not isinstance(cameras, dict):
-        return
-
-    for camera_name, camera_data in cameras.items():
-        if not isinstance(camera_data, dict):
-            continue
-        inputs = camera_data.get("ffmpeg", {}).get("inputs")
-        if not isinstance(inputs, list):
-            continue
-        existing = config.cameras.get(camera_name)
-        if existing is None:
-            continue
-        existing_paths = [inp.path for inp in existing.ffmpeg.inputs]
-        for index, input_obj in enumerate(inputs):
-            if not isinstance(input_obj, dict):
-                continue
-            path = input_obj.get("path")
-            if not isinstance(path, str):
-                continue
-            if ("://*:*@" in path or "user=*&password=*" in path) and index < len(
-                existing_paths
-            ):
-                input_obj["path"] = existing_paths[index]
-
-
 def _config_set_in_memory(request: Request, body: AppConfigSetBody) -> JSONResponse:
    """Apply config changes in-memory only, without writing to YAML.

@@ -543,7 +504,6 @@ def _config_set_in_memory(request: Request, body: AppConfigSetBody) -> JSONRespo
    try:
        updates = {}
        if body.config_data:
-            _restore_masked_camera_paths(body.config_data, request.app.frigate_config)
            updates = flatten_config_data(body.config_data)
            updates = {k: ("" if v is None else v) for k, v in updates.items()}

@@ -650,9 +610,6 @@ def config_set(request: Request, body: AppConfigSetBody):
                if query_string:
                    updates = process_config_query_string(query_string)
                elif body.config_data:
-                    _restore_masked_camera_paths(
-                        body.config_data, request.app.frigate_config
-                    )
                    updates = flatten_config_data(body.config_data)
                    # Convert None values to empty strings for deletion (e.g., when deleting masks)
                    updates = {k: ("" if v is None else v) for k, v in updates.items()}
@@ -812,11 +812,6 @@ limiter = Limiter(key_func=get_remote_addr)
 )
@limiter.limit(limit_value=rateLimiter.get_limit)
 def login(request: Request, body: AppPostLoginBody):
-    if not request.app.frigate_config.auth.enabled:
-        return JSONResponse(
-            content={"message": "Authentication is disabled"}, status_code=404
-        )
-
    JWT_COOKIE_NAME = request.app.frigate_config.auth.cookie_name
    JWT_COOKIE_SECURE = request.app.frigate_config.auth.cookie_secure
    JWT_SESSION_LENGTH = request.app.frigate_config.auth.session_length
@@ -36,8 +36,6 @@ from frigate.api.defs.response.chat_response import (
 )
 from frigate.api.defs.tags import Tags
 from frigate.api.event import events
-from frigate.config import FrigateConfig
-from frigate.config.ui import UnitSystemEnum
 from frigate.genai.utils import build_assistant_message_for_conversation
 from frigate.jobs.vlm_watch import (
    get_vlm_watch_job,
@@ -403,38 +401,9 @@ def get_tools() -> JSONResponse:
    return JSONResponse(content={"tools": tools})


-def _resolve_zones(
-    zones: List[str],
-    config: FrigateConfig,
-    target_cameras: List[str],
-) -> List[str]:
-    """Map zone names to their canonical config keys, case-insensitively.
-
-    LLMs frequently echo a user's casing ("Front Yard") instead of the
-    configured key ("front_yard"). The downstream zone filter is a SQLite GLOB
-    over the JSON-encoded zones column, which is case-sensitive — so an
-    unnormalized name silently returns zero matches. Build a lookup over the
-    relevant cameras' configured zones and substitute when we find a match;
-    unknown names pass through so behavior matches what the model asked for.
-    """
-    if not zones:
-        return zones
-
-    lookup: Dict[str, str] = {}
-    for camera_id in target_cameras:
-        camera_config = config.cameras.get(camera_id)
-        if camera_config is None:
-            continue
-        for zone_name in camera_config.zones.keys():
-            lookup.setdefault(zone_name.lower(), zone_name)
-
-    return [lookup.get(z.lower(), z) for z in zones]
-
-
 async def _execute_search_objects(
    arguments: Dict[str, Any],
    allowed_cameras: List[str],
-    config: FrigateConfig,
 ) -> JSONResponse:
    """
    Execute the search_objects tool.
@@ -468,11 +437,6 @@ async def _execute_search_objects(
    # Convert zones array to comma-separated string if provided
    zones = arguments.get("zones")
    if isinstance(zones, list):
-        camera_arg = arguments.get("camera")
-        target_cameras = (
-            [camera_arg] if camera_arg and camera_arg != "all" else allowed_cameras
-        )
-        zones = _resolve_zones(zones, config, target_cameras)
        zones = ",".join(zones)
    elif zones is None:
        zones = "all"
@@ -564,11 +528,6 @@ async def _execute_find_similar_objects(
    sub_labels = arguments.get("sub_labels")
    zones = arguments.get("zones")

-    if zones:
-        zones = _resolve_zones(
-            zones, request.app.frigate_config, cameras or list(allowed_cameras)
-        )
-
    similarity_mode = arguments.get("similarity_mode", "fused")
    if similarity_mode not in ("visual", "semantic", "fused"):
        similarity_mode = "fused"
@@ -696,9 +655,7 @@ async def execute_tool(
    logger.debug(f"Executing tool: {tool_name} with arguments: {arguments}")

    if tool_name == "search_objects":
-        return await _execute_search_objects(
-            arguments, allowed_cameras, request.app.frigate_config
-        )
+        return await _execute_search_objects(arguments, allowed_cameras)

    if tool_name == "find_similar_objects":
        result = await _execute_find_similar_objects(
@@ -878,9 +835,7 @@ async def _execute_tool_internal(
    This is used by the chat completion endpoint to execute tools.
    """
    if tool_name == "search_objects":
-        response = await _execute_search_objects(
-            arguments, allowed_cameras, request.app.frigate_config
-        )
+        response = await _execute_search_objects(arguments, allowed_cameras)
        try:
            if hasattr(response, "body"):
                body_str = response.body.decode("utf-8")
@@ -944,9 +899,6 @@ async def _execute_start_camera_watch(

    await require_camera_access(camera, request=request)

-    if zones:
-        zones = _resolve_zones(zones, config, [camera])
-
    genai_manager = request.app.genai_manager
    chat_client = genai_manager.chat_client
    if chat_client is None or not chat_client.supports_vision:
@@ -1302,7 +1254,6 @@ async def chat_completion(

    cameras_info = []
    config = request.app.frigate_config
-    has_speed_zone = False
    for camera_id in allowed_cameras:
        if camera_id not in config.cameras:
            continue
@@ -1313,10 +1264,6 @@ async def chat_completion(
            else camera_id.replace("_", " ").title()
        )
        zone_names = list(camera_config.zones.keys())
-        if not has_speed_zone:
-            has_speed_zone = any(
-                zone.distances for zone in camera_config.zones.values()
-            )
        if zone_names:
            cameras_info.append(
                f"  - {friendly_name} (ID: {camera_id}, zones: {', '.join(zone_names)})"
@@ -1332,13 +1279,6 @@ async def chat_completion(
            + "\n\nWhen users refer to cameras by their friendly name (e.g., 'Back Deck Camera'), use the corresponding camera ID (e.g., 'back_deck_cam') in tool calls."
        )

-    speed_units_section = ""
-    if has_speed_zone:
-        speed_unit = (
-            "mph" if config.ui.unit_system == UnitSystemEnum.imperial else "km/h"
-        )
-        speed_units_section = f"\n\nReport object speeds to the user in {speed_unit}."
-
    system_prompt = f"""You are a helpful assistant for Frigate, a security camera NVR system. You help users answer questions about their cameras, detected objects, and events.

 Current server local date and time: {current_date_str} at {current_time_str}
@@ -1350,7 +1290,7 @@ When users ask about "today", "yesterday", "this week", etc., use the current da
 When searching for objects or events, use ISO 8601 format for dates (e.g., {current_date_str}T00:00:00Z for the start of today).
 Always be accurate with time calculations based on the current date provided.

-When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{cameras_section}{speed_units_section}"""
+When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{cameras_section}"""

    conversation.append(
        {
@@ -10,7 +10,6 @@ from pydantic import BaseModel, Field

 from frigate.api.auth import require_role
 from frigate.api.defs.tags import Tags
-from frigate.jobs.debug_replay import start_debug_replay_job

 logger = logging.getLogger(__name__)

@@ -30,17 +29,10 @@ class DebugReplayStartResponse(BaseModel):

    success: bool
    replay_camera: str
-    job_id: str


 class DebugReplayStatusResponse(BaseModel):
-    """Response for debug replay status.
-
-    Returns only session-presence fields. Startup progress and error
-    details flow through the job_state WebSocket topic via the
-    debug_replay job (see frigate.jobs.debug_replay); the
-    Replay page subscribes there with useJobStatus("debug_replay").
-    """
+    """Response for debug replay status."""

    active: bool
    replay_camera: str | None = None
@@ -59,32 +51,15 @@ class DebugReplayStopResponse(BaseModel):
@router.post(
    "/debug_replay/start",
    response_model=DebugReplayStartResponse,
-    status_code=202,
-    responses={
-        400: {"description": "Invalid camera, time range, or no recordings"},
-        409: {"description": "A replay session is already active"},
-    },
    dependencies=[Depends(require_role(["admin"]))],
    summary="Start debug replay",
-    description="Start a debug replay session from camera recordings. Returns "
-    "immediately while clip generation runs as a background job; subscribe "
-    "to the 'debug_replay' job_state WS topic to track progress.",
+    description="Start a debug replay session from camera recordings.",
 )
 async def start_debug_replay(request: Request, body: DebugReplayStartBody):
-    """Start a debug replay session asynchronously."""
+    """Start a debug replay session."""
    replay_manager = request.app.replay_manager

-    try:
-        job_id = await asyncio.to_thread(
-            start_debug_replay_job,
-            source_camera=body.camera,
-            start_ts=body.start_time,
-            end_ts=body.end_time,
-            frigate_config=request.app.frigate_config,
-            config_publisher=request.app.config_publisher,
-            replay_manager=replay_manager,
-        )
-    except RuntimeError:
+    if replay_manager.active:
        return JSONResponse(
            content={
                "success": False,
@@ -92,23 +67,38 @@ async def start_debug_replay(request: Request, body: DebugReplayStartBody):
            },
            status_code=409,
        )
+
+    try:
+        replay_camera = await asyncio.to_thread(
+            replay_manager.start,
+            source_camera=body.camera,
+            start_ts=body.start_time,
+            end_ts=body.end_time,
+            frigate_config=request.app.frigate_config,
+            config_publisher=request.app.config_publisher,
+        )
    except ValueError:
-        logger.exception("Rejected debug replay start request")
+        logger.exception("Invalid parameters for debug replay start request")
        return JSONResponse(
            content={
                "success": False,
-                "message": "Invalid debug replay parameters",
+                "message": "Invalid debug replay request parameters",
            },
            status_code=400,
        )
+    except RuntimeError:
+        logger.exception("Error while starting debug replay session")
+        return JSONResponse(
+            content={
+                "success": False,
+                "message": "An internal error occurred while starting debug replay",
+            },
+            status_code=500,
+        )

-    return JSONResponse(
-        content={
-            "success": True,
-            "replay_camera": replay_manager.replay_camera_name,
-            "job_id": job_id,
-        },
-        status_code=202,
+    return DebugReplayStartResponse(
+        success=True,
+        replay_camera=replay_camera,
    )


@@ -128,16 +118,12 @@ def get_debug_replay_status(request: Request):

    if replay_manager.active and replay_camera:
        frame_processor = request.app.detected_frames_processor
-        frame = (
-            frame_processor.get_current_frame(replay_camera)
-            if frame_processor is not None
-            else None
-        )
+        frame = frame_processor.get_current_frame(replay_camera)

        if frame is not None:
            frame_time = frame_processor.get_current_frame_time(replay_camera)
            camera_config = request.app.frigate_config.cameras.get(replay_camera)
-            retry_interval = 10.0
+            retry_interval = 10

            if camera_config is not None:
                retry_interval = float(camera_config.ffmpeg.retry_interval or 10)
@@ -754,15 +754,6 @@ def events_search(
                status_code=404,
            )

-        if search_event.camera not in allowed_cameras:
-            return JSONResponse(
-                content={
-                    "success": False,
-                    "message": "Event not found",
-                },
-                status_code=404,
-            )
-
        thumb_result = context.search_thumbnail(search_event)
        thumb_ids = {result[0]: result[1] for result in thumb_result}
        search_results = {
@@ -5,15 +5,13 @@ import logging
 import random
 import string
 import time
-import zipfile
-from collections import deque
 from pathlib import Path
-from typing import Iterator, List, Optional
+from typing import List, Optional

 import psutil
 from fastapi import APIRouter, Depends, Query, Request
-from fastapi.responses import JSONResponse, StreamingResponse
-from pathvalidate import sanitize_filename, sanitize_filepath
+from fastapi.responses import JSONResponse
+from pathvalidate import sanitize_filepath
 from peewee import DoesNotExist
 from playhouse.shortcuts import model_to_dict

@@ -363,136 +361,6 @@ def get_export_case(case_id: str):
        )


-_ZIP_STREAM_CHUNK_SIZE = 1024 * 1024  # 1 MiB
-
-
-class _StreamingZipBuffer:
-    """File-like sink for ZipFile that exposes written bytes via drain().
-
-    ZipFile writes synchronously into this buffer; the generator drains the
-    queue between writes so StreamingResponse can yield bytes without
-    materializing the whole archive in memory.
-    """
-
-    def __init__(self) -> None:
-        self._queue: deque[bytes] = deque()
-        self._offset = 0
-
-    def write(self, data: bytes) -> int:
-        if data:
-            self._queue.append(bytes(data))
-            self._offset += len(data)
-        return len(data)
-
-    def tell(self) -> int:
-        return self._offset
-
-    def flush(self) -> None:
-        pass
-
-    def drain(self) -> Iterator[bytes]:
-        while self._queue:
-            yield self._queue.popleft()
-
-
-def _unique_archive_name(export: Export, used: set[str]) -> str:
-    base = sanitize_filename(export.name) if export.name else None
-    if not base:
-        base = f"{export.camera}_{int(datetime.datetime.timestamp(export.date))}"
-
-    candidate = f"{base}.mp4"
-    counter = 1
-    while candidate in used:
-        candidate = f"{base}_{counter}.mp4"
-        counter += 1
-
-    used.add(candidate)
-    return candidate
-
-
-def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
-    """Yield bytes of a zip archive built from the given exports' mp4 files."""
-    buffer = _StreamingZipBuffer()
-    used_names: set[str] = set()
-
-    # ZIP_STORED: mp4 is already compressed, recompressing wastes CPU for ~0% size win.
-    with zipfile.ZipFile(
-        buffer,
-        mode="w",
-        compression=zipfile.ZIP_STORED,
-        allowZip64=True,
-    ) as archive:
-        for export in exports:
-            source = Path(export.video_path)
-            if not source.exists():
-                continue
-
-            arcname = _unique_archive_name(export, used_names)
-
-            with (
-                archive.open(arcname, mode="w", force_zip64=True) as entry,
-                source.open("rb") as src,
-            ):
-                while True:
-                    chunk = src.read(_ZIP_STREAM_CHUNK_SIZE)
-                    if not chunk:
-                        break
-
-                    entry.write(chunk)
-                    yield from buffer.drain()
-
-            yield from buffer.drain()
-
-    yield from buffer.drain()
-
-
-@router.get(
-    "/cases/{case_id}/download",
-    dependencies=[Depends(allow_any_authenticated())],
-    summary="Download export case as zip",
-    description="Streams a zip archive containing every completed export's mp4 for the given case.",
-)
-def download_export_case(
-    case_id: str,
-    allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
-):
-    try:
-        case = ExportCase.get(ExportCase.id == case_id)
-    except DoesNotExist:
-        return JSONResponse(
-            content={"success": False, "message": "Export case not found"},
-            status_code=404,
-        )
-
-    exports = list(
-        Export.select()
-        .where(
-            Export.export_case == case_id,
-            ~Export.in_progress,
-            Export.camera << allowed_cameras,
-        )
-        .order_by(Export.date.asc())
-    )
-
-    if not exports:
-        return JSONResponse(
-            content={"success": False, "message": "No exports available to download."},
-            status_code=404,
-        )
-
-    archive_base = sanitize_filename(case.name) if case.name else ""
-    if not archive_base:
-        archive_base = case_id
-
-    return StreamingResponse(
-        _stream_case_archive(exports),
-        media_type="application/zip",
-        headers={
-            "Content-Disposition": f'attachment; filename="{archive_base}.zip"',
-        },
-    )
-
-
@router.patch(
    "/cases/{case_id}",
    response_model=GenericResponse,
@@ -174,10 +174,12 @@ async def latest_frame(
    }
    quality_params = get_image_quality_params(extension.value, params.quality)

-    camera_config = request.app.frigate_config.cameras.get(camera_name)
-    if camera_config is not None:
+    if camera_name in request.app.frigate_config.cameras:
        frame = frame_processor.get_current_frame(camera_name, draw_options)
-        retry_interval = float(camera_config.ffmpeg.retry_interval or 10)
+        retry_interval = float(
+            request.app.frigate_config.cameras.get(camera_name).ffmpeg.retry_interval
+            or 10
+        )

        is_offline = False
        if frame is None or datetime.now().timestamp() > (
@@ -1366,17 +1368,12 @@ def preview_gif(
        file_start = f"preview_{camera_name}-"
        start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
        end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
-
-        camera_files = [
-            entry.name
-            for entry in os.scandir(preview_dir)
-            if entry.name.startswith(file_start)
-        ]
-        camera_files.sort()
-
        selected_previews = []

-        for file in camera_files:
+        for file in sorted(os.listdir(preview_dir)):
+            if not file.startswith(file_start):
+                continue
+
            if file < start_file:
                continue

@@ -1553,17 +1550,12 @@ def preview_mp4(
        file_start = f"preview_{camera_name}-"
        start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
        end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
-
-        camera_files = [
-            entry.name
-            for entry in os.scandir(preview_dir)
-            if entry.name.startswith(file_start)
-        ]
-        camera_files.sort()
-
        selected_previews = []

-        for file in camera_files:
+        for file in sorted(os.listdir(preview_dir)):
+            if not file.startswith(file_start):
+                continue
+
            if file < start_file:
                continue

@@ -148,17 +148,12 @@ def get_preview_frames_from_cache(camera_name: str, start_ts: float, end_ts: flo
    file_start = f"preview_{camera_name}-"
    start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
    end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
-
-    camera_files = [
-        entry.name
-        for entry in os.scandir(preview_dir)
-        if entry.name.startswith(file_start)
-    ]
-    camera_files.sort()
-
    selected_previews = []

-    for file in camera_files:
+    for file in sorted(os.listdir(preview_dir)):
+        if not file.startswith(file_start):
+            continue
+
        if file < start_file:
            continue

@@ -35,7 +35,7 @@ logger = logging.getLogger(__name__)
 router = APIRouter(tags=[Tags.recordings])


-@router.get("/recordings/storage", dependencies=[Depends(require_role(["admin"]))])
+@router.get("/recordings/storage", dependencies=[Depends(allow_any_authenticated())])
 def get_recordings_storage_usage(request: Request):
    recording_stats = request.app.stats_emitter.get_latest_stats()["service"][
        "storage"
@@ -189,6 +189,17 @@ class FrigateApp:
            except PermissionError:
                logger.error("Unable to write to /config to save DB state")

+        def cleanup_timeline_db(db: SqliteExtDatabase) -> None:
+            db.execute_sql(
+                "DELETE FROM timeline WHERE source_id NOT IN (SELECT id FROM event);"
+            )
+
+            try:
+                with open(f"{CONFIG_DIR}/.timeline", "w") as f:
+                    f.write(str(datetime.datetime.now().timestamp()))
+            except PermissionError:
+                logger.error("Unable to write to /config to save DB state")
+
        # Migrate DB schema
        migrate_db = SqliteExtDatabase(self.config.database.path)

@@ -205,6 +216,11 @@ class FrigateApp:

        router.run()

+        # this is a temporary check to clean up user DB from beta
+        # will be removed before final release
+        if not os.path.exists(f"{CONFIG_DIR}/.timeline"):
+            cleanup_timeline_db(migrate_db)
+
        # check if vacuum needs to be run
        if os.path.exists(f"{CONFIG_DIR}/.vacuum"):
            with open(f"{CONFIG_DIR}/.vacuum") as f:
@@ -429,10 +429,7 @@ class WebPushClient(Communicator):
            else:
                title = base_title

-            if payload["after"]["data"]["metadata"].get("shortSummary"):
-                message = payload["after"]["data"]["metadata"]["shortSummary"]
-            else:
-                message = f"Detected on {camera_name}"
+            message = payload["after"]["data"]["metadata"]["shortSummary"]
        else:
            zone_names = payload["after"]["data"]["zones"]
            formatted_zone_names = []
@@ -552,14 +549,6 @@ class WebPushClient(Communicator):
        logger.debug(f"Sending camera monitoring push notification for {camera_name}")

        for user in self.web_pushers:
-            if not self._user_has_camera_access(user, camera):
-                logger.debug(
-                    "Skipping notification for user %s - no access to camera %s",
-                    user,
-                    camera,
-                )
-                continue
-
            self.send_push_notification(
                user=user,
                payload=payload,
@@ -17,90 +17,9 @@ from ws4py.websocket import WebSocket as WebSocket_

 from frigate.comms.base_communicator import Communicator
 from frigate.config import FrigateConfig
-from frigate.const import (
-    CLEAR_ONGOING_REVIEW_SEGMENTS,
-    EXPIRE_AUDIO_ACTIVITY,
-    INSERT_MANY_RECORDINGS,
-    INSERT_PREVIEW,
-    NOTIFICATION_TEST,
-    REQUEST_REGION_GRID,
-    UPDATE_AUDIO_ACTIVITY,
-    UPDATE_AUDIO_TRANSCRIPTION_STATE,
-    UPDATE_BIRDSEYE_LAYOUT,
-    UPDATE_CAMERA_ACTIVITY,
-    UPDATE_EMBEDDINGS_REINDEX_PROGRESS,
-    UPDATE_EVENT_DESCRIPTION,
-    UPDATE_MODEL_STATE,
-    UPDATE_REVIEW_DESCRIPTION,
-    UPSERT_REVIEW_SEGMENT,
-)

 logger = logging.getLogger(__name__)

-# Internal IPC topics — NEVER allowed from WebSocket, regardless of role
-_WS_BLOCKED_TOPICS = frozenset(
-    {
-        INSERT_MANY_RECORDINGS,
-        INSERT_PREVIEW,
-        REQUEST_REGION_GRID,
-        UPSERT_REVIEW_SEGMENT,
-        CLEAR_ONGOING_REVIEW_SEGMENTS,
-        UPDATE_CAMERA_ACTIVITY,
-        UPDATE_AUDIO_ACTIVITY,
-        EXPIRE_AUDIO_ACTIVITY,
-        UPDATE_EVENT_DESCRIPTION,
-        UPDATE_REVIEW_DESCRIPTION,
-        UPDATE_MODEL_STATE,
-        UPDATE_EMBEDDINGS_REINDEX_PROGRESS,
-        UPDATE_BIRDSEYE_LAYOUT,
-        UPDATE_AUDIO_TRANSCRIPTION_STATE,
-        NOTIFICATION_TEST,
-    }
-)
-
-# Read-only topics any authenticated user (including viewer) can send
-_WS_VIEWER_TOPICS = frozenset(
-    {
-        "onConnect",
-        "modelState",
-        "audioTranscriptionState",
-        "birdseyeLayout",
-        "embeddingsReindexProgress",
-    }
-)
-
-
-def _check_ws_authorization(
-    topic: str,
-    role_header: str | None,
-    separator: str,
-) -> bool:
-    """Check if a WebSocket message is authorized.
-
-    Args:
-        topic: The message topic.
-        role_header: The HTTP_REMOTE_ROLE header value, or None.
-        separator: The role separator character from proxy config.
-
-    Returns:
-        True if authorized, False if blocked.
-    """
-    # Block IPC-only topics unconditionally
-    if topic in _WS_BLOCKED_TOPICS:
-        return False
-
-    # No role header: default to viewer (fail-closed)
-    if role_header is None:
-        return topic in _WS_VIEWER_TOPICS
-
-    # Check if any role is admin
-    roles = [r.strip() for r in role_header.split(separator)]
-    if "admin" in roles:
-        return True
-
-    # Non-admin: only viewer topics allowed
-    return topic in _WS_VIEWER_TOPICS
-

 class WebSocket(WebSocket_):  # type: ignore[misc]
    def unhandled_error(self, error: Any) -> None:
@@ -130,7 +49,6 @@ class WebSocketClient(Communicator):

        class _WebSocketHandler(WebSocket):
            receiver = self._dispatcher
-            role_separator = self.config.proxy.separator or ","

            def received_message(self, message: WebSocket.received_message) -> None:  # type: ignore[name-defined]
                try:
@@ -145,25 +63,11 @@ class WebSocketClient(Communicator):
                    )
                    return

-                topic = json_message["topic"]
-
-                # Authorization check (skip when environ is None — direct internal connection)
-                role_header = (
-                    self.environ.get("HTTP_REMOTE_ROLE") if self.environ else None
+                logger.debug(
+                    f"Publishing mqtt message from websockets at {json_message['topic']}."
                )
-                if self.environ is not None and not _check_ws_authorization(
-                    topic, role_header, self.role_separator
-                ):
-                    logger.warning(
-                        "Blocked unauthorized WebSocket message: topic=%s, role=%s",
-                        topic,
-                        role_header,
-                    )
-                    return
-
-                logger.debug(f"Publishing mqtt message from websockets at {topic}.")
                self.receiver(
-                    topic,
+                    json_message["topic"],
                    json_message["payload"],
                )

@@ -76,7 +76,7 @@ class CameraConfig(FrigateBaseModel):
    # Options with global fallback
    audio: AudioConfig = Field(
        default_factory=AudioConfig,
-        title="Audio detection",
+        title="Audio events",
        description="Settings for audio-based event detection for this camera.",
    )
    audio_transcription: CameraAudioTranscriptionConfig = Field(
@@ -41,7 +41,8 @@ class GenAIConfig(FrigateBaseModel):
        title="Model",
        description="The model to use from the provider for generating descriptions or summaries.",
    )
-    provider: GenAIProviderEnum = Field(
+    provider: GenAIProviderEnum | None = Field(
+        default=None,
        title="Provider",
        description="The GenAI provider to use (for example: ollama, gemini, openai).",
    )
@@ -20,7 +20,6 @@ class CameraConfigUpdateEnum(str, Enum):
    ffmpeg = "ffmpeg"
    live = "live"
    motion = "motion"  # includes motion and motion masks
-    mqtt = "mqtt"
    notifications = "notifications"
    objects = "objects"
    object_genai = "object_genai"
@@ -34,7 +33,6 @@ class CameraConfigUpdateEnum(str, Enum):
    lpr = "lpr"
    snapshots = "snapshots"
    timestamp_style = "timestamp_style"
-    ui = "ui"
    zones = "zones"


@@ -121,10 +119,7 @@ class CameraConfigUpdateSubscriber:
        elif update_type == CameraConfigUpdateEnum.objects:
            config.objects = updated_config
        elif update_type == CameraConfigUpdateEnum.record:
-            old_enabled_in_config = config.record.enabled_in_config
            config.record = updated_config
-            if old_enabled_in_config != updated_config.enabled_in_config:
-                config.recreate_ffmpeg_cmds()
        elif update_type == CameraConfigUpdateEnum.review:
            config.review = updated_config
        elif update_type == CameraConfigUpdateEnum.review_genai:
@@ -26,11 +26,6 @@ class EnrichmentsDeviceEnum(str, Enum):
    CPU = "CPU"


-class ModelSizeEnum(str, Enum):
-    small = "small"
-    large = "large"
-
-
 class TriggerType(str, Enum):
    THUMBNAIL = "thumbnail"
    DESCRIPTION = "description"
@@ -58,13 +53,13 @@ class AudioTranscriptionConfig(FrigateBaseModel):
        title="Transcription language",
        description="Language code used for transcription/translation (for example 'en' for English). See https://whisper-api.com/docs/languages/ for supported language codes.",
    )
-    device: EnrichmentsDeviceEnum = Field(
+    device: Optional[EnrichmentsDeviceEnum] = Field(
        default=EnrichmentsDeviceEnum.CPU,
        title="Transcription device",
        description="Device key (CPU/GPU) to run the transcription model on. Only NVIDIA CUDA GPUs are currently supported for transcription.",
    )
-    model_size: ModelSizeEnum = Field(
-        default=ModelSizeEnum.small,
+    model_size: str = Field(
+        default="small",
        title="Model size",
        description="Model size to use for offline audio event transcription.",
    )
@@ -194,8 +189,8 @@ class SemanticSearchConfig(FrigateBaseModel):
                return v
        return v

-    model_size: ModelSizeEnum = Field(
-        default=ModelSizeEnum.small,
+    model_size: str = Field(
+        default="small",
        title="Model size",
        description="Select model size; 'small' runs on CPU and 'large' typically requires GPU.",
    )
@@ -258,8 +253,8 @@ class FaceRecognitionConfig(FrigateBaseModel):
        title="Enable face recognition",
        description="Enable or disable face recognition for all cameras; can be overridden per-camera.",
    )
-    model_size: ModelSizeEnum = Field(
-        default=ModelSizeEnum.small,
+    model_size: str = Field(
+        default="small",
        title="Model size",
        description="Model size to use for face embeddings (small/large); larger may require GPU.",
    )
@@ -340,8 +335,8 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
        title="Enable LPR",
        description="Enable or disable license plate recognition for all cameras; can be overridden per-camera.",
    )
-    model_size: ModelSizeEnum = Field(
-        default=ModelSizeEnum.small,
+    model_size: str = Field(
+        default="small",
        title="Model size",
        description="Model size used for text detection/recognition. Most users should use 'small'.",
    )
@@ -1,6 +1,5 @@
 from __future__ import annotations

-import io
 import json
 import logging
 import os
@@ -81,40 +80,17 @@ logger = logging.getLogger(__name__)

 yaml = YAML()

-DEFAULT_DETECTORS = {
-    "ov": {
-        "type": "openvino",
-        "device": "CPU",
-    }
-}
-DEFAULT_MODEL = {
-    "width": 300,
-    "height": 300,
-    "input_tensor": "nhwc",
-    "input_pixel_format": "bgr",
-    "path": "/openvino-model/ssdlite_mobilenet_v2.xml",
-    "labelmap_path": "/openvino-model/coco_91cl_bkgr.txt",
-}
-DEFAULT_DETECT_DIMENSIONS = {"width": 1280, "height": 720}
-
-
-def _render_default_yaml(data: dict) -> str:
-    buf = io.StringIO()
-    _yaml_writer = YAML()
-    _yaml_writer.indent(mapping=2, sequence=4, offset=2)
-    _yaml_writer.dump(data, buf)
-    return buf.getvalue()
-
-
 DEFAULT_CONFIG = f"""
 mqtt:
  enabled: False

-{_render_default_yaml({"detectors": DEFAULT_DETECTORS, "model": DEFAULT_MODEL})}
 cameras: {{}}  # No cameras defined, UI wizard should be used
 version: {CURRENT_CONFIG_VERSION}
 """

+DEFAULT_DETECTORS = {"cpu": {"type": "cpu"}}
+DEFAULT_DETECT_DIMENSIONS = {"width": 1280, "height": 720}
+
 # stream info handler
 stream_info_retriever = StreamInfoRetriever()

@@ -477,7 +453,7 @@ class FrigateConfig(FrigateBaseModel):
    cameras: Dict[str, CameraConfig] = Field(title="Cameras", description="Cameras")
    audio: AudioConfig = Field(
        default_factory=AudioConfig,
-        title="Audio detection",
+        title="Audio events",
        description="Settings for audio-based event detection for all cameras; can be overridden per-camera.",
    )
    birdseye: BirdseyeConfig = Field(
@@ -703,9 +679,6 @@ class FrigateConfig(FrigateBaseModel):
                    model_config["path"] = "/cpu_model.tflite"
                elif detector_config.type == "edgetpu":
                    model_config["path"] = "/edgetpu_model.tflite"
-                elif detector_config.type == "openvino":
-                    for default_key, default_value in DEFAULT_MODEL.items():
-                        model_config.setdefault(default_key, default_value)

            model = ModelConfig.model_validate(model_config)
            model.check_and_load_plus_model(self.plus_api, detector_config.type)
@@ -25,8 +25,8 @@ class StatsConfig(FrigateBaseModel):
    )
    intel_gpu_device: Optional[str] = Field(
        default=None,
-        title="Intel GPU device",
-        description="PCI bus address or DRM device path (e.g. /dev/dri/card1) used to pin Intel GPU stats to a specific device when multiple are present.",
+        title="SR-IOV device",
+        description="Device identifier used when treating Intel GPUs as SR-IOV to fix GPU stats.",
    )


@@ -15,7 +15,7 @@ TRIGGER_DIR = f"{CLIPS_DIR}/triggers"
 BIRDSEYE_PIPE = "/tmp/cache/birdseye"
 CACHE_DIR = "/tmp/cache"
 REPLAY_CAMERA_PREFIX = "_replay_"
-REPLAY_DIR = os.path.join(CLIPS_DIR, "replay")
+REPLAY_DIR = os.path.join(CACHE_DIR, "replay")
 PLUS_ENV_VAR = "PLUS_API_KEY"
 PLUS_API_HOST = "https://api.frigate.video"

@@ -133,61 +133,6 @@ class FaceRecognizer(ABC):
            return 0.0


-def build_class_mean(
-    embs: list[np.ndarray],
-    trim: float = 0.15,
-    outlier_threshold: float = 0.30,
-    min_keep_frac: float = 0.7,
-    max_iters: int = 3,
-) -> np.ndarray:
-    """Build a class-mean embedding with two-layer outlier protection.
-
-    Layer 1 (iterative, vector-wise): drop whole embeddings whose cosine
-    similarity to the current class mean is below ``outlier_threshold``.
-    Catches mislabeled or corrupted training samples (wrong face in the
-    folder, full-frame screenshots, extreme crops) that per-dimension
-    trimming cannot detect.
-
-    Layer 2 (per-dimension): ``scipy.stats.trim_mean`` on the retained set
-    to smooth per-component noise (lighting, expression, alignment jitter).
-
-    Collections with fewer than 5 images bypass outlier rejection — too few
-    samples to establish a reliable class center.
-    """
-    arr = np.stack(embs, axis=0)
-
-    if len(arr) < 5:
-        return np.asarray(stats.trim_mean(arr, trim, axis=0))
-
-    keep = np.ones(len(arr), dtype=bool)
-    floor = max(5, int(np.ceil(min_keep_frac * len(arr))))
-
-    for _ in range(max_iters):
-        mean = stats.trim_mean(arr[keep], trim, axis=0)
-        m_norm = mean / (np.linalg.norm(mean) + 1e-9)
-        e_norms = arr / (np.linalg.norm(arr, axis=1, keepdims=True) + 1e-9)
-        cos = e_norms @ m_norm
-        new_keep = cos >= outlier_threshold
-
-        if new_keep.sum() < floor:
-            top = np.argsort(-cos)[:floor]
-            new_keep = np.zeros(len(arr), dtype=bool)
-            new_keep[top] = True
-
-        if np.array_equal(new_keep, keep):
-            break
-        keep = new_keep
-
-    dropped = int((~keep).sum())
-
-    if dropped:
-        logger.debug(
-            f"Vector-wise outlier filter dropped {dropped}/{len(arr)} embeddings"
-        )
-
-    return np.asarray(stats.trim_mean(arr[keep], trim, axis=0))
-
-
 def similarity_to_confidence(
    cosine_similarity: float,
    median: float = 0.3,
@@ -284,7 +229,7 @@ class FaceNetRecognizer(FaceRecognizer):

        for name, embs in face_embeddings_map.items():
            if embs:
-                self.mean_embs[name] = build_class_mean(embs)
+                self.mean_embs[name] = stats.trim_mean(embs, 0.15)

        logger.debug("Finished building ArcFace model")

@@ -395,7 +340,7 @@ class ArcFaceRecognizer(FaceRecognizer):

        for name, embs in face_embeddings_map.items():
            if embs:
-                self.mean_embs[name] = build_class_mean(embs)
+                self.mean_embs[name] = stats.trim_mean(embs, 0.15)

        logger.debug("Finished building ArcFace model")

@@ -1073,6 +1073,10 @@ class LicensePlateProcessingMixin:
                    top_score = score
                    top_box = bbox

+                if score > top_score:
+                    top_score = score
+                    top_box = bbox
+
        # Return the top scoring bounding box if found
        if top_box is not None:
            # expand box by 5% to help with OCR
@@ -1088,6 +1092,9 @@ class LicensePlateProcessingMixin:
                ]
            ).clip(0, [input.shape[1], input.shape[0]] * 2)

+            logger.debug(
+                f"{camera}: Found license plate. Bounding box: {expanded_box.astype(int)}"
+            )
            return tuple(int(x) for x in expanded_box)  # type: ignore[return-value]
        else:
            return None  # No detection above the threshold
@@ -1353,8 +1360,8 @@ class LicensePlateProcessingMixin:
                )

                # check that license plate is valid
-                # quadruple the value because we've doubled both dimensions of the car
-                if license_plate_area < self.config.cameras[camera].lpr.min_area * 4:
+                # double the value because we've doubled the size of the car
+                if license_plate_area < self.config.cameras[camera].lpr.min_area * 2:
                    logger.debug(f"{camera}: License plate is less than min_area")
                    return

@@ -1458,7 +1465,6 @@ class LicensePlateProcessingMixin:
                    license_plate_frame,
                )

-        logger.debug(f"{camera}: Found license plate. Bounding box: {list(plate_box)}")
        logger.debug(f"{camera}: Running plate recognition for id: {id}.")

        # run detection, returns results sorted by confidence, best first
@@ -39,8 +39,6 @@ logger = logging.getLogger(__name__)

 RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
 MIN_RECORDING_DURATION = 10
-MAX_IMAGE_TOKENS = 24000
-MAX_FRAMES_PER_SECOND = 1


 class ReviewDescriptionProcessor(PostProcessorApi):
@@ -62,22 +60,14 @@ class ReviewDescriptionProcessor(PostProcessorApi):
    def calculate_frame_count(
        self,
        camera: str,
-        duration: float,
        image_source: ImageSourceEnum = ImageSourceEnum.preview,
        height: int = 480,
    ) -> int:
-        """Calculate optimal number of frames based on event duration, context size,
-        image source, and resolution.
+        """Calculate optimal number of frames based on context size, image source, and resolution.

-        Per-image token cost is asked of the GenAI provider so providers that know
-        their model's true cost (e.g. llama.cpp can probe the loaded mmproj) can
-        diverge from the default ~1-token-per-1250-pixels heuristic. The frame
-        budget is bounded by:
-          - remaining context window after prompt + response reservations
-          - a fixed MAX_IMAGE_TOKENS ceiling
-          - MAX_FRAMES_PER_SECOND x duration, to avoid drowning short events in
-            near-duplicate frames where the model latches onto the redundant middle
-            and skips the start/end action
+        Token usage varies by resolution: larger images (ultra-wide aspect ratios) use more tokens.
+        Estimates ~1 token per 1250 pixels. Targets 98% context utilization with safety margin.
+        Capped at 20 frames.
        """
        client = self.genai_manager.description_client

@@ -115,15 +105,14 @@ class ReviewDescriptionProcessor(PostProcessorApi):
                width = target_width
                height = int(target_width / aspect_ratio)

-        tokens_per_image = client.estimate_image_tokens(width, height)
+        pixels_per_image = width * height
+        tokens_per_image = pixels_per_image / 1250
        prompt_tokens = 3800
        response_tokens = 300
-        context_budget = context_size - prompt_tokens - response_tokens
-        image_token_budget = min(context_budget, MAX_IMAGE_TOKENS)
-        max_frames_by_tokens = int(image_token_budget / tokens_per_image)
-        max_frames_by_duration = int(duration * MAX_FRAMES_PER_SECOND)
-        max_frames = min(max_frames_by_tokens, max_frames_by_duration)
-        return max(max_frames, 3)
+        available_tokens = context_size - prompt_tokens - response_tokens
+        max_frames = int(available_tokens / tokens_per_image)
+
+        return min(max(max_frames, 3), 20)

    def process_data(
        self, data: dict[str, Any], data_type: PostProcessDataEnum
@@ -366,17 +355,12 @@ class ReviewDescriptionProcessor(PostProcessorApi):
        file_start = f"preview_{camera}-"
        start_file = f"{file_start}{start_time}.webp"
        end_file = f"{file_start}{end_time}.webp"
-
-        camera_files = [
-            entry.name
-            for entry in os.scandir(preview_dir)
-            if entry.name.startswith(file_start)
-        ]
-        camera_files.sort()
-
        all_frames: list[str] = []

-        for file in camera_files:
+        for file in sorted(os.listdir(preview_dir)):
+            if not file.startswith(file_start):
+                continue
+
            if file < start_file:
                if len(all_frames):
                    all_frames[0] = os.path.join(preview_dir, file)
@@ -392,9 +376,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
            all_frames.append(os.path.join(preview_dir, file))

        frame_count = len(all_frames)
-        desired_frame_count = self.calculate_frame_count(
-            camera, duration=end_time - start_time
-        )
+        desired_frame_count = self.calculate_frame_count(camera)

        if frame_count <= desired_frame_count:
            return all_frames
@@ -418,7 +400,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
        """Get frames from recordings at specified timestamps."""
        duration = end_time - start_time
        desired_frame_count = self.calculate_frame_count(
-            camera, duration, ImageSourceEnum.recordings, height
+            camera, ImageSourceEnum.recordings, height
        )

        # Calculate evenly spaced timestamps throughout the duration
@@ -1,48 +1,21 @@
-from typing import Annotated
-
-from pydantic import BaseModel, ConfigDict, Field, StringConstraints
-
-ObservationItem = Annotated[str, StringConstraints(min_length=20, max_length=160)]
+from pydantic import BaseModel, ConfigDict, Field


 class ReviewMetadata(BaseModel):
    model_config = ConfigDict(extra="ignore", protected_namespaces=())

-    observations: list[ObservationItem] = Field(
-        ...,
-        min_length=3,
-        max_length=15,
-        description=(
-            "Enumerate the significant observations across all frames, in "
-            "chronological order, BEFORE composing the scene narrative. "
-            "Include the very start of the activity — for example, a vehicle "
-            "entering the frame or pulling into the driveway — even if it "
-            "lasts only a few frames and the rest of the clip is dominated "
-            "by a longer activity. Include each arrival, departure, motion "
-            "event, object handled, and notable change in position or state. "
-            "Each item is a single concrete fact written as a complete "
-            "sentence. Do not summarize, interpret, or assign meaning here — "
-            "that belongs in the scene field."
-        ),
-    )
    title: str = Field(
-        max_length=80,
-        description="Under 10 words. Name the apparent purpose or outcome of the activity together with the location involved. Do not narrate or list the sequence of actions step by step.",
+        description="A short title characterizing what took place and where, under 10 words."
    )
    scene: str = Field(
-        min_length=150,
-        max_length=600,
-        description="A chronological narrative of what happens from start to finish, drawing directly from the items in observations.",
+        description="A chronological narrative of what happens from start to finish."
    )
    shortSummary: str = Field(
-        min_length=70,
-        max_length=120,
-        description="A brief 2-sentence summary of the scene, suitable for notifications.",
+        description="A brief 2-sentence summary of the scene, suitable for notifications."
    )
    confidence: float = Field(
        ge=0.0,
-        le=1.0,
-        description="Confidence in the analysis as a decimal between 0.0 and 1.0, where 0.0 means no confidence and 1.0 means complete confidence. Express ONLY as a decimal.",
+        description="Confidence in the analysis, from 0 to 1.",
    )
    potential_threat_level: int = Field(
        ge=0,
@@ -229,10 +229,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
                logger.debug(f"No person box available for {id}")
                return

-            # YuNet (cv2.FaceDetectorYN) is trained on BGR
-            bgr = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
+            rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
            left, top, right, bottom = person_box
-            person = bgr[top:bottom, left:right]
+            person = rgb[top:bottom, left:right]
            face_box = self.__detect_face(person, self.face_config.detection_threshold)

            if not face_box:
@@ -251,6 +250,11 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
                )
                return

+            try:
+                face_frame = cv2.cvtColor(face_frame, cv2.COLOR_RGB2BGR)
+            except Exception as e:
+                logger.debug(f"Failed to convert face frame color for {id}: {e}")
+                return
        else:
            # don't run for object without attributes
            if not obj_data.get("current_attributes"):
@@ -1,13 +1,9 @@
-"""Debug replay camera management for replaying recordings with detection overlays.
-
-The startup work (ffmpeg concat + camera config publish) lives in
-frigate.jobs.debug_replay. This module owns only session presence
-(active), session metadata, and post-session cleanup.
-"""
+"""Debug replay camera management for replaying recordings with detection overlays."""

 import logging
 import os
 import shutil
+import subprocess as sp
 import threading

 from ruamel.yaml import YAML
@@ -25,7 +21,7 @@ from frigate.const import (
    REPLAY_DIR,
    THUMB_DIR,
 )
-from frigate.jobs.debug_replay import cancel_debug_replay_job, wait_for_runner
+from frigate.models import Recordings
 from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
 from frigate.util.config import find_config_file

@@ -33,14 +29,7 @@ logger = logging.getLogger(__name__)


 class DebugReplayManager:
-    """Owns the lifecycle pointers for a single debug replay session.
-
-    A session exists from the moment mark_starting is called (synchronously,
-    inside the API handler) until clear_session runs (on success cleanup,
-    failure, or stop). The active property is the source of truth that the
-    status bar consumes — broader than the startup job, which only covers the
-    preparing_clip / starting_camera window.
-    """
+    """Manages a single debug replay session."""

    def __init__(self) -> None:
        self._lock = threading.Lock()
@@ -52,66 +41,144 @@ class DebugReplayManager:

    @property
    def active(self) -> bool:
-        """True from mark_starting until clear_session."""
+        """Whether a replay session is currently active."""
        return self.replay_camera_name is not None

-    def mark_starting(
+    def start(
        self,
        source_camera: str,
-        replay_camera_name: str,
        start_ts: float,
        end_ts: float,
-    ) -> None:
-        """Synchronously claim the session before the job runner starts.
-
-        Called inside the API handler so the status bar sees active=True
-        immediately, before the worker thread does any ffmpeg work.
-        """
-        with self._lock:
-            self.replay_camera_name = replay_camera_name
-            self.source_camera = source_camera
-            self.start_ts = start_ts
-            self.end_ts = end_ts
-            self.clip_path = None
-
-    def mark_session_ready(self, clip_path: str) -> None:
-        """Record the on-disk clip path after the camera has been published."""
-        with self._lock:
-            self.clip_path = clip_path
-
-    def clear_session(self) -> None:
-        """Reset session pointers without publishing camera removal.
-
-        Used by the job runner on failure paths. stop() does the camera
-        teardown plus this clear in one step.
-        """
-        with self._lock:
-            self._clear_locked()
-
-    def _clear_locked(self) -> None:
-        self.replay_camera_name = None
-        self.source_camera = None
-        self.clip_path = None
-        self.start_ts = None
-        self.end_ts = None
-
-    def publish_camera(
-        self,
-        source_camera: str,
-        replay_name: str,
-        clip_path: str,
        frigate_config: FrigateConfig,
        config_publisher: CameraConfigUpdatePublisher,
-    ) -> None:
-        """Build the in-memory replay camera config and publish the add event.
+    ) -> str:
+        """Start a debug replay session.

-        Called by the job runner during the starting_camera phase.
+        Args:
+            source_camera: Name of the source camera to replay
+            start_ts: Start timestamp
+            end_ts: End timestamp
+            frigate_config: Current Frigate configuration
+            config_publisher: Publisher for camera config updates
+
+        Returns:
+            The replay camera name
+
+        Raises:
+            ValueError: If a session is already active or parameters are invalid
+            RuntimeError: If clip generation fails
        """
+        with self._lock:
+            return self._start_locked(
+                source_camera, start_ts, end_ts, frigate_config, config_publisher
+            )
+
+    def _start_locked(
+        self,
+        source_camera: str,
+        start_ts: float,
+        end_ts: float,
+        frigate_config: FrigateConfig,
+        config_publisher: CameraConfigUpdatePublisher,
+    ) -> str:
+        if self.active:
+            raise ValueError("A replay session is already active")
+
+        if source_camera not in frigate_config.cameras:
+            raise ValueError(f"Camera '{source_camera}' not found")
+
+        if end_ts <= start_ts:
+            raise ValueError("End time must be after start time")
+
+        # Query recordings for the source camera in the time range
+        recordings = (
+            Recordings.select(
+                Recordings.path,
+                Recordings.start_time,
+                Recordings.end_time,
+            )
+            .where(
+                Recordings.start_time.between(start_ts, end_ts)
+                | Recordings.end_time.between(start_ts, end_ts)
+                | ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
+            )
+            .where(Recordings.camera == source_camera)
+            .order_by(Recordings.start_time.asc())
+        )
+
+        if not recordings.count():
+            raise ValueError(
+                f"No recordings found for camera '{source_camera}' in the specified time range"
+            )
+
+        # Create replay directory
+        os.makedirs(REPLAY_DIR, exist_ok=True)
+
+        # Generate replay camera name
+        replay_name = f"{REPLAY_CAMERA_PREFIX}{source_camera}"
+
+        # Build concat file for ffmpeg
+        concat_file = os.path.join(REPLAY_DIR, f"{replay_name}_concat.txt")
+        clip_path = os.path.join(REPLAY_DIR, f"{replay_name}.mp4")
+
+        with open(concat_file, "w") as f:
+            for recording in recordings:
+                f.write(f"file '{recording.path}'\n")
+
+        # Concatenate recordings into a single clip with -c copy (fast)
+        ffmpeg_cmd = [
+            frigate_config.ffmpeg.ffmpeg_path,
+            "-hide_banner",
+            "-y",
+            "-f",
+            "concat",
+            "-safe",
+            "0",
+            "-i",
+            concat_file,
+            "-c",
+            "copy",
+            "-movflags",
+            "+faststart",
+            clip_path,
+        ]
+
+        logger.info(
+            "Generating replay clip for %s (%.1f - %.1f)",
+            source_camera,
+            start_ts,
+            end_ts,
+        )
+
+        try:
+            result = sp.run(
+                ffmpeg_cmd,
+                capture_output=True,
+                text=True,
+                timeout=120,
+            )
+            if result.returncode != 0:
+                logger.error("FFmpeg error: %s", result.stderr)
+                raise RuntimeError(
+                    f"Failed to generate replay clip: {result.stderr[-500:]}"
+                )
+        except sp.TimeoutExpired:
+            raise RuntimeError("Clip generation timed out")
+        finally:
+            # Clean up concat file
+            if os.path.exists(concat_file):
+                os.remove(concat_file)
+
+        if not os.path.exists(clip_path):
+            raise RuntimeError("Clip file was not created")
+
+        # Build camera config dict for the replay camera
        source_config = frigate_config.cameras[source_camera]
        camera_dict = self._build_camera_config_dict(
            source_config, replay_name, clip_path
        )

+        # Build an in-memory config with the replay camera added
        config_file = find_config_file()
        yaml_parser = YAML()
        with open(config_file, "r") as f:
@@ -124,48 +191,75 @@ class DebugReplayManager:
        try:
            new_config = FrigateConfig.parse_object(config_data)
        except Exception as e:
-            raise RuntimeError(f"Failed to validate replay camera config: {e}") from e
+            raise RuntimeError(f"Failed to validate replay camera config: {e}")
+
+        # Update the running config
        frigate_config.cameras[replay_name] = new_config.cameras[replay_name]

+        # Publish the add event
        config_publisher.publish_update(
            CameraConfigUpdateTopic(CameraConfigUpdateEnum.add, replay_name),
            new_config.cameras[replay_name],
        )

+        # Store session state
+        self.replay_camera_name = replay_name
+        self.source_camera = source_camera
+        self.clip_path = clip_path
+        self.start_ts = start_ts
+        self.end_ts = end_ts
+
+        logger.info("Debug replay started: %s -> %s", source_camera, replay_name)
+        return replay_name
+
    def stop(
        self,
        frigate_config: FrigateConfig,
        config_publisher: CameraConfigUpdatePublisher,
    ) -> None:
-        """Cancel any in-flight startup job and tear down the active session.
+        """Stop the active replay session and clean up all artifacts.

-        Safe to call when no session is active (no-op with a warning).
+        Args:
+            frigate_config: Current Frigate configuration
+            config_publisher: Publisher for camera config updates
        """
-        cancel_debug_replay_job()
-        wait_for_runner(timeout=2.0)
-
        with self._lock:
-            if not self.active:
-                logger.warning("No active replay session to stop")
-                return
+            self._stop_locked(frigate_config, config_publisher)

-            replay_name = self.replay_camera_name
+    def _stop_locked(
+        self,
+        frigate_config: FrigateConfig,
+        config_publisher: CameraConfigUpdatePublisher,
+    ) -> None:
+        if not self.active:
+            logger.warning("No active replay session to stop")
+            return

-            # Only publish remove if the camera was actually added to the live
-            # config (i.e. the runner reached the starting_camera phase).
-            if replay_name is not None and replay_name in frigate_config.cameras:
-                config_publisher.publish_update(
-                    CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, replay_name),
-                    frigate_config.cameras[replay_name],
-                )
+        replay_name = self.replay_camera_name

-            if replay_name is not None:
-                self._cleanup_db(replay_name)
-                self._cleanup_files(replay_name)
+        # Publish remove event so subscribers stop and remove from their config
+        if replay_name in frigate_config.cameras:
+            config_publisher.publish_update(
+                CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, replay_name),
+                frigate_config.cameras[replay_name],
+            )
+            # Do NOT pop here — let subscribers handle removal from the shared
+            # config dict when they process the ZMQ message to avoid race conditions

-            self._clear_locked()
+        # Defensive DB cleanup
+        self._cleanup_db(replay_name)

-            logger.info("Debug replay stopped and cleaned up: %s", replay_name)
+        # Remove filesystem artifacts
+        self._cleanup_files(replay_name)
+
+        # Reset state
+        self.replay_camera_name = None
+        self.source_camera = None
+        self.clip_path = None
+        self.start_ts = None
+        self.end_ts = None
+
+        logger.info("Debug replay stopped and cleaned up: %s", replay_name)

    def _build_camera_config_dict(
        self,
@@ -173,7 +267,16 @@ class DebugReplayManager:
        replay_name: str,
        clip_path: str,
    ) -> dict:
-        """Build a camera config dictionary for the replay camera."""
+        """Build a camera config dictionary for the replay camera.
+
+        Args:
+            source_config: Source camera's CameraConfig
+            replay_name: Name for the replay camera
+            clip_path: Path to the replay clip file
+
+        Returns:
+            Camera config as a dictionary
+        """
        # Extract detect config (exclude computed fields)
        detect_dict = source_config.detect.model_dump(
            exclude={"min_initialized", "max_disappeared", "enabled_in_config"}
@@ -208,6 +311,7 @@ class DebugReplayManager:
            zone_dump = zone_config.model_dump(
                exclude={"contour", "color"}, exclude_defaults=True
            )
+            # Always include required fields
            zone_dump.setdefault("coordinates", zone_config.coordinates)
            zones_dict[zone_name] = zone_dump

@@ -132,6 +132,7 @@ class ONNXModelRunner(BaseModelRunner):
        return model_type in [
            EnrichmentModelTypeEnum.paddleocr.value,
            EnrichmentModelTypeEnum.jina_v2.value,
+            EnrichmentModelTypeEnum.arcface.value,
            ModelTypeEnum.rfdetr.value,
            ModelTypeEnum.dfine.value,
        ]
@@ -52,12 +52,6 @@ class OvDetector(DetectionApi):
        self.h = detector_config.model.height
        self.w = detector_config.model.width

-        logger.info(
-            "Loading OpenVINO model %s on device %s",
-            detector_config.model.path,
-            detector_config.device,
-        )
-
        self.runner = OpenVINOModelRunner(
            model_path=detector_config.model.path,
            device=detector_config.device,
@@ -4,7 +4,6 @@ import base64
 import json
 import logging
 import os
-import sys
 import threading
 from json.decoder import JSONDecodeError
 from multiprocessing.synchronize import Event as MpEvent
@@ -53,14 +52,6 @@ class EmbeddingProcess(FrigateProcess):
            self.stop_event,
        )
        maintainer.start()
-        maintainer.join()
-
-        # If the maintainer thread exited but no shutdown was requested, it
-        # crashed. Surface as a non-zero exit so the watchdog restarts us
-        # instead of treating the silent thread death as a clean shutdown.
-        if not self.stop_event.is_set():
-            logger.error("Embeddings maintainer thread exited unexpectedly")
-            sys.exit(1)


 class EmbeddingsContext:
@@ -310,10 +310,6 @@ class EmbeddingMaintainer(threading.Thread):
            self._handle_custom_classification_update(topic, payload)
            return

-        if topic == "config/genai":
-            self.config.genai = payload
-            self.genai_manager.update_config(self.config)
-
        # Broadcast to all processors — each decides if the topic is relevant
        for processor in self.realtime_processors:
            processor.update_config(topic, payload)
@@ -517,16 +513,10 @@ class EmbeddingMaintainer(threading.Thread):
                try:
                    event: Event = Event.get(Event.id == event_id)
                except DoesNotExist:
-                    for processor in self.post_processors:
-                        if isinstance(processor, ObjectDescriptionProcessor):
-                            processor.cleanup_event(event_id)
                    continue

                # Skip the event if not an object
                if event.data.get("type") != "object":
-                    for processor in self.post_processors:
-                        if isinstance(processor, ObjectDescriptionProcessor):
-                            processor.cleanup_event(event_id)
                    continue

                # Extract valid thumbnail
@@ -205,7 +205,6 @@ class AudioEventMaintainer(threading.Thread):
            self.transcription_thread.start()

        self.was_enabled = camera.enabled
-        self.was_audio_enabled = camera.audio.enabled

    def detect_audio(self, audio: np.ndarray) -> None:
        if not self.camera_config.audio.enabled or self.stop_event.is_set():
@@ -364,17 +363,6 @@ class AudioEventMaintainer(threading.Thread):
                time.sleep(0.1)
                continue

-            audio_enabled = self.camera_config.audio.enabled
-            if audio_enabled != self.was_audio_enabled:
-                if not audio_enabled:
-                    self.logger.debug(
-                        f"Disabling audio detections for {self.camera_config.name}, ending events"
-                    )
-                    self.requestor.send_data(
-                        EXPIRE_AUDIO_ACTIVITY, self.camera_config.name
-                    )
-                self.was_audio_enabled = audio_enabled
-
            self.read_audio()

        if self.audio_listener:
@@ -2,7 +2,6 @@

 import datetime
 import importlib
-import json
 import logging
 import os
 import re
@@ -10,7 +9,6 @@ from typing import Any, Callable, Optional

 import numpy as np
 from playhouse.shortcuts import model_to_dict
-from pydantic import ValidationError

 from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum
 from frigate.const import CLIPS_DIR
@@ -153,6 +151,9 @@ Each line represents a detection state, not necessarily unique individuals. The
            if "other_concerns" in schema.get("required", []):
                schema["required"].remove("other_concerns")

+        # OpenAI strict mode requires additionalProperties: false on all objects
+        schema["additionalProperties"] = False
+
        response_format = {
            "type": "json_schema",
            "json_schema": {
@@ -180,36 +181,7 @@ Each line represents a detection state, not necessarily unique individuals. The

            try:
                metadata = ReviewMetadata.model_validate_json(clean_json)
-            except ValidationError as ve:
-                # Constraint violations (length, item count, ranges) are logged
-                # at debug and the response is kept anyway — a slightly
-                # off-spec answer is still usable, and dropping the whole
-                # response loses the narrative content the model produced.
-                for err in ve.errors():
-                    loc = ".".join(str(p) for p in err["loc"]) or "<root>"
-                    logger.debug(
-                        "Review metadata soft validation: %s — %s (input: %r)",
-                        loc,
-                        err["msg"],
-                        err.get("input"),
-                    )
-                try:
-                    raw = json.loads(clean_json)
-                except json.JSONDecodeError as je:
-                    logger.error("Failed to parse review description JSON: %s", je)
-                    return None
-                # observations and confidence are required on the model; fill an empty default
-                # if the response omitted it so attribute access stays safe.
-                raw.setdefault("observations", [])
-                raw.setdefault("confidence", 0.0)
-                metadata = ReviewMetadata.model_construct(**raw)
-            except Exception as e:
-                logger.error(
-                    f"Failed to parse review description as the response did not match expected format. {e}"
-                )
-                return None

-            try:
                # Normalize confidence if model returned a percentage (e.g. 85 instead of 0.85)
                if metadata.confidence > 1.0:
                    metadata.confidence = min(metadata.confidence / 100.0, 1.0)
@@ -222,7 +194,10 @@ Each line represents a detection state, not necessarily unique individuals. The
                metadata.time = review_data["start"]
                return metadata
            except Exception as e:
-                logger.error(f"Failed to post-process review metadata: {e}")
+                # rarely LLMs can fail to follow directions on output format
+                logger.warning(
+                    f"Failed to parse review description as the response did not match expected format. {e}"
+                )
                return None
        else:
            logger.debug(
@@ -369,14 +344,6 @@ Guidelines:
        """Get the context window size for this provider in tokens."""
        return 4096

-    def estimate_image_tokens(self, width: int, height: int) -> float:
-        """Estimate prompt tokens consumed by a single image of the given dimensions.
-
-        Default heuristic: ~1 token per 1250 pixels. Providers that can measure or
-        know their model's exact image-token cost should override.
-        """
-        return (width * height) / 1250
-
    def embed(
        self,
        texts: list[str] | None = None,
@@ -136,44 +136,22 @@ class GeminiClient(GenAIClient):
                            )
                        )
                elif role == "assistant":
-                    parts: list[types.Part] = []
-                    if content:
-                        parts.append(types.Part.from_text(text=content))
-                    for tc in msg.get("tool_calls") or []:
-                        func = tc.get("function") or {}
-                        tc_name = func.get("name") or ""
-                        tc_args: Any = func.get("arguments")
-                        if isinstance(tc_args, str):
-                            try:
-                                tc_args = json.loads(tc_args)
-                            except (json.JSONDecodeError, TypeError):
-                                tc_args = {}
-                        if not isinstance(tc_args, dict):
-                            tc_args = {}
-                        if tc_name:
-                            parts.append(
-                                types.Part.from_function_call(
-                                    name=tc_name, args=tc_args
-                                )
-                            )
-                    if not parts:
-                        parts.append(types.Part.from_text(text=" "))
-                    gemini_messages.append(types.Content(role="model", parts=parts))
+                    gemini_messages.append(
+                        types.Content(
+                            role="model", parts=[types.Part.from_text(text=content)]
+                        )
+                    )
                elif role == "tool":
                    # Handle tool response
-                    response_payload = (
-                        content if isinstance(content, dict) else {"result": content}
-                    )
+                    function_response = {
+                        "name": msg.get("name", ""),
+                        "response": content,
+                    }
                    gemini_messages.append(
                        types.Content(
                            role="function",
                            parts=[
-                                types.Part.from_function_response(
-                                    name=msg.get("name")
-                                    or msg.get("tool_call_id")
-                                    or "",
-                                    response=response_payload,
-                                )
+                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
                            ],
                        )
                    )
@@ -365,44 +343,22 @@ class GeminiClient(GenAIClient):
                            )
                        )
                elif role == "assistant":
-                    parts: list[types.Part] = []
-                    if content:
-                        parts.append(types.Part.from_text(text=content))
-                    for tc in msg.get("tool_calls") or []:
-                        func = tc.get("function") or {}
-                        tc_name = func.get("name") or ""
-                        tc_args: Any = func.get("arguments")
-                        if isinstance(tc_args, str):
-                            try:
-                                tc_args = json.loads(tc_args)
-                            except (json.JSONDecodeError, TypeError):
-                                tc_args = {}
-                        if not isinstance(tc_args, dict):
-                            tc_args = {}
-                        if tc_name:
-                            parts.append(
-                                types.Part.from_function_call(
-                                    name=tc_name, args=tc_args
-                                )
-                            )
-                    if not parts:
-                        parts.append(types.Part.from_text(text=" "))
-                    gemini_messages.append(types.Content(role="model", parts=parts))
+                    gemini_messages.append(
+                        types.Content(
+                            role="model", parts=[types.Part.from_text(text=content)]
+                        )
+                    )
                elif role == "tool":
                    # Handle tool response
-                    response_payload = (
-                        content if isinstance(content, dict) else {"result": content}
-                    )
+                    function_response = {
+                        "name": msg.get("name", ""),
+                        "response": content,
+                    }
                    gemini_messages.append(
                        types.Content(
                            role="function",
                            parts=[
-                                types.Part.from_function_response(
-                                    name=msg.get("name")
-                                    or msg.get("tool_call_id")
-                                    or "",
-                                    response=response_payload,
-                                )
+                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
                            ],
                        )
                    )
@@ -42,9 +42,6 @@ class LlamaCppClient(GenAIClient):
    _supports_vision: bool
    _supports_audio: bool
    _supports_tools: bool
-    _image_token_cache: dict[tuple[int, int], int]
-    _text_baseline_tokens: int | None
-    _media_marker: str

    def _init_provider(self) -> str | None:
        """Initialize the client and query model metadata from the server."""
@@ -55,9 +52,6 @@ class LlamaCppClient(GenAIClient):
        self._supports_vision = False
        self._supports_audio = False
        self._supports_tools = False
-        self._image_token_cache = {}
-        self._text_baseline_tokens = None
-        self._media_marker = "<__media__>"

        base_url = (
            self.genai_config.base_url.rstrip("/")
@@ -143,13 +137,6 @@ class LlamaCppClient(GenAIClient):
            chat_caps = props.get("chat_template_caps", {})
            self._supports_tools = chat_caps.get("supports_tools", False)

-            # Media marker for multimodal embeddings; the server randomizes this
-            # per startup unless LLAMA_MEDIA_MARKER is set, so we must read it
-            # from /props rather than hardcoding "<__media__>".
-            media_marker = props.get("media_marker")
-            if isinstance(media_marker, str) and media_marker:
-                self._media_marker = media_marker
-
            logger.info(
                "llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s",
                configured_model,
@@ -285,91 +272,6 @@ class LlamaCppClient(GenAIClient):
            return self._context_size
        return 4096

-    def estimate_image_tokens(self, width: int, height: int) -> float:
-        """Probe the llama.cpp server to learn the model's image-token cost at the
-        requested dimensions.
-
-        llama.cpp's image tokenization is a deterministic function of dimensions and
-        the loaded mmproj, so the result is cached per (width, height) for the
-        lifetime of the process. Falls back to the base pixel heuristic if the
-        server is unreachable or the response is malformed.
-        """
-        if self.provider is None:
-            return super().estimate_image_tokens(width, height)
-
-        cached = self._image_token_cache.get((width, height))
-
-        if cached is not None:
-            return cached
-
-        try:
-            baseline = self._probe_baseline_tokens()
-            with_image = self._probe_image_prompt_tokens(width, height)
-            tokens = max(1, with_image - baseline)
-        except Exception as e:
-            logger.debug(
-                "llama.cpp image-token probe failed for %dx%d (%s); using heuristic",
-                width,
-                height,
-                e,
-            )
-            return super().estimate_image_tokens(width, height)
-
-        self._image_token_cache[(width, height)] = tokens
-        logger.debug(
-            "llama.cpp model '%s' uses ~%d tokens for %dx%d images",
-            self.genai_config.model,
-            tokens,
-            width,
-            height,
-        )
-        return tokens
-
-    def _probe_baseline_tokens(self) -> int:
-        """Return prompt_tokens for a minimal text-only request. Cached after first call."""
-        if self._text_baseline_tokens is not None:
-            return self._text_baseline_tokens
-
-        self._text_baseline_tokens = self._probe_prompt_tokens(
-            [{"type": "text", "text": "."}]
-        )
-        return self._text_baseline_tokens
-
-    def _probe_image_prompt_tokens(self, width: int, height: int) -> int:
-        """Return prompt_tokens for a single synthetic image plus minimal text."""
-        img = Image.new("RGB", (width, height), (128, 128, 128))
-        buf = io.BytesIO()
-        img.save(buf, format="JPEG", quality=60)
-        encoded = base64.b64encode(buf.getvalue()).decode("utf-8")
-        return self._probe_prompt_tokens(
-            [
-                {"type": "text", "text": "."},
-                {
-                    "type": "image_url",
-                    "image_url": {"url": f"data:image/jpeg;base64,{encoded}"},
-                },
-            ]
-        )
-
-    def _probe_prompt_tokens(self, content: list[dict[str, Any]]) -> int:
-        """POST a 1-token chat completion and return reported prompt_tokens.
-
-        Uses a generous timeout to absorb a cold model load on the first probe
-        when the server lazily loads models on demand (e.g. llama-swap).
-        """
-        payload = {
-            "model": self.genai_config.model,
-            "messages": [{"role": "user", "content": content}],
-            "max_tokens": 1,
-        }
-        response = requests.post(
-            f"{self.provider}/v1/chat/completions",
-            json=payload,
-            timeout=60,
-        )
-        response.raise_for_status()
-        return int(response.json()["usage"]["prompt_tokens"])
-
    def _build_payload(
        self,
        messages: list[dict[str, Any]],
@@ -474,11 +376,10 @@ class LlamaCppClient(GenAIClient):
            jpeg_bytes = _to_jpeg(img)
            to_encode = jpeg_bytes if jpeg_bytes is not None else img
            encoded = base64.b64encode(to_encode).decode("utf-8")
-            # prompt_string must contain the server's media marker placeholder.
-            # The marker is randomized per server startup (read from /props).
+            # prompt_string must contain <__media__> placeholder for image tokenization
            content.append(
                {
-                    "prompt_string": f"{self._media_marker}\n",
+                    "prompt_string": "<__media__>\n",
                    "multimodal_data": [encoded],  # type: ignore[dict-item]
                }
            )
@@ -1,7 +1,5 @@
 """Ollama Provider for Frigate AI."""

-import base64
-import binascii
 import json
 import logging
 from typing import Any, AsyncGenerator, Optional
@@ -18,41 +16,6 @@ from frigate.genai.utils import parse_tool_calls_from_message
 logger = logging.getLogger(__name__)


-def _normalize_multimodal_content(
-    content: Any,
-) -> tuple[Optional[str], Optional[list[bytes]]]:
-    """Convert OpenAI-style multimodal content to Ollama's (text, images) shape.
-
-    The chat API constructs user messages with content as a list of
-    ``{"type": "text"}`` and ``{"type": "image_url"}`` parts when a tool
-    returns a live frame. Ollama's SDK requires content to be a string and
-    images to be passed in a separate field, so we extract each.
-    """
-    if not isinstance(content, list):
-        return content, None
-
-    text_parts: list[str] = []
-    images: list[bytes] = []
-    for part in content:
-        if not isinstance(part, dict):
-            continue
-        part_type = part.get("type")
-        if part_type == "text":
-            text = part.get("text")
-            if text:
-                text_parts.append(str(text))
-        elif part_type == "image_url":
-            url = (part.get("image_url") or {}).get("url", "")
-            if isinstance(url, str) and url.startswith("data:"):
-                try:
-                    encoded = url.split(",", 1)[1]
-                    images.append(base64.b64decode(encoded, validate=True))
-                except (ValueError, IndexError, binascii.Error) as e:
-                    logger.debug("Failed to decode multimodal image url: %s", e)
-
-    return ("\n".join(text_parts) if text_parts else None), (images or None)
-
-
@register_genai_provider(GenAIProviderEnum.ollama)
 class OllamaClient(GenAIClient):
    """Generative AI client for Frigate using Ollama."""
@@ -68,12 +31,6 @@ class OllamaClient(GenAIClient):
    provider: ApiClient | None
    provider_options: dict[str, Any]

-    def _auth_headers(self) -> dict | None:
-        if self.genai_config.api_key:
-            return {"Authorization": "Bearer " + self.genai_config.api_key}
-
-        return None
-
    def _init_provider(self) -> ApiClient | None:
        """Initialize the client."""
        self.provider_options = {
@@ -82,11 +39,7 @@ class OllamaClient(GenAIClient):
        }

        try:
-            client = ApiClient(
-                host=self.genai_config.base_url,
-                timeout=self.timeout,
-                headers=self._auth_headers(),
-            )
+            client = ApiClient(host=self.genai_config.base_url, timeout=self.timeout)
            # ensure the model is available locally
            response = client.show(self.genai_config.model)
            if response.get("error"):
@@ -160,15 +113,6 @@ class OllamaClient(GenAIClient):
                schema = response_format.get("json_schema", {}).get("schema")
                if schema:
                    ollama_options["format"] = self._clean_schema_for_ollama(schema)
-            logger.debug(
-                "Ollama generate request: model=%s, prompt_len=%s, image_count=%s, "
-                "has_format=%s, options=%s",
-                self.genai_config.model,
-                len(prompt),
-                len(images) if images else 0,
-                "format" in ollama_options,
-                {k: v for k, v in ollama_options.items() if k != "format"},
-            )
            result = self.provider.generate(
                self.genai_config.model,
                prompt,
@@ -176,24 +120,9 @@ class OllamaClient(GenAIClient):
                **ollama_options,
            )
            logger.debug(
-                "Ollama generate response: done=%s, done_reason=%s, eval_count=%s, "
-                "prompt_eval_count=%s, response_len=%s",
-                result.get("done"),
-                result.get("done_reason"),
-                result.get("eval_count"),
-                result.get("prompt_eval_count"),
-                len(result.get("response", "") or ""),
+                f"Ollama tokens used: eval_count={result.get('eval_count')}, prompt_eval_count={result.get('prompt_eval_count')}"
            )
-            response_text = str(result["response"]).strip()
-            if not response_text:
-                logger.warning(
-                    "Ollama returned a blank response for model %s (done_reason=%s, "
-                    "eval_count=%s). Check model output, ensure thinking is disabled.",
-                    self.genai_config.model,
-                    result.get("done_reason"),
-                    result.get("eval_count"),
-                )
-            return response_text
+            return str(result["response"]).strip()
        except (
            TimeoutException,
            ResponseError,
@@ -213,9 +142,7 @@ class OllamaClient(GenAIClient):
                return []
            try:
                client = ApiClient(
-                    host=self.genai_config.base_url,
-                    timeout=self.timeout,
-                    headers=self._auth_headers(),
+                    host=self.genai_config.base_url, timeout=self.timeout
                )
            except Exception:
                return []
@@ -244,13 +171,10 @@ class OllamaClient(GenAIClient):
        """Build request_messages and params for chat (sync or stream)."""
        request_messages = []
        for msg in messages:
-            content, images = _normalize_multimodal_content(msg.get("content", ""))
-            msg_dict: dict[str, Any] = {
+            msg_dict = {
                "role": msg.get("role"),
-                "content": content if content is not None else "",
+                "content": msg.get("content", ""),
            }
-            if images:
-                msg_dict["images"] = images
            if msg.get("tool_call_id"):
                msg_dict["tool_call_id"] = msg["tool_call_id"]
            if msg.get("name"):
@@ -396,7 +320,6 @@ class OllamaClient(GenAIClient):
                async_client = OllamaAsyncClient(
                    host=self.genai_config.base_url,
                    timeout=self.timeout,
-                    headers=self._auth_headers(),
                )
                response = await async_client.chat(**request_params)
                result = self._message_from_response(response)
@@ -412,7 +335,6 @@ class OllamaClient(GenAIClient):
            async_client = OllamaAsyncClient(
                host=self.genai_config.base_url,
                timeout=self.timeout,
-                headers=self._auth_headers(),
            )
            content_parts: list[str] = []
            final_message: dict[str, Any] | None = None
@@ -73,39 +73,14 @@ class OpenAIClient(GenAIClient):
                **self.genai_config.runtime_options,
            }
            if response_format:
-                # OpenAI strict mode requires additionalProperties: false on the schema
-                if response_format.get("type") == "json_schema" and response_format.get(
-                    "json_schema", {}
-                ).get("strict"):
-                    schema = response_format.get("json_schema", {}).get("schema")
-                    if isinstance(schema, dict):
-                        schema["additionalProperties"] = False
                request_params["response_format"] = response_format
-
            result = self.provider.chat.completions.create(**request_params)
-
            if (
                result is not None
                and hasattr(result, "choices")
                and len(result.choices) > 0
            ):
-                message = result.choices[0].message
-                content = message.content
-
-                if not content:
-                    # When reasoning is enabled for some OpenAI backends the actual response
-                    # is incorrectly placed in reasoning_content instead of content.
-                    # This is buggy/incorrect behavior — reasoning should not be
-                    # enabled for these models.
-                    reasoning_content = getattr(message, "reasoning_content", None)
-                    if reasoning_content:
-                        logger.warning(
-                            "Response content was empty but reasoning_content was provided; "
-                            "reasoning appears to be enabled and should be disabled for this model."
-                        )
-                        content = reasoning_content
-
-                return str(content.strip()) if content else None
+                return str(result.choices[0].message.content.strip())
            return None
        except (TimeoutException, Exception) as e:
            logger.warning("OpenAI returned an error: %s", str(e))
@@ -1,386 +0,0 @@
-"""Debug replay startup job: ffmpeg concat + camera config publish.
-
-The runner orchestrates the async portion of starting a debug replay
-session. The DebugReplayManager (in frigate.debug_replay) owns session
-presence so the status bar can keep reading a single `active` flag from
-/debug_replay/status for the entire session window — which is broader
-than this job's lifetime.
-"""
-
-import logging
-import os
-import subprocess as sp
-import threading
-import time
-from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any, Optional, cast
-
-from peewee import ModelSelect
-
-from frigate.config import FrigateConfig
-from frigate.config.camera.updater import CameraConfigUpdatePublisher
-from frigate.const import REPLAY_CAMERA_PREFIX, REPLAY_DIR
-from frigate.jobs.export import JobStatePublisher
-from frigate.jobs.job import Job
-from frigate.jobs.manager import job_is_running, set_current_job
-from frigate.models import Recordings
-from frigate.types import JobStatusTypesEnum
-from frigate.util.ffmpeg import run_ffmpeg_with_progress
-
-if TYPE_CHECKING:
-    from frigate.debug_replay import DebugReplayManager
-
-logger = logging.getLogger(__name__)
-
-# Coalesce frequent ffmpeg progress callbacks so the WS isn't flooded.
-PROGRESS_BROADCAST_MIN_INTERVAL = 1.0
-
-JOB_TYPE = "debug_replay"
-
-STEP_PREPARING_CLIP = "preparing_clip"
-STEP_STARTING_CAMERA = "starting_camera"
-
-
-_active_runner: Optional["DebugReplayJobRunner"] = None
-_runner_lock = threading.Lock()
-
-
-def _set_active_runner(runner: Optional["DebugReplayJobRunner"]) -> None:
-    global _active_runner
-    with _runner_lock:
-        _active_runner = runner
-
-
-def get_active_runner() -> Optional["DebugReplayJobRunner"]:
-    with _runner_lock:
-        return _active_runner
-
-
-@dataclass
-class DebugReplayJob(Job):
-    """Job state for a debug replay startup."""
-
-    job_type: str = JOB_TYPE
-    source_camera: str = ""
-    replay_camera_name: str = ""
-    start_ts: float = 0.0
-    end_ts: float = 0.0
-    current_step: Optional[str] = None
-    progress_percent: float = 0.0
-
-    def to_dict(self) -> dict[str, Any]:
-        """Whitelisted payload for the job_state WS topic.
-
-        Replay-specific fields land in results so the frontend's
-        generic Job<TResults> type can be parameterised cleanly.
-        """
-        return {
-            "id": self.id,
-            "job_type": self.job_type,
-            "status": self.status,
-            "start_time": self.start_time,
-            "end_time": self.end_time,
-            "error_message": self.error_message,
-            "results": {
-                "current_step": self.current_step,
-                "progress_percent": self.progress_percent,
-                "source_camera": self.source_camera,
-                "replay_camera_name": self.replay_camera_name,
-                "start_ts": self.start_ts,
-                "end_ts": self.end_ts,
-            },
-        }
-
-
-def query_recordings(source_camera: str, start_ts: float, end_ts: float) -> ModelSelect:
-    """Return the Recordings query for the time range.
-
-    Module-level so tests can patch it without instantiating a runner.
-    """
-    query = (
-        Recordings.select(
-            Recordings.path,
-            Recordings.start_time,
-            Recordings.end_time,
-        )
-        .where(
-            Recordings.start_time.between(start_ts, end_ts)
-            | Recordings.end_time.between(start_ts, end_ts)
-            | ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
-        )
-        .where(Recordings.camera == source_camera)
-        .order_by(Recordings.start_time.asc())
-    )
-    return cast(ModelSelect, query)
-
-
-class DebugReplayJobRunner(threading.Thread):
-    """Worker thread that drives the startup job to completion.
-
-    Owns the live ffmpeg Popen reference for cancellation. Cancellation
-    is two-step (threading.Event + proc.terminate()) so the runner
-    both knows it should stop and is unblocked from its blocking subprocess
-    wait.
-    """
-
-    def __init__(
-        self,
-        job: DebugReplayJob,
-        frigate_config: FrigateConfig,
-        config_publisher: CameraConfigUpdatePublisher,
-        replay_manager: "DebugReplayManager",
-        publisher: Optional[JobStatePublisher] = None,
-    ) -> None:
-        super().__init__(daemon=True, name=f"debug_replay_{job.id}")
-        self.job = job
-        self.frigate_config = frigate_config
-        self.config_publisher = config_publisher
-        self.replay_manager = replay_manager
-        self.publisher = publisher if publisher is not None else JobStatePublisher()
-        self._cancel_event = threading.Event()
-        self._active_process: sp.Popen | None = None
-        self._proc_lock = threading.Lock()
-        self._last_broadcast_monotonic: float = 0.0
-
-    def cancel(self) -> None:
-        """Request cancellation. Idempotent."""
-        self._cancel_event.set()
-        with self._proc_lock:
-            proc = self._active_process
-        if proc is not None:
-            try:
-                proc.terminate()
-            except Exception as exc:
-                logger.warning("Failed to terminate ffmpeg subprocess: %s", exc)
-
-    def is_cancelled(self) -> bool:
-        return self._cancel_event.is_set()
-
-    def _record_proc(self, proc: sp.Popen) -> None:
-        with self._proc_lock:
-            self._active_process = proc
-        # Race: cancel arrived between Popen and _record_proc.
-        if self._cancel_event.is_set():
-            try:
-                proc.terminate()
-            except Exception:
-                pass
-
-    def _broadcast(self, force: bool = False) -> None:
-        now = time.monotonic()
-        if (
-            not force
-            and now - self._last_broadcast_monotonic < PROGRESS_BROADCAST_MIN_INTERVAL
-        ):
-            return
-        self._last_broadcast_monotonic = now
-
-        try:
-            self.publisher.publish(self.job.to_dict())
-        except Exception as err:
-            logger.warning("Publisher raised during job state broadcast: %s", err)
-
-    def run(self) -> None:
-        replay_name = self.job.replay_camera_name
-        os.makedirs(REPLAY_DIR, exist_ok=True)
-        concat_file = os.path.join(REPLAY_DIR, f"{replay_name}_concat.txt")
-        clip_path = os.path.join(REPLAY_DIR, f"{replay_name}.mp4")
-
-        self.job.status = JobStatusTypesEnum.running
-        self.job.start_time = time.time()
-        self.job.current_step = STEP_PREPARING_CLIP
-        self._broadcast(force=True)
-
-        try:
-            recordings = query_recordings(
-                self.job.source_camera, self.job.start_ts, self.job.end_ts
-            )
-            with open(concat_file, "w") as f:
-                for recording in recordings:
-                    f.write(f"file '{recording.path}'\n")
-
-            ffmpeg_cmd = [
-                self.frigate_config.ffmpeg.ffmpeg_path,
-                "-hide_banner",
-                "-y",
-                "-f",
-                "concat",
-                "-safe",
-                "0",
-                "-i",
-                concat_file,
-                "-c",
-                "copy",
-                "-movflags",
-                "+faststart",
-                clip_path,
-            ]
-
-            logger.info(
-                "Generating replay clip for %s (%.1f - %.1f)",
-                self.job.source_camera,
-                self.job.start_ts,
-                self.job.end_ts,
-            )
-
-            def _on_progress(percent: float) -> None:
-                self.job.progress_percent = percent
-                self._broadcast()
-
-            try:
-                returncode, stderr = run_ffmpeg_with_progress(
-                    ffmpeg_cmd,
-                    expected_duration_seconds=max(
-                        0.0, self.job.end_ts - self.job.start_ts
-                    ),
-                    on_progress=_on_progress,
-                    process_started=self._record_proc,
-                    use_low_priority=True,
-                )
-            finally:
-                with self._proc_lock:
-                    self._active_process = None
-
-            if self._cancel_event.is_set():
-                self._finalize_cancelled(clip_path)
-                return
-
-            if returncode != 0:
-                raise RuntimeError(f"FFmpeg failed: {stderr[-500:]}")
-
-            if not os.path.exists(clip_path):
-                raise RuntimeError("Clip file was not created")
-
-            self.job.current_step = STEP_STARTING_CAMERA
-            self.job.progress_percent = 100.0
-            self._broadcast(force=True)
-
-            if self._cancel_event.is_set():
-                self._finalize_cancelled(clip_path)
-                return
-
-            self.replay_manager.publish_camera(
-                source_camera=self.job.source_camera,
-                replay_name=replay_name,
-                clip_path=clip_path,
-                frigate_config=self.frigate_config,
-                config_publisher=self.config_publisher,
-            )
-            self.replay_manager.mark_session_ready(clip_path)
-
-            self.job.status = JobStatusTypesEnum.success
-            self.job.end_time = time.time()
-            self._broadcast(force=True)
-            logger.info(
-                "Debug replay started: %s -> %s",
-                self.job.source_camera,
-                replay_name,
-            )
-        except Exception as exc:
-            logger.exception("Debug replay startup failed")
-            self.job.status = JobStatusTypesEnum.failed
-            self.job.error_message = str(exc)
-            self.job.end_time = time.time()
-            self._broadcast(force=True)
-            self.replay_manager.clear_session()
-            _remove_silent(clip_path)
-        finally:
-            _remove_silent(concat_file)
-            _set_active_runner(None)
-
-    def _finalize_cancelled(self, clip_path: str) -> None:
-        logger.info("Debug replay startup cancelled")
-        self.job.status = JobStatusTypesEnum.cancelled
-        self.job.end_time = time.time()
-        self._broadcast(force=True)
-        # The caller of cancel_debug_replay_job (DebugReplayManager.stop) owns
-        # session cleanup — db rows, filesystem artifacts, clear_session. We
-        # only clean up the partial concat output we created.
-        _remove_silent(clip_path)
-
-
-def _remove_silent(path: str) -> None:
-    try:
-        if os.path.exists(path):
-            os.remove(path)
-    except OSError:
-        pass
-
-
-def start_debug_replay_job(
-    *,
-    source_camera: str,
-    start_ts: float,
-    end_ts: float,
-    frigate_config: FrigateConfig,
-    config_publisher: CameraConfigUpdatePublisher,
-    replay_manager: "DebugReplayManager",
-) -> str:
-    """Validate, create job, start runner. Returns the job id.
-
-    Raises ValueError for bad params (camera missing, time range
-    invalid, no recordings) and RuntimeError if a session is already
-    active.
-    """
-    if job_is_running(JOB_TYPE) or replay_manager.active:
-        raise RuntimeError("A replay session is already active")
-
-    if source_camera not in frigate_config.cameras:
-        raise ValueError(f"Camera '{source_camera}' not found")
-
-    if end_ts <= start_ts:
-        raise ValueError("End time must be after start time")
-
-    recordings = query_recordings(source_camera, start_ts, end_ts)
-    if not recordings.count():
-        raise ValueError(
-            f"No recordings found for camera '{source_camera}' in the specified time range"
-        )
-
-    replay_name = f"{REPLAY_CAMERA_PREFIX}{source_camera}"
-    replay_manager.mark_starting(
-        source_camera=source_camera,
-        replay_camera_name=replay_name,
-        start_ts=start_ts,
-        end_ts=end_ts,
-    )
-
-    job = DebugReplayJob(
-        source_camera=source_camera,
-        replay_camera_name=replay_name,
-        start_ts=start_ts,
-        end_ts=end_ts,
-    )
-    set_current_job(job)
-
-    runner = DebugReplayJobRunner(
-        job=job,
-        frigate_config=frigate_config,
-        config_publisher=config_publisher,
-        replay_manager=replay_manager,
-    )
-    _set_active_runner(runner)
-    runner.start()
-
-    return job.id
-
-
-def cancel_debug_replay_job() -> bool:
-    """Signal the active runner to cancel.
-
-    Returns True if a runner was signalled, False if no job was active.
-    """
-    runner = get_active_runner()
-    if runner is None:
-        return False
-    runner.cancel()
-    return True
-
-
-def wait_for_runner(timeout: float = 2.0) -> bool:
-    """Join the active runner. Returns True if the runner ended in time."""
-    runner = get_active_runner()
-    if runner is None:
-        return True
-    runner.join(timeout=timeout)
-    return not runner.is_alive()
@@ -8,6 +8,7 @@ import os
 import queue
 import subprocess as sp
 import threading
+import time
 import traceback
 from multiprocessing.synchronize import Event as MpEvent
 from typing import Any, Optional
@@ -18,7 +19,6 @@ import numpy as np
 from frigate.comms.inter_process import InterProcessRequestor
 from frigate.config import BirdseyeModeEnum, FfmpegConfig, FrigateConfig
 from frigate.const import BASE_DIR, BIRDSEYE_PIPE, INSTALL_DIR, UPDATE_BIRDSEYE_LAYOUT
-from frigate.output.ws_auth import ws_has_camera_access
 from frigate.util.image import (
    SharedMemoryFrameManager,
    copy_yuv_to_position,
@@ -236,14 +236,12 @@ class BroadcastThread(threading.Thread):
        converter: FFMpegConverter,
        websocket_server: Any,
        stop_event: MpEvent,
-        config: FrigateConfig,
    ):
        super().__init__()
        self.camera = camera
        self.converter = converter
        self.websocket_server = websocket_server
        self.stop_event = stop_event
-        self.config = config

    def run(self) -> None:
        while not self.stop_event.is_set():
@@ -258,7 +256,6 @@ class BroadcastThread(threading.Thread):
                    if (
                        not ws.terminated
                        and ws.environ["PATH_INFO"] == f"/{self.camera}"
-                        and ws_has_camera_access(ws, self.camera, self.config)
                    ):
                        try:
                            ws.send(buf, binary=True)
@@ -809,11 +806,7 @@ class Birdseye:
            config.birdseye.restream,
        )
        self.broadcaster = BroadcastThread(
-            "birdseye",
-            self.converter,
-            websocket_server,
-            stop_event,
-            config,
+            "birdseye", self.converter, websocket_server, stop_event
        )
        self.birdseye_manager = BirdsEyeFrameManager(self.config, stop_event)
        self.frame_manager = SharedMemoryFrameManager()
@@ -881,7 +874,7 @@ class Birdseye:
                coordinates = self.birdseye_manager.get_camera_coordinates()
                self.requestor.send_data(UPDATE_BIRDSEYE_LAYOUT, coordinates)
        if self._idle_interval:
-            now = datetime.datetime.now().timestamp()
+            now = time.monotonic()
            is_idle = len(self.birdseye_manager.camera_layout) == 0
            if (
                is_idle
@@ -7,8 +7,7 @@ import threading
 from multiprocessing.synchronize import Event as MpEvent
 from typing import Any

-from frigate.config import CameraConfig, FfmpegConfig, FrigateConfig
-from frigate.output.ws_auth import ws_has_camera_access
+from frigate.config import CameraConfig, FfmpegConfig

 logger = logging.getLogger(__name__)

@@ -103,14 +102,12 @@ class BroadcastThread(threading.Thread):
        converter: FFMpegConverter,
        websocket_server: Any,
        stop_event: MpEvent,
-        config: FrigateConfig,
    ):
        super().__init__()
        self.camera = camera
        self.converter = converter
        self.websocket_server = websocket_server
        self.stop_event = stop_event
-        self.config = config

    def run(self) -> None:
        while not self.stop_event.is_set():
@@ -125,7 +122,6 @@ class BroadcastThread(threading.Thread):
                    if (
                        not ws.terminated
                        and ws.environ["PATH_INFO"] == f"/{self.camera}"
-                        and ws_has_camera_access(ws, self.camera, self.config)
                    ):
                        try:
                            ws.send(buf, binary=True)
@@ -139,11 +135,7 @@ class BroadcastThread(threading.Thread):

 class JsmpegCamera:
    def __init__(
-        self,
-        config: CameraConfig,
-        frigate_config: FrigateConfig,
-        stop_event: MpEvent,
-        websocket_server: Any,
+        self, config: CameraConfig, stop_event: MpEvent, websocket_server: Any
    ) -> None:
        self.config = config
        self.input: queue.Queue[bytes] = queue.Queue(maxsize=config.detect.fps)
@@ -162,11 +154,7 @@ class JsmpegCamera:
            config.live.quality,
        )
        self.broadcaster = BroadcastThread(
-            config.name or "",
-            self.converter,
-            websocket_server,
-            stop_event,
-            frigate_config,
+            config.name or "", self.converter, websocket_server, stop_event
        )

        self.converter.start()
@@ -32,7 +32,6 @@ from frigate.const import (
 from frigate.output.birdseye import Birdseye
 from frigate.output.camera import JsmpegCamera
 from frigate.output.preview import PreviewRecorder
-from frigate.output.ws_auth import ws_has_camera_access
 from frigate.util.image import SharedMemoryFrameManager, get_blank_yuv_frame
 from frigate.util.process import FrigateProcess

@@ -103,7 +102,7 @@ class OutputProcess(FrigateProcess):
    ) -> None:
        camera_config = self.config.cameras[camera]
        jsmpeg_cameras[camera] = JsmpegCamera(
-            camera_config, self.config, self.stop_event, websocket_server
+            camera_config, self.stop_event, websocket_server
        )
        preview_recorders[camera] = PreviewRecorder(camera_config)
        preview_write_times[camera] = 0
@@ -263,7 +262,6 @@ class OutputProcess(FrigateProcess):
            # send camera frame to ffmpeg process if websockets are connected
            if any(
                ws.environ["PATH_INFO"].endswith(camera)
-                and ws_has_camera_access(ws, camera, self.config)
                for ws in websocket_server.manager
            ):
                # write to the converter for the camera if clients are listening to the specific camera
@@ -277,7 +275,6 @@ class OutputProcess(FrigateProcess):
                    self.config.birdseye.restream
                    or any(
                        ws.environ["PATH_INFO"].endswith("birdseye")
-                        and ws_has_camera_access(ws, "birdseye", self.config)
                        for ws in websocket_server.manager
                    )
                )
@@ -349,13 +346,6 @@ def move_preview_frames(loc: str) -> None:
            if not os.path.exists(preview_holdover):
                return

-            if not os.access(preview_holdover, os.R_OK | os.W_OK):
-                logger.error(
-                    "Insufficient permissions on preview restart cache at %s",
-                    preview_holdover,
-                )
-                return
-
            shutil.move(preview_holdover, preview_cache)
    except shutil.Error:
        logger.error("Failed to restore preview cache.")
@@ -361,17 +361,14 @@ class PreviewRecorder:
            small_frame,
            cv2.COLOR_YUV2BGR_I420,
        )
-        cache_path = get_cache_image_name(self.camera_name, frame_time)
-
-        if not cv2.imwrite(
-            cache_path,
+        cv2.imwrite(
+            get_cache_image_name(self.camera_name, frame_time),
            small_frame,
            [
                int(cv2.IMWRITE_WEBP_QUALITY),
                PREVIEW_QUALITY_WEBP[self.config.record.preview.quality],
            ],
-        ):
-            logger.error("Failed to write preview frame to %s", cache_path)
+        )

    def write_data(
        self,
@@ -1,43 +0,0 @@
-"""Authorization helpers for JSMPEG websocket clients."""
-
-from typing import Any
-
-from frigate.config import FrigateConfig
-from frigate.models import User
-
-
-def _get_valid_ws_roles(ws: Any, config: FrigateConfig) -> list[str]:
-    role_header = ws.environ.get("HTTP_REMOTE_ROLE", "")
-    roles = [
-        role.strip()
-        for role in role_header.split(config.proxy.separator)
-        if role.strip()
-    ]
-    return [role for role in roles if role in config.auth.roles]
-
-
-def ws_has_camera_access(ws: Any, camera_name: str, config: FrigateConfig) -> bool:
-    """Return True when a websocket client is authorized for the camera path."""
-    roles = _get_valid_ws_roles(ws, config)
-
-    if not roles:
-        return False
-
-    roles_dict = config.auth.roles
-
-    # Birdseye is a composite stream, so only users with unrestricted access
-    # should receive it.
-    if camera_name == "birdseye":
-        return any(role == "admin" or not roles_dict.get(role) for role in roles)
-
-    all_camera_names = set(config.cameras.keys())
-
-    for role in roles:
-        if role == "admin" or not roles_dict.get(role):
-            return True
-
-        allowed_cameras = User.get_allowed_cameras(role, roles_dict, all_camera_names)
-        if camera_name in allowed_cameras:
-            return True
-
-    return False
@@ -351,11 +351,9 @@ class RecordingCleanup(threading.Thread):
                )
                .where(
                    ReviewSegment.camera == camera,
-                    # candidate recordings can extend up to continuous_expire_date
-                    # (the no-motion no-audio branch of the recordings query),
-                    # so reviews must cover that full range to avoid deleting
-                    # segments that overlap recent alerts/detections.
-                    ReviewSegment.start_time < continuous_expire_date,
+                    # need to ensure segments for all reviews starting
+                    # before the expire date are included
+                    ReviewSegment.start_time < motion_expire_date,
                )
                .order_by(ReviewSegment.start_time)
                .namedtuples()
@@ -13,7 +13,6 @@ from enum import Enum
 from pathlib import Path
 from typing import Callable, Optional

-import pytz  # type: ignore[import-untyped]
 from peewee import DoesNotExist

 from frigate.config import FfmpegConfig, FrigateConfig
@@ -23,13 +22,13 @@ from frigate.const import (
    EXPORT_DIR,
    MAX_PLAYLIST_SECONDS,
    PREVIEW_FRAME_TYPE,
+    PROCESS_PRIORITY_LOW,
 )
 from frigate.ffmpeg_presets import (
    EncodeTypeEnum,
    parse_preset_hardware_acceleration_encode,
 )
-from frigate.models import Export, Previews, Recordings, ReviewSegment
-from frigate.util.ffmpeg import run_ffmpeg_with_progress
+from frigate.models import Export, Previews, Recordings
 from frigate.util.time import is_current_hour

 logger = logging.getLogger(__name__)
@@ -243,171 +242,110 @@ class RecordingExporter(threading.Thread):

        return total

+    def _inject_progress_flags(self, ffmpeg_cmd: list[str]) -> list[str]:
+        """Insert FFmpeg progress reporting flags before the output path.
+
+        ``-progress pipe:2`` writes structured key=value lines to stderr,
+        ``-nostats`` suppresses the noisy default stats output.
+        """
+        if not ffmpeg_cmd:
+            return ffmpeg_cmd
+        return ffmpeg_cmd[:-1] + ["-progress", "pipe:2", "-nostats", ffmpeg_cmd[-1]]
+
    def _run_ffmpeg_with_progress(
        self,
        ffmpeg_cmd: list[str],
        playlist_lines: str | list[str],
        step: str = "encoding",
    ) -> tuple[int, str]:
-        """Delegate to the shared helper, mapping percent → (step, percent).
+        """Run an FFmpeg export command, parsing progress events from stderr.

-        Returns ``(returncode, captured_stderr)``.
+        Returns ``(returncode, captured_stderr)``. Stdout is left attached to
+        the parent process so we don't have to drain it (and risk a deadlock
+        if the buffer fills). Progress percent is computed against the
+        expected output duration; values are clamped to [0, 100] inside
+        :py:meth:`_emit_progress`.
        """
+        cmd = ["nice", "-n", str(PROCESS_PRIORITY_LOW)] + self._inject_progress_flags(
+            ffmpeg_cmd
+        )
+
        if isinstance(playlist_lines, list):
            stdin_payload = "\n".join(playlist_lines)
        else:
            stdin_payload = playlist_lines

-        return run_ffmpeg_with_progress(
-            ffmpeg_cmd,
-            expected_duration_seconds=self._expected_output_duration_seconds(),
-            on_progress=lambda percent: self._emit_progress(step, percent),
-            stdin_payload=stdin_payload,
-            use_low_priority=True,
+        expected_duration = self._expected_output_duration_seconds()
+
+        self._emit_progress(step, 0.0)
+
+        proc = sp.Popen(
+            cmd,
+            stdin=sp.PIPE,
+            stderr=sp.PIPE,
+            text=True,
+            encoding="ascii",
+            errors="replace",
        )

-    def get_datetime_from_timestamp(self, timestamp: int) -> str:
-        # return in iso format using the configured ui.timezone when set,
-        # so the auto-generated export name reflects local time rather
-        # than the container's UTC clock
-        tz_name = self.config.ui.timezone
-        if tz_name:
+        assert proc.stdin is not None
+        assert proc.stderr is not None
+
+        try:
+            proc.stdin.write(stdin_payload)
+        except (BrokenPipeError, OSError):
+            # FFmpeg may have rejected the input early; still wait for it
+            # to terminate so the returncode is meaningful.
+            pass
+        finally:
            try:
-                tz = pytz.timezone(tz_name)
-            except pytz.UnknownTimeZoneError:
-                tz = None
-            if tz is not None:
-                return datetime.datetime.fromtimestamp(timestamp, tz=tz).strftime(
-                    "%Y-%m-%d %H:%M:%S"
-                )
-        return datetime.datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")
+                proc.stdin.close()
+            except (BrokenPipeError, OSError):
+                pass

-    def _chapter_metadata_path(self) -> str:
-        return os.path.join(CACHE_DIR, f"export_chapters_{self.export_id}.txt")
-
-    def _build_chapter_metadata_file(self, recordings: list) -> Optional[str]:
-        """Write an FFmpeg metadata file with chapters for review items in range.
-
-        Chapter offsets are computed in *output time*: the VOD endpoint
-        concatenates recording clips back-to-back, so wall-clock gaps
-        between recordings collapse in the produced video. We walk the
-        same recording rows that feed the playlist and convert each
-        review item's wall-clock boundaries into output-time offsets.
-        Returns ``None`` when there are no recordings, no review items,
-        or any chapter would have zero output duration.
-        """
-        if not recordings:
-            return None
-
-        windows: list[tuple[float, float, float]] = []
-        output_offset = 0.0
-        for rec in recordings:
-            clipped_start = max(float(rec.start_time), float(self.start_time))
-            clipped_end = min(float(rec.end_time), float(self.end_time))
-            if clipped_end <= clipped_start:
-                continue
-            windows.append((clipped_start, clipped_end, output_offset))
-            output_offset += clipped_end - clipped_start
-
-        if not windows:
-            return None
+        captured: list[str] = []

        try:
-            review_rows = list(
-                ReviewSegment.select(
-                    ReviewSegment.start_time,
-                    ReviewSegment.end_time,
-                    ReviewSegment.severity,
-                    ReviewSegment.data,
-                )
-                .where(
-                    ReviewSegment.start_time.between(self.start_time, self.end_time)
-                    | ReviewSegment.end_time.between(self.start_time, self.end_time)
-                    | (
-                        (self.start_time > ReviewSegment.start_time)
-                        & (self.end_time < ReviewSegment.end_time)
-                    )
-                )
-                .where(ReviewSegment.camera == self.camera)
-                .order_by(ReviewSegment.start_time.asc())
-                .iterator()
-            )
+            for raw_line in proc.stderr:
+                captured.append(raw_line)
+                line = raw_line.strip()
+
+                if not line:
+                    continue
+
+                if line.startswith("out_time_us="):
+                    if expected_duration <= 0:
+                        continue
+                    try:
+                        out_time_us = int(line.split("=", 1)[1])
+                    except (ValueError, IndexError):
+                        continue
+                    if out_time_us < 0:
+                        continue
+                    out_seconds = out_time_us / 1_000_000.0
+                    percent = (out_seconds / expected_duration) * 100.0
+                    self._emit_progress(step, percent)
+                elif line == "progress=end":
+                    self._emit_progress(step, 100.0)
+                    break
        except Exception:
-            logger.exception(
-                "Failed to query review segments for export %s", self.export_id
-            )
-            return None
+            logger.exception("Failed reading FFmpeg progress for %s", self.export_id)

-        if not review_rows:
-            return None
+        proc.wait()

-        total_output = windows[-1][2] + (windows[-1][1] - windows[-1][0])
-        last_recorded_end = windows[-1][1]
-
-        def wall_to_output(t: float) -> float:
-            t = max(float(self.start_time), min(float(self.end_time), t))
-            for w_start, w_end, w_offset in windows:
-                if t < w_start:
-                    return w_offset
-                if t <= w_end:
-                    return w_offset + (t - w_start)
-            return total_output
-
-        chapter_blocks: list[str] = []
-        for review in review_rows:
-            if review.start_time is None:
-                continue
-            # In-progress segments have a NULL end_time until the activity
-            # closes; clamp to the last recorded second so the chapter never
-            # extends past the actual video.
-            review_end = (
-                float(review.end_time)
-                if review.end_time is not None
-                else last_recorded_end
-            )
-            start_out = wall_to_output(float(review.start_time))
-            end_out = wall_to_output(review_end)
-
-            # Drop chapters that fall entirely in a recording gap, or are
-            # too short to be navigable in a player.
-            if end_out - start_out < 1.0:
-                continue
-
-            data = review.data or {}
-            labels: list[str] = []
-            for obj in data.get("objects") or []:
-                label = str(obj).split("-")[0]
-                if label and label not in labels:
-                    labels.append(label)
-
-            title = str(review.severity).capitalize()
-            if labels:
-                title = f"{title}: {', '.join(labels)}"
-
-            chapter_blocks.append(
-                "[CHAPTER]\n"
-                "TIMEBASE=1/1000\n"
-                f"START={int(start_out * 1000)}\n"
-                f"END={int(end_out * 1000)}\n"
-                f"title={title}"
-            )
-
-        if not chapter_blocks:
-            return None
-
-        meta_path = self._chapter_metadata_path()
+        # Drain any remaining stderr so callers can log it on failure.
        try:
-            with open(meta_path, "w", encoding="utf-8") as f:
-                f.write(";FFMETADATA1\n")
-                f.write("\n".join(chapter_blocks))
-                f.write("\n")
-        except OSError:
-            logger.exception(
-                "Failed to write chapter metadata file for export %s", self.export_id
-            )
-            return None
+            remaining = proc.stderr.read()
+            if remaining:
+                captured.append(remaining)
+        except Exception:
+            pass

-        return meta_path
+        return proc.returncode, "".join(captured)
+
+    def get_datetime_from_timestamp(self, timestamp: int) -> str:
+        # return in iso format
+        return datetime.datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")

    def save_thumbnail(self, id: str) -> str:
        thumb_path = os.path.join(CLIPS_DIR, f"export/{id}.webp")
@@ -449,14 +387,16 @@ class RecordingExporter(threading.Thread):
            except DoesNotExist:
                return ""

-            diff = max(0.0, float(self.start_time) - float(preview.start_time))
+            diff = self.start_time - preview.start_time
+            minutes = int(diff / 60)
+            seconds = int(diff % 60)
            ffmpeg_cmd = [
                "/usr/lib/ffmpeg/7.0/bin/ffmpeg",  # hardcode path for exports thumbnail due to missing libwebp support
                "-hide_banner",
                "-loglevel",
                "warning",
                "-ss",
-                f"{diff:.3f}",
+                f"00:{minutes}:{seconds}",
                "-i",
                preview.path,
                "-frames",
@@ -482,18 +422,12 @@ class RecordingExporter(threading.Thread):
            start_file = f"{file_start}{self.start_time}.{PREVIEW_FRAME_TYPE}"
            end_file = f"{file_start}{self.end_time}.{PREVIEW_FRAME_TYPE}"
            selected_preview = None
-            # Preview frames are written at most 1-2 fps during activity
-            # and as little as one every 30s during quiet periods, so a
-            # short export window can contain zero frames. Track the most
-            # recent frame before the window as a fallback.
-            fallback_preview = None

            for file in sorted(os.listdir(preview_dir)):
                if not file.startswith(file_start):
                    continue

                if file < start_file:
-                    fallback_preview = os.path.join(preview_dir, file)
                    continue

                if file > end_file:
@@ -502,9 +436,6 @@ class RecordingExporter(threading.Thread):
                selected_preview = os.path.join(preview_dir, file)
                break

-            if not selected_preview:
-                selected_preview = fallback_preview
-
            if not selected_preview:
                return ""

@@ -520,24 +451,6 @@ class RecordingExporter(threading.Thread):
        if type(internal_port) is str:
            internal_port = int(internal_port.split(":")[-1])

-        recordings = list(
-            Recordings.select(
-                Recordings.start_time,
-                Recordings.end_time,
-            )
-            .where(
-                Recordings.start_time.between(self.start_time, self.end_time)
-                | Recordings.end_time.between(self.start_time, self.end_time)
-                | (
-                    (self.start_time > Recordings.start_time)
-                    & (self.end_time < Recordings.end_time)
-                )
-            )
-            .where(Recordings.camera == self.camera)
-            .order_by(Recordings.start_time.asc())
-            .iterator()
-        )
-
        playlist_lines: list[str] = []
        if (self.end_time - self.start_time) <= MAX_PLAYLIST_SECONDS:
            playlist_url = f"http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{self.start_time}/end/{self.end_time}/index.m3u8"
@@ -545,13 +458,32 @@ class RecordingExporter(threading.Thread):
                f"-y -protocol_whitelist pipe,file,http,tcp -i {playlist_url}"
            )
        else:
-            # Chunk the recording rows into pages so each playlist line
-            # references a bounded sub-range rather than the full export.
+            # get full set of recordings
+            export_recordings = (
+                Recordings.select(
+                    Recordings.start_time,
+                    Recordings.end_time,
+                )
+                .where(
+                    Recordings.start_time.between(self.start_time, self.end_time)
+                    | Recordings.end_time.between(self.start_time, self.end_time)
+                    | (
+                        (self.start_time > Recordings.start_time)
+                        & (self.end_time < Recordings.end_time)
+                    )
+                )
+                .where(Recordings.camera == self.camera)
+                .order_by(Recordings.start_time.asc())
+            )
+
+            # Use pagination to process records in chunks
            page_size = 1000
-            for i in range(0, len(recordings), page_size):
-                chunk = recordings[i : i + page_size]
+            num_pages = (export_recordings.count() + page_size - 1) // page_size
+
+            for page in range(1, num_pages + 1):
+                playlist = export_recordings.paginate(page, page_size)
                playlist_lines.append(
-                    f"file 'http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{float(chunk[0].start_time)}/end/{float(chunk[-1].end_time)}/index.m3u8'"
+                    f"file 'http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{float(playlist[0].start_time)}/end/{float(playlist[-1].end_time)}/index.m3u8'"
                )

            ffmpeg_input = "-y -protocol_whitelist pipe,file,http,tcp -f concat -safe 0 -i /dev/stdin"
@@ -572,12 +504,8 @@ class RecordingExporter(threading.Thread):
                )
            ).split(" ")
        else:
-            chapters_path = self._build_chapter_metadata_file(recordings)
-            chapter_args = (
-                f" -i {chapters_path} -map 0 -map_metadata 1" if chapters_path else ""
-            )
            ffmpeg_cmd = (
-                f"{self.config.ffmpeg.ffmpeg_path} -hide_banner {ffmpeg_input}{chapter_args} -c copy -movflags +faststart"
+                f"{self.config.ffmpeg.ffmpeg_path} -hide_banner {ffmpeg_input} -c copy -movflags +faststart"
            ).split(" ")

        # add metadata
@@ -763,8 +691,6 @@ class RecordingExporter(threading.Thread):
                ffmpeg_cmd, playlist_lines, step="encoding_retry"
            )

-        Path(self._chapter_metadata_path()).unlink(missing_ok=True)
-
        if returncode != 0:
            logger.error(
                f"Failed to export {self.playback_source.value} for command {' '.join(ffmpeg_cmd)}"
@@ -1,123 +0,0 @@
-"""Tests for /debug_replay API endpoints."""
-
-from unittest.mock import patch
-
-from frigate.models import Event, Recordings, ReviewSegment
-from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
-
-
-class TestDebugReplayAPI(BaseTestHttp):
-    def setUp(self):
-        super().setUp([Event, Recordings, ReviewSegment])
-        self.app = self.create_app()
-
-    def test_start_returns_202_with_job_id(self):
-        # Stub the factory to skip validation/threading and just record the
-        # name on the manager the way the real factory's mark_starting would.
-        def fake_start(**kwargs):
-            kwargs["replay_manager"].mark_starting(
-                source_camera=kwargs["source_camera"],
-                replay_camera_name="_replay_front",
-                start_ts=kwargs["start_ts"],
-                end_ts=kwargs["end_ts"],
-            )
-            return "job-1234"
-
-        with patch(
-            "frigate.api.debug_replay.start_debug_replay_job",
-            side_effect=fake_start,
-        ):
-            with AuthTestClient(self.app) as client:
-                resp = client.post(
-                    "/debug_replay/start",
-                    json={
-                        "camera": "front",
-                        "start_time": 100,
-                        "end_time": 200,
-                    },
-                )
-
-        self.assertEqual(resp.status_code, 202)
-        body = resp.json()
-        self.assertTrue(body["success"])
-        self.assertEqual(body["job_id"], "job-1234")
-        self.assertEqual(body["replay_camera"], "_replay_front")
-
-    def test_start_returns_400_on_validation_error(self):
-        with patch(
-            "frigate.api.debug_replay.start_debug_replay_job",
-            side_effect=ValueError("Camera 'missing' not found"),
-        ):
-            with AuthTestClient(self.app) as client:
-                resp = client.post(
-                    "/debug_replay/start",
-                    json={
-                        "camera": "missing",
-                        "start_time": 100,
-                        "end_time": 200,
-                    },
-                )
-
-        self.assertEqual(resp.status_code, 400)
-        body = resp.json()
-        self.assertFalse(body["success"])
-        # Message is hard-coded so we don't echo exception text back to clients
-        # (CodeQL: information exposure through an exception).
-        self.assertEqual(body["message"], "Invalid debug replay parameters")
-
-    def test_start_returns_409_when_session_already_active(self):
-        with patch(
-            "frigate.api.debug_replay.start_debug_replay_job",
-            side_effect=RuntimeError("A replay session is already active"),
-        ):
-            with AuthTestClient(self.app) as client:
-                resp = client.post(
-                    "/debug_replay/start",
-                    json={
-                        "camera": "front",
-                        "start_time": 100,
-                        "end_time": 200,
-                    },
-                )
-
-        self.assertEqual(resp.status_code, 409)
-        body = resp.json()
-        self.assertFalse(body["success"])
-
-    def test_status_inactive_when_no_session(self):
-        with AuthTestClient(self.app) as client:
-            resp = client.get("/debug_replay/status")
-
-        self.assertEqual(resp.status_code, 200)
-        body = resp.json()
-        self.assertFalse(body["active"])
-        self.assertIsNone(body["replay_camera"])
-        self.assertIsNone(body["source_camera"])
-        self.assertIsNone(body["start_time"])
-        self.assertIsNone(body["end_time"])
-        self.assertFalse(body["live_ready"])
-        # Make sure deprecated fields are gone
-        self.assertNotIn("state", body)
-        self.assertNotIn("progress_percent", body)
-        self.assertNotIn("error_message", body)
-
-    def test_status_active_after_mark_starting(self):
-        manager = self.app.replay_manager
-        manager.mark_starting(
-            source_camera="front",
-            replay_camera_name="_replay_front",
-            start_ts=100.0,
-            end_ts=200.0,
-        )
-
-        with AuthTestClient(self.app) as client:
-            resp = client.get("/debug_replay/status")
-
-        self.assertEqual(resp.status_code, 200)
-        body = resp.json()
-        self.assertTrue(body["active"])
-        self.assertEqual(body["replay_camera"], "_replay_front")
-        self.assertEqual(body["source_camera"], "front")
-        self.assertEqual(body["start_time"], 100.0)
-        self.assertEqual(body["end_time"], 200.0)
-        self.assertFalse(body["live_ready"])
@@ -23,26 +23,6 @@ class TestHttpApp(BaseTestHttp):
            response_json = response.json()
            assert response_json == self.test_stats

-    def test_recordings_storage_requires_admin(self):
-        stats = Mock(spec=StatsEmitter)
-        stats.get_latest_stats.return_value = self.test_stats
-        app = super().create_app(stats)
-        app.storage_maintainer = Mock()
-        app.storage_maintainer.calculate_camera_usages.return_value = {
-            "front_door": {"usage": 2.0},
-        }
-
-        with AuthTestClient(app) as client:
-            response = client.get(
-                "/recordings/storage",
-                headers={"remote-user": "viewer", "remote-role": "viewer"},
-            )
-            assert response.status_code == 403
-
-            response = client.get("/recordings/storage")
-            assert response.status_code == 200
-            assert response.json()["front_door"]["usage_percent"] == 25.0
-
    def test_config_set_in_memory_replaces_objects_track_list(self):
        self.minimal_config["cameras"]["front_door"]["objects"] = {
            "track": ["person", "car"],
@@ -219,25 +219,6 @@ class TestHttpApp(BaseTestHttp):
            assert len(events) == 1
            assert events[0]["id"] == event_id

-    def test_similarity_search_hides_unauthorized_anchor_event(self):
-        mock_embeddings = Mock()
-        self.app.frigate_config.semantic_search.enabled = True
-        self.app.embeddings = mock_embeddings
-
-        with AuthTestClient(self.app) as client:
-            super().insert_mock_event("hidden.anchor", camera="back_door")
-            response = client.get(
-                "/events/search",
-                params={
-                    "search_type": "similarity",
-                    "event_id": "hidden.anchor",
-                },
-            )
-
-        assert response.status_code == 404
-        assert response.json()["message"] == "Event not found"
-        mock_embeddings.search_thumbnail.assert_not_called()
-
    def test_get_good_event(self):
        id = "123456.random"

@@ -145,12 +145,9 @@ class TestExecuteFindSimilarObjects(unittest.TestCase):
            embeddings=embeddings,
            frigate_config=SimpleNamespace(
                semantic_search=SimpleNamespace(enabled=semantic_enabled),
-                cameras={"driveway": object()},
-                auth=SimpleNamespace(roles={"admin": [], "viewer": ["driveway"]}),
-                proxy=SimpleNamespace(separator=","),
            ),
        )
-        return SimpleNamespace(app=app, headers={})
+        return SimpleNamespace(app=app)

    def test_semantic_search_disabled_returns_error(self):
        req = self._make_request(semantic_enabled=False)
@@ -183,7 +180,7 @@ class TestExecuteFindSimilarObjects(unittest.TestCase):
            _execute_find_similar_objects(
                req,
                {"event_id": "anchor", "cameras": ["nonexistent_cam"]},
-                allowed_cameras=["driveway"],
+                allowed_cameras=["nonexistent_cam"],
            )
        )
        self.assertEqual(result["results"], [])
@@ -64,9 +64,9 @@ class TestConfig(unittest.TestCase):

    def test_config_class(self):
        frigate_config = FrigateConfig(**self.minimal)
-        assert "ov" in frigate_config.detectors.keys()
-        assert frigate_config.detectors["ov"].type == DetectorTypeEnum.openvino
-        assert frigate_config.detectors["ov"].model.width == 300
+        assert "cpu" in frigate_config.detectors.keys()
+        assert frigate_config.detectors["cpu"].type == DetectorTypeEnum.cpu
+        assert frigate_config.detectors["cpu"].model.width == 320

    @patch("frigate.detectors.detector_config.load_labels")
    def test_detector_custom_model_path(self, mock_labels):
@@ -1005,7 +1005,6 @@ class TestConfig(unittest.TestCase):

        config = {
            "mqtt": {"host": "mqtt"},
-            "detectors": {"cpu": {"type": "cpu"}},
            "model": {"path": "plus://test"},
            "cameras": {
                "back": {
@@ -1,242 +0,0 @@
-"""Tests for the simplified DebugReplayManager.
-
-Startup orchestration lives in ``frigate.jobs.debug_replay`` (covered by
-``test_debug_replay_job``). The manager owns only session presence and
-cleanup.
-"""
-
-import unittest
-import unittest.mock
-from unittest.mock import MagicMock, patch
-
-
-class TestDebugReplayManagerSession(unittest.TestCase):
-    def test_inactive_by_default(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-
-        self.assertFalse(manager.active)
-        self.assertIsNone(manager.replay_camera_name)
-        self.assertIsNone(manager.source_camera)
-        self.assertIsNone(manager.clip_path)
-        self.assertIsNone(manager.start_ts)
-        self.assertIsNone(manager.end_ts)
-
-    def test_mark_starting_sets_session_pointers_and_active(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-
-        manager.mark_starting(
-            source_camera="front",
-            replay_camera_name="_replay_front",
-            start_ts=100.0,
-            end_ts=200.0,
-        )
-
-        self.assertTrue(manager.active)
-        self.assertEqual(manager.replay_camera_name, "_replay_front")
-        self.assertEqual(manager.source_camera, "front")
-        self.assertEqual(manager.start_ts, 100.0)
-        self.assertEqual(manager.end_ts, 200.0)
-        self.assertIsNone(manager.clip_path)
-
-    def test_mark_session_ready_sets_clip_path(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        manager.mark_starting("front", "_replay_front", 100.0, 200.0)
-
-        manager.mark_session_ready(clip_path="/tmp/replay/_replay_front.mp4")
-
-        self.assertEqual(manager.clip_path, "/tmp/replay/_replay_front.mp4")
-        self.assertTrue(manager.active)
-
-    def test_clear_session_resets_all_pointers(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        manager.mark_starting("front", "_replay_front", 100.0, 200.0)
-        manager.mark_session_ready("/tmp/replay/clip.mp4")
-
-        manager.clear_session()
-
-        self.assertFalse(manager.active)
-        self.assertIsNone(manager.replay_camera_name)
-        self.assertIsNone(manager.source_camera)
-        self.assertIsNone(manager.clip_path)
-        self.assertIsNone(manager.start_ts)
-        self.assertIsNone(manager.end_ts)
-
-
-class TestDebugReplayManagerStop(unittest.TestCase):
-    def test_stop_when_inactive_is_a_noop(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        frigate_config = MagicMock()
-        frigate_config.cameras = {}
-        publisher = MagicMock()
-
-        # Should not raise; should not publish any events.
-        manager.stop(frigate_config=frigate_config, config_publisher=publisher)
-
-        publisher.publish_update.assert_not_called()
-
-    def test_stop_publishes_remove_when_camera_was_published(self) -> None:
-        from frigate.config.camera.updater import CameraConfigUpdateEnum
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        manager.mark_starting("front", "_replay_front", 100.0, 200.0)
-        manager.mark_session_ready("/tmp/replay/_replay_front.mp4")
-
-        camera_config = MagicMock()
-        frigate_config = MagicMock()
-        frigate_config.cameras = {"_replay_front": camera_config}
-        publisher = MagicMock()
-
-        with (
-            patch.object(manager, "_cleanup_db"),
-            patch.object(manager, "_cleanup_files"),
-            patch("frigate.debug_replay.cancel_debug_replay_job", return_value=False),
-        ):
-            manager.stop(frigate_config=frigate_config, config_publisher=publisher)
-
-        # One publish_update call with a remove topic.
-        self.assertEqual(publisher.publish_update.call_count, 1)
-        topic_arg = publisher.publish_update.call_args.args[0]
-        self.assertEqual(topic_arg.update_type, CameraConfigUpdateEnum.remove)
-        self.assertFalse(manager.active)
-
-    def test_stop_skips_remove_publish_when_camera_not_in_config(self) -> None:
-        """Cancellation during preparing_clip: no camera was published yet."""
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        manager.mark_starting("front", "_replay_front", 100.0, 200.0)
-        # clip_path stays None because we cancelled before camera publish.
-
-        frigate_config = MagicMock()
-        frigate_config.cameras = {}  # _replay_front not present
-        publisher = MagicMock()
-
-        with (
-            patch.object(manager, "_cleanup_db"),
-            patch.object(manager, "_cleanup_files"),
-            patch("frigate.debug_replay.cancel_debug_replay_job", return_value=True),
-        ):
-            manager.stop(frigate_config=frigate_config, config_publisher=publisher)
-
-        publisher.publish_update.assert_not_called()
-        self.assertFalse(manager.active)
-
-    def test_stop_calls_cancel_debug_replay_job(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        manager.mark_starting("front", "_replay_front", 100.0, 200.0)
-
-        frigate_config = MagicMock()
-        frigate_config.cameras = {}
-        publisher = MagicMock()
-
-        with (
-            patch.object(manager, "_cleanup_db"),
-            patch.object(manager, "_cleanup_files"),
-            patch(
-                "frigate.debug_replay.cancel_debug_replay_job",
-                return_value=True,
-            ) as mock_cancel,
-        ):
-            manager.stop(frigate_config=frigate_config, config_publisher=publisher)
-
-        mock_cancel.assert_called_once()
-
-
-class TestDebugReplayManagerPublishCamera(unittest.TestCase):
-    def test_publish_camera_invokes_publisher_with_add_topic(self) -> None:
-        from frigate.config.camera.updater import CameraConfigUpdateEnum
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-
-        source_config = MagicMock()
-        new_camera_config = MagicMock()
-        frigate_config = MagicMock()
-        frigate_config.cameras = {"front": source_config}
-        publisher = MagicMock()
-
-        with (
-            patch.object(
-                manager,
-                "_build_camera_config_dict",
-                return_value={"enabled": True},
-            ),
-            patch("frigate.debug_replay.find_config_file", return_value="/cfg.yml"),
-            patch("frigate.debug_replay.YAML") as yaml_cls,
-            patch("frigate.debug_replay.FrigateConfig.parse_object") as parse_object,
-            patch("builtins.open", unittest.mock.mock_open(read_data="cameras:\n")),
-        ):
-            yaml_instance = yaml_cls.return_value
-            yaml_instance.load.return_value = {"cameras": {}}
-            parsed = MagicMock()
-            parsed.cameras = {"_replay_front": new_camera_config}
-            parse_object.return_value = parsed
-
-            manager.publish_camera(
-                source_camera="front",
-                replay_name="_replay_front",
-                clip_path="/tmp/clip.mp4",
-                frigate_config=frigate_config,
-                config_publisher=publisher,
-            )
-
-        # Camera registered into the live config dict
-        self.assertIn("_replay_front", frigate_config.cameras)
-        # Publisher invoked with an add topic
-        self.assertEqual(publisher.publish_update.call_count, 1)
-        topic_arg = publisher.publish_update.call_args.args[0]
-        self.assertEqual(topic_arg.update_type, CameraConfigUpdateEnum.add)
-
-    def test_publish_camera_wraps_parse_failure_in_runtime_error(self) -> None:
-        from frigate.debug_replay import DebugReplayManager
-
-        manager = DebugReplayManager()
-        frigate_config = MagicMock()
-        frigate_config.cameras = {"front": MagicMock()}
-        publisher = MagicMock()
-
-        with (
-            patch.object(
-                manager,
-                "_build_camera_config_dict",
-                return_value={"enabled": True},
-            ),
-            patch("frigate.debug_replay.find_config_file", return_value="/cfg.yml"),
-            patch("frigate.debug_replay.YAML") as yaml_cls,
-            patch(
-                "frigate.debug_replay.FrigateConfig.parse_object",
-                side_effect=ValueError("zone foo has invalid coordinates"),
-            ),
-            patch("builtins.open", unittest.mock.mock_open(read_data="cameras:\n")),
-        ):
-            yaml_cls.return_value.load.return_value = {"cameras": {}}
-
-            with self.assertRaises(RuntimeError) as ctx:
-                manager.publish_camera(
-                    source_camera="front",
-                    replay_name="_replay_front",
-                    clip_path="/tmp/clip.mp4",
-                    frigate_config=frigate_config,
-                    config_publisher=publisher,
-                )
-
-        self.assertIn("replay camera config", str(ctx.exception))
-        self.assertIn("invalid coordinates", str(ctx.exception))
-        publisher.publish_update.assert_not_called()
-
-
-if __name__ == "__main__":
-    unittest.main()
@@ -1,460 +0,0 @@
-"""Tests for the debug replay job runner and factory."""
-
-import threading
-import time
-import unittest
-import unittest.mock
-from unittest.mock import MagicMock, patch
-
-from frigate.debug_replay import DebugReplayManager
-from frigate.jobs.debug_replay import (
-    DebugReplayJob,
-    cancel_debug_replay_job,
-    get_active_runner,
-    start_debug_replay_job,
-)
-from frigate.jobs.export import JobStatePublisher
-from frigate.jobs.manager import _completed_jobs, _current_jobs
-from frigate.types import JobStatusTypesEnum
-
-
-def _reset_job_manager() -> None:
-    """Clear the global job manager state between tests."""
-    _current_jobs.clear()
-    _completed_jobs.clear()
-
-
-def _patch_publisher(test_case: unittest.TestCase) -> None:
-    """Replace JobStatePublisher.publish with a no-op to avoid hanging on IPC."""
-    publisher_patch = patch.object(
-        JobStatePublisher, "publish", lambda self, payload: None
-    )
-    publisher_patch.start()
-    test_case.addCleanup(publisher_patch.stop)
-
-
-class TestDebugReplayJob(unittest.TestCase):
-    def test_default_fields(self) -> None:
-        job = DebugReplayJob()
-
-        self.assertEqual(job.job_type, "debug_replay")
-        self.assertEqual(job.status, JobStatusTypesEnum.queued)
-        self.assertIsNone(job.current_step)
-        self.assertEqual(job.progress_percent, 0.0)
-
-    def test_to_dict_whitelist(self) -> None:
-        job = DebugReplayJob(
-            source_camera="front",
-            replay_camera_name="_replay_front",
-            start_ts=100.0,
-            end_ts=200.0,
-        )
-        job.current_step = "preparing_clip"
-        job.progress_percent = 42.5
-
-        payload = job.to_dict()
-
-        # Top-level matches the standard Job<TResults> shape.
-        for key in (
-            "id",
-            "job_type",
-            "status",
-            "start_time",
-            "end_time",
-            "error_message",
-            "results",
-        ):
-            self.assertIn(key, payload, f"missing top-level field: {key}")
-
-        results = payload["results"]
-        self.assertEqual(results["source_camera"], "front")
-        self.assertEqual(results["replay_camera_name"], "_replay_front")
-        self.assertEqual(results["current_step"], "preparing_clip")
-        self.assertEqual(results["progress_percent"], 42.5)
-        self.assertEqual(results["start_ts"], 100.0)
-        self.assertEqual(results["end_ts"], 200.0)
-
-
-class TestStartDebugReplayJob(unittest.TestCase):
-    def setUp(self) -> None:
-        _reset_job_manager()
-        _patch_publisher(self)
-        self.manager = DebugReplayManager()
-        self.frigate_config = MagicMock()
-        self.frigate_config.cameras = {"front": MagicMock()}
-        self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
-        self.publisher = MagicMock()
-
-        self.recordings_qs = MagicMock()
-        self.recordings_qs.count.return_value = 1
-        self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
-
-    def tearDown(self) -> None:
-        runner = get_active_runner()
-        if runner is not None:
-            runner.cancel()
-            runner.join(timeout=2.0)
-        _reset_job_manager()
-
-    def test_rejects_unknown_camera(self) -> None:
-        with self.assertRaises(ValueError):
-            start_debug_replay_job(
-                source_camera="missing",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-    def test_rejects_invalid_time_range(self) -> None:
-        with self.assertRaises(ValueError):
-            start_debug_replay_job(
-                source_camera="front",
-                start_ts=200.0,
-                end_ts=100.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-    def test_rejects_when_no_recordings(self) -> None:
-        empty_qs = MagicMock()
-        empty_qs.count.return_value = 0
-        with patch("frigate.jobs.debug_replay.query_recordings", return_value=empty_qs):
-            with self.assertRaises(ValueError):
-                start_debug_replay_job(
-                    source_camera="front",
-                    start_ts=100.0,
-                    end_ts=200.0,
-                    frigate_config=self.frigate_config,
-                    config_publisher=self.publisher,
-                    replay_manager=self.manager,
-                )
-
-    def test_returns_job_id_and_marks_session_starting(self) -> None:
-        block = threading.Event()
-
-        def slow_helper(cmd, **kwargs):
-            block.wait(timeout=5)
-            return 0, ""
-
-        with (
-            patch(
-                "frigate.jobs.debug_replay.query_recordings",
-                return_value=self.recordings_qs,
-            ),
-            patch(
-                "frigate.jobs.debug_replay.run_ffmpeg_with_progress",
-                side_effect=slow_helper,
-            ),
-            patch.object(self.manager, "publish_camera"),
-            patch("os.path.exists", return_value=True),
-            patch("os.makedirs"),
-            patch("builtins.open", unittest.mock.mock_open()),
-        ):
-            job_id = start_debug_replay_job(
-                source_camera="front",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-            self.assertIsInstance(job_id, str)
-            self.assertTrue(self.manager.active)
-            self.assertEqual(self.manager.replay_camera_name, "_replay_front")
-            self.assertEqual(self.manager.source_camera, "front")
-
-            block.set()
-
-    def test_rejects_concurrent_calls(self) -> None:
-        block = threading.Event()
-
-        def slow_helper(cmd, **kwargs):
-            block.wait(timeout=5)
-            return 0, ""
-
-        with (
-            patch(
-                "frigate.jobs.debug_replay.query_recordings",
-                return_value=self.recordings_qs,
-            ),
-            patch(
-                "frigate.jobs.debug_replay.run_ffmpeg_with_progress",
-                side_effect=slow_helper,
-            ),
-            patch.object(self.manager, "publish_camera"),
-            patch("os.path.exists", return_value=True),
-            patch("os.makedirs"),
-            patch("builtins.open", unittest.mock.mock_open()),
-        ):
-            start_debug_replay_job(
-                source_camera="front",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-            with self.assertRaises(RuntimeError):
-                start_debug_replay_job(
-                    source_camera="front",
-                    start_ts=100.0,
-                    end_ts=200.0,
-                    frigate_config=self.frigate_config,
-                    config_publisher=self.publisher,
-                    replay_manager=self.manager,
-                )
-
-            block.set()
-
-
-class TestRunnerHappyPath(unittest.TestCase):
-    def setUp(self) -> None:
-        _reset_job_manager()
-        _patch_publisher(self)
-        self.manager = DebugReplayManager()
-        self.frigate_config = MagicMock()
-        self.frigate_config.cameras = {"front": MagicMock()}
-        self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
-        self.publisher = MagicMock()
-
-        self.recordings_qs = MagicMock()
-        self.recordings_qs.count.return_value = 1
-        self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
-
-    def tearDown(self) -> None:
-        runner = get_active_runner()
-        if runner is not None:
-            runner.cancel()
-            runner.join(timeout=2.0)
-        _reset_job_manager()
-
-    def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
-        deadline = time.time() + timeout
-        while time.time() < deadline:
-            if predicate():
-                return True
-            time.sleep(0.02)
-        return False
-
-    def test_progress_callback_updates_job_percent(self) -> None:
-        captured: list[float] = []
-
-        def fake_helper(cmd, *, on_progress=None, **kwargs):
-            on_progress(0.0)
-            on_progress(50.0)
-            on_progress(100.0)
-            return 0, ""
-
-        with (
-            patch(
-                "frigate.jobs.debug_replay.query_recordings",
-                return_value=self.recordings_qs,
-            ),
-            patch(
-                "frigate.jobs.debug_replay.run_ffmpeg_with_progress",
-                side_effect=fake_helper,
-            ),
-            patch.object(
-                self.manager,
-                "publish_camera",
-                side_effect=lambda *a, **kw: captured.append("published"),
-            ),
-            patch("os.path.exists", return_value=True),
-            patch("os.makedirs"),
-            patch("builtins.open", unittest.mock.mock_open()),
-        ):
-            start_debug_replay_job(
-                source_camera="front",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-            self.assertTrue(
-                self._wait_for(lambda: get_active_runner() is None),
-                "runner did not finish",
-            )
-
-        from frigate.jobs.manager import get_current_job
-
-        job = get_current_job("debug_replay")
-        self.assertIsNotNone(job)
-        self.assertEqual(job.status, JobStatusTypesEnum.success)
-        self.assertEqual(job.progress_percent, 100.0)
-        self.assertEqual(captured, ["published"])
-        # Manager should have been told the session is ready with the clip path.
-        self.assertIsNotNone(self.manager.clip_path)
-
-
-class TestRunnerFailurePath(unittest.TestCase):
-    def setUp(self) -> None:
-        _reset_job_manager()
-        _patch_publisher(self)
-        self.manager = DebugReplayManager()
-        self.frigate_config = MagicMock()
-        self.frigate_config.cameras = {"front": MagicMock()}
-        self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
-        self.publisher = MagicMock()
-        self.recordings_qs = MagicMock()
-        self.recordings_qs.count.return_value = 1
-        self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
-
-    def tearDown(self) -> None:
-        runner = get_active_runner()
-        if runner is not None:
-            runner.cancel()
-            runner.join(timeout=2.0)
-        _reset_job_manager()
-
-    def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
-        deadline = time.time() + timeout
-        while time.time() < deadline:
-            if predicate():
-                return True
-            time.sleep(0.02)
-        return False
-
-    def test_ffmpeg_failure_marks_job_failed_and_clears_session(self) -> None:
-        def failing_helper(cmd, **kwargs):
-            return 1, "ffmpeg exploded"
-
-        with (
-            patch(
-                "frigate.jobs.debug_replay.query_recordings",
-                return_value=self.recordings_qs,
-            ),
-            patch(
-                "frigate.jobs.debug_replay.run_ffmpeg_with_progress",
-                side_effect=failing_helper,
-            ),
-            patch("os.path.exists", return_value=True),
-            patch("os.makedirs"),
-            patch("os.remove"),
-            patch("builtins.open", unittest.mock.mock_open()),
-        ):
-            start_debug_replay_job(
-                source_camera="front",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-            self.assertTrue(
-                self._wait_for(lambda: get_active_runner() is None),
-                "runner did not finish",
-            )
-
-        from frigate.jobs.manager import get_current_job
-
-        job = get_current_job("debug_replay")
-        self.assertIsNotNone(job)
-        self.assertEqual(job.status, JobStatusTypesEnum.failed)
-        self.assertIsNotNone(job.error_message)
-        self.assertIn("ffmpeg", job.error_message.lower())
-        # Session cleared so a new /start is allowed
-        self.assertFalse(self.manager.active)
-
-
-class TestRunnerCancellation(unittest.TestCase):
-    def setUp(self) -> None:
-        _reset_job_manager()
-        _patch_publisher(self)
-        self.manager = DebugReplayManager()
-        self.frigate_config = MagicMock()
-        self.frigate_config.cameras = {"front": MagicMock()}
-        self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
-        self.publisher = MagicMock()
-        self.recordings_qs = MagicMock()
-        self.recordings_qs.count.return_value = 1
-        self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
-
-    def tearDown(self) -> None:
-        runner = get_active_runner()
-        if runner is not None:
-            runner.cancel()
-            runner.join(timeout=2.0)
-        _reset_job_manager()
-
-    def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
-        deadline = time.time() + timeout
-        while time.time() < deadline:
-            if predicate():
-                return True
-            time.sleep(0.02)
-        return False
-
-    def test_cancel_terminates_ffmpeg_and_marks_cancelled(self) -> None:
-        terminated = threading.Event()
-        fake_proc = MagicMock()
-        fake_proc.terminate = MagicMock(side_effect=lambda: terminated.set())
-
-        def fake_helper(cmd, *, process_started=None, **kwargs):
-            if process_started is not None:
-                process_started(fake_proc)
-            terminated.wait(timeout=5)
-            return -15, "killed"
-
-        with (
-            patch(
-                "frigate.jobs.debug_replay.query_recordings",
-                return_value=self.recordings_qs,
-            ),
-            patch(
-                "frigate.jobs.debug_replay.run_ffmpeg_with_progress",
-                side_effect=fake_helper,
-            ),
-            patch("os.path.exists", return_value=True),
-            patch("os.makedirs"),
-            patch("os.remove"),
-            patch("builtins.open", unittest.mock.mock_open()),
-        ):
-            start_debug_replay_job(
-                source_camera="front",
-                start_ts=100.0,
-                end_ts=200.0,
-                frigate_config=self.frigate_config,
-                config_publisher=self.publisher,
-                replay_manager=self.manager,
-            )
-
-            # Wait for the runner to register the active process.
-            self.assertTrue(
-                self._wait_for(
-                    lambda: (
-                        get_active_runner() is not None
-                        and get_active_runner()._active_process is fake_proc
-                    )
-                )
-            )
-
-            cancelled = cancel_debug_replay_job()
-            self.assertTrue(cancelled)
-            self.assertTrue(fake_proc.terminate.called)
-
-            self.assertTrue(
-                self._wait_for(lambda: get_active_runner() is None),
-                "runner did not finish",
-            )
-
-        from frigate.jobs.manager import get_current_job
-
-        job = get_current_job("debug_replay")
-        self.assertEqual(job.status, JobStatusTypesEnum.cancelled)
-        # Runner must not clear the manager session on cancellation —
-        # that belongs to the caller of cancel_debug_replay_job (stop()).
-        # If the runner cleared it, stop() would log "no active session"
-        # and skip its cleanup_db / cleanup_files calls.
-        self.assertTrue(self.manager.active)
-
-
-if __name__ == "__main__":
-    unittest.main()
@@ -1,9 +1,6 @@
 """Tests for export progress tracking, broadcast, and FFmpeg parsing."""

 import io
-import os
-import shutil
-import tempfile
 import unittest
 from unittest.mock import MagicMock, patch

@@ -14,7 +11,6 @@ from frigate.jobs.export import (
 )
 from frigate.record.export import PlaybackSourceEnum, RecordingExporter
 from frigate.types import JobStatusTypesEnum
-from frigate.util.ffmpeg import inject_progress_flags


 def _make_exporter(
@@ -119,9 +115,10 @@ class TestExpectedOutputDuration(unittest.TestCase):

 class TestProgressFlagInjection(unittest.TestCase):
    def test_inserts_before_output_path(self) -> None:
+        exporter = _make_exporter()
        cmd = ["ffmpeg", "-i", "input.m3u8", "-c", "copy", "/tmp/output.mp4"]

-        result = inject_progress_flags(cmd)
+        result = exporter._inject_progress_flags(cmd)

        assert result == [
            "ffmpeg",
@@ -136,7 +133,8 @@ class TestProgressFlagInjection(unittest.TestCase):
        ]

    def test_handles_empty_cmd(self) -> None:
-        assert inject_progress_flags([]) == []
+        exporter = _make_exporter()
+        assert exporter._inject_progress_flags([]) == []


 class TestFfmpegProgressParsing(unittest.TestCase):
@@ -166,7 +164,7 @@ class TestFfmpegProgressParsing(unittest.TestCase):
        fake_proc.returncode = 0
        fake_proc.wait = MagicMock(return_value=0)

-        with patch("frigate.util.ffmpeg.sp.Popen", return_value=fake_proc):
+        with patch("frigate.record.export.sp.Popen", return_value=fake_proc):
            returncode, _stderr = exporter._run_ffmpeg_with_progress(
                ["ffmpeg", "-i", "x.m3u8", "/tmp/out.mp4"], "playlist", step="encoding"
            )
@@ -365,121 +363,6 @@ class TestBroadcastAggregation(unittest.TestCase):
        assert job.progress_percent == 33.0


-class TestGetDatetimeFromTimestamp(unittest.TestCase):
-    """Auto-generated export name should honor config.ui.timezone, not
-    fall back to the container's UTC clock when a timezone is configured.
-    """
-
-    def test_uses_configured_ui_timezone(self) -> None:
-        exporter = _make_exporter()
-        exporter.config.ui.timezone = "America/New_York"
-        # 2025-01-15 12:00:00 UTC is 07:00:00 EST
-        assert exporter.get_datetime_from_timestamp(1736942400) == "2025-01-15 07:00:00"
-
-    def test_falls_back_to_local_when_timezone_unset(self) -> None:
-        exporter = _make_exporter()
-        exporter.config.ui.timezone = None
-        # No assertion on the exact wall-clock value — just confirm no
-        # exception and that pytz isn't required when the field is unset.
-        assert isinstance(exporter.get_datetime_from_timestamp(1736942400), str)
-
-    def test_invalid_timezone_falls_back_to_local(self) -> None:
-        exporter = _make_exporter()
-        exporter.config.ui.timezone = "Not/A_Real_Zone"
-        assert isinstance(exporter.get_datetime_from_timestamp(1736942400), str)
-
-
-class TestSaveThumbnailFromPreviewFrames(unittest.TestCase):
-    """Short exports in the current hour can fall between preview frame
-    writes (1-2 fps during activity, every 30s otherwise). When no frame
-    falls inside the export window, save_thumbnail should fall back to
-    the most recent prior frame instead of returning no thumbnail."""
-
-    def setUp(self) -> None:
-        self.tmp_root = tempfile.mkdtemp(prefix="frigate_thumb_test_")
-        self.preview_dir = os.path.join(self.tmp_root, "cache", "preview_frames")
-        self.export_clips = os.path.join(self.tmp_root, "clips", "export")
-        os.makedirs(self.preview_dir, exist_ok=True)
-        os.makedirs(self.export_clips, exist_ok=True)
-
-    def tearDown(self) -> None:
-        shutil.rmtree(self.tmp_root, ignore_errors=True)
-
-    def _write_frame(self, camera: str, frame_time: float) -> str:
-        path = os.path.join(self.preview_dir, f"preview_{camera}-{frame_time}.webp")
-        with open(path, "wb") as f:
-            f.write(b"fake-webp-bytes")
-        return path
-
-    def _make_short_current_hour_exporter(self) -> RecordingExporter:
-        # Use a "now-ish" timestamp so save_thumbnail's start-of-hour
-        # comparison takes the current-hour branch (preview frames).
-        import datetime
-
-        now = datetime.datetime.now(datetime.timezone.utc).timestamp()
-        exporter = _make_exporter()
-        exporter.export_id = "thumb_short"
-        exporter.start_time = now
-        exporter.end_time = now + 3
-        return exporter
-
-    def test_short_export_falls_back_to_prior_preview_frame(self) -> None:
-        exporter = self._make_short_current_hour_exporter()
-        # Most recent preview frame is 10s before the export window
-        prior = self._write_frame(exporter.camera, exporter.start_time - 10.0)
-        thumb_target = os.path.join(self.export_clips, f"{exporter.export_id}.webp")
-
-        with (
-            patch(
-                "frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
-            ),
-            patch(
-                "frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
-            ),
-        ):
-            result = exporter.save_thumbnail(exporter.export_id)
-
-        assert result == thumb_target
-        assert os.path.isfile(thumb_target)
-        with open(thumb_target, "rb") as f, open(prior, "rb") as src:
-            assert f.read() == src.read()
-
-    def test_returns_empty_when_no_preview_frames_exist(self) -> None:
-        exporter = self._make_short_current_hour_exporter()
-
-        with (
-            patch(
-                "frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
-            ),
-            patch(
-                "frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
-            ),
-        ):
-            result = exporter.save_thumbnail(exporter.export_id)
-
-        assert result == ""
-
-    def test_prefers_in_window_frame_over_prior_frame(self) -> None:
-        exporter = self._make_short_current_hour_exporter()
-        self._write_frame(exporter.camera, exporter.start_time - 10.0)
-        in_window = self._write_frame(exporter.camera, exporter.start_time + 1.0)
-        thumb_target = os.path.join(self.export_clips, f"{exporter.export_id}.webp")
-
-        with (
-            patch(
-                "frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
-            ),
-            patch(
-                "frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
-            ),
-        ):
-            result = exporter.save_thumbnail(exporter.export_id)
-
-        assert result == thumb_target
-        with open(thumb_target, "rb") as f, open(in_window, "rb") as src:
-            assert f.read() == src.read()
-
-
 class TestSchedulesCleanup(unittest.TestCase):
    def test_schedule_job_cleanup_removes_after_delay(self) -> None:
        config = MagicMock()
@@ -498,56 +381,5 @@ class TestSchedulesCleanup(unittest.TestCase):
            assert job.id not in manager.jobs


-class TestChapterMetadataInProgressReview(unittest.TestCase):
-    """Regression: in-progress review segments have end_time=NULL until the
-    activity closes. The chapter builder must clamp the chapter end to the
-    last recorded second instead of crashing on float(None)."""
-
-    def _fake_select_returning(self, rows: list) -> MagicMock:
-        mock_query = MagicMock()
-        mock_query.where.return_value = mock_query
-        mock_query.order_by.return_value = mock_query
-        mock_query.iterator.return_value = iter(rows)
-        return mock_query
-
-    def test_in_progress_review_does_not_crash_and_clamps_to_last_recording(
-        self,
-    ) -> None:
-        exporter = _make_exporter(end_minus_start=200)
-        # Recordings cover [1000, 1150]; export window is [1000, 1200] so
-        # the last recorded second is 1150 (a 50s gap at the tail).
-        recordings = [
-            MagicMock(start_time=1000.0, end_time=1150.0),
-        ]
-        in_progress = MagicMock(
-            start_time=1100.0,
-            end_time=None,
-            severity="alert",
-            data={"objects": ["person"]},
-        )
-
-        with tempfile.TemporaryDirectory() as tmpdir:
-            chapter_path = os.path.join(tmpdir, "chapters.txt")
-            exporter._chapter_metadata_path = lambda: chapter_path  # type: ignore[method-assign]
-
-            with patch(
-                "frigate.record.export.ReviewSegment.select",
-                return_value=self._fake_select_returning([in_progress]),
-            ):
-                result = exporter._build_chapter_metadata_file(recordings)
-
-            assert result == chapter_path
-            with open(chapter_path) as f:
-                content = f.read()
-
-        # Output time is windows[-1][1] - windows[-1][0] = 150s.
-        # Review starts at wall=1100, output offset = 100s -> 100000ms.
-        # Clamped end = last_recorded_end (1150) -> output offset = 150s -> 150000ms.
-        assert "[CHAPTER]" in content
-        assert "START=100000" in content
-        assert "END=150000" in content
-        assert "title=Alert: person" in content
-
-
 if __name__ == "__main__":
    unittest.main()
@@ -1,111 +0,0 @@
-"""Tests for the shared ffmpeg progress helper."""
-
-import unittest
-from unittest.mock import MagicMock, patch
-
-from frigate.util.ffmpeg import inject_progress_flags, run_ffmpeg_with_progress
-
-
-class TestInjectProgressFlags(unittest.TestCase):
-    def test_inserts_flags_before_output_path(self):
-        cmd = ["ffmpeg", "-i", "in.mp4", "-c", "copy", "out.mp4"]
-        result = inject_progress_flags(cmd)
-        self.assertEqual(
-            result,
-            [
-                "ffmpeg",
-                "-i",
-                "in.mp4",
-                "-c",
-                "copy",
-                "-progress",
-                "pipe:2",
-                "-nostats",
-                "out.mp4",
-            ],
-        )
-
-    def test_empty_cmd_returns_empty(self):
-        self.assertEqual(inject_progress_flags([]), [])
-
-
-class TestRunFfmpegWithProgress(unittest.TestCase):
-    def _make_fake_proc(self, stderr_lines, returncode=0):
-        proc = MagicMock()
-        proc.stderr = iter(stderr_lines)
-        proc.stdin = MagicMock()
-        proc.returncode = returncode
-        proc.wait = MagicMock()
-        return proc
-
-    def test_emits_percent_from_out_time_us_lines(self):
-        captured: list[float] = []
-
-        def on_progress(percent: float) -> None:
-            captured.append(percent)
-
-        stderr_lines = [
-            "out_time_us=1000000\n",
-            "out_time_us=5000000\n",
-            "progress=end\n",
-        ]
-        proc = self._make_fake_proc(stderr_lines)
-        proc.stderr = MagicMock()
-        proc.stderr.__iter__ = lambda self: iter(stderr_lines)
-        proc.stderr.read = MagicMock(return_value="")
-
-        with patch("subprocess.Popen", return_value=proc):
-            returncode, _stderr = run_ffmpeg_with_progress(
-                ["ffmpeg", "-i", "in", "out"],
-                expected_duration_seconds=10.0,
-                on_progress=on_progress,
-                use_low_priority=False,
-            )
-
-        self.assertEqual(returncode, 0)
-        self.assertEqual(len(captured), 4)  # initial 0.0 + two parsed + final 100.0
-        self.assertAlmostEqual(captured[0], 0.0)
-        self.assertAlmostEqual(captured[1], 10.0)
-        self.assertAlmostEqual(captured[2], 50.0)
-        self.assertAlmostEqual(captured[3], 100.0)
-
-    def test_passes_started_process_to_callback(self):
-        proc = self._make_fake_proc([])
-        proc.stderr = MagicMock()
-        proc.stderr.__iter__ = lambda self: iter([])
-        proc.stderr.read = MagicMock(return_value="")
-
-        seen: list = []
-
-        with patch("subprocess.Popen", return_value=proc):
-            run_ffmpeg_with_progress(
-                ["ffmpeg", "out"],
-                expected_duration_seconds=1.0,
-                process_started=lambda p: seen.append(p),
-                use_low_priority=False,
-            )
-
-        self.assertEqual(seen, [proc])
-
-    def test_clamps_percent_to_0_100(self):
-        captured: list[float] = []
-
-        def on_progress(percent: float) -> None:
-            captured.append(percent)
-
-        stderr_lines = ["out_time_us=999999999999\n"]
-        proc = self._make_fake_proc(stderr_lines)
-        proc.stderr = MagicMock()
-        proc.stderr.__iter__ = lambda self: iter(stderr_lines)
-        proc.stderr.read = MagicMock(return_value="")
-
-        with patch("subprocess.Popen", return_value=proc):
-            run_ffmpeg_with_progress(
-                ["ffmpeg", "out"],
-                expected_duration_seconds=10.0,
-                on_progress=on_progress,
-                use_low_priority=False,
-            )
-
-        # initial 0.0 then a clamped reading
-        self.assertEqual(captured[-1], 100.0)
@@ -7,6 +7,8 @@ from frigate.util.services import get_amd_gpu_stats, get_intel_gpu_stats
 class TestGpuStats(unittest.TestCase):
    def setUp(self):
        self.amd_results = "Unknown Radeon card. <= R500 won't work, new cards might.\nDumping to -, line limit 1.\n1664070990.607556: bus 10, gpu 4.17%, ee 0.00%, vgt 0.00%, ta 0.00%, tc 0.00%, sx 0.00%, sh 0.00%, spi 0.83%, smx 0.00%, cr 0.00%, sc 0.00%, pa 0.00%, db 0.00%, cb 0.00%, vram 60.37% 294.04mb, gtt 0.33% 52.21mb, mclk 100.00% 1.800ghz, sclk 26.65% 0.533ghz\n"
+        self.intel_results = """{"period":{"duration":1.194033,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":3349.991164,"unit":"irq/s"},"rc6":{"value":47.844741,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":4.533124,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":6.194385,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}},{"period":{"duration":1.189291,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":0.000000,"unit":"irq/s"},"rc6":{"value":100.000000,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}}"""
+        self.nvidia_results = "name, utilization.gpu [%], memory.used [MiB], memory.total [MiB]\nNVIDIA GeForce RTX 3050, 42 %, 5036 MiB, 8192 MiB\n"

    @patch("subprocess.run")
    def test_amd_gpu_stats(self, sp):
@@ -17,76 +19,32 @@ class TestGpuStats(unittest.TestCase):
        amd_stats = get_amd_gpu_stats()
        assert amd_stats == {"gpu": "4.17%", "mem": "60.37%"}

-    @patch("frigate.util.services.time.sleep")
-    @patch("frigate.util.services.time.monotonic")
-    @patch("frigate.util.services._read_intel_drm_fdinfo")
-    def test_intel_gpu_stats_fdinfo(self, read_fdinfo, monotonic, sleep):
-        # 1 second of wall clock between snapshots
-        monotonic.side_effect = [0.0, 1.0]
+    # @patch("subprocess.run")
+    # def test_nvidia_gpu_stats(self, sp):
+    #    process = MagicMock()
+    #    process.returncode = 0
+    #    process.stdout = self.nvidia_results
+    #    sp.return_value = process
+    #    nvidia_stats = get_nvidia_gpu_stats()
+    #    assert nvidia_stats == {
+    #        "name": "NVIDIA GeForce RTX 3050",
+    #        "gpu": "42 %",
+    #        "mem": "61.5 %",
+    #    }

-        # Two i915 clients on the same iGPU. Engine values are cumulative ns.
-        # Deltas over the 1s window:
-        #   client A (pid 100): render +200_000_000 (20%), video +500_000_000 (50%),
-        #                       video-enhance +100_000_000 (10%)
-        #   client B (pid 200): compute +100_000_000 (10%)
-        # Engine totals → render 20, video 50, video-enhance 10, compute 10
-        # → compute = render + compute = 30
-        # → dec = video + video-enhance = 60
-        # → gpu = compute + dec = 90
-        snapshot_a = {
-            ("0000:00:02.0", "1", "100"): {
-                "driver": "i915",
-                "pid": "100",
-                "engines": {
-                    "render": (1_000_000_000, 0),
-                    "video": (5_000_000_000, 0),
-                    "video-enhance": (200_000_000, 0),
-                    "compute": (0, 0),
-                },
-            },
-            ("0000:00:02.0", "2", "200"): {
-                "driver": "i915",
-                "pid": "200",
-                "engines": {
-                    "render": (0, 0),
-                    "compute": (2_000_000_000, 0),
-                },
-            },
-        }
-        snapshot_b = {
-            ("0000:00:02.0", "1", "100"): {
-                "driver": "i915",
-                "pid": "100",
-                "engines": {
-                    "render": (1_200_000_000, 0),
-                    "video": (5_500_000_000, 0),
-                    "video-enhance": (300_000_000, 0),
-                    "compute": (0, 0),
-                },
-            },
-            ("0000:00:02.0", "2", "200"): {
-                "driver": "i915",
-                "pid": "200",
-                "engines": {
-                    "render": (0, 0),
-                    "compute": (2_100_000_000, 0),
-                },
-            },
-        }
-        read_fdinfo.side_effect = [snapshot_a, snapshot_b]
-
-        intel_stats = get_intel_gpu_stats(None)
-
-        sleep.assert_called_once()
+    @patch("subprocess.run")
+    def test_intel_gpu_stats(self, sp):
+        process = MagicMock()
+        process.returncode = 124
+        process.stdout = self.intel_results
+        sp.return_value = process
+        intel_stats = get_intel_gpu_stats(False)
+        # rc6 values: 47.844741 and 100.0 → avg 73.92 → gpu = 100 - 73.92 = 26.08%
+        # Render/3D/0: 0.0 and 0.0 → enc = 0.0%
+        # Video/0: 4.533124 and 0.0 → dec = 2.27%
        assert intel_stats == {
-            "gpu": "90.0%",
+            "gpu": "26.08%",
            "mem": "-%",
-            "compute": "30.0%",
-            "dec": "60.0%",
-            "clients": {"100": "80.0%", "200": "10.0%"},
+            "compute": "0.0%",
+            "dec": "2.27%",
        }
-
-    @patch("frigate.util.services._read_intel_drm_fdinfo")
-    def test_intel_gpu_stats_no_clients(self, read_fdinfo):
-        read_fdinfo.return_value = {}
-        assert get_intel_gpu_stats(None) is None
@@ -1,57 +0,0 @@
-"""Tests for JSMPEG websocket authorization."""
-
-import unittest
-from types import SimpleNamespace
-
-from frigate.config import FrigateConfig
-from frigate.output.ws_auth import ws_has_camera_access
-
-
-class TestWsHasCameraAccess(unittest.TestCase):
-    def setUp(self):
-        self.config = FrigateConfig(
-            mqtt={"host": "mqtt"},
-            auth={"roles": {"limited_user": ["front_door"]}},
-            cameras={
-                "front_door": {
-                    "ffmpeg": {
-                        "inputs": [
-                            {"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
-                        ]
-                    },
-                    "detect": {"height": 1080, "width": 1920, "fps": 5},
-                },
-                "back_door": {
-                    "ffmpeg": {
-                        "inputs": [
-                            {"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]}
-                        ]
-                    },
-                    "detect": {"height": 1080, "width": 1920, "fps": 5},
-                },
-            },
-        )
-
-    def _make_ws(self, role: str):
-        return SimpleNamespace(environ={"HTTP_REMOTE_ROLE": role})
-
-    def test_restricted_role_only_gets_allowed_camera(self):
-        ws = self._make_ws("limited_user")
-        self.assertTrue(ws_has_camera_access(ws, "front_door", self.config))
-        self.assertFalse(ws_has_camera_access(ws, "back_door", self.config))
-
-    def test_unrestricted_role_can_access_any_camera(self):
-        ws = self._make_ws("viewer")
-        self.assertTrue(ws_has_camera_access(ws, "front_door", self.config))
-        self.assertTrue(ws_has_camera_access(ws, "back_door", self.config))
-
-    def test_birdseye_requires_unrestricted_access(self):
-        self.assertTrue(
-            ws_has_camera_access(self._make_ws("admin"), "birdseye", self.config)
-        )
-        self.assertTrue(
-            ws_has_camera_access(self._make_ws("viewer"), "birdseye", self.config)
-        )
-        self.assertFalse(
-            ws_has_camera_access(self._make_ws("limited_user"), "birdseye", self.config)
-        )
@@ -1,29 +0,0 @@
-"""Tests for camera monitoring notification authorization."""
-
-import unittest
-from types import SimpleNamespace
-from unittest.mock import MagicMock
-
-from frigate.comms.webpush import WebPushClient
-
-
-class TestCameraMonitoringNotifications(unittest.TestCase):
-    def test_send_camera_monitoring_filters_by_camera_access(self):
-        client = WebPushClient.__new__(WebPushClient)
-        client.config = SimpleNamespace(
-            cameras={"front_door": SimpleNamespace(friendly_name=None)}
-        )
-        client.web_pushers = {"allowed": [], "denied": []}
-        client.user_cameras = {"allowed": {"front_door"}, "denied": set()}
-        client.check_registrations = MagicMock()
-        client.cleanup_registrations = MagicMock()
-        client.send_push_notification = MagicMock()
-
-        client.send_camera_monitoring(
-            {"camera": "front_door", "message": "Monitoring condition met"}
-        )
-
-        self.assertEqual(client.send_push_notification.call_count, 1)
-        self.assertEqual(
-            client.send_push_notification.call_args.kwargs["user"], "allowed"
-        )
@@ -1,166 +0,0 @@
-"""Tests for WebSocket authorization checks."""
-
-import unittest
-
-from frigate.comms.ws import _check_ws_authorization
-from frigate.const import INSERT_MANY_RECORDINGS, UPDATE_CAMERA_ACTIVITY
-
-
-class TestCheckWsAuthorization(unittest.TestCase):
-    """Tests for the _check_ws_authorization pure function."""
-
-    DEFAULT_SEPARATOR = ","
-
-    # --- IPC topic blocking (unconditional, regardless of role) ---
-
-    def test_ipc_topic_blocked_for_admin(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                INSERT_MANY_RECORDINGS, "admin", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_ipc_topic_blocked_for_viewer(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                UPDATE_CAMERA_ACTIVITY, "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_ipc_topic_blocked_when_no_role(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                INSERT_MANY_RECORDINGS, None, self.DEFAULT_SEPARATOR
-            )
-        )
-
-    # --- Viewer allowed topics ---
-
-    def test_viewer_can_send_on_connect(self):
-        self.assertTrue(
-            _check_ws_authorization("onConnect", "viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_viewer_can_send_model_state(self):
-        self.assertTrue(
-            _check_ws_authorization("modelState", "viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_viewer_can_send_audio_transcription_state(self):
-        self.assertTrue(
-            _check_ws_authorization(
-                "audioTranscriptionState", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_viewer_can_send_birdseye_layout(self):
-        self.assertTrue(
-            _check_ws_authorization("birdseyeLayout", "viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_viewer_can_send_embeddings_reindex_progress(self):
-        self.assertTrue(
-            _check_ws_authorization(
-                "embeddingsReindexProgress", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    # --- Viewer blocked from admin topics ---
-
-    def test_viewer_blocked_from_restart(self):
-        self.assertFalse(
-            _check_ws_authorization("restart", "viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_viewer_blocked_from_camera_detect_set(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                "front_door/detect/set", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_viewer_blocked_from_camera_ptz(self):
-        self.assertFalse(
-            _check_ws_authorization("front_door/ptz", "viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_viewer_blocked_from_global_notifications_set(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                "notifications/set", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_viewer_blocked_from_camera_notifications_suspend(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                "front_door/notifications/suspend", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_viewer_blocked_from_arbitrary_unknown_topic(self):
-        self.assertFalse(
-            _check_ws_authorization(
-                "some_random_topic", "viewer", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    # --- Admin access ---
-
-    def test_admin_can_send_restart(self):
-        self.assertTrue(
-            _check_ws_authorization("restart", "admin", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_admin_can_send_camera_detect_set(self):
-        self.assertTrue(
-            _check_ws_authorization(
-                "front_door/detect/set", "admin", self.DEFAULT_SEPARATOR
-            )
-        )
-
-    def test_admin_can_send_camera_ptz(self):
-        self.assertTrue(
-            _check_ws_authorization("front_door/ptz", "admin", self.DEFAULT_SEPARATOR)
-        )
-
-    # --- Comma-separated roles ---
-
-    def test_comma_separated_admin_viewer_grants_admin(self):
-        self.assertTrue(
-            _check_ws_authorization("restart", "admin,viewer", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_comma_separated_viewer_admin_grants_admin(self):
-        self.assertTrue(
-            _check_ws_authorization("restart", "viewer,admin", self.DEFAULT_SEPARATOR)
-        )
-
-    def test_comma_separated_with_spaces(self):
-        self.assertTrue(
-            _check_ws_authorization("restart", "viewer, admin", self.DEFAULT_SEPARATOR)
-        )
-
-    # --- Custom separator ---
-
-    def test_pipe_separator(self):
-        self.assertTrue(_check_ws_authorization("restart", "viewer|admin", "|"))
-
-    def test_pipe_separator_no_admin(self):
-        self.assertFalse(_check_ws_authorization("restart", "viewer|editor", "|"))
-
-    # --- No role header (fail-closed) ---
-
-    def test_no_role_header_blocks_admin_topics(self):
-        self.assertFalse(
-            _check_ws_authorization("restart", None, self.DEFAULT_SEPARATOR)
-        )
-
-    def test_no_role_header_allows_viewer_topics(self):
-        self.assertTrue(
-            _check_ws_authorization("onConnect", None, self.DEFAULT_SEPARATOR)
-        )
-
-
-if __name__ == "__main__":
-    unittest.main()
@@ -773,9 +773,7 @@ class TrackedObjectProcessor(threading.Thread):
                logger.debug(f"Camera {camera} disabled, skipping update")
                continue

-            camera_state = self.camera_states.get(camera)
-            if camera_state is None:
-                continue
+            camera_state = self.camera_states[camera]

            camera_state.update(
                frame_name, frame_time, current_tracked_objects, motion_boxes, regions
@@ -330,12 +330,7 @@ class TrackedObject:
            if self.obj_data["position_changes"] != obj_data["position_changes"]:
                significant_change = True

-            # disappearance of a per-frame attribute can be caused by detection
-            # skipping the object on a frame (stationary objects on non-interval
-            # frames), so only flag when a new attribute label appears
-            prev_labels = {a["label"] for a in self.obj_data["attributes"]}
-            curr_labels = {a["label"] for a in obj_data["attributes"]}
-            if curr_labels - prev_labels:
+            if self.obj_data["attributes"] != obj_data["attributes"]:
                significant_change = True

            # if the state changed between stationary and active
@@ -24,12 +24,8 @@ from frigate.log import redirect_output_to_logger, suppress_stderr_during
 from frigate.models import Event, Recordings, ReviewSegment
 from frigate.types import ModelStatusTypesEnum
 from frigate.util.downloader import ModelDownloader
-from frigate.util.file import get_event_thumbnail_bytes, load_event_snapshot_image
-from frigate.util.image import (
-    calculate_region,
-    get_image_from_recording,
-    relative_box_to_absolute,
-)
+from frigate.util.file import get_event_thumbnail_bytes
+from frigate.util.image import get_image_from_recording
 from frigate.util.process import FrigateProcess

 BATCH_SIZE = 16
@@ -717,7 +713,7 @@ def collect_object_classification_examples(
    This function:
    1. Queries events for the specified label
    2. Selects 100 balanced events across different cameras and times
-    3. Crops each event's clean snapshot around the object bounding box
+    3. Retrieves thumbnails for selected events (with 33% center crop applied)
    4. Selects 24 most visually distinct thumbnails
    5. Saves to dataset directory

@@ -836,106 +832,66 @@ def _select_balanced_events(

 def _extract_event_thumbnails(events: list[Event], output_dir: str) -> list[str]:
    """
-    Extract a training image for each event.
-
-    Preferred path: load the full-frame clean snapshot and crop around the
-    stored bounding box with the same calculate_region(..., max(w, h), 1.0)
-    call the live ObjectClassificationProcessor uses, so wizard examples
-    are framed like inference-time inputs.
-
-    Fallback: if no clean snapshot exists (snapshots disabled, or only a
-    legacy annotated JPG is on disk), center-crop the stored thumbnail
-    using a step ladder sized from the box/region area ratio.
+    Extract thumbnails from events and save to disk.

    Args:
        events: List of Event objects
-        output_dir: Directory to save crops
+        output_dir: Directory to save thumbnails

    Returns:
-        List of paths to successfully extracted images
+        List of paths to successfully extracted thumbnail images
    """
-    image_paths = []
+    thumbnail_paths = []

    for idx, event in enumerate(events):
        try:
-            img = _load_event_classification_crop(event)
-            if img is None:
-                continue
+            thumbnail_bytes = get_event_thumbnail_bytes(event)

-            resized = cv2.resize(img, (224, 224))
-            output_path = os.path.join(output_dir, f"thumbnail_{idx:04d}.jpg")
-            cv2.imwrite(output_path, resized)
-            image_paths.append(output_path)
+            if thumbnail_bytes:
+                nparr = np.frombuffer(thumbnail_bytes, np.uint8)
+                img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
+
+                if img is not None:
+                    height, width = img.shape[:2]
+
+                    crop_size = 1.0
+                    if event.data and "box" in event.data and "region" in event.data:
+                        box = event.data["box"]
+                        region = event.data["region"]
+
+                        if len(box) == 4 and len(region) == 4:
+                            box_w, box_h = box[2], box[3]
+                            region_w, region_h = region[2], region[3]
+
+                            box_area = (box_w * box_h) / (region_w * region_h)
+
+                            if box_area < 0.05:
+                                crop_size = 0.4
+                            elif box_area < 0.10:
+                                crop_size = 0.5
+                            elif box_area < 0.20:
+                                crop_size = 0.65
+                            elif box_area < 0.35:
+                                crop_size = 0.80
+                            else:
+                                crop_size = 0.95
+
+                    crop_width = int(width * crop_size)
+                    crop_height = int(height * crop_size)
+
+                    x1 = (width - crop_width) // 2
+                    y1 = (height - crop_height) // 2
+                    x2 = x1 + crop_width
+                    y2 = y1 + crop_height
+
+                    cropped = img[y1:y2, x1:x2]
+                    resized = cv2.resize(cropped, (224, 224))
+                    output_path = os.path.join(output_dir, f"thumbnail_{idx:04d}.jpg")
+                    cv2.imwrite(output_path, resized)
+                    thumbnail_paths.append(output_path)

        except Exception as e:
-            logger.debug(f"Failed to extract image for event {event.id}: {e}")
+            logger.debug(f"Failed to extract thumbnail for event {event.id}: {e}")
            continue

-    return image_paths
-
-
-def _load_event_classification_crop(event: Event) -> np.ndarray | None:
-    """Prefer a snapshot-based object crop; fall back to a center-cropped thumbnail."""
-    if event.data and "box" in event.data:
-        snapshot, _ = load_event_snapshot_image(event, clean_only=True)
-        if snapshot is not None:
-            abs_box = relative_box_to_absolute(snapshot.shape, event.data["box"])
-            if abs_box is not None:
-                xmin, ymin, xmax, ymax = abs_box
-                box_w = xmax - xmin
-                box_h = ymax - ymin
-                if box_w > 0 and box_h > 0:
-                    x1, y1, x2, y2 = calculate_region(
-                        snapshot.shape,
-                        xmin,
-                        ymin,
-                        xmax,
-                        ymax,
-                        max(box_w, box_h),
-                        1.0,
-                    )
-                    cropped = snapshot[y1:y2, x1:x2]
-                    if cropped.size > 0:
-                        return cropped
-
-    thumbnail_bytes = get_event_thumbnail_bytes(event)
-    if not thumbnail_bytes:
-        return None
-
-    nparr = np.frombuffer(thumbnail_bytes, np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    if img is None or img.size == 0:
-        return None
-
-    height, width = img.shape[:2]
-    crop_size = 1.0
-
-    if event.data and "box" in event.data and "region" in event.data:
-        box = event.data["box"]
-        region = event.data["region"]
-
-        if len(box) == 4 and len(region) == 4:
-            box_w, box_h = box[2], box[3]
-            region_w, region_h = region[2], region[3]
-            box_area = (box_w * box_h) / (region_w * region_h)
-
-            if box_area < 0.05:
-                crop_size = 0.4
-            elif box_area < 0.10:
-                crop_size = 0.5
-            elif box_area < 0.20:
-                crop_size = 0.65
-            elif box_area < 0.35:
-                crop_size = 0.80
-            else:
-                crop_size = 0.95
-
-    crop_width = int(width * crop_size)
-    crop_height = int(height * crop_size)
-    x1 = (width - crop_width) // 2
-    y1 = (height - crop_height) // 2
-    cropped = img[y1 : y1 + crop_height, x1 : x1 + crop_width]
-    if cropped.size == 0:
-        return None
-
-    return cropped
+    return thumbnail_paths
@@ -2,9 +2,8 @@

 import logging
 import subprocess as sp
-from typing import Any, Callable, Optional
+from typing import Any

-from frigate.const import PROCESS_PRIORITY_LOW
 from frigate.log import LogPipe


@@ -47,124 +46,3 @@ def start_or_restart_ffmpeg(
            start_new_session=True,
        )
    return process
-
-
-logger = logging.getLogger(__name__)
-
-
-def inject_progress_flags(cmd: list[str]) -> list[str]:
-    """Insert `-progress pipe:2 -nostats` immediately before the output path.
-
-    `-progress pipe:2` writes structured key=value lines to stderr;
-    `-nostats` suppresses the noisy default stats output. The output path
-    is conventionally the last token in an FFmpeg argv.
-    """
-    if not cmd:
-        return cmd
-    return cmd[:-1] + ["-progress", "pipe:2", "-nostats", cmd[-1]]
-
-
-def run_ffmpeg_with_progress(
-    cmd: list[str],
-    *,
-    expected_duration_seconds: float,
-    on_progress: Optional[Callable[[float], None]] = None,
-    stdin_payload: Optional[str] = None,
-    process_started: Optional[Callable[[sp.Popen], None]] = None,
-    use_low_priority: bool = True,
-) -> tuple[int, str]:
-    """Run an ffmpeg command, streaming progress via `-progress pipe:2`.
-
-    Args:
-        cmd: ffmpeg argv. Output path must be the last token.
-        expected_duration_seconds: Duration of the expected output clip in
-            seconds. Used to convert ffmpeg's `out_time_us` into a percent.
-        on_progress: Optional callback invoked with a percent in [0, 100].
-            Called once with 0.0 at start, again on each `out_time_us=`
-            stderr line, and once with 100.0 on `progress=end`.
-        stdin_payload: Optional string written to ffmpeg stdin (used by
-            export for concat playlists).
-        process_started: Optional callback invoked with the live `Popen`
-            once spawned — lets callers store the ref for cancellation.
-        use_low_priority: When True, prepend `nice -n PROCESS_PRIORITY_LOW`
-            so concat doesn't starve detection.
-
-    Returns:
-        Tuple of `(returncode, captured_stderr)`. Stdout is left attached
-        to the parent process to avoid buffer-full deadlocks.
-    """
-    full_cmd = inject_progress_flags(cmd)
-    if use_low_priority:
-        full_cmd = ["nice", "-n", str(PROCESS_PRIORITY_LOW)] + full_cmd
-
-    def emit(percent: float) -> None:
-        if on_progress is None:
-            return
-        try:
-            on_progress(max(0.0, min(100.0, percent)))
-        except Exception:
-            logger.exception("FFmpeg progress callback failed")
-
-    emit(0.0)
-
-    proc = sp.Popen(
-        full_cmd,
-        stdin=sp.PIPE if stdin_payload is not None else None,
-        stderr=sp.PIPE,
-        text=True,
-        encoding="ascii",
-        errors="replace",
-    )
-    if process_started is not None:
-        try:
-            process_started(proc)
-        except Exception:
-            logger.exception("FFmpeg process_started callback failed")
-
-    if stdin_payload is not None and proc.stdin is not None:
-        try:
-            proc.stdin.write(stdin_payload)
-        except (BrokenPipeError, OSError):
-            pass
-        finally:
-            try:
-                proc.stdin.close()
-            except (BrokenPipeError, OSError):
-                pass
-
-    captured: list[str] = []
-    if proc.stderr is not None:
-        try:
-            for raw_line in proc.stderr:
-                captured.append(raw_line)
-                line = raw_line.strip()
-                if not line:
-                    continue
-                if line.startswith("out_time_us="):
-                    if expected_duration_seconds <= 0:
-                        continue
-                    try:
-                        out_time_us = int(line.split("=", 1)[1])
-                    except (ValueError, IndexError):
-                        continue
-                    if out_time_us < 0:
-                        continue
-                    out_seconds = out_time_us / 1_000_000.0
-                    emit((out_seconds / expected_duration_seconds) * 100.0)
-                elif line == "progress=end":
-                    emit(100.0)
-                    break
-        except Exception:
-            logger.exception("Failed reading FFmpeg progress stream")
-
-    proc.wait()
-
-    if proc.stderr is not None:
-        try:
-            remaining = proc.stderr.read()
-            if remaining:
-                captured.append(remaining)
-        except Exception:
-            pass
-
-    return proc.returncode or 0, "".join(captured)
@@ -94,7 +94,7 @@ def remove_empty_directories(root: Path, paths: Iterable[Path]) -> None:

        paths = parents

-    logger.debug(f"Removed {count} empty directories")
+    logger.debug("Removed {count} empty directories")


 def sync_recordings(
@@ -264,214 +264,156 @@ def get_amd_gpu_stats() -> Optional[dict[str, str]]:
        return results


-_INTEL_FDINFO_SAMPLE_SECONDS = 1.0
+def get_intel_gpu_stats(intel_gpu_device: Optional[str]) -> Optional[dict[str, str]]:
+    """Get stats using intel_gpu_top.

-# Engines we track. Render/3D and Compute are pooled into "compute"; Video and
-# VideoEnhance into "dec" (VideoEnhance is the post-process engine that handles
-# VAAPI scaling/deinterlace/CSC, e.g. ffmpeg `-vf scale_vaapi=...`). The Copy
-# (DMA blitter) engine is intentionally ignored — it represents transparent
-# memory transfers, not user-visible GPU work.
-# i915 fdinfo keys (cumulative ns) → logical engine name.
-_I915_ENGINE_KEYS = {
-    "drm-engine-render": "render",
-    "drm-engine-video": "video",
-    "drm-engine-video-enhance": "video-enhance",
-    "drm-engine-compute": "compute",
-}
-# Xe fdinfo suffixes (cumulative cycles, paired with drm-total-cycles-*).
-_XE_ENGINE_KEYS = {
-    "rcs": "render",
-    "vcs": "video",
-    "vecs": "video-enhance",
-    "ccs": "compute",
-}
-
-
-def _resolve_intel_gpu_pdev(device: Optional[str]) -> Optional[str]:
-    """Map a configured GPU hint (/dev/dri/card1, renderD128, or a PCI bus
-    address) to its drm-pdev string so we can filter fdinfo entries to that
-    device. Returns None when no hint is supplied or it cannot be resolved."""
-    if not device:
-        return None
-
-    if re.match(r"^[0-9a-fA-F]{4}:[0-9a-fA-F]{2}:[0-9a-fA-F]{2}\.[0-9a-fA-F]$", device):
-        return device
-
-    name = os.path.basename(device.rstrip("/"))
-    try:
-        return os.path.basename(os.path.realpath(f"/sys/class/drm/{name}/device"))
-    except OSError:
-        return None
-
-
-def _read_intel_drm_fdinfo(target_pdev: Optional[str]) -> dict:
-    """Snapshot DRM fdinfo for every Intel client visible in /proc.
-
-    Returns a dict keyed by (pdev, drm-client-id, pid) so the same context
-    seen via multiple file descriptors on a single process collapses to one
-    entry.
+    Returns overall GPU usage derived from rc6 residency (idle time),
+    plus individual engine breakdowns:
+      - enc: Render/3D engine (compute/shader encoder, used by QSV)
+      - dec: Video engines (fixed-function codec, used by VAAPI)
    """
-    snapshot: dict = {}
+
+    def get_stats_manually(output: str) -> dict[str, str]:
+        """Find global stats via regex when json fails to parse."""
+        reading = "".join(output)
+        results: dict[str, str] = {}
+
+        # rc6 residency for overall GPU usage
+        rc6_match = re.search(r'"rc6":\{"value":([\d.]+)', reading)
+        if rc6_match:
+            rc6_value = float(rc6_match.group(1))
+            results["gpu"] = f"{round(100.0 - rc6_value, 2)}%"
+        else:
+            results["gpu"] = "-%"
+
+        results["mem"] = "-%"
+
+        # Render/3D is the compute/encode engine
+        render = []
+        for result in re.findall(r'"Render/3D/0":{[a-z":\d.,%]+}', reading):
+            packet = json.loads(result[14:])
+            single = packet.get("busy", 0.0)
+            render.append(float(single))
+
+        if render:
+            results["compute"] = f"{round(sum(render) / len(render), 2)}%"
+
+        # Video engines are the fixed-function decode engines
+        video = []
+        for result in re.findall(r'"Video/\d":{[a-z":\d.,%]+}', reading):
+            packet = json.loads(result[10:])
+            single = packet.get("busy", 0.0)
+            video.append(float(single))
+
+        if video:
+            results["dec"] = f"{round(sum(video) / len(video), 2)}%"
+
+        return results
+
+    intel_gpu_top_command = [
+        "timeout",
+        "0.5s",
+        "intel_gpu_top",
+        "-J",
+        "-o",
+        "-",
+        "-s",
+        "1000",  # Intel changed this from seconds to milliseconds in 2024+ versions
+    ]
+
+    if intel_gpu_device:
+        intel_gpu_top_command += ["-d", intel_gpu_device]

    try:
-        proc_entries = os.listdir("/proc")
-    except OSError:
-        return snapshot
+        p = sp.run(
+            intel_gpu_top_command,
+            encoding="ascii",
+            capture_output=True,
+        )
+    except UnicodeDecodeError:
+        return None

-    for entry in proc_entries:
-        if not entry.isdigit():
-            continue
+    # timeout has a non-zero returncode when timeout is reached
+    if p.returncode != 124:
+        logger.error(f"Unable to poll intel GPU stats: {p.stderr}")
+        return None
+    else:
+        output = "".join(p.stdout.split())

-        fdinfo_dir = f"/proc/{entry}/fdinfo"
        try:
-            fds = os.listdir(fdinfo_dir)
-        except (FileNotFoundError, PermissionError, NotADirectoryError, OSError):
-            continue
+            data = json.loads(f"[{output}]")
+        except json.JSONDecodeError:
+            return get_stats_manually(output)

-        for fd in fds:
-            try:
-                with open(f"{fdinfo_dir}/{fd}") as f:
-                    content = f.read()
-            except (FileNotFoundError, PermissionError, OSError):
-                continue
+        results: dict[str, str] = {}
+        rc6_values = []
+        render_global = []
+        video_global = []
+        # per-client: {pid: [total_busy_per_sample, ...]}
+        client_usages: dict[str, list[float]] = {}

-            if "drm-driver" not in content:
-                continue
+        for block in data:
+            # rc6 residency: percentage of time GPU is idle
+            rc6 = block.get("rc6", {}).get("value")
+            if rc6 is not None:
+                rc6_values.append(float(rc6))

-            fields: dict[str, str] = {}
-            for line in content.splitlines():
-                key, sep, value = line.partition(":")
-                if sep:
-                    fields[key.strip()] = value.strip()
+            global_engine = block.get("engines")

-            driver = fields.get("drm-driver")
-            if driver not in ("i915", "xe"):
-                continue
+            if global_engine:
+                render_frame = global_engine.get("Render/3D/0", {}).get("busy")
+                video_frame = global_engine.get("Video/0", {}).get("busy")

-            pdev = fields.get("drm-pdev", "")
-            if target_pdev and pdev != target_pdev:
-                continue
+                if render_frame is not None:
+                    render_global.append(float(render_frame))

-            client_id = fields.get("drm-client-id")
-            if not client_id:
-                continue
+                if video_frame is not None:
+                    video_global.append(float(video_frame))

-            key = (pdev, client_id, entry)
-            if key in snapshot:
-                continue
+            clients = block.get("clients", {})

-            engines: dict[str, tuple[int, int]] = {}
+            if clients:
+                for client_block in clients.values():
+                    pid = client_block["pid"]

-            if driver == "i915":
-                for fkey, engine in _I915_ENGINE_KEYS.items():
-                    raw = fields.get(fkey)
-                    if not raw:
-                        continue
-                    try:
-                        engines[engine] = (int(raw.split()[0]), 0)
-                    except (ValueError, IndexError):
-                        continue
-            else:
-                for suffix, engine in _XE_ENGINE_KEYS.items():
-                    busy_raw = fields.get(f"drm-cycles-{suffix}")
-                    total_raw = fields.get(f"drm-total-cycles-{suffix}")
-                    if not (busy_raw and total_raw):
-                        continue
-                    try:
-                        engines[engine] = (
-                            int(busy_raw.split()[0]),
-                            int(total_raw.split()[0]),
-                        )
-                    except (ValueError, IndexError):
-                        continue
+                    if pid not in client_usages:
+                        client_usages[pid] = []

-            if not engines:
-                continue
+                    # Sum all engine-class busy values for this client
+                    total_busy = 0.0
+                    for engine in client_block.get("engine-classes", {}).values():
+                        busy = engine.get("busy")
+                        if busy is not None:
+                            total_busy += float(busy)

-            snapshot[key] = {"driver": driver, "pid": entry, "engines": engines}
+                    client_usages[pid].append(total_busy)

-    return snapshot
+        # Overall GPU usage from rc6 (idle) residency
+        if rc6_values:
+            rc6_avg = sum(rc6_values) / len(rc6_values)
+            results["gpu"] = f"{round(100.0 - rc6_avg, 2)}%"

+        results["mem"] = "-%"

-def get_intel_gpu_stats(intel_gpu_device: Optional[str]) -> Optional[dict[str, Any]]:
-    """Get stats by reading DRM fdinfo files.
+        # Compute: Render/3D engine (compute/shader workloads and QSV encode)
+        if render_global:
+            results["compute"] = f"{round(sum(render_global) / len(render_global), 2)}%"

-    Each DRM client FD exposes monotonic per-engine busy counters via
-    /proc/<pid>/fdinfo/<fd> (i915 since kernel 5.19, Xe since first release).
-    We sample twice and divide busy-time deltas by wall-clock to derive
-    utilization. Render/3D and Compute are pooled into "compute"; Video and
-    VideoEnhance into "dec". Overall "gpu" is the sum of those pools (clamped
-    to 100%).
-    """
-    target_pdev = _resolve_intel_gpu_pdev(intel_gpu_device)
+        # Decoder: Video engine (fixed-function codec)
+        if video_global:
+            results["dec"] = f"{round(sum(video_global) / len(video_global), 2)}%"

-    snapshot_a = _read_intel_drm_fdinfo(target_pdev)
-    if not snapshot_a:
-        return None
+        # Per-client GPU usage (sum of all engines per process)
+        if client_usages:
+            results["clients"] = {}

-    start = time.monotonic()
-    time.sleep(_INTEL_FDINFO_SAMPLE_SECONDS)
-    elapsed_ns = (time.monotonic() - start) * 1e9
+            for pid, samples in client_usages.items():
+                if samples:
+                    results["clients"][pid] = (
+                        f"{round(sum(samples) / len(samples), 2)}%"
+                    )

-    snapshot_b = _read_intel_drm_fdinfo(target_pdev)
-    if not snapshot_b or elapsed_ns <= 0:
-        return None
-
-    engine_pct: dict[str, float] = {
-        "render": 0.0,
-        "video": 0.0,
-        "video-enhance": 0.0,
-        "compute": 0.0,
-    }
-    pid_pct: dict[str, float] = {}
-
-    for key, data_b in snapshot_b.items():
-        data_a = snapshot_a.get(key)
-        if not data_a or data_a["driver"] != data_b["driver"]:
-            continue
-
-        client_total = 0.0
-        for engine, (busy_b, total_b) in data_b["engines"].items():
-            if engine not in engine_pct:
-                continue
-
-            busy_a, total_a = data_a["engines"].get(engine, (busy_b, total_b))
-
-            if data_b["driver"] == "i915":
-                delta = max(0, busy_b - busy_a)
-                pct = min(100.0, delta / elapsed_ns * 100.0)
-            else:
-                delta_busy = max(0, busy_b - busy_a)
-                delta_total = total_b - total_a
-                if delta_total <= 0:
-                    continue
-                pct = min(100.0, delta_busy / delta_total * 100.0)
-
-            engine_pct[engine] += pct
-            client_total += pct
-
-        pid_pct[data_b["pid"]] = pid_pct.get(data_b["pid"], 0.0) + client_total
-
-    for engine in engine_pct:
-        engine_pct[engine] = min(100.0, engine_pct[engine])
-
-    compute_pct = min(100.0, engine_pct["render"] + engine_pct["compute"])
-    dec_pct = min(100.0, engine_pct["video"] + engine_pct["video-enhance"])
-    overall_pct = min(100.0, compute_pct + dec_pct)
-
-    results: dict[str, Any] = {
-        "gpu": f"{round(overall_pct, 2)}%",
-        "mem": "-%",
-        "compute": f"{round(compute_pct, 2)}%",
-        "dec": f"{round(dec_pct, 2)}%",
-    }
-
-    if pid_pct:
-        results["clients"] = {
-            pid: f"{round(min(100.0, pct), 2)}%" for pid, pct in pid_pct.items()
-        }
-
-    return results
+        return results


 def get_openvino_npu_stats() -> Optional[dict[str, str]]:
@@ -769,44 +711,23 @@ def ffprobe_stream(ffmpeg, path: str, detailed: bool = False) -> sp.CompletedPro
    else:
        format_entries = None

-    def run(rtsp_transport: Optional[str] = None) -> sp.CompletedProcess:
-        cmd = [ffmpeg.ffprobe_path]
-        if rtsp_transport:
-            cmd += ["-rtsp_transport", rtsp_transport]
-        cmd += [
-            "-timeout",
-            "1000000",
-            "-print_format",
-            "json",
-            "-show_entries",
-            f"stream={stream_entries}",
-        ]
-        if detailed and format_entries:
-            cmd.extend(["-show_entries", f"format={format_entries}"])
-        cmd.extend(["-loglevel", "error", clean_path])
-        try:
-            return sp.run(cmd, capture_output=True, timeout=6)
-        except sp.TimeoutExpired as e:
-            logger.info(
-                "ffprobe timed out while probing %s (transport=%s)",
-                clean_camera_user_pass(path),
-                rtsp_transport or "default",
-            )
-            return sp.CompletedProcess(
-                args=cmd,
-                returncode=1,
-                stdout=e.stdout or b"",
-                stderr=(e.stderr or b"") + b"\nffprobe timed out",
-            )
+    ffprobe_cmd = [
+        ffmpeg.ffprobe_path,
+        "-timeout",
+        "1000000",
+        "-print_format",
+        "json",
+        "-show_entries",
+        f"stream={stream_entries}",
+    ]

-    result = run()
+    # Add format entries for detailed mode
+    if detailed and format_entries:
+        ffprobe_cmd.extend(["-show_entries", f"format={format_entries}"])

-    # For RTSP: retry with explicit TCP transport if the first attempt failed
-    # (default UDP may be blocked)
-    if result.returncode != 0 and clean_path.startswith("rtsp://"):
-        result = run(rtsp_transport="tcp")
+    ffprobe_cmd.extend(["-loglevel", "error", clean_path])

-    return result
+    return sp.run(ffprobe_cmd, capture_output=True)


 def vainfo_hwaccel(device_name: Optional[str] = None) -> sp.CompletedProcess:
@@ -886,15 +807,10 @@ async def get_video_properties(
 ) -> dict[str, Any]:
    async def probe_with_ffprobe(
        url: str,
-        rtsp_transport: Optional[str] = None,
    ) -> tuple[bool, int, int, Optional[str], float]:
        """Fallback using ffprobe: returns (valid, width, height, codec, duration)."""
-        cmd = [ffmpeg.ffprobe_path]
-        if rtsp_transport:
-            cmd += ["-rtsp_transport", rtsp_transport]
-        cmd += [
-            "-rw_timeout",
-            "5000000",
+        cmd = [
+            ffmpeg.ffprobe_path,
            "-v",
            "quiet",
            "-print_format",
@@ -903,23 +819,11 @@ async def get_video_properties(
            "-show_streams",
            url,
        ]
-        proc = None
        try:
            proc = await asyncio.create_subprocess_exec(
                *cmd, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
            )
-            try:
-                stdout, _ = await asyncio.wait_for(proc.communicate(), timeout=6)
-            except asyncio.TimeoutError:
-                logger.info(
-                    "ffprobe timed out while probing %s (transport=%s)",
-                    clean_camera_user_pass(url),
-                    rtsp_transport or "default",
-                )
-                proc.kill()
-                await proc.wait()
-                return False, 0, 0, None, -1
-
+            stdout, _ = await proc.communicate()
            if proc.returncode != 0:
                return False, 0, 0, None, -1

@@ -968,26 +872,12 @@ async def get_video_properties(
        cap.release()
        return valid, width, height, fourcc, duration

-    is_rtsp = url.startswith("rtsp://")
+    # try cv2 first
+    has_video, width, height, fourcc, duration = probe_with_cv2(url)

-    if is_rtsp:
-        # skip cv2 for RTSP: its FFmpeg backend has a hardcoded ~30s internal
-        # timeout that cannot be shortened per-call, and ffprobe bounded by
-        # -rw_timeout handles RTSP probing reliably
+    # fallback to ffprobe if needed
+    if not has_video or (get_duration and duration < 0):
        has_video, width, height, fourcc, duration = await probe_with_ffprobe(url)
-    else:
-        # try cv2 first for local files, HTTP, RTMP
-        has_video, width, height, fourcc, duration = probe_with_cv2(url)
-
-        # fallback to ffprobe if needed
-        if not has_video or (get_duration and duration < 0):
-            has_video, width, height, fourcc, duration = await probe_with_ffprobe(url)
-
-    # last resort for RTSP: try TCP transport, since default UDP may be blocked
-    if (not has_video or (get_duration and duration < 0)) and is_rtsp:
-        has_video, width, height, fourcc, duration = await probe_with_ffprobe(
-            url, rtsp_transport="tcp"
-        )

    result: dict[str, Any] = {"has_valid_video": has_video}
    if has_video:
@@ -438,32 +438,34 @@ def process_frames(
            else:
                object_tracker.update_frame_times(frame_name, frame_time)

+        # group the attribute detections based on what label they apply to
+        attribute_detections: dict[str, list[TrackedObjectAttribute]] = {}
+        for label, attribute_labels in attributes_map.items():
+            attribute_detections[label] = [
+                TrackedObjectAttribute(d)
+                for d in consolidated_detections
+                if d[0] in attribute_labels
+            ]
+
        # build detections
        detections = {}
        for obj in object_tracker.tracked_objects.values():
            detections[obj["id"]] = {**obj, "attributes": []}

-        # assign each detected attribute to the best matching object.
-        # iterate consolidated_detections once so attributes that appear under
-        # multiple parent labels in attributes_map (e.g. license_plate is in
-        # both "car" and "motorcycle") are not appended more than once
+        # find the best object for each attribute to be assigned to
        all_objects: list[dict[str, Any]] = object_tracker.tracked_objects.values()
-        detected_attributes = [
-            TrackedObjectAttribute(d)
-            for d in consolidated_detections
-            if d[0] in all_attributes
-        ]
-        for attribute in detected_attributes:
-            filtered_objects = filter(
-                lambda o: attribute.label in attributes_map.get(o["label"], []),
-                all_objects,
-            )
-            selected_object_id = attribute.find_best_object(filtered_objects)
-
-            if selected_object_id is not None:
-                detections[selected_object_id]["attributes"].append(
-                    attribute.get_tracking_data()
+        for attributes in attribute_detections.values():
+            for attribute in attributes:
+                filtered_objects = filter(
+                    lambda o: attribute.label in attributes_map.get(o["label"], []),
+                    all_objects,
                )
+                selected_object_id = attribute.find_best_object(filtered_objects)
+
+                if selected_object_id is not None:
+                    detections[selected_object_id]["attributes"].append(
+                        attribute.get_tracking_data()
+                    )

        # debug object tracking
        if False:
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
ZhaiSoul	d007bd0a6f	docs: add more icon support	2026-04-21 22:23:09 +08:00
ZhaiSoul	2420fdc4ce	docs: add docker compose generator	2026-04-21 20:59:16 +08:00