Merge 806faf8c78 into 814c497bef

* use ReplayState enum

* extract shared ffmpeg progress helper

* make start call non-blocking with worker thread

* expose replay state on status endpoint and return 202 from start

* cancel in-flight ffmpeg when stop is called during preparation

* add replay i18n strings for preparing and error states

* show status in replay UI

* navigate immediately on 202 from debug replay menus and dialog

* remove unused

* simplify to use Job infrastructure

* tests

* cleanup and tweaks

* fetch schema

* update api spec

* formatting

* fix e2e test

* mypy

* clean up

* formatting

* fix

* fix test

* don't try to show camera image until status reports ready

* simplify loading logic

* fix race in latest_frame on debug replay shutdown

* remove toast when successfully stopping

it gets hidden almost immediately

.github/pull_request_template.md

@@ -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 large/pinned features):
+- Link to discussion with maintainers (**required** for any large or "planned" features):
 
 ## For new features
 

.github/workflows/pr_template_check.yml

@@ -13,7 +13,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Check PR description against template
-        uses: actions/github-script@v7
+        uses: actions/github-script@v9
         with:
           script: |
             const maintainers = ['blakeblackshear', 'NickM-27', 'hawkeye217', 'dependabot[bot]', 'weblate'];

.github/workflows/pull_request.yml

@@ -72,7 +72,7 @@ jobs:
         run: npm run e2e
         working-directory: ./web
       - name: Upload test artifacts
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v7
         if: failure()
         with:
           name: playwright-report

.github/workflows/stale.yml

@@ -18,9 +18,9 @@ jobs:
           close-issue-message: ""
           days-before-stale: 30
           days-before-close: 3
-          exempt-draft-pr: true
-          exempt-issue-labels: "pinned,security"
-          exempt-pr-labels: "pinned,security,dependencies"
+          exempt-draft-pr: false
+          exempt-issue-labels: "planned,security"
+          exempt-pr-labels: "planned,security,dependencies"
           operations-per-run: 120
       - name: Print outputs
         env:

.gitignore

@@ -22,3 +22,8 @@ core
 !/web/**/*.ts
 .idea/*
 .ipynb_checkpoints
+
+# Auto-generated Docker Compose Generator config files
+docs/src/components/DockerComposeGenerator/config/devices.ts
+docs/src/components/DockerComposeGenerator/config/hardware.ts
+docs/src/components/DockerComposeGenerator/config/ports.ts

CONTRIBUTING.md

@@ -10,11 +10,14 @@ If you've found a bug and want to fix it, go for it. Link to the relevant issue
 
 ### New features
 
-Every new feature adds scope that the maintainers must test, maintain, and support long-term. Before writing code for a new feature:
+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.
 
-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.
+**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.
 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
 
@@ -39,6 +42,8 @@ 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

docs/docs/configuration/face_recognition.md

@@ -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/#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/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 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 be able to extract features from gray-scale 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.
 - 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.
 

docs/docs/configuration/genai/config.md

@@ -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 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).
+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).
 
 #### Configuration
 
@@ -210,7 +210,8 @@ Ollama also supports [cloud models](https://ollama.com/cloud), where your local
 
 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`)
+   - 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 **Model** to the cloud model name
 
 </TabItem>
@@ -223,6 +224,16 @@ 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>
 

docs/docs/configuration/object_detectors.md

@@ -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](#d-fine)                     | ❌  | ❌  |                                                              |
+| [D-FINE / DEIMv2](#d-fine--deimv2)    | ❌  | ❌  |                                                              |
 
 #### SSDLite MobileNet v2
 
@@ -710,13 +710,13 @@ model:
 
 </details>
 
-#### D-FINE
+#### D-FINE / DEIMv2
 
-[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.
+[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.
 
 :::warning
 
-Currently D-FINE models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
+Currently D-FINE / DEIMv2 models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
 
 :::
 
@@ -766,6 +766,31 @@ 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`.
@@ -947,7 +972,7 @@ 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 models are not supported
+- D-FINE / DEIMv2 models are not supported
 - YOLO-NAS models are known to not run well on integrated GPUs
 
 ## ONNX
@@ -1003,7 +1028,7 @@ detectors:
 | [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                        |
+| [D-FINE / DEIMv2](#d-fine--deimv2-1) | ⚠️         | ❌      | Not supported by CUDA Graphs                        |
 
 There is no default model provided, the following formats are supported:
 
@@ -1215,9 +1240,9 @@ model:
 
 </details>
 
-#### D-FINE
+#### D-FINE / DEIMv2
 
-[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.
+[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.
 
 <details>
   <summary>D-FINE Setup & Config</summary>
@@ -1262,6 +1287,28 @@ 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)
@@ -1405,7 +1452,7 @@ 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/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/2p1/tools/neural_compiler.html#usage).
 
 **Note:** The default model for the MemryX detector is YOLO-NAS 320x320.
 
@@ -1459,7 +1506,7 @@ 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/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/2p1/tools/neural_compiler.html#usage).
 
 ##### Configuration
 
@@ -1601,19 +1648,39 @@ model:
 
 #### Using a Custom Model
 
-To use your own 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.
 
-1.  Package your compiled model into a `.zip` file.
+#### Compile the Model
 
-2.  The `.zip` must contain the compiled `.dfp` file.
+Custom models must be compiled using **MemryX SDK 2.1**.
 
-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`.
+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**.
 
-4.  Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.
+> **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.
 
-5.  Update the `labelmap_path` to match your custom model's labels.
+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.
 
-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).
+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.
 
 ```yaml
 # The detector automatically selects the default model if nothing is provided in the config.
@@ -2274,6 +2341,49 @@ 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.

docs/docs/configuration/record.md

@@ -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?
 
-As of Frigate 0.12 if there is less than an hour left of storage, the oldest 2 hours of recordings will be deleted.
+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.
 
 ## Configuring Recording Retention
 

docs/docs/configuration/restream.md

@@ -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. 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 and other applications. An example is below:
 
 :::warning
 
@@ -244,16 +244,11 @@ The `exec:`, `echo:`, and `expr:` sources are disabled by default for security.
 
 :::
 
-:::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}}`
+NOTE: RTSP output will need to be passed with two curly braces `{{output}}`, whereas pipe output must be passed without curly braces.
 
 ```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 -
 ```

docs/docs/frigate/installation.md

@@ -4,12 +4,15 @@ 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#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.md#configuring-frigate) to configure Frigate.
 
 :::
 
@@ -286,7 +289,7 @@ 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/get_started/hardware_setup.html).
+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).
 
 Then follow these steps for installing the correct driver/runtime configuration:
 
@@ -295,6 +298,12 @@ 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`
@@ -468,6 +477,16 @@ 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:
@@ -501,6 +520,10 @@ 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:
 

docs/package-lock.json

@@ -14,9 +14,11 @@
         "@docusaurus/theme-mermaid": "^3.7.0",
         "@inkeep/docusaurus": "^2.0.16",
         "@mdx-js/react": "^3.1.0",
+        "@types/js-yaml": "^4.0.9",
         "clsx": "^2.1.1",
         "docusaurus-plugin-openapi-docs": "^4.5.1",
         "docusaurus-theme-openapi-docs": "^4.5.1",
+        "js-yaml": "^4.1.1",
         "prism-react-renderer": "^2.4.1",
         "raw-loader": "^4.0.2",
         "react": "^18.3.1",
@@ -5747,6 +5749,11 @@
         "@types/istanbul-lib-report": "*"
       }
     },
+    "node_modules/@types/js-yaml": {
+      "version": "4.0.9",
+      "resolved": "https://mirrors.tencent.com/npm/@types/js-yaml/-/js-yaml-4.0.9.tgz",
+      "integrity": "sha512-k4MGaQl5TGo/iipqb2UDG2UwjXziSWkh0uysQelTlJpX1qGlpUZYm8PnO4DxG1qBomtJUdYJ6qR6xdIah10JLg=="
+    },
     "node_modules/@types/json-schema": {
       "version": "7.0.15",
       "resolved": "https://registry.npmjs.org/@types/json-schema/-/json-schema-7.0.15.tgz",
@@ -12883,7 +12890,7 @@
     },
     "node_modules/js-yaml": {
       "version": "4.1.1",
-      "resolved": "https://registry.npmjs.org/js-yaml/-/js-yaml-4.1.1.tgz",
+      "resolved": "https://mirrors.tencent.com/npm/js-yaml/-/js-yaml-4.1.1.tgz",
       "integrity": "sha512-qQKT4zQxXl8lLwBtHMWwaTcGfFOZviOJet3Oy/xmGk2gZH677CJM9EvtfdSkgWcATZhj/55JZ0rmy3myCT5lsA==",
       "license": "MIT",
       "dependencies": {

docs/package.json

@@ -3,9 +3,10 @@
   "version": "0.0.0",
   "private": true,
   "scripts": {
+    "build:config": "node scripts/build-config.mjs",
     "docusaurus": "docusaurus",
-    "start": "npm run regen-docs && docusaurus start --host 0.0.0.0",
-    "build": "npm run regen-docs && docusaurus build",
+    "start": "npm run build:config && npm run regen-docs && docusaurus start --host 0.0.0.0",
+    "build": "npm run build:config && npm run regen-docs && docusaurus build",
     "swizzle": "docusaurus swizzle",
     "deploy": "docusaurus deploy",
     "clear": "docusaurus clear",
@@ -23,9 +24,11 @@
     "@docusaurus/theme-mermaid": "^3.7.0",
     "@inkeep/docusaurus": "^2.0.16",
     "@mdx-js/react": "^3.1.0",
+    "@types/js-yaml": "^4.0.9",
     "clsx": "^2.1.1",
     "docusaurus-plugin-openapi-docs": "^4.5.1",
     "docusaurus-theme-openapi-docs": "^4.5.1",
+    "js-yaml": "^4.1.1",
     "prism-react-renderer": "^2.4.1",
     "raw-loader": "^4.0.2",
     "react": "^18.3.1",

docs/scripts/build-config.mjs

@@ -0,0 +1,64 @@
+#!/usr/bin/env node
+
+/**
+ * Build script: reads config.yaml and generates TypeScript files
+ * for the Docker Compose Generator.
+ *
+ * Usage: node scripts/build-config.mjs
+ */
+
+import fs from "node:fs";
+import path from "node:path";
+import { fileURLToPath } from "node:url";
+import yaml from "js-yaml";
+
+const __dirname = path.dirname(fileURLToPath(import.meta.url));
+const CONFIG_DIR = path.resolve(__dirname, "../src/components/DockerComposeGenerator/config");
+const YAML_PATH = path.join(CONFIG_DIR, "config.yaml");
+
+// Read & parse YAML
+const raw = fs.readFileSync(YAML_PATH, "utf8");
+const config = yaml.load(raw);
+
+if (!config.devices || !config.hardware || !config.ports) {
+  console.error("config.yaml must contain 'devices', 'hardware', and 'ports' sections.");
+  process.exit(1);
+}
+
+/**
+ * Generate a .ts file from a section of the YAML config.
+ */
+function generateTsFile(sectionName, items, typeName, varName, mapVarName, yamlFilename) {
+  const jsonItems = JSON.stringify(items, null, 2);
+  // Indent JSON to fit inside the array literal
+  const indented = jsonItems
+    .split("\n")
+    .map((line, i) => (i === 0 ? line : "  " + line))
+    .join("\n");
+
+  const content = `/**
+ * AUTO-GENERATED FILE — do not edit directly.
+ * Source: ${yamlFilename}
+ * To update, edit the YAML file and run: npm run build:config
+ */
+
+import type { ${typeName} } from "./types";
+
+export const ${varName}: ${typeName}[] = ${indented};
+
+/** Lookup map for quick access by ID */
+export const ${mapVarName}: Map<string, ${typeName}> = new Map(${varName}.map((item) => [item.id, item]));
+`;
+
+  const outPath = path.join(CONFIG_DIR, `${sectionName}.ts`);
+  fs.writeFileSync(outPath, content, "utf8");
+  console.log(`  ✓ Generated ${sectionName}.ts (${items.length} items)`);
+}
+
+console.log("Building config from config.yaml...");
+
+generateTsFile("devices", config.devices, "DeviceConfig", "devices", "deviceMap", "config.yaml");
+generateTsFile("hardware", config.hardware, "HardwareOption", "hardwareOptions", "hardwareMap", "config.yaml");
+generateTsFile("ports", config.ports, "PortConfig", "ports", "portMap", "config.yaml");
+
+console.log("Done!");

docs/src/components/DockerComposeGenerator/DockerComposeGenerator.tsx

@@ -0,0 +1,108 @@
+import React from "react";
+import Admonition from "@theme/Admonition";
+import DeviceSelector from "./components/DeviceSelector";
+import HardwareOptions from "./components/HardwareOptions";
+import PortConfigSection from "./components/PortConfig";
+import StoragePaths from "./components/StoragePaths";
+import NvidiaGpuConfig from "./components/NvidiaGpuConfig";
+import OtherOptions from "./components/OtherOptions";
+import GeneratedOutput from "./components/GeneratedOutput";
+import { useConfigGenerator } from "./hooks/useConfigGenerator";
+import styles from "./styles.module.css";
+
+/**
+ * Simple markdown-link-to-React renderer for help text.
+ * Only supports [text](url) syntax — no nested brackets.
+ */
+function renderHelpText(text: string): React.ReactNode {
+  const parts = text.split(/(\[[^\]]+\]\([^)]+\))/g);
+  return parts.map((part, i) => {
+    const match = part.match(/^\[([^\]]+)\]\(([^)]+)\)$/);
+    if (match) {
+      return (
+        <a key={i} href={match[2]}>
+          {match[1]}
+        </a>
+      );
+    }
+    return <React.Fragment key={i}>{part}</React.Fragment>;
+  });
+}
+
+export default function DockerComposeGenerator() {
+  const {
+    deviceId, device, hardwareEnabled,
+    portEnabled,
+    nvidiaGpuCount, nvidiaGpuDeviceId,
+    configPath, mediaPath, rtspPassword, timezone, shmSize,
+    shmSizeError, gpuDeviceIdError, configPathError, mediaPathError,
+    hasAnyHardware, generatedYaml,
+    selectDevice, toggleHardware, togglePort,
+    handleShmSizeChange, handleConfigPathChange, handleMediaPathChange,
+    handleNvidiaGpuCountChange, handleNvidiaGpuDeviceIdChange,
+    setRtspPassword, setTimezone, isHardwareDisabled,
+  } = useConfigGenerator();
+
+  return (
+    <div className={styles.generator}>
+      <div className={styles.card}>
+        <DeviceSelector selectedId={deviceId} onSelect={selectDevice} />
+
+        {device.helpText && (
+          <Admonition type={device.helpType || "info"}>
+            {renderHelpText(device.helpText)}
+          </Admonition>
+        )}
+
+        {device.needsNvidiaConfig && (
+          <NvidiaGpuConfig
+            gpuCount={nvidiaGpuCount}
+            gpuDeviceId={nvidiaGpuDeviceId}
+            gpuDeviceIdError={gpuDeviceIdError}
+            onGpuCountChange={handleNvidiaGpuCountChange}
+            onGpuDeviceIdChange={handleNvidiaGpuDeviceIdChange}
+          />
+        )}
+
+        <HardwareOptions
+          deviceId={deviceId}
+          hardwareEnabled={hardwareEnabled}
+          onToggle={toggleHardware}
+          isDisabled={isHardwareDisabled}
+        />
+
+        <StoragePaths
+          configPath={configPath}
+          mediaPath={mediaPath}
+          configPathError={configPathError}
+          mediaPathError={mediaPathError}
+          onConfigPathChange={handleConfigPathChange}
+          onMediaPathChange={handleMediaPathChange}
+        />
+
+        <PortConfigSection
+          portEnabled={portEnabled}
+          onTogglePort={togglePort}
+        />
+
+        <OtherOptions
+          rtspPassword={rtspPassword}
+          timezone={timezone}
+          shmSize={shmSize}
+          shmSizeError={shmSizeError}
+          onRtspPasswordChange={setRtspPassword}
+          onTimezoneChange={setTimezone}
+          onShmSizeChange={handleShmSizeChange}
+        />
+
+        <GeneratedOutput
+          yaml={generatedYaml}
+          configPath={configPath}
+          mediaPath={mediaPath}
+          hasAnyHardware={hasAnyHardware}
+          deviceId={deviceId}
+        />
+      </div>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/DeviceSelector.tsx

@@ -0,0 +1,147 @@
+import React from "react";
+import { useColorMode } from "@docusaurus/theme-common";
+import { devices } from "../config";
+import type { DeviceConfig } from "../config";
+import styles from "../styles.module.css";
+
+interface Props {
+  selectedId: string;
+  onSelect: (id: string) => void;
+}
+
+/**
+ * Determine the icon type from the icon string:
+ * - Starts with "<svg" → inline SVG
+ * - Starts with "/" or "http" → image URL/path
+ * - Otherwise → emoji text
+ */
+function getIconType(icon: string): "svg" | "image" | "emoji" {
+  const trimmed = icon.trim();
+  if (trimmed.startsWith("<svg")) return "svg";
+  if (trimmed.startsWith("/") || trimmed.startsWith("http://") || trimmed.startsWith("https://")) return "image";
+  return "emoji";
+}
+
+/**
+ * Check if the style object contains background-* properties,
+ * indicating the image should be rendered as a CSS background-image
+ * rather than an <img> tag.
+ */
+function hasBackgroundProps(style: React.CSSProperties | undefined): boolean {
+  if (!style) return false;
+  return Object.keys(style).some((key) => {
+    const k = key.toLowerCase().replace(/-/g, "");
+    return k === "backgroundsize" || k === "backgroundposition" || k === "backgroundrepeat" || k === "backgroundimage";
+  });
+}
+
+/**
+ * Convert a style object to CSS custom properties (e.g. { width: "24px" } → { "--svg-width": "24px" })
+ * so they can be consumed by CSS rules targeting child elements like <svg>.
+ */
+function toCssVars(style: React.CSSProperties | undefined, prefix: string): React.CSSProperties {
+  if (!style) return {};
+  const vars: Record<string, string> = {};
+  for (const [key, value] of Object.entries(style)) {
+    const cssKey = key.replace(/([A-Z])/g, "-$1").toLowerCase();
+    vars[`--${prefix}-${cssKey}`] = value;
+  }
+  return vars as React.CSSProperties;
+}
+
+function DeviceIcon({ device }: { device: DeviceConfig }) {
+  const { isDarkTheme } = useColorMode();
+  const iconStr = isDarkTheme && device.iconDark ? device.iconDark : device.icon;
+  const iconStyle = (isDarkTheme && device.iconDarkStyle
+    ? device.iconDarkStyle
+    : device.iconStyle) as React.CSSProperties | undefined;
+  const svgStyle = (isDarkTheme && device.svgDarkStyle
+    ? device.svgDarkStyle
+    : device.svgStyle) as React.CSSProperties | undefined;
+
+  const iconType = getIconType(iconStr);
+
+  if (iconType === "svg") {
+    return (
+      <div
+        className={styles.deviceIconSvg}
+        style={{ ...iconStyle, ...toCssVars(svgStyle, "svg") }}
+        dangerouslySetInnerHTML={{ __html: iconStr }}
+      />
+    );
+  }
+
+  if (iconType === "image") {
+    // When iconStyle contains background-* properties, render as background-image
+    // on the container div instead of an <img> tag, enabling background-size/position control.
+    if (hasBackgroundProps(iconStyle)) {
+      return (
+        <div
+          className={styles.deviceIconImage}
+          style={{
+            backgroundImage: `url(${iconStr})`,
+            backgroundRepeat: "no-repeat",
+            backgroundPosition: "center",
+            backgroundSize: "contain",
+            ...iconStyle,
+          }}
+        />
+      );
+    }
+    return (
+      <div className={styles.deviceIconImage}>
+        <img src={iconStr} alt={device.name} style={iconStyle} />
+      </div>
+    );
+  }
+
+  return (
+    <div className={styles.deviceIcon} style={iconStyle}>
+      {iconStr}
+    </div>
+  );
+}
+
+function DeviceCard({
+  device,
+  active,
+  onClick,
+}: {
+  device: DeviceConfig;
+  active: boolean;
+  onClick: () => void;
+}) {
+  return (
+    <div
+      className={`${styles.deviceCard} ${active ? styles.deviceCardActive : ""}`}
+      onClick={onClick}
+      role="button"
+      tabIndex={0}
+      onKeyDown={(e) => {
+        if (e.key === "Enter" || e.key === " ") onClick();
+      }}
+    >
+      <DeviceIcon device={device} />
+      <div className={styles.deviceName}>{device.name}</div>
+      <div className={styles.deviceDesc}>{device.description}</div>
+    </div>
+  );
+}
+
+export default function DeviceSelector({ selectedId, onSelect }: Props) {
+  return (
+    <div className={styles.formSection}>
+      <h4>Device Type</h4>
+      <div className={styles.deviceGrid}>
+        {devices.map((d) => (
+          <DeviceCard
+            key={d.id}
+            device={d}
+            active={selectedId === d.id}
+            onClick={() => onSelect(d.id)}
+          />
+        ))}
+      </div>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/GeneratedOutput.tsx

@@ -0,0 +1,60 @@
+import React, { useState, useCallback } from "react";
+import CodeBlock from "@theme/CodeBlock";
+import Admonition from "@theme/Admonition";
+import styles from "../styles.module.css";
+
+interface Props {
+  yaml: string;
+  configPath: string;
+  mediaPath: string;
+  hasAnyHardware: boolean;
+  deviceId: string;
+}
+
+export default function GeneratedOutput({
+  yaml,
+  configPath,
+  mediaPath,
+  hasAnyHardware,
+  deviceId,
+}: Props) {
+  const [copied, setCopied] = useState(false);
+
+  const handleCopy = useCallback(() => {
+    navigator.clipboard.writeText(yaml).then(() => {
+      setCopied(true);
+      setTimeout(() => setCopied(false), 2000);
+    });
+  }, [yaml]);
+
+  return (
+    <div className={styles.resultSection}>
+      <div className={styles.resultHeader}>
+        <h4>Generated Configuration</h4>
+        <button className="button button--primary button--sm" onClick={handleCopy}>
+          {copied ? "Copied!" : "Copy"}
+        </button>
+      </div>
+
+      {!configPath && (
+        <Admonition type="tip">
+          <p>You haven&apos;t specified a config file directory. You may want to modify the default path.</p>
+        </Admonition>
+      )}
+      {!mediaPath && (
+        <Admonition type="tip">
+          <p>You haven&apos;t specified a recording storage directory. You may want to modify the default path.</p>
+        </Admonition>
+      )}
+      {deviceId === "stable" && !hasAnyHardware && (
+        <Admonition type="warning">
+          <p>You haven&apos;t selected any hardware acceleration. Please check if you have supported hardware available.</p>
+        </Admonition>
+      )}
+
+      <CodeBlock language="yaml" title="docker-compose.yml">
+        {yaml}
+      </CodeBlock>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/HardwareOptions.tsx

@@ -0,0 +1,62 @@
+import React from "react";
+import { hardwareOptions } from "../config";
+import type { HardwareOption } from "../config";
+import styles from "../styles.module.css";
+
+interface Props {
+  deviceId: string;
+  hardwareEnabled: Record<string, boolean>;
+  onToggle: (hwId: string) => void;
+  isDisabled: (hwId: string) => boolean;
+}
+
+function renderDescription(text: string): React.ReactNode {
+  const parts = text.split(/(\[[^\]]+\]\([^)]+\))/g);
+  return parts.map((part, i) => {
+    const match = part.match(/^\[([^\]]+)\]\(([^)]+)\)$/);
+    if (match) {
+      return <a key={i} href={match[2]}>{match[1]}</a>;
+    }
+    return <React.Fragment key={i}>{part}</React.Fragment>;
+  });
+}
+
+function HardwareCheckbox({
+  hw, disabled, checked, onToggle,
+}: {
+  hw: HardwareOption; disabled: boolean; checked: boolean; onToggle: () => void;
+}) {
+  return (
+    <div className={styles.hardwareItem}>
+      <label className={`${styles.checkboxLabel} ${disabled ? styles.checkboxDisabled : ""}`}>
+        <input type="checkbox" checked={checked} onChange={onToggle} disabled={disabled} />
+        <span>{hw.label}</span>
+      </label>
+      {checked && hw.description && (
+        <div className={styles.hardwareDescription}>{renderDescription(hw.description)}</div>
+      )}
+    </div>
+  );
+}
+
+export default function HardwareOptions({ deviceId, hardwareEnabled, onToggle, isDisabled }: Props) {
+  return (
+    <div className={styles.formSection}>
+      <h4>Generic Hardware Devices</h4>
+      {deviceId !== "stable" && (
+        <p className={styles.helpText}>
+          Some options have been auto-configured based on your device type.
+        </p>
+      )}
+      <div className={styles.checkboxGrid}>
+        {hardwareOptions.map((hw) => {
+          const disabled = isDisabled(hw.id);
+          const checked = disabled ? false : !!hardwareEnabled[hw.id];
+          return (
+            <HardwareCheckbox key={hw.id} hw={hw} disabled={disabled} checked={checked} onToggle={() => onToggle(hw.id)} />
+          );
+        })}
+      </div>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/NvidiaGpuConfig.tsx

@@ -0,0 +1,64 @@
+import React from "react";
+import styles from "../styles.module.css";
+
+interface Props {
+  gpuCount: string;
+  gpuDeviceId: string;
+  gpuDeviceIdError: boolean;
+  onGpuCountChange: (value: string) => void;
+  onGpuDeviceIdChange: (value: string) => void;
+}
+
+export default function NvidiaGpuConfig({
+  gpuCount,
+  gpuDeviceId,
+  gpuDeviceIdError,
+  onGpuCountChange,
+  onGpuDeviceIdChange,
+}: Props) {
+  const showDeviceId = gpuCount !== "";
+
+  return (
+    <div className={styles.nvidiaConfig}>
+      <div className={styles.formGroup}>
+        <label htmlFor="dcg-gpu-count" className={styles.label}>
+          GPU count:
+        </label>
+        <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, ""))}
+        />
+      </div>
+      {showDeviceId && (
+        <div className={styles.formGroup}>
+          <label htmlFor="dcg-gpu-device-id" className={styles.label}>
+            GPU device IDs (required, comma-separated):
+          </label>
+          <input
+            id="dcg-gpu-device-id"
+            type="text"
+            className={`${styles.input} ${gpuDeviceIdError ? styles.inputError : ""}`}
+            value={gpuDeviceId}
+            placeholder="0"
+            onChange={(e) => onGpuDeviceIdChange(e.target.value)}
+          />
+          {gpuDeviceIdError ? (
+            <p className={styles.helpText}>
+              ⚠️ GPU device IDs are required when GPU count is a number
+            </p>
+          ) : (
+            <p className={styles.helpText}>
+              Single GPU: 0 &nbsp;|&nbsp; Multiple GPUs: 0,1,2
+            </p>
+          )}
+        </div>
+      )}
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/OtherOptions.tsx

@@ -0,0 +1,122 @@
+import React, { useMemo } 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;
+  shmSize: string;
+  shmSizeError: boolean;
+  onRtspPasswordChange: (value: string) => void;
+  onTimezoneChange: (value: string) => void;
+  onShmSizeChange: (value: string) => void;
+}
+
+export default function OtherOptions({
+  rtspPassword,
+  timezone,
+  shmSize,
+  shmSizeError,
+  onRtspPasswordChange,
+  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-timezone" className={styles.label}>
+            Timezone:
+          </label>
+          <select
+            id="dcg-timezone"
+            className={`${styles.input} ${styles.select}`}
+            value={selectedValue}
+            onChange={(e) =>
+              onTimezoneChange(
+                e.target.value === AUTO_TIMEZONE_VALUE ? "" : e.target.value
+              )
+            }
+          >
+            <option value={AUTO_TIMEZONE_VALUE}>
+              Use browser timezone ({systemTimezone})
+            </option>
+            {timezones.map((tz) => (
+              <option key={tz} value={tz}>
+                {tz}
+              </option>
+            ))}
+          </select>
+        </div>
+        <div className={styles.formGroup}>
+          <label htmlFor="dcg-shm-size" className={styles.label}>
+            Shared memory (SHM):
+          </label>
+          <input
+            id="dcg-shm-size"
+            type="text"
+            className={`${styles.input} ${shmSizeError ? styles.inputError : ""}`}
+            value={shmSize}
+            placeholder="512mb"
+            onChange={(e) => onShmSizeChange(e.target.value)}
+          />
+          {shmSizeError ? (
+            <p className={styles.helpText}>
+              ⚠️ Invalid format. Use a number followed by a unit (e.g. 512mb, 1gb)
+            </p>
+          ) : (
+            <p className={styles.helpText}>
+              See{" "}
+              <a href="/frigate/installation#calculating-required-shm-size">
+                calculating required SHM size
+              </a>{" "}
+              for the correct value.
+            </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>
+  );
+}

docs/src/components/DockerComposeGenerator/components/PortConfig.tsx

@@ -0,0 +1,71 @@
+import React from "react";
+import Admonition from "@theme/Admonition";
+import { ports } from "../config";
+import styles from "../styles.module.css";
+
+interface Props {
+  portEnabled: Record<string, boolean>;
+  onTogglePort: (portId: string) => void;
+}
+
+function PortItem({
+  port,
+  enabled,
+  onToggle,
+}: {
+  port: typeof ports[number];
+  enabled: boolean;
+  onToggle: () => void;
+}) {
+  const showWarning = port.warningContent && (
+    port.warningWhen === "checked" ? enabled :
+    port.warningWhen === "unchecked" ? !enabled : enabled
+  );
+
+  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}
+        </Admonition>
+      )}
+    </div>
+  );
+}
+
+export default function PortConfigSection({
+  portEnabled,
+  onTogglePort,
+}: Props) {
+  return (
+    <div className={styles.formSection}>
+      <h4>Port Configuration</h4>
+      <div className={styles.checkboxGrid}>
+        {ports.map((port) => (
+          <PortItem
+            key={port.id}
+            port={port}
+            enabled={!!portEnabled[port.id]}
+            onToggle={() => onTogglePort(port.id)}
+          />
+        ))}
+      </div>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/components/StoragePaths.tsx

@@ -0,0 +1,66 @@
+import React from "react";
+import styles from "../styles.module.css";
+
+interface Props {
+  configPath: string;
+  mediaPath: string;
+  configPathError: boolean;
+  mediaPathError: boolean;
+  onConfigPathChange: (value: string) => void;
+  onMediaPathChange: (value: string) => void;
+}
+
+export default function StoragePaths({
+  configPath,
+  mediaPath,
+  configPathError,
+  mediaPathError,
+  onConfigPathChange,
+  onMediaPathChange,
+}: Props) {
+  return (
+    <div className={styles.formSection}>
+      <h4>Storage Paths</h4>
+      <div className={styles.formGrid}>
+        <div className={styles.formGroup}>
+          <label htmlFor="dcg-config-path" className={styles.label}>
+            Config / DB / model cache directory (on your host):
+          </label>
+          <input
+            id="dcg-config-path"
+            type="text"
+            className={`${styles.input} ${configPathError ? styles.inputError : ""}`}
+            value={configPath}
+            placeholder="/path/to/your/config"
+            onChange={(e) => onConfigPathChange(e.target.value)}
+          />
+          {configPathError && (
+            <p className={styles.helpText}>
+              ⚠️ Path contains invalid characters. Only letters, numbers,
+              underscores, hyphens, slashes, and dots are allowed.
+            </p>
+          )}
+        </div>
+        <div className={styles.formGroup}>
+          <label htmlFor="dcg-media-path" className={styles.label}>
+            Recording storage directory (on your host):
+          </label>
+          <input
+            id="dcg-media-path"
+            type="text"
+            className={`${styles.input} ${mediaPathError ? styles.inputError : ""}`}
+            value={mediaPath}
+            placeholder="/path/to/your/storage"
+            onChange={(e) => onMediaPathChange(e.target.value)}
+          />
+          {mediaPathError && (
+            <p className={styles.helpText}>
+              ⚠️ Path contains invalid characters. Only letters, numbers,
+              underscores, hyphens, slashes, and dots are allowed.
+            </p>
+          )}
+        </div>
+      </div>
+    </div>
+  );
+}

docs/src/components/DockerComposeGenerator/config/index.ts

@@ -0,0 +1,12 @@
+export { devices, deviceMap } from "./devices";
+export { hardwareOptions, hardwareMap } from "./hardware";
+export { ports, portMap } from "./ports";
+
+export type {
+  DeviceConfig,
+  DeviceMapping,
+  VolumeMapping,
+  HardwareOption,
+  PortConfig,
+  NvidiaDeployConfig,
+} from "./types";

docs/src/components/DockerComposeGenerator/config/types.ts

@@ -0,0 +1,154 @@
+/**
+ * Type definitions for the Docker Compose Generator configuration.
+ * All device, hardware, and port options are declaratively defined
+ * so that adding a new device only requires editing config files.
+ */
+
+/** A single device mapping entry (e.g. /dev/dri:/dev/dri) */
+export interface DeviceMapping {
+  /** Host device path */
+  host: string;
+  /** Container device path (defaults to host if omitted) */
+  container?: string;
+  /** Inline comment for this device line */
+  comment?: string;
+}
+
+/** A single volume mapping entry */
+export interface VolumeMapping {
+  /** Host path */
+  host: string;
+  /** Container path */
+  container: string;
+  /** Whether the mount is read-only */
+  readOnly?: boolean;
+  /** Inline comment */
+  comment?: string;
+}
+
+/** NVIDIA deploy configuration for docker-compose */
+export interface NvidiaDeployConfig {
+  /** "all" or a specific number */
+  count: string;
+  /** Specific GPU device IDs (when count is a number) */
+  deviceIds?: string[];
+}
+
+/** Full device type definition */
+export interface DeviceConfig {
+  /** Unique identifier, e.g. "intel" */
+  id: string;
+  /** Display name, e.g. "Intel GPU" */
+  name: string;
+  /** Short description */
+  description: string;
+  /**
+   * Icon for the device card. Supports:
+   * - Emoji string (e.g. "🖥️")
+   * - Image URL or static path (e.g. "/img/intel.svg", "https://example.com/icon.png")
+   * - Inline SVG markup (e.g. "<svg>...</svg>")
+   */
+  icon: string;
+  /**
+   * Additional CSS properties applied to the icon element.
+   * - For image-type icons: if any `background-*` property (e.g. `background-size`,
+   *   `background-position`) is present, the image is rendered as a CSS `background-image`
+   *   on the container div, enabling full background positioning control.
+   *   Otherwise the image is rendered as an `<img>` tag and styles apply to it.
+   * - For emoji/SVG icons: styles apply to the container div.
+   */
+  iconStyle?: Record<string, string>;
+  /**
+   * Additional CSS properties applied directly to the inner `<svg>` element
+   * when the icon is an inline SVG. Use this to override the default
+   * `width: 100%; height: 100%` or set `fill`, `transform`, etc.
+   * Ignored for emoji and image-type icons.
+   */
+  svgStyle?: Record<string, string>;
+  /**
+   * Icon for dark mode. Same format as `icon`. When provided, this icon
+   * replaces `icon` when the user is in dark mode.
+   */
+  iconDark?: string;
+  /** Additional CSS properties for the dark mode icon container */
+  iconDarkStyle?: Record<string, string>;
+  /**
+   * SVG-specific styles for dark mode. Same as `svgStyle` but applied
+   * when dark mode is active. Merged over `svgStyle` in dark mode.
+   */
+  svgDarkStyle?: Record<string, string>;
+  /** Docker image tag, e.g. "stable" */
+  imageTag: string;
+  /**
+   * Image tag suffix appended to the base tag.
+   * e.g. "-standard-arm64" produces "stable-standard-arm64"
+   */
+  imageTagSuffix?: string;
+  /** Hardware option IDs to auto-enable when this device is selected */
+  autoHardware: string[];
+  /** Help text shown as an admonition when this device is selected */
+  helpText?: string;
+  /** Admonition type for help text */
+  helpType?: "info" | "warning" | "danger";
+  /** Device mappings always added for this device type */
+  devices?: DeviceMapping[];
+  /** Volume mappings always added for this device type */
+  volumes?: VolumeMapping[];
+  /** Extra environment variables for this device type */
+  env?: Record<string, string>;
+  /** NVIDIA deploy config (only for tensorrt) */
+  nvidiaDeploy?: NvidiaDeployConfig;
+  /** Runtime setting, e.g. "nvidia" for Jetson */
+  runtime?: string;
+  /** Extra hosts entries, e.g. "host.docker.internal:host-gateway" */
+  extraHosts?: string[];
+  /** Security options, e.g. ["apparmor=unconfined"] */
+  securityOpt?: string[];
+  /** Whether this device type needs the NVIDIA GPU config UI */
+  needsNvidiaConfig?: boolean;
+}
+
+/** Generic hardware acceleration option definition */
+export interface HardwareOption {
+  /** Unique identifier, e.g. "usbCoral" */
+  id: string;
+  /** Display label */
+  label: string;
+  /**
+   * Description shown below the checkbox when this option is enabled.
+   * Supports markdown link syntax: [text](url)
+   */
+  description?: string;
+  /** Device IDs that disable this option */
+  disabledWhen?: string[];
+  /** Device mappings added when this option is enabled */
+  devices?: DeviceMapping[];
+  /** Volume mappings added when this option is enabled */
+  volumes?: VolumeMapping[];
+  /** Extra environment variables */
+  env?: Record<string, string>;
+}
+
+/** Port definition */
+export interface PortConfig {
+  /** Unique identifier (also the default host port as string) */
+  id: string;
+  /** Host port number */
+  host: number;
+  /** Container port number */
+  container: number;
+  /** Protocol */
+  protocol?: "tcp" | "udp";
+  /** Description of the port's purpose */
+  description: string;
+  /** Whether enabled by default */
+  defaultEnabled: boolean;
+  /** Whether this port is locked (always enabled, cannot be toggled off) */
+  locked?: 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";
+}

docs/src/components/DockerComposeGenerator/generator/index.ts

@@ -0,0 +1,250 @@
+import type {
+  DeviceConfig,
+  DeviceMapping,
+  VolumeMapping,
+} from "../config/types";
+import { hardwareMap } from "../config";
+
+// ---------------------------------------------------------------------------
+// Input type
+// ---------------------------------------------------------------------------
+
+export interface GeneratorInput {
+  device: DeviceConfig;
+  selectedHardware: string[];
+  enabledPorts: string[];
+  configPath: string;
+  mediaPath: string;
+  rtspPassword?: string;
+  timezone: string;
+  shmSize: string;
+  nvidiaGpuCount?: string;
+  nvidiaGpuDeviceId?: string;
+}
+
+// ---------------------------------------------------------------------------
+// Helpers
+// ---------------------------------------------------------------------------
+
+function deviceLine(dm: DeviceMapping): string {
+  const host = dm.host;
+  const container = dm.container ?? dm.host;
+  const mapping = host === container ? host : `${host}:${container}`;
+  const comment = dm.comment ? ` # ${dm.comment}` : "";
+  return `      - ${mapping}${comment}`;
+}
+
+function volumeLine(vm: VolumeMapping): string {
+  const ro = vm.readOnly ? ":ro" : "";
+  const comment = vm.comment ? ` # ${vm.comment}` : "";
+  return `      - ${vm.host}:${vm.container}${ro}${comment}`;
+}
+
+// ---------------------------------------------------------------------------
+// YAML builder — each section returns an array of lines
+// ---------------------------------------------------------------------------
+
+function buildImage(device: DeviceConfig): string[] {
+  const tag = device.imageTagSuffix
+    ? `${device.imageTag}${device.imageTagSuffix}`
+    : device.imageTag;
+  return [`    image: ghcr.io/blakeblackshear/frigate:${tag}`];
+}
+
+function buildDevices(
+  device: DeviceConfig,
+  hwDevices: DeviceMapping[]
+): string[] {
+  const all: DeviceMapping[] = [
+    ...(device.devices ?? []),
+    ...hwDevices,
+  ];
+  if (all.length === 0) return [];
+  return [
+    "    devices:",
+    ...all.map(deviceLine),
+  ];
+}
+
+function buildVolumes(
+  device: DeviceConfig,
+  hwVolumes: VolumeMapping[],
+  configPath: string,
+  mediaPath: string
+): string[] {
+  const all: VolumeMapping[] = [
+    ...(device.volumes ?? []),
+    ...hwVolumes,
+  ];
+  return [
+    "    volumes:",
+    "      - /etc/localtime:/etc/localtime:ro # Sync host time",
+    `      - ${configPath}:/config # Config file directory`,
+    `      - ${mediaPath}:/media/frigate # Recording storage directory`,
+    "      - type: tmpfs # 1GB in-memory filesystem for recording segment storage",
+    "        target: /tmp/cache",
+    "        tmpfs:",
+    "          size: 1000000000",
+    ...all.map(volumeLine),
+  ];
+}
+
+function buildPorts(enabledPorts: string[]): string[] {
+  return [
+    "    ports:",
+    ...enabledPorts,
+  ];
+}
+
+function buildEnvironment(
+  device: DeviceConfig,
+  hwEnv: Record<string, string>,
+  rtspPassword: string | undefined,
+  timezone: string
+): string[] {
+  const allEnv: Record<string, string> = {
+    ...hwEnv,
+    ...(device.env ?? {}),
+  };
+
+  const lines: string[] = ["    environment:"];
+
+  if (rtspPassword) {
+    lines.push(
+      `      FRIGATE_RTSP_PASSWORD: "${rtspPassword}" # RTSP password — change to your own`
+    );
+  }
+
+  lines.push(`      TZ: "${timezone}" # Timezone`);
+
+  for (const [key, value] of Object.entries(allEnv)) {
+    lines.push(`      ${key}: "${value}"`);
+  }
+
+  return lines;
+}
+
+function buildDeploy(device: DeviceConfig, input: GeneratorInput): string[] {
+  if (device.id === "stable-tensorrt") {
+    const count = input.nvidiaGpuCount || "all";
+    const isAll = count === "all";
+    const deviceId = input.nvidiaGpuDeviceId?.trim();
+
+    if (isAll) {
+      return [
+        "    deploy:",
+        "      resources:",
+        "        reservations:",
+        "          devices:",
+        "            - driver: nvidia",
+        "              count: all # Use all GPUs",
+        "              capabilities: [gpu]",
+      ];
+    }
+
+    if (deviceId) {
+      const ids = deviceId
+        .split(",")
+        .map((s) => s.trim())
+        .filter(Boolean)
+        .map((s) => `'${s}'`)
+        .join(", ");
+      return [
+        "    deploy:",
+        "      resources:",
+        "        reservations:",
+        "          devices:",
+        "            - driver: nvidia",
+        `              device_ids: [${ids}] # GPU device IDs`,
+        `              count: ${count} # GPU count`,
+        "              capabilities: [gpu]",
+      ];
+    }
+
+    return [
+      "    deploy:",
+      "      resources:",
+      "        reservations:",
+      "          devices:",
+      "            - driver: nvidia",
+      `              count: ${count} # GPU count`,
+      "              capabilities: [gpu]",
+    ];
+  }
+
+  return [];
+}
+
+function buildRuntime(device: DeviceConfig): string[] {
+  if (device.runtime) {
+    return [`    runtime: ${device.runtime}`];
+  }
+  return [];
+}
+
+function buildExtraHosts(device: DeviceConfig): string[] {
+  if (!device.extraHosts?.length) return [];
+  return [
+    "    extra_hosts:",
+    ...device.extraHosts.map(
+      (h, i) =>
+        `      - "${h}"${i === 0 ? " # Required to talk to the NPU detector" : ""}`
+    ),
+  ];
+}
+
+function buildSecurityOpt(device: DeviceConfig): string[] {
+  if (!device.securityOpt?.length) return [];
+  return [
+    "    security_opt:",
+    ...device.securityOpt.map((s) => `      - ${s}`),
+  ];
+}
+
+// ---------------------------------------------------------------------------
+// Public API
+// ---------------------------------------------------------------------------
+
+/**
+ * Generate a docker-compose YAML string from the given input.
+ * The output is pure YAML with inline comments (no Shiki annotations).
+ */
+export function generateDockerCompose(input: GeneratorInput): string {
+  const { device } = input;
+
+  // Collect hardware-level devices, volumes, and env
+  const hwDevices: DeviceMapping[] = [];
+  const hwVolumes: VolumeMapping[] = [];
+  const hwEnv: Record<string, string> = {};
+
+  for (const hwId of input.selectedHardware) {
+    const hw = hardwareMap.get(hwId);
+    if (!hw) continue;
+    // Skip GPU device mapping for tensorrt images (it uses deploy instead)
+    if (hw.id === "gpu" && device.imageTag === "stable-tensorrt") continue;
+    hwDevices.push(...(hw.devices ?? []));
+    hwVolumes.push(...(hw.volumes ?? []));
+    Object.assign(hwEnv, hw.env ?? {});
+  }
+
+  const lines: string[] = [
+    "services:",
+    "  frigate:",
+    "    container_name: frigate",
+    "    privileged: true # This may not be necessary for all setups",
+    "    restart: unless-stopped",
+    "    stop_grace_period: 30s # Allow enough time to shut down the various services",
+    ...buildImage(device),
+    `    shm_size: "${input.shmSize || "512mb"}" # Update for your cameras based on SHM calculation`,
+    ...buildRuntime(device),
+    ...buildDeploy(device, input),
+    ...buildExtraHosts(device),
+    ...buildSecurityOpt(device),
+    ...buildDevices(device, hwDevices),
+    ...buildVolumes(device, hwVolumes, input.configPath, input.mediaPath),
+    ...buildPorts(input.enabledPorts),
+    ...buildEnvironment(device, hwEnv, input.rtspPassword, input.timezone),
+  ];
+
+  return lines.join("\n");
+}

docs/src/components/DockerComposeGenerator/hooks/useConfigGenerator.ts

@@ -0,0 +1,195 @@
+import { useState, useCallback, useMemo } from "react";
+import { deviceMap, hardwareMap, portMap } from "../config";
+import { generateDockerCompose } from "../generator";
+import type { GeneratorInput } from "../generator";
+
+/**
+ * Main hook that holds all form state and generates the Docker Compose output.
+ * Configuration is loaded synchronously from build-time generated .ts files.
+ */
+export function useConfigGenerator() {
+  const [deviceId, setDeviceId] = useState("stable");
+
+  const [hardwareEnabled, setHardwareEnabled] = useState<Record<string, boolean>>(() => {
+    const defaultDevice = deviceMap.get("stable");
+    const initial: Record<string, boolean> = {};
+    if (defaultDevice) {
+      for (const hwId of defaultDevice.autoHardware) {
+        initial[hwId] = true;
+      }
+    }
+    return initial;
+  });
+
+  const [portEnabled, setPortEnabled] = useState<Record<string, boolean>>(() => {
+    const initial: Record<string, boolean> = {};
+    for (const p of portMap.values()) {
+      initial[p.id] = p.defaultEnabled;
+    }
+    return initial;
+  });
+
+  const [nvidiaGpuCount, setNvidiaGpuCount] = useState("");
+  const [nvidiaGpuDeviceId, setNvidiaGpuDeviceId] = useState("");
+  const [configPath, setConfigPath] = useState("");
+  const [mediaPath, setMediaPath] = useState("");
+  const [rtspPassword, setRtspPassword] = useState("");
+  const [timezone, setTimezone] = useState("");
+  const [shmSize, setShmSize] = useState("512mb");
+  const [shmSizeError, setShmSizeError] = useState(false);
+  const [gpuDeviceIdError, setGpuDeviceIdError] = useState(false);
+  const [configPathError, setConfigPathError] = useState(false);
+  const [mediaPathError, setMediaPathError] = useState(false);
+
+  const device = useMemo(() => deviceMap.get(deviceId)!, [deviceId]);
+
+  const selectDevice = useCallback((id: string) => {
+    const newDevice = deviceMap.get(id);
+    if (!newDevice) return;
+    setDeviceId(id);
+    setHardwareEnabled(() => {
+      const next: Record<string, boolean> = {};
+      for (const hwId of newDevice.autoHardware) {
+        next[hwId] = true;
+      }
+      return next;
+    });
+    setNvidiaGpuCount("");
+    setNvidiaGpuDeviceId("");
+    setGpuDeviceIdError(false);
+  }, []);
+
+  const toggleHardware = useCallback((hwId: string) => {
+    setHardwareEnabled((prev) => ({ ...prev, [hwId]: !prev[hwId] }));
+  }, []);
+
+  const togglePort = useCallback((portId: string) => {
+    const port = portMap.get(portId);
+    if (port?.locked) return;
+    setPortEnabled((prev) => ({ ...prev, [portId]: !prev[portId] }));
+  }, []);
+
+  const isHardwareDisabled = useCallback(
+    (hwId: string): boolean => {
+      const hw = hardwareMap.get(hwId);
+      if (!hw) return false;
+      return hw.disabledWhen?.includes(deviceId) ?? false;
+    },
+    [deviceId]
+  );
+
+  const validateShmSize = useCallback((value: string): boolean => {
+    if (!value) return true;
+    return /^\d+(\.\d+)?[bkmgBKMG]{1,2}$/.test(value);
+  }, []);
+
+  const validatePath = useCallback((value: string): boolean => {
+    if (!value) return true;
+    return /^[a-zA-Z0-9_\-/./]+$/.test(value);
+  }, []);
+
+  const handleShmSizeChange = useCallback(
+    (value: string) => {
+      const filtered = value.replace(/[^0-9.bkmgBKMG]/g, "");
+      const valid = validateShmSize(filtered);
+      setShmSize(filtered);
+      setShmSizeError(!valid && filtered !== "");
+    },
+    [validateShmSize]
+  );
+
+  const handleConfigPathChange = useCallback(
+    (value: string) => {
+      const filtered = value.replace(/[^a-zA-Z0-9_\-/./]/g, "");
+      const valid = validatePath(filtered);
+      setConfigPath(filtered);
+      setConfigPathError(!valid && filtered !== "");
+    },
+    [validatePath]
+  );
+
+  const handleMediaPathChange = useCallback(
+    (value: string) => {
+      const filtered = value.replace(/[^a-zA-Z0-9_\-/./]/g, "");
+      const valid = validatePath(filtered);
+      setMediaPath(filtered);
+      setMediaPathError(!valid && filtered !== "");
+    },
+    [validatePath]
+  );
+
+  const handleNvidiaGpuCountChange = useCallback((value: string) => {
+    // Only allow digits
+    setNvidiaGpuCount(value);
+    if (value === "") {
+      setNvidiaGpuDeviceId("");
+      setGpuDeviceIdError(false);
+    } else {
+      setGpuDeviceIdError(false);
+    }
+  }, []);
+
+  const handleNvidiaGpuDeviceIdChange = useCallback((value: string) => {
+    setNvidiaGpuDeviceId(value.trim());
+    setGpuDeviceIdError(false);
+  }, []);
+
+  const enabledPortLines = useMemo(() => {
+    const lines: string[] = [];
+    for (const [id, enabled] of Object.entries(portEnabled)) {
+      if (!enabled) continue;
+      const p = portMap.get(id);
+      if (!p) continue;
+      const proto = p.protocol && p.protocol !== "tcp" ? `/${p.protocol}` : "";
+      const comment = p.description ? ` # ${p.description}` : "";
+      lines.push(`      - "${p.host}:${p.container}${proto}"${comment}`);
+    }
+    return lines;
+  }, [portEnabled]);
+
+  const selectedHardwareIds = useMemo(() => {
+    return Object.entries(hardwareEnabled)
+      .filter(([id, enabled]) => {
+        if (!enabled) return false;
+        const hw = hardwareMap.get(id);
+        if (!hw) return false;
+        if (hw.disabledWhen?.includes(deviceId)) return false;
+        return true;
+      })
+      .map(([id]) => id);
+  }, [hardwareEnabled, deviceId]);
+
+  const generatedYaml = useMemo(() => {
+    const input: GeneratorInput = {
+      device,
+      selectedHardware: selectedHardwareIds,
+      enabledPorts: enabledPortLines,
+      configPath: configPath || "/path/to/your/config",
+      mediaPath: mediaPath || "/path/to/your/storage",
+      rtspPassword,
+      timezone: timezone || Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC",
+      shmSize: shmSize || "512mb",
+      nvidiaGpuCount,
+      nvidiaGpuDeviceId,
+    };
+    return generateDockerCompose(input);
+  }, [
+    device, selectedHardwareIds, enabledPortLines,
+    configPath, mediaPath, rtspPassword, timezone, shmSize,
+    nvidiaGpuCount, nvidiaGpuDeviceId,
+  ]);
+
+  const hasAnyHardware = selectedHardwareIds.length > 0 || !!device?.devices?.length;
+
+  return {
+    deviceId, device, hardwareEnabled, portEnabled,
+    nvidiaGpuCount, nvidiaGpuDeviceId,
+    configPath, mediaPath, rtspPassword, timezone, shmSize,
+    shmSizeError, gpuDeviceIdError, configPathError, mediaPathError,
+    hasAnyHardware, generatedYaml,
+    selectDevice, toggleHardware, togglePort,
+    handleShmSizeChange, handleConfigPathChange, handleMediaPathChange,
+    handleNvidiaGpuCountChange, handleNvidiaGpuDeviceIdChange,
+    setRtspPassword, setTimezone, isHardwareDisabled,
+  };
+}

docs/src/components/DockerComposeGenerator/index.ts

@@ -0,0 +1 @@
+export { default } from "./DockerComposeGenerator";

docs/src/components/DockerComposeGenerator/styles.module.css

@@ -0,0 +1,381 @@
+/* ===================================================================
+   Docker Compose Generator — styles
+   Uses Docusaurus / Infima CSS variables for theme compatibility.
+   =================================================================== */
+
+.generator {
+  margin: 2rem 0;
+}
+
+.card {
+  background: var(--ifm-background-surface-color);
+  border: 1px solid var(--ifm-color-emphasis-400);
+  border-radius: 12px;
+  padding: 2rem;
+  box-shadow: var(--ifm-global-shadow-lw);
+}
+
+[data-theme="light"] .card {
+  background: var(--ifm-color-emphasis-100);
+  border: 1px solid var(--ifm-color-emphasis-300);
+}
+
+/* --- Form sections --- */
+
+.formSection {
+  margin-bottom: 1.5rem;
+  padding-bottom: 1.5rem;
+  border-bottom: 1px solid var(--ifm-color-emphasis-400);
+}
+
+.formSection:last-child {
+  border-bottom: none;
+  margin-bottom: 0;
+  padding-bottom: 0;
+}
+
+.formSection h4 {
+  margin: 0 0 1rem 0;
+  color: var(--ifm-font-color-base);
+  font-size: 1.1rem;
+  font-weight: var(--ifm-font-weight-semibold);
+}
+
+/* --- Form controls --- */
+
+.formGroup {
+  margin-bottom: 1rem;
+}
+
+.formGroup:last-child {
+  margin-bottom: 0;
+}
+
+.label {
+  display: block;
+  margin-bottom: 0.25rem;
+  color: var(--ifm-font-color-base);
+  font-weight: var(--ifm-font-weight-semibold);
+  font-size: 0.9rem;
+}
+
+.input {
+  width: 100%;
+  padding: 0.5rem 0.75rem;
+  border: 1px solid var(--ifm-color-emphasis-400);
+  border-radius: 6px;
+  background: var(--ifm-background-color);
+  color: var(--ifm-font-color-base);
+  font-size: 0.95rem;
+  transition: border-color 0.2s, box-shadow 0.2s;
+}
+
+[data-theme="light"] .input {
+  background: #fff;
+  border: 1px solid #d0d7de;
+}
+
+.input:focus {
+  outline: none;
+  border-color: var(--ifm-color-primary);
+  box-shadow: 0 0 0 3px var(--ifm-color-primary-lightest);
+}
+
+[data-theme="dark"] .input {
+  border-color: var(--ifm-color-emphasis-300);
+}
+
+.inputError {
+  border-color: #e74c3c;
+  animation: shake 0.3s ease-in-out;
+}
+
+@keyframes shake {
+  0%,
+  100% {
+    transform: translateX(0);
+  }
+  25% {
+    transform: translateX(-5px);
+  }
+  75% {
+    transform: translateX(5px);
+  }
+}
+
+/* --- 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;
+  color: var(--ifm-font-color-secondary);
+  line-height: 1.5;
+}
+
+.helpText a {
+  color: var(--ifm-color-primary);
+}
+
+/* --- Device grid --- */
+
+.deviceGrid {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, minmax(130px, 1fr));
+  gap: 0.75rem;
+  margin-top: 0.5rem;
+}
+
+.deviceCard {
+  padding: 0.75rem;
+  border: 2px solid var(--ifm-color-emphasis-400);
+  border-radius: 12px;
+  cursor: pointer;
+  transition: all 0.2s;
+  text-align: center;
+  background: var(--ifm-background-color);
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+}
+
+[data-theme="light"] .deviceCard {
+  border: 2px solid #d0d7de;
+  background: #fff;
+}
+
+.deviceCard:hover {
+  border-color: var(--ifm-color-primary);
+  background: var(--ifm-color-emphasis-100);
+  transform: translateY(-2px);
+}
+
+.deviceCardActive {
+  border-color: var(--ifm-color-primary);
+  background: var(--ifm-color-primary-lightest);
+  box-shadow: 0 0 0 1px var(--ifm-color-primary);
+}
+
+[data-theme="light"] .deviceCardActive {
+  background: color-mix(in srgb, var(--ifm-color-primary) 12%, #fff);
+}
+
+[data-theme="dark"] .deviceCardActive {
+  background: color-mix(in srgb, var(--ifm-color-primary) 25%, #1b1b1b);
+}
+
+[data-theme="dark"] .deviceCardActive .deviceName {
+  color: var(--ifm-color-primary-light);
+}
+
+[data-theme="dark"] .deviceCardActive .deviceDesc {
+  color: var(--ifm-color-primary-light);
+  opacity: 0.85;
+}
+
+.deviceIcon {
+  font-size: 2rem;
+  margin-bottom: 0.25rem;
+  height: 40px;
+  width: 50px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+}
+
+.deviceIconSvg {
+  margin-bottom: 0.25rem;
+  height: 40px;
+  width: 50px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  overflow: visible;
+  /* Allow iconStyle width/height to override */
+  flex-shrink: 0;
+}
+
+.deviceIconSvg svg {
+  width: var(--svg-width, 100%);
+  height: var(--svg-height, 100%);
+  fill: var(--svg-fill, currentColor);
+  transform: var(--svg-transform, none);
+}
+
+.deviceIconImage {
+  margin-bottom: 0.25rem;
+  height: 40px;
+  width: 50px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+}
+
+.deviceIconImage img {
+  max-width: 100%;
+  max-height: 100%;
+  object-fit: contain;
+}
+
+.deviceName {
+  font-weight: var(--ifm-font-weight-semibold);
+  color: var(--ifm-font-color-base);
+  margin-bottom: 0.15rem;
+  font-size: 0.9rem;
+}
+
+.deviceDesc {
+  font-size: 0.75rem;
+  color: var(--ifm-font-color-secondary);
+  line-height: 1.3;
+}
+
+/* --- Checkbox grid --- */
+
+.checkboxGrid {
+  display: grid;
+  grid-template-columns: repeat(2, 1fr);
+  gap: 0.5rem;
+}
+
+@media (max-width: 576px) {
+  .checkboxGrid {
+    grid-template-columns: 1fr;
+  }
+}
+
+.hardwareItem {
+  margin-bottom: 0;
+}
+
+.hardwareDescription {
+  margin: 0.15rem 0 0.4rem 1.6rem;
+  font-size: 0.8rem;
+  color: var(--ifm-font-color-secondary);
+  line-height: 1.5;
+}
+
+.hardwareDescription a {
+  color: var(--ifm-color-primary);
+  text-decoration: underline;
+  text-underline-offset: 2px;
+}
+
+.checkboxLabel {
+  display: flex;
+  align-items: center;
+  gap: 0.5rem;
+  cursor: pointer;
+  padding: 0.4rem 0.5rem;
+  border-radius: 6px;
+  transition: background-color 0.2s;
+  font-size: 0.9rem;
+}
+
+.checkboxLabel:hover {
+  background: var(--ifm-color-emphasis-100);
+}
+
+.checkboxLabel input[type="checkbox"] {
+  width: 1.1rem;
+  height: 1.1rem;
+  cursor: pointer;
+  flex-shrink: 0;
+}
+
+.checkboxLabel span {
+  color: var(--ifm-font-color-base);
+}
+
+.checkboxDisabled {
+  cursor: not-allowed;
+}
+
+.checkboxDisabled:hover {
+  background: transparent;
+}
+
+.checkboxDisabled input[type="checkbox"] {
+  cursor: not-allowed;
+  opacity: 0.5;
+}
+
+/* --- Form grid (side-by-side) --- */
+
+.formGrid {
+  display: grid;
+  grid-template-columns: repeat(2, 1fr);
+  gap: 1rem;
+}
+
+@media (max-width: 576px) {
+  .formGrid {
+    grid-template-columns: 1fr;
+  }
+}
+
+.formGrid .formGroup {
+  margin-bottom: 0;
+}
+
+/* --- Port section --- */
+
+.portSection {
+  margin-bottom: 0.75rem;
+}
+
+.warningBadge {
+  margin-left: auto;
+  color: #e67e22;
+  font-size: 0.85rem;
+}
+
+/* --- NVIDIA config --- */
+
+.nvidiaConfig {
+  margin-top: 1rem;
+  margin-bottom: 1.5rem;
+  padding: 1rem;
+  background: var(--ifm-background-color);
+  border-radius: 8px;
+  border-left: 3px solid var(--ifm-color-primary);
+}
+
+[data-theme="light"] .nvidiaConfig {
+  background: #f6f8fa;
+  border-left: 3px solid var(--ifm-color-primary);
+}
+
+/* --- Result section --- */
+
+.resultSection {
+  margin-top: 2rem;
+}
+
+.resultHeader {
+  display: flex;
+  justify-content: space-between;
+  align-items: center;
+  margin-bottom: 1rem;
+}
+
+.resultHeader h4 {
+  margin: 0;
+  color: var(--ifm-font-color-base);
+}

docs/static/frigate-api.yaml

@@ -5997,7 +5997,10 @@ paths:
       tags:
         - App
       summary: Start debug replay
-      description: Start a debug replay session from camera recordings.
+      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.
       operationId: start_debug_replay_debug_replay_start_post
       requestBody:
         required: true
@@ -6006,12 +6009,16 @@ paths:
             schema:
               $ref: "#/components/schemas/DebugReplayStartBody"
       responses:
-        "200":
+        "202":
           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:
@@ -6272,10 +6279,14 @@ 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:

frigate/api/app.py

@@ -146,8 +146,13 @@ def config(request: Request):
         for name, detector in config_obj.detectors.items()
     }
 
-    # remove the mqtt password
+    # remove environment_vars for non-admin users
+    if request.headers.get("remote-role") != "admin":
+        config.pop("environment_vars", None)
+
+    # remove mqtt credentials
     config["mqtt"].pop("password", None)
+    config["mqtt"].pop("user", None)
 
     # remove the proxy secret
     config["proxy"].pop("auth_secret", None)

frigate/api/debug_replay.py

@@ -10,6 +10,7 @@ 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__)
 
@@ -29,10 +30,17 @@ class DebugReplayStartResponse(BaseModel):
 
     success: bool
     replay_camera: str
+    job_id: str
 
 
 class DebugReplayStatusResponse(BaseModel):
-    """Response for debug replay status."""
+    """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").
+    """
 
     active: bool
     replay_camera: str | None = None
@@ -51,15 +59,32 @@ 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.",
+    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.",
 )
 async def start_debug_replay(request: Request, body: DebugReplayStartBody):
-    """Start a debug replay session."""
+    """Start a debug replay session asynchronously."""
     replay_manager = request.app.replay_manager
 
-    if replay_manager.active:
+    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:
         return JSONResponse(
             content={
                 "success": False,
@@ -67,38 +92,23 @@ 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("Invalid parameters for debug replay start request")
+        logger.exception("Rejected debug replay start request")
         return JSONResponse(
             content={
                 "success": False,
-                "message": "Invalid debug replay request parameters",
+                "message": "Invalid debug replay 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 DebugReplayStartResponse(
-        success=True,
-        replay_camera=replay_camera,
+    return JSONResponse(
+        content={
+            "success": True,
+            "replay_camera": replay_manager.replay_camera_name,
+            "job_id": job_id,
+        },
+        status_code=202,
     )
 
 
@@ -118,12 +128,16 @@ 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)
+        frame = (
+            frame_processor.get_current_frame(replay_camera)
+            if frame_processor is not None
+            else None
+        )
 
         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
+            retry_interval = 10.0
 
             if camera_config is not None:
                 retry_interval = float(camera_config.ffmpeg.retry_interval or 10)

frigate/api/media.py

@@ -174,12 +174,10 @@ async def latest_frame(
     }
     quality_params = get_image_quality_params(extension.value, params.quality)
 
-    if camera_name in request.app.frigate_config.cameras:
+    camera_config = request.app.frigate_config.cameras.get(camera_name)
+    if camera_config is not None:
         frame = frame_processor.get_current_frame(camera_name, draw_options)
-        retry_interval = float(
-            request.app.frigate_config.cameras.get(camera_name).ffmpeg.retry_interval
-            or 10
-        )
+        retry_interval = float(camera_config.ffmpeg.retry_interval or 10)
 
         is_offline = False
         if frame is None or datetime.now().timestamp() > (
@@ -1368,12 +1366,17 @@ 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 sorted(os.listdir(preview_dir)):
-            if not file.startswith(file_start):
-                continue
-
+        for file in camera_files:
             if file < start_file:
                 continue
 
@@ -1550,12 +1553,17 @@ 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 sorted(os.listdir(preview_dir)):
-            if not file.startswith(file_start):
-                continue
-
+        for file in camera_files:
             if file < start_file:
                 continue
 

frigate/api/preview.py

@@ -148,12 +148,17 @@ 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 sorted(os.listdir(preview_dir)):
-        if not file.startswith(file_start):
-            continue
-
+    for file in camera_files:
         if file < start_file:
             continue
 

frigate/comms/webpush.py

@@ -429,7 +429,10 @@ class WebPushClient(Communicator):
             else:
                 title = base_title
 
-            message = payload["after"]["data"]["metadata"]["shortSummary"]
+            if payload["after"]["data"]["metadata"].get("shortSummary"):
+                message = payload["after"]["data"]["metadata"]["shortSummary"]
+            else:
+                message = f"Detected on {camera_name}"
         else:
             zone_names = payload["after"]["data"]["zones"]
             formatted_zone_names = []

frigate/comms/ws.py

@@ -17,9 +17,90 @@ 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:
@@ -49,6 +130,7 @@ 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:
@@ -63,11 +145,25 @@ class WebSocketClient(Communicator):
                     )
                     return
 
-                logger.debug(
-                    f"Publishing mqtt message from websockets at {json_message['topic']}."
+                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
                 )
+                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(
-                    json_message["topic"],
+                    topic,
                     json_message["payload"],
                 )
 

frigate/const.py

@@ -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(CACHE_DIR, "replay")
+REPLAY_DIR = os.path.join(CLIPS_DIR, "replay")
 PLUS_ENV_VAR = "PLUS_API_KEY"
 PLUS_API_HOST = "https://api.frigate.video"
 

frigate/data_processing/common/license_plate/mixin.py

@@ -1073,10 +1073,6 @@ 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
@@ -1092,9 +1088,6 @@ 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
@@ -1360,8 +1353,8 @@ class LicensePlateProcessingMixin:
                 )
 
                 # check that license plate is valid
-                # double the value because we've doubled the size of the car
-                if license_plate_area < self.config.cameras[camera].lpr.min_area * 2:
+                # quadruple the value because we've doubled both dimensions of the car
+                if license_plate_area < self.config.cameras[camera].lpr.min_area * 4:
                     logger.debug(f"{camera}: License plate is less than min_area")
                     return
 
@@ -1465,6 +1458,7 @@ 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

frigate/data_processing/post/review_descriptions.py

@@ -366,12 +366,17 @@ 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 sorted(os.listdir(preview_dir)):
-            if not file.startswith(file_start):
-                continue
-
+        for file in camera_files:
             if file < start_file:
                 if len(all_frames):
                     all_frames[0] = os.path.join(preview_dir, file)

frigate/debug_replay.py

@@ -1,9 +1,13 @@
-"""Debug replay camera management for replaying recordings with detection overlays."""
+"""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.
+"""
 
 import logging
 import os
 import shutil
-import subprocess as sp
 import threading
 
 from ruamel.yaml import YAML
@@ -21,7 +25,7 @@ from frigate.const import (
     REPLAY_DIR,
     THUMB_DIR,
 )
-from frigate.models import Recordings
+from frigate.jobs.debug_replay import cancel_debug_replay_job, wait_for_runner
 from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
 from frigate.util.config import find_config_file
 
@@ -29,7 +33,14 @@ logger = logging.getLogger(__name__)
 
 
 class DebugReplayManager:
-    """Manages a single debug replay session."""
+    """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.
+    """
 
     def __init__(self) -> None:
         self._lock = threading.Lock()
@@ -41,144 +52,66 @@ class DebugReplayManager:
 
     @property
     def active(self) -> bool:
-        """Whether a replay session is currently active."""
+        """True from mark_starting until clear_session."""
         return self.replay_camera_name is not None
 
-    def start(
+    def mark_starting(
         self,
         source_camera: str,
+        replay_camera_name: str,
         start_ts: float,
         end_ts: float,
-        frigate_config: FrigateConfig,
-        config_publisher: CameraConfigUpdatePublisher,
-    ) -> str:
-        """Start a debug replay session.
+    ) -> None:
+        """Synchronously claim the session before the job runner starts.
 
-        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
+        Called inside the API handler so the status bar sees active=True
+        immediately, before the worker thread does any ffmpeg work.
         """
         with self._lock:
-            return self._start_locked(
-                source_camera, start_ts, end_ts, frigate_config, config_publisher
-            )
+            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 _start_locked(
+    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,
-        start_ts: float,
-        end_ts: float,
+        replay_name: str,
+        clip_path: str,
         frigate_config: FrigateConfig,
         config_publisher: CameraConfigUpdatePublisher,
-    ) -> str:
-        if self.active:
-            raise ValueError("A replay session is already active")
+    ) -> None:
+        """Build the in-memory replay camera config and publish the add event.
 
-        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
+        Called by the job runner during the starting_camera phase.
+        """
         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:
@@ -191,75 +124,48 @@ class DebugReplayManager:
         try:
             new_config = FrigateConfig.parse_object(config_data)
         except Exception as e:
-            raise RuntimeError(f"Failed to validate replay camera config: {e}")
-
-        # Update the running config
+            raise RuntimeError(f"Failed to validate replay camera config: {e}") from e
         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:
-        """Stop the active replay session and clean up all artifacts.
+        """Cancel any in-flight startup job and tear down the active session.
 
-        Args:
-            frigate_config: Current Frigate configuration
-            config_publisher: Publisher for camera config updates
+        Safe to call when no session is active (no-op with a warning).
         """
+        cancel_debug_replay_job()
+        wait_for_runner(timeout=2.0)
+
         with self._lock:
-            self._stop_locked(frigate_config, config_publisher)
+            if not self.active:
+                logger.warning("No active replay session to stop")
+                return
 
-    def _stop_locked(
-        self,
-        frigate_config: FrigateConfig,
-        config_publisher: CameraConfigUpdatePublisher,
-    ) -> None:
-        if not self.active:
-            logger.warning("No active replay session to stop")
-            return
+            replay_name = self.replay_camera_name
 
-        replay_name = self.replay_camera_name
+            # 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],
+                )
 
-        # 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
+            if replay_name is not None:
+                self._cleanup_db(replay_name)
+                self._cleanup_files(replay_name)
 
-        # Defensive DB cleanup
-        self._cleanup_db(replay_name)
+            self._clear_locked()
 
-        # 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)
+            logger.info("Debug replay stopped and cleaned up: %s", replay_name)
 
     def _build_camera_config_dict(
         self,
@@ -267,16 +173,7 @@ class DebugReplayManager:
         replay_name: str,
         clip_path: str,
     ) -> dict:
-        """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
-        """
+        """Build a camera config dictionary for the replay camera."""
         # Extract detect config (exclude computed fields)
         detect_dict = source_config.detect.model_dump(
             exclude={"min_initialized", "max_disappeared", "enabled_in_config"}
@@ -311,7 +208,6 @@ 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
 

frigate/detectors/plugins/openvino.py

@@ -52,6 +52,12 @@ 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,

frigate/embeddings/__init__.py

@@ -4,6 +4,7 @@ import base64
 import json
 import logging
 import os
+import sys
 import threading
 from json.decoder import JSONDecodeError
 from multiprocessing.synchronize import Event as MpEvent
@@ -52,6 +53,14 @@ 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:

frigate/genai/__init__.py

@@ -153,9 +153,6 @@ 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": {

frigate/genai/gemini.py

@@ -136,22 +136,44 @@ class GeminiClient(GenAIClient):
                             )
                         )
                 elif role == "assistant":
-                    gemini_messages.append(
-                        types.Content(
-                            role="model", parts=[types.Part.from_text(text=content)]
-                        )
-                    )
+                    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))
                 elif role == "tool":
                     # Handle tool response
-                    function_response = {
-                        "name": msg.get("name", ""),
-                        "response": content,
-                    }
+                    response_payload = (
+                        content if isinstance(content, dict) else {"result": content}
+                    )
                     gemini_messages.append(
                         types.Content(
                             role="function",
                             parts=[
-                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
+                                types.Part.from_function_response(
+                                    name=msg.get("name")
+                                    or msg.get("tool_call_id")
+                                    or "",
+                                    response=response_payload,
+                                )
                             ],
                         )
                     )
@@ -343,22 +365,44 @@ class GeminiClient(GenAIClient):
                             )
                         )
                 elif role == "assistant":
-                    gemini_messages.append(
-                        types.Content(
-                            role="model", parts=[types.Part.from_text(text=content)]
-                        )
-                    )
+                    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))
                 elif role == "tool":
                     # Handle tool response
-                    function_response = {
-                        "name": msg.get("name", ""),
-                        "response": content,
-                    }
+                    response_payload = (
+                        content if isinstance(content, dict) else {"result": content}
+                    )
                     gemini_messages.append(
                         types.Content(
                             role="function",
                             parts=[
-                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
+                                types.Part.from_function_response(
+                                    name=msg.get("name")
+                                    or msg.get("tool_call_id")
+                                    or "",
+                                    response=response_payload,
+                                )
                             ],
                         )
                     )

frigate/genai/llama_cpp.py

@@ -44,6 +44,7 @@ class LlamaCppClient(GenAIClient):
     _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."""
@@ -56,6 +57,7 @@ class LlamaCppClient(GenAIClient):
         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("/")
@@ -141,6 +143,13 @@ 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,
@@ -465,10 +474,11 @@ 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 <__media__> placeholder for image tokenization
+            # prompt_string must contain the server's media marker placeholder.
+            # The marker is randomized per server startup (read from /props).
             content.append(
                 {
-                    "prompt_string": "<__media__>\n",
+                    "prompt_string": f"{self._media_marker}\n",
                     "multimodal_data": [encoded],  # type: ignore[dict-item]
                 }
             )

frigate/genai/ollama.py

@@ -31,6 +31,12 @@ 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 = {
@@ -39,7 +45,11 @@ class OllamaClient(GenAIClient):
         }
 
         try:
-            client = ApiClient(host=self.genai_config.base_url, timeout=self.timeout)
+            client = ApiClient(
+                host=self.genai_config.base_url,
+                timeout=self.timeout,
+                headers=self._auth_headers(),
+            )
             # ensure the model is available locally
             response = client.show(self.genai_config.model)
             if response.get("error"):
@@ -166,7 +176,9 @@ class OllamaClient(GenAIClient):
                 return []
             try:
                 client = ApiClient(
-                    host=self.genai_config.base_url, timeout=self.timeout
+                    host=self.genai_config.base_url,
+                    timeout=self.timeout,
+                    headers=self._auth_headers(),
                 )
             except Exception:
                 return []
@@ -344,6 +356,7 @@ 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)
@@ -359,6 +372,7 @@ 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

frigate/genai/openai.py

@@ -73,8 +73,17 @@ 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")

frigate/jobs/debug_replay.py

@@ -0,0 +1,386 @@
+"""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()

frigate/output/birdseye.py

@@ -8,7 +8,6 @@ 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
@@ -882,7 +881,7 @@ class Birdseye:
                 coordinates = self.birdseye_manager.get_camera_coordinates()
                 self.requestor.send_data(UPDATE_BIRDSEYE_LAYOUT, coordinates)
         if self._idle_interval:
-            now = time.monotonic()
+            now = datetime.datetime.now().timestamp()
             is_idle = len(self.birdseye_manager.camera_layout) == 0
             if (
                 is_idle

frigate/output/output.py

@@ -349,6 +349,13 @@ 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.")

frigate/output/preview.py

@@ -361,14 +361,17 @@ class PreviewRecorder:
             small_frame,
             cv2.COLOR_YUV2BGR_I420,
         )
-        cv2.imwrite(
-            get_cache_image_name(self.camera_name, frame_time),
+        cache_path = get_cache_image_name(self.camera_name, frame_time)
+
+        if not cv2.imwrite(
+            cache_path,
             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,

frigate/record/export.py

@@ -13,6 +13,7 @@ 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
@@ -22,13 +23,13 @@ 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
+from frigate.models import Export, Previews, Recordings, ReviewSegment
+from frigate.util.ffmpeg import run_ffmpeg_with_progress
 from frigate.util.time import is_current_hour
 
 logger = logging.getLogger(__name__)
@@ -242,111 +243,172 @@ 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]:
-        """Run an FFmpeg export command, parsing progress events from stderr.
+        """Delegate to the shared helper, mapping percent → (step, percent).
 
-        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`.
+        Returns ``(returncode, captured_stderr)``.
         """
-        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
 
-        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",
+        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,
         )
 
-        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:
-                proc.stdin.close()
-            except (BrokenPipeError, OSError):
-                pass
-
-        captured: list[str] = []
-
-        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 <= 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 reading FFmpeg progress for %s", self.export_id)
-
-        proc.wait()
-
-        # Drain any remaining stderr so callers can log it on failure.
-        try:
-            remaining = proc.stderr.read()
-            if remaining:
-                captured.append(remaining)
-        except Exception:
-            pass
-
-        return proc.returncode, "".join(captured)
-
     def get_datetime_from_timestamp(self, timestamp: int) -> str:
-        # return in iso format
+        # 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:
+            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")
 
+    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
+
+        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()
+            )
+        except Exception:
+            logger.exception(
+                "Failed to query review segments for export %s", self.export_id
+            )
+            return None
+
+        if not review_rows:
+            return None
+
+        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()
+        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
+
+        return meta_path
+
     def save_thumbnail(self, id: str) -> str:
         thumb_path = os.path.join(CLIPS_DIR, f"export/{id}.webp")
 
@@ -387,16 +449,14 @@ class RecordingExporter(threading.Thread):
             except DoesNotExist:
                 return ""
 
-            diff = self.start_time - preview.start_time
-            minutes = int(diff / 60)
-            seconds = int(diff % 60)
+            diff = max(0.0, float(self.start_time) - float(preview.start_time))
             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"00:{minutes}:{seconds}",
+                f"{diff:.3f}",
                 "-i",
                 preview.path,
                 "-frames",
@@ -422,12 +482,18 @@ 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:
@@ -436,6 +502,9 @@ 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 ""
 
@@ -451,6 +520,24 @@ 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"
@@ -458,32 +545,13 @@ class RecordingExporter(threading.Thread):
                 f"-y -protocol_whitelist pipe,file,http,tcp -i {playlist_url}"
             )
         else:
-            # 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
+            # Chunk the recording rows into pages so each playlist line
+            # references a bounded sub-range rather than the full export.
             page_size = 1000
-            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)
+            for i in range(0, len(recordings), page_size):
+                chunk = recordings[i : i + page_size]
                 playlist_lines.append(
-                    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'"
+                    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'"
                 )
 
             ffmpeg_input = "-y -protocol_whitelist pipe,file,http,tcp -f concat -safe 0 -i /dev/stdin"
@@ -504,8 +572,12 @@ 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} -c copy -movflags +faststart"
+                f"{self.config.ffmpeg.ffmpeg_path} -hide_banner {ffmpeg_input}{chapter_args} -c copy -movflags +faststart"
             ).split(" ")
 
         # add metadata
@@ -691,6 +763,8 @@ 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)}"

frigate/test/http_api/test_debug_replay_api.py

@@ -0,0 +1,123 @@
+"""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"])

frigate/test/test_debug_replay.py

@@ -0,0 +1,242 @@
+"""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()

frigate/test/test_debug_replay_job.py

@@ -0,0 +1,460 @@
+"""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()

frigate/test/test_export_progress.py

@@ -1,6 +1,9 @@
 """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
 
@@ -11,6 +14,7 @@ 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(
@@ -115,10 +119,9 @@ 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 = exporter._inject_progress_flags(cmd)
+        result = inject_progress_flags(cmd)
 
         assert result == [
             "ffmpeg",
@@ -133,8 +136,7 @@ class TestProgressFlagInjection(unittest.TestCase):
         ]
 
     def test_handles_empty_cmd(self) -> None:
-        exporter = _make_exporter()
-        assert exporter._inject_progress_flags([]) == []
+        assert inject_progress_flags([]) == []
 
 
 class TestFfmpegProgressParsing(unittest.TestCase):
@@ -164,7 +166,7 @@ class TestFfmpegProgressParsing(unittest.TestCase):
         fake_proc.returncode = 0
         fake_proc.wait = MagicMock(return_value=0)
 
-        with patch("frigate.record.export.sp.Popen", return_value=fake_proc):
+        with patch("frigate.util.ffmpeg.sp.Popen", return_value=fake_proc):
             returncode, _stderr = exporter._run_ffmpeg_with_progress(
                 ["ffmpeg", "-i", "x.m3u8", "/tmp/out.mp4"], "playlist", step="encoding"
             )
@@ -363,6 +365,121 @@ 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()
@@ -381,5 +498,56 @@ 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()

frigate/test/test_ffmpeg_progress.py

@@ -0,0 +1,111 @@
+"""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)

frigate/test/test_ws_auth.py

@@ -0,0 +1,166 @@
+"""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()

frigate/util/ffmpeg.py

@@ -2,8 +2,9 @@
 
 import logging
 import subprocess as sp
-from typing import Any
+from typing import Any, Callable, Optional
 
+from frigate.const import PROCESS_PRIORITY_LOW
 from frigate.log import LogPipe
 
 
@@ -46,3 +47,124 @@ 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)

frigate/video/ffmpeg.py

@@ -24,7 +24,7 @@ from frigate.config.camera.updater import (
 )
 from frigate.const import PROCESS_PRIORITY_HIGH
 from frigate.log import LogPipe
-from frigate.util.builtin import EventsPerSecond
+from frigate.util.builtin import EventsPerSecond, get_ffmpeg_arg_list
 from frigate.util.ffmpeg import start_or_restart_ffmpeg, stop_ffmpeg
 from frigate.util.image import (
     FrameManager,
@@ -34,6 +34,23 @@ from frigate.util.process import FrigateProcess
 
 logger = logging.getLogger(__name__)
 
+# all built-in record presets use this segment_time
+DEFAULT_RECORD_SEGMENT_TIME = 10
+
+
+def _get_record_segment_time(config: CameraConfig) -> int:
+    """Extract -segment_time from the camera's record output args."""
+    record_args = get_ffmpeg_arg_list(config.ffmpeg.output_args.record)
+
+    if record_args and record_args[0].startswith("preset"):
+        return DEFAULT_RECORD_SEGMENT_TIME
+
+    try:
+        idx = record_args.index("-segment_time")
+        return int(record_args[idx + 1])
+    except (ValueError, IndexError):
+        return DEFAULT_RECORD_SEGMENT_TIME
+
 
 def capture_frames(
     ffmpeg_process: sp.Popen[Any],
@@ -164,6 +181,12 @@ class CameraWatchdog(threading.Thread):
         self.latest_cache_segment_time: float = 0
         self.record_enable_time: datetime | None = None
 
+        # `valid` segments are published with the segment's start time, so the
+        # gap between consecutive publishes can reach 2 * segment_time. Pad the
+        # staleness threshold so it's never tighter than that worst case.
+        segment_time = _get_record_segment_time(self.config)
+        self.record_stale_threshold = max(120, 2 * segment_time + 30)
+
         # Stall tracking (based on last processed frame)
         self._stall_timestamps: deque[float] = deque()
         self._stall_active: bool = False
@@ -413,16 +436,17 @@ class CameraWatchdog(threading.Thread):
 
                     # ensure segments are still being created and that they have valid video data
                     # Skip checks during grace period to allow segments to start being created
+                    stale_window = timedelta(seconds=self.record_stale_threshold)
                     cache_stale = not in_grace_period and now_utc > (
-                        latest_cache_dt + timedelta(seconds=120)
+                        latest_cache_dt + stale_window
                     )
                     valid_stale = not in_grace_period and now_utc > (
-                        latest_valid_dt + timedelta(seconds=120)
+                        latest_valid_dt + stale_window
                     )
                     invalid_stale_condition = (
                         self.latest_invalid_segment_time > 0
                         and not in_grace_period
-                        and now_utc > (latest_invalid_dt + timedelta(seconds=120))
+                        and now_utc > (latest_invalid_dt + stale_window)
                         and self.latest_valid_segment_time
                         <= self.latest_invalid_segment_time
                     )
@@ -439,7 +463,7 @@ class CameraWatchdog(threading.Thread):
                             )
 
                         self.logger.error(
-                            f"{reason} for {self.config.name} in the last 120s. Restarting the ffmpeg record process..."
+                            f"{reason} for {self.config.name} in the last {self.record_stale_threshold}s. Restarting the ffmpeg record process..."
                         )
                         p["process"] = start_or_restart_ffmpeg(
                             p["cmd"],

frigate/watchdog.py

@@ -28,6 +28,7 @@ class MonitoredProcess:
     restart_timestamps: deque[float] = field(
         default_factory=lambda: deque(maxlen=MAX_RESTARTS)
     )
+    clean_exit_logged: bool = False
 
     def is_restarting_too_fast(self, now: float) -> bool:
         while (
@@ -72,7 +73,9 @@ class FrigateWatchdog(threading.Thread):
 
         exitcode = entry.process.exitcode
         if exitcode == 0:
-            logger.info("Process %s exited cleanly, not restarting", entry.name)
+            if not entry.clean_exit_logged:
+                logger.info("Process %s exited cleanly, not restarting", entry.name)
+                entry.clean_exit_logged = True
             return
 
         logger.warning(

notebooks/YOLO_NAS_Pretrained_Export.ipynb

@@ -1,88 +1,95 @@
 {
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "rmuF9iKWTbdk"
-      },
-      "outputs": [],
-      "source": [
-        "! pip install -q git+https://github.com/Deci-AI/super-gradients.git"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "NiRCt917KKcL"
-      },
-      "outputs": [],
-      "source": [
-        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/pretrained_models.py\n",
-        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.12/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "dTB0jy_NNSFz"
-      },
-      "outputs": [],
-      "source": [
-        "from super_gradients.common.object_names import Models\n",
-        "from super_gradients.conversion import DetectionOutputFormatMode\n",
-        "from super_gradients.training import models\n",
-        "\n",
-        "model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "GymUghyCNXem"
-      },
-      "outputs": [],
-      "source": [
-        "# export the model for compatibility with Frigate\n",
-        "\n",
-        "model.export(\"yolo_nas_s.onnx\",\n",
-        "             output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
-        "             max_predictions_per_image=20,\n",
-        "             num_pre_nms_predictions=300,\n",
-        "             confidence_threshold=0.4,\n",
-        "             input_image_shape=(320,320),\n",
-        "            )"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "uBhXV5g4Nh42"
-      },
-      "outputs": [],
-      "source": [
-        "from google.colab import files\n",
-        "\n",
-        "files.download('yolo_nas_s.onnx')"
-      ]
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "id": "runtime-notice"
+   },
+   "source": [
+    "**Before running:** go to **Runtime → Change runtime type → Fallback runtime version: 2025.07** (Python 3.11). The current Colab default (Python 3.12+) is incompatible with `super-gradients`."
+   ]
   },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "rmuF9iKWTbdk"
+   },
+   "outputs": [],
+   "source": [
+    "! pip install -q \"jedi>=0.16\"\n",
+    "! pip install -q git+https://github.com/Deci-AI/super-gradients.git"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "NiRCt917KKcL"
+   },
+   "outputs": [],
+   "source": "! sed -i 's/sghub\\.deci\\.ai/d2gjn4b69gu75n.cloudfront.net/g; s/sg-hub-nv\\.s3\\.amazonaws\\.com/d2gjn4b69gu75n.cloudfront.net/g' /usr/local/lib/python*/dist-packages/super_gradients/training/pretrained_models.py\n! sed -i 's/sghub\\.deci\\.ai/d2gjn4b69gu75n.cloudfront.net/g; s/sg-hub-nv\\.s3\\.amazonaws\\.com/d2gjn4b69gu75n.cloudfront.net/g' /usr/local/lib/python*/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "dTB0jy_NNSFz"
+   },
+   "outputs": [],
+   "source": [
+    "from super_gradients.common.object_names import Models\n",
+    "from super_gradients.conversion import DetectionOutputFormatMode\n",
+    "from super_gradients.training import models\n",
+    "\n",
+    "model = models.get(Models.YOLO_NAS_S, pretrained_weights=\"coco\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GymUghyCNXem"
+   },
+   "outputs": [],
+   "source": [
+    "# export the model for compatibility with Frigate\n",
+    "\n",
+    "model.export(\"yolo_nas_s.onnx\",\n",
+    "             output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
+    "             max_predictions_per_image=20,\n",
+    "             num_pre_nms_predictions=300,\n",
+    "             confidence_threshold=0.4,\n",
+    "             input_image_shape=(320,320),\n",
+    "            )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "uBhXV5g4Nh42"
+   },
+   "outputs": [],
+   "source": [
+    "from google.colab import files\n",
+    "\n",
+    "files.download('yolo_nas_s.onnx')"
+   ]
+  }
+ ],
+ "metadata": {
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}

web/e2e/specs/navigation.spec.ts

@@ -69,17 +69,18 @@ test.describe("Navigation — conditional items @critical", () => {
     ).toBeVisible();
   });
 
-  test("/chat is hidden when genai.model is none (desktop)", async ({
+  test("/chat is hidden when no agent has the chat role (desktop)", async ({
     frigateApp,
   }) => {
     test.skip(frigateApp.isMobile, "Desktop sidebar");
     await frigateApp.installDefaults({
       config: {
         genai: {
-          enabled: false,
-          provider: "ollama",
-          model: "none",
-          base_url: "",
+          descriptions_only: {
+            provider: "ollama",
+            model: "llava",
+            roles: ["descriptions"],
+          },
         },
       },
     });
@@ -89,12 +90,20 @@ test.describe("Navigation — conditional items @critical", () => {
     ).toHaveCount(0);
   });
 
-  test("/chat is visible when genai.model is set (desktop)", async ({
+  test("/chat is visible when an agent has the chat role (desktop)", async ({
     frigateApp,
   }) => {
     test.skip(frigateApp.isMobile, "Desktop sidebar");
     await frigateApp.installDefaults({
-      config: { genai: { enabled: true, model: "llava" } },
+      config: {
+        genai: {
+          chat_agent: {
+            provider: "ollama",
+            model: "llava",
+            roles: ["chat"],
+          },
+        },
+      },
     });
     await frigateApp.goto("/");
     await expect(

web/e2e/specs/replay.spec.ts

@@ -31,7 +31,7 @@ test.describe("Replay — no active session @medium", () => {
     await expect(
       frigateApp.page.getByRole("heading", {
         level: 2,
-        name: /No Active Replay Session/i,
+        name: /No Active Debug Replay Session/i,
       }),
     ).toBeVisible({ timeout: 10_000 });
     const goButton = frigateApp.page.getByRole("button", {
@@ -48,7 +48,7 @@ test.describe("Replay — no active session @medium", () => {
     await expect(
       frigateApp.page.getByRole("heading", {
         level: 2,
-        name: /No Active Replay Session/i,
+        name: /No Active Debug Replay Session/i,
       }),
     ).toBeVisible({ timeout: 10_000 });
     await frigateApp.page
@@ -297,7 +297,7 @@ test.describe("Replay — mobile @medium @mobile", () => {
     await expect(
       frigateApp.page.getByRole("heading", {
         level: 2,
-        name: /No Active Replay Session/i,
+        name: /No Active Debug Replay Session/i,
       }),
     ).toBeVisible({ timeout: 10_000 });
   });

web/public/locales/bg/config/global.json

@@ -1 +1,8 @@
-{}
+{
+    "auth": {
+        "label": "Автентикация",
+        "session_length": {
+            "label": "Продължителност на сесията"
+        }
+    }
+}

web/public/locales/ca/common.json

@@ -109,7 +109,8 @@
     "classification": "Classificació",
     "chat": "Xat",
     "actions": "Accions",
-    "profiles": "Perfils"
+    "profiles": "Perfils",
+    "features": "Característiques"
   },
   "pagination": {
     "previous": {

web/public/locales/ca/components/dialog.json

@@ -60,15 +60,76 @@
         "noVaildTimeSelected": "No s'ha seleccionat un rang de temps vàlid",
         "failed": "No s'ha pogut inciar l'exportació: {{error}}"
       },
-      "view": "Vista"
+      "view": "Vista",
+      "queued": "Exporta a la cua. Mostra el progrés a la pàgina d'exportacions.",
+      "batchSuccess_one": "S'ha iniciat l'exportació 1. Obrint el cas ara.",
+      "batchSuccess_many": "S'han iniciat {{count}} exportacions. Obrint el cas ara.",
+      "batchSuccess_other": "S'han iniciat {{count}} exportacions. Obrint el cas ara.",
+      "batchPartial": "S'han iniciat {{successful}} de {{total}} exportacions. Càmeres fallides: {{failedCameras}}",
+      "batchFailed": "No s'han pogut iniciar {{total}} exportacions. Càmeres fallides: {{failedCameras}}",
+      "batchQueuedSuccess_one": "Exporta a la cua 1. Obrint el cas ara.",
+      "batchQueuedSuccess_many": "{{count}} exportacions a la cua. Obrint el cas ara.",
+      "batchQueuedSuccess_other": "{{count}} exportacions a la cua. Obrint el cas ara.",
+      "batchQueuedPartial": "{{successful}} de {{total}} exportacions a la cua. Càmeres fallides: {{failedCameras}}",
+      "batchQueueFailed": "No s'han pogut posar a la cua {{total}} exportacions. Càmeres fallides: {{failedCameras}}"
     },
     "fromTimeline": {
       "saveExport": "Guardar exportació",
-      "previewExport": "Previsualitzar exportació"
+      "previewExport": "Previsualitzar exportació",
+      "queueingExport": "S'està fent la cua de l'exportació...",
+      "useThisRange": "Utilitza aquest interval"
     },
     "case": {
       "label": "Cas",
-      "placeholder": "Selecciona un cas"
+      "placeholder": "Selecciona un cas",
+      "newCaseOption": "Crea un cas no",
+      "newCaseNamePlaceholder": "Nom de cas nou",
+      "newCaseDescriptionPlaceholder": "Descripció del cas",
+      "nonAdminHelp": "Es crearà un nou cas per a aquestes exportacions."
+    },
+    "queueing": "S'està fent la cua de l'exportació...",
+    "tabs": {
+      "export": "Càmera única",
+      "multiCamera": "Multicàmera"
+    },
+    "multiCamera": {
+      "timeRange": "Interval de temps",
+      "selectFromTimeline": "Selecciona des de la línia de temps",
+      "cameraSelection": "Càmeres",
+      "cameraSelectionHelp": "Les càmeres amb objectes rastrejats en aquest interval de temps estan preseleccionades",
+      "checkingActivity": "Comprovant l'activitat de la càmera...",
+      "noCameras": "No hi ha càmeres disponibles",
+      "detectionCount_one": "1 objecte rastrejat",
+      "detectionCount_many": "{{count}} objectes rastrejats",
+      "detectionCount_other": "{{count}} objectes rastrejats",
+      "nameLabel": "Nom de l'exportació",
+      "namePlaceholder": "Nom base opcional per a aquestes exportacions",
+      "queueingButton": "S'estan posant a la cua les exportacions...",
+      "exportButton_one": "Exporta 1 càmera",
+      "exportButton_many": "Exporta {{count}} càmeres",
+      "exportButton_other": "Exporta {{count}} càmeres"
+    },
+    "multi": {
+      "title_one": "Exporta {{count}} ressenyes",
+      "title_many": "Exporta {{count}} ressenyes",
+      "title_other": "Exporta {{count}} ressenyes",
+      "description": "Exporta cada revisió seleccionada. Totes les exportacions s'agruparan en un sol cas.",
+      "descriptionNoCase": "Exporta cada revisió seleccionada.",
+      "caseNamePlaceholder": "Exporta la revisió - {{date}}",
+      "exportButton_one": "Exporta {{count}} ressenyes",
+      "exportButton_many": "Exporta {{count}} ressenyes",
+      "exportButton_other": "Exporta {{count}} ressenyes",
+      "exportingButton": "S'està exportant...",
+      "toast": {
+        "started_one": "S'ha iniciat l'exportació 1. Obrint el cas ara.",
+        "started_many": "S'han iniciat {{count}} exportacions. Obrint el cas ara.",
+        "started_other": "S'han iniciat {{count}} exportacions. Obrint el cas ara.",
+        "startedNoCase_one": "S'ha iniciat l'exportació 1.",
+        "startedNoCase_many": "S'han iniciat {{count}} exportacions.",
+        "startedNoCase_other": "S'han iniciat {{count}} exportacions.",
+        "partial": "S'han iniciat {{successful}} de {{total}} exportacions. Ha fallat: {{failedItems}}",
+        "failed": "No s'han pogut iniciar {{total}} exportacions. Ha fallat: {{failedItems}}"
+      }
     }
   },
   "streaming": {
@@ -116,6 +177,14 @@
         "success": "Els enregistraments de vídeo associats als elements de revisió seleccionats s’han suprimit correctament.",
         "error": "No s'ha pogut suprimir: {{error}}"
       }
+    },
+    "shareTimestamp": {
+      "label": "Comparteix la marca horària",
+      "title": "Comparteix la marca horària",
+      "description": "Comparteix un URL amb marca horària de la posició actual del jugador o tria una marca horària personalitzada. Tingueu en compte que aquest no és un URL de compartició pública i només és accessible per als usuaris amb accés a Frigate i aquesta càmera.",
+      "custom": "Marca horària personalitzada",
+      "button": "Comparteix l'URL de la marca horària",
+      "shareTitle": "Marca de temps de revisió de Frigate: {{camera}}"
     }
   },
   "imagePicker": {

web/public/locales/ca/components/player.json

@@ -32,7 +32,8 @@
   "noPreviewFoundFor": "No s'ha trobat cap previsualització per a {{cameraName}}",
   "submitFrigatePlus": {
     "title": "Enviar aquesta imatge a Frigate+?",
-    "submit": "Enviar"
+    "submit": "Enviar",
+    "previewError": "No s'ha pogut carregar la vista prèvia de la instantània. És possible que l'enregistrament no estigui disponible en aquest moment."
   },
   "livePlayerRequiredIOSVersion": "Es requereix iOS 17.1 o superior per a aquest tipus de reproducció en directe.",
   "streamOffline": {

web/public/locales/ca/config/global.json

@@ -1951,7 +1951,7 @@
         },
         "roles": {
             "label": "Rols",
-            "description": "Funcions genAI (eines, visió, incrustacions); un proveïdor per rol."
+            "description": "Rols de GenAI (xat, descripcions, incrustacions); un proveïdor per rol."
         },
         "provider_options": {
             "label": "Opcions del proveïdor",

web/public/locales/ca/views/events.json

@@ -27,7 +27,9 @@
   },
   "documentTitle": "Revisió - Frigate",
   "recordings": {
-    "documentTitle": "Enregistraments - Frigate"
+    "documentTitle": "Enregistraments - Frigate",
+    "invalidSharedLink": "No s'ha pogut obrir l'enllaç d'enregistrament amb marques de temps a causa d'un error d'anàlisi.",
+    "invalidSharedCamera": "No s'ha pogut obrir l'enllaç d'enregistrament amb marques de temps a causa d'una càmera desconeguda o no autoritzada."
   },
   "calendarFilter": {
     "last24Hours": "Últimes 24 hores"

web/public/locales/ca/views/explore.json

@@ -248,7 +248,7 @@
   "dialog": {
     "confirmDelete": {
       "title": "Confirmar la supressió",
-      "desc": "Eliminant aquest objecte seguit borrarà l'snapshot, qualsevol embedding gravat, i qualsevol detall de seguiment. Les imatges gravades d'aquest objecte seguit en l'historial <em>NO</em> seràn eliminades.<br /><br />Estas segur que vols continuar?"
+      "desc": "Suprimir aquest objecte rastrejat elimina la instantània, qualsevol incrustació desada, i qualsevol entrada de detalls de seguiment associada. Les imatges gravades d'aquest objecte seguit en l'historial <em>NO</em> seràn eliminades.<br /><br />Estas segur que vols continuar?"
     },
     "toast": {
       "error": "S'ha produït un error en suprimir aquest objecte rastrejat: {{errorMessage}}"
@@ -289,7 +289,10 @@
         "zones": "Zones",
         "ratio": "Ràtio",
         "area": "Àrea",
-        "score": "Puntuació"
+        "score": "Puntuació",
+        "computedScore": "Puntuació calculada",
+        "topScore": "Puntuació superior",
+        "toggleAdvancedScores": "Commuta les puntuacions avançades"
       }
     },
     "annotationSettings": {

web/public/locales/ca/views/exports.json

@@ -14,7 +14,9 @@
   "toast": {
     "error": {
       "renameExportFailed": "Error al canviar el nom de l’exportació: {{errorMessage}}",
-      "assignCaseFailed": "No s'ha pogut actualitzar l'assignació de cas:{{errorMessage}}"
+      "assignCaseFailed": "No s'ha pogut actualitzar l'assignació de cas:{{errorMessage}}",
+      "caseSaveFailed": "No s'ha pogut desar el cas: {{errorMessage}}",
+      "caseDeleteFailed": "No s'ha pogut suprimir el cas: {{errorMessage}}"
     }
   },
   "tooltip": {
@@ -22,7 +24,8 @@
     "downloadVideo": "Baixa el vídeo",
     "editName": "Edita el nom",
     "deleteExport": "Suprimeix l'exportació",
-    "assignToCase": "Afegeix al cas"
+    "assignToCase": "Afegeix al cas",
+    "removeFromCase": "Elimina del cas"
   },
   "headings": {
     "cases": "Casos",
@@ -35,5 +38,91 @@
     "newCaseOption": "Crea un cas nou",
     "nameLabel": "Nom del cas",
     "descriptionLabel": "Descripció"
+  },
+  "toolbar": {
+    "newCase": "Cas nou",
+    "addExport": "Afegeix una exportació",
+    "editCase": "Edita el cas",
+    "deleteCase": "Suprimeix el cas"
+  },
+  "deleteCase": {
+    "label": "Suprimeix el cas",
+    "desc": "Esteu segur que voleu suprimir {{caseName}}?",
+    "descKeepExports": "Les exportacions continuaran estant disponibles com a exportacions sense categoria.",
+    "descDeleteExports": "Totes les exportacions en aquest cas s'eliminaran permanentment.",
+    "deleteExports": "Elimina també les exportacions"
+  },
+  "caseCard": {
+    "emptyCase": "Encara no hi ha exportacions"
+  },
+  "jobCard": {
+    "defaultName": "Exportació de {{camera}}",
+    "queued": "En cua",
+    "running": "En execució",
+    "preparing": "Preparant",
+    "copying": "Copiant",
+    "encoding": "Codificant",
+    "encodingRetry": "Codificant (reintent)",
+    "finalizing": "Finalitzant"
+  },
+  "caseView": {
+    "noDescription": "Sense descripció",
+    "createdAt": "{{value}} creat",
+    "exportCount_one": "1 exportació",
+    "exportCount_other": "{{count}} exportacions",
+    "cameraCount_one": "1 càmera",
+    "cameraCount_other": "{{count}} càmeres",
+    "showMore": "Mostra'n més",
+    "showLess": "Mostra menys",
+    "emptyTitle": "Aquest cas és buit",
+    "emptyDescription": "Afegeix les exportacions no categoritzades existents per mantenir el cas organitzat.",
+    "emptyDescriptionNoExports": "Encara no hi ha exportacions sense categoria per afegir."
+  },
+  "caseEditor": {
+    "createTitle": "Crea un cas",
+    "editTitle": "Edita el cas",
+    "namePlaceholder": "Nom del cas",
+    "descriptionPlaceholder": "Afegeix notes o context per a aquest cas"
+  },
+  "addExportDialog": {
+    "title": "Afegeix l'exportació a {{caseName}}",
+    "searchPlaceholder": "Cerca exportacions sense categoria",
+    "empty": "No hi ha exportacions sense categoria que coincideixin amb aquesta cerca.",
+    "addButton_one": "Afegeix 1 exportació",
+    "addButton_other": "Afegeix {{count}} exportacions",
+    "adding": "S'està afegint..."
+  },
+  "selected_one": "{{count}} seleccionats",
+  "selected_other": "{{count}} seleccionats",
+  "bulkActions": {
+    "addToCase": "Afegeix al cas",
+    "moveToCase": "Mou al cas",
+    "removeFromCase": "Elimina del cas",
+    "delete": "Suprimeix",
+    "deleteNow": "Suprimeix ara"
+  },
+  "bulkDelete": {
+    "title": "Suprimeix les exportacions",
+    "desc_one": "Esteu segur que voleu suprimir {{count}} l'exportació?",
+    "desc_other": "steu segur que voleu suprimir {{count}} exportacions?"
+  },
+  "bulkRemoveFromCase": {
+    "title": "Elimina del cas",
+    "desc_one": "Voleu suprimir {{count}} d'aquest cas?",
+    "desc_other": "Voleu eliminar {{count}} exportacions d'aquest cas?",
+    "descKeepExports": "Les exportacions es mouran a sense categoria.",
+    "descDeleteExports": "Les exportacions s'eliminaran permanentment.",
+    "deleteExports": "Suprimeix les exportacions"
+  },
+  "bulkToast": {
+    "success": {
+      "delete": "Exportacions suprimides amb èxit",
+      "reassign": "Assignació de cas actualitzada amb èxit",
+      "remove": "S'han eliminat les exportacions del cas"
+    },
+    "error": {
+      "deleteFailed": "No s'han pogut suprimir les exportacions: {{errorMessage}}",
+      "reassignFailed": "No s'ha pogut actualitzar l'assignació de cas: {{errorMessage}}"
+    }
   }
 }

web/public/locales/ca/views/faceLibrary.json

@@ -38,7 +38,7 @@
     "uploadFace": "Puja una imatge del rostre",
     "nextSteps": "Següents passos",
     "description": {
-      "uploadFace": "Puja una imatge de {{name}} que mostri el seu rostre de cares. No cal que la imatge estigui retallada només al rostre."
+      "uploadFace": "Pugeu una imatge de {{name}} que mostra la seva cara des d'un angle frontal. La imatge no necessita ser retallada a la seva cara."
     }
   },
   "selectFace": "Seleccionar rostre",

web/public/locales/ca/views/settings.json

@@ -1280,7 +1280,8 @@
         },
         "hikvision": {
           "substreamWarning": "El substream 1 està bloquejat a una resolució baixa. Moltes càmeres Hikvision suporten subfluxos addicionals que han d'estar habilitats a la configuració de la càmera. Es recomana comprovar i utilitzar aquests corrents si estan disponibles."
-        }
+        },
+        "resolutionUnknown": "La resolució d'aquest flux no s'ha pogut investigar. Heu d'establir manualment la resolució de detecció a Configuració o a la configuració."
       }
     }
   },
@@ -1297,7 +1298,13 @@
       "enableDesc": "Inhabilita temporalment una càmera habilitada fins que es reiniciï Frigate. La inhabilitació d'una càmera atura completament el processament de Frigate dels fluxos d'aquesta càmera. La detecció, l'enregistrament i la depuració no estaran disponibles.<br /> <em>Nota: això no desactiva les retransmissions de go2rtc.</em>",
       "disableLabel": "Càmeres inhabilitades",
       "disableDesc": "Habilita una càmera que actualment no és visible a la interfície d'usuari i està desactivada a la configuració. Es requereix un reinici de Frigate després d'activar-la.",
-      "enableSuccess": "{{cameraName}} activat a la configuració. Reinicia Frigate per aplicar els canvis."
+      "enableSuccess": "{{cameraName}} activat a la configuració. Reinicia Frigate per aplicar els canvis.",
+      "friendlyName": {
+        "edit": "Edita el nom de la pantalla de la càmera",
+        "title": "Edita el nom de la pantalla",
+        "description": "Estableix el nom amigable que es mostra per a aquesta càmera a tota la interfície d'usuari de la Fragata. Deixeu-ho en blanc per utilitzar l'ID de la càmera.",
+        "rename": "Canvia el nom"
+      }
     },
     "cameraConfig": {
       "add": "Afegeix una càmera",
@@ -1659,7 +1666,16 @@
       "empty": "No hi ha etiquetes disponibles",
       "allNonAlertDetections": "Totes les activitats no alertes s'inclouran com a deteccions."
     },
-    "addCustomLabel": "Afegeix una etiqueta personalitzada..."
+    "addCustomLabel": "Afegeix una etiqueta personalitzada...",
+    "genaiModel": {
+      "placeholder": "Selecciona el model…",
+      "search": "Cerca models…",
+      "noModels": "No hi ha models disponibles"
+    },
+    "knownPlates": {
+      "namePlaceholder": "per exemple. Cotxe de la parella",
+      "platePlaceholder": "Matricula o regex"
+    }
   },
   "globalConfig": {
     "title": "Configuració global",

web/public/locales/de/components/dialog.json

@@ -64,20 +64,73 @@
     "toast": {
       "error": {
         "endTimeMustAfterStartTime": "Die Endzeit darf nicht vor der Startzeit liegen",
-        "failed": "Fehler beim Starten des Exports: {{error}}",
+        "failed": "Fehler beim Export in die Warteschlange: {{error}}",
         "noVaildTimeSelected": "Kein gültiger Zeitraum ausgewählt"
       },
       "success": "Export erfolgreich gestartet. Die Datei befindet sich auf der Exportseite.",
-      "view": "Ansicht"
+      "view": "Ansicht",
+      "queued": "Export in Warteschlange gestellt. Fortschritt auf der Exportseite verfolgen.",
+      "batchSuccess_one": "1 Export gestartet. Öffne den Fall jetzt.",
+      "batchSuccess_other": "{{count}} Exports gestartet. Öffne den Fall jetzt.",
+      "batchPartial": "{{successful}} von {{total}} Exporten gestartet. Fehlgeschlagene Kameras: {{failedCameras}}",
+      "batchFailed": "Fehler beim Starten der {{total}} Exporte. Fehlgeschlagene Kameras: {{failedCameras}}",
+      "batchQueuedSuccess_one": "1 Export in die Warteschlange gestellt. Fall wird jetzt geöffnet.",
+      "batchQueuedSuccess_other": "{{count}} Exporte in der Warteschlange. Fall wird jetzt geöffnet.",
+      "batchQueuedPartial": "{{successful}} von {{total}} Exporten in die Warteschlange gestellt. Fehlerhafte Kameras: {{failedCameras}}",
+      "batchQueueFailed": "Fehler beim Einreihen von {{total}} Exporten in die Warteschlange. Fehlerhafte Kameras: {{failedCameras}}"
     },
     "fromTimeline": {
       "saveExport": "Export speichern",
-      "previewExport": "Exportvorschau"
+      "previewExport": "Exportvorschau",
+      "queueingExport": "Export wird in die Warteschlange gestellt...",
+      "useThisRange": "Nutzen Sie diesen Bereich"
     },
     "export": "Exportieren",
     "case": {
       "label": "Fall",
-      "placeholder": "Einen Fall auswählen"
+      "placeholder": "Einen Fall auswählen",
+      "newCaseOption": "Einen neuen Fall erstellen",
+      "newCaseNamePlaceholder": "Neuer Fallname",
+      "newCaseDescriptionPlaceholder": "Fall Beschreibung",
+      "nonAdminHelp": "Für diese Exporte wird ein neuer Fall angelegt."
+    },
+    "queueing": "Export wird in die Warteschlange gestellt...",
+    "tabs": {
+      "export": "Einzelne Kamera",
+      "multiCamera": "Mehrere-Kameras"
+    },
+    "multiCamera": {
+      "timeRange": "Zeitbereich",
+      "selectFromTimeline": "Wählen Sie aus der Zeitleiste aus",
+      "cameraSelection": "Kameras",
+      "cameraSelectionHelp": "Kameras, die in diesem Zeitbereich Objekte verfolgen, sind vorausgewählt",
+      "checkingActivity": "Kameraaktivität wird überprüft...",
+      "noCameras": "keine kamaeras verfügbar",
+      "detectionCount_one": "1 verfolgtes Objekt",
+      "detectionCount_other": "{{count}} verfolgtesObjekte",
+      "nameLabel": "Export Name",
+      "namePlaceholder": "Optionaler Basisname für diese Exporte",
+      "queueingButton": "Exporte werden in die Warteschlange gestellt...",
+      "exportButton_one": "Export 1 Kamera",
+      "exportButton_other": "xport {{count}} Kameras"
+    },
+    "multi": {
+      "title_one": "1 Bewertung exportieren",
+      "title_other": "{{count}} Bewertung exportieren",
+      "description": "Exportieren Sie jede ausgewählte Rezension. Alle Exporte werden in einem einzigen Fall zusammengefasst.",
+      "descriptionNoCase": "Jede ausgewählte Bewertung exportieren.",
+      "caseNamePlaceholder": "Export prüfen - {{date}}",
+      "exportButton_one": "1 Bewertung exportieren",
+      "exportButton_other": "{{count}} Bewertung exportieren",
+      "exportingButton": "Exportieren...",
+      "toast": {
+        "started_one": "1 Export gestartet. Fall wird jetzt geöffnet.",
+        "started_other": "{{count}} Exporte gestartet. Fall wird jetzt geöffnet.",
+        "startedNoCase_one": "1 Export gestartet.",
+        "startedNoCase_other": "{{count}} Exports gestartet.",
+        "partial": "{{successful}} von {{total}} Exporten gestartet. Fehlgeschlagen: {{failedItems}}",
+        "failed": "Fehler beim Starten der {{total}} Exporte. Fehler: {{failedItems}}"
+      }
     }
   },
   "streaming": {

web/public/locales/de/config/global.json

@@ -1710,7 +1710,7 @@
         },
         "roles": {
             "label": "Rollen",
-            "description": "GenAI-Rollen (Tools, Vision, Einbettungen); ein Anbieter pro Rolle."
+            "description": "GenAI-Rollen (Nachrichten, Beschreibung, Einbettungen); ein Anbieter pro Rolle."
         },
         "provider_options": {
             "label": "Anbieter Optionen",

web/public/locales/de/views/explore.json

@@ -282,7 +282,10 @@
         "zones": "Zonen",
         "ratio": "Verhältnis",
         "area": "Bereich",
-        "score": "Bewertung"
+        "score": "Bewertung",
+        "computedScore": "Berechnetes Ergebnis",
+        "topScore": "Bester Treffer",
+        "toggleAdvancedScores": "Erweiterte Ergebnisse umschalten"
       }
     },
     "annotationSettings": {

web/public/locales/de/views/exports.json

@@ -14,7 +14,9 @@
   "toast": {
     "error": {
       "renameExportFailed": "Umbenennen des Exports fehlgeschlagen: {{errorMessage}}",
-      "assignCaseFailed": "Aktualisierung der Fallzuweisung fehlgeschlagen: {{errorMessage}}"
+      "assignCaseFailed": "Aktualisierung der Fallzuweisung fehlgeschlagen: {{errorMessage}}",
+      "caseSaveFailed": "Fehler beim speichern vom Fall: {{errorMessage}}",
+      "caseDeleteFailed": "Fehler beim löschem vom Fall: {{errorMessage}}"
     }
   },
   "tooltip": {
@@ -22,7 +24,8 @@
     "downloadVideo": "Video herunterladen",
     "editName": "Name ändern",
     "deleteExport": "Export löschen",
-    "assignToCase": "Hinzufügen zum Fall"
+    "assignToCase": "Hinzufügen zum Fall",
+    "removeFromCase": "Vom Gehäuse entfernen"
   },
   "headings": {
     "cases": "Fälle",
@@ -35,5 +38,91 @@
     "newCaseOption": "Neuen Fall erstellen",
     "nameLabel": "Fallname",
     "descriptionLabel": "Beschreibung"
+  },
+  "toolbar": {
+    "newCase": "Neuer Fall",
+    "addExport": "Zum expotieren hinzufügen",
+    "editCase": "Fall bearbeiten",
+    "deleteCase": "Fall löschen"
+  },
+  "deleteCase": {
+    "label": "Fall löschen",
+    "desc": "Sind sie sich sicher löschen von{{caseName}}?",
+    "descKeepExports": "Exporte bleiben als nicht kategorisierte Exporte verfügbar.",
+    "descDeleteExports": "Alle Exporte werden in diesem Fall endgültig gelöscht.",
+    "deleteExports": "Exporte auch löschen"
+  },
+  "caseCard": {
+    "emptyCase": "Noch keine Exporte"
+  },
+  "jobCard": {
+    "defaultName": "{{camera}} export",
+    "queued": "In der Warteschlange",
+    "running": "läuft",
+    "preparing": "Vorbereitung",
+    "copying": "kopieren",
+    "encoding": "Codierung",
+    "encodingRetry": "Kodierung (Wiederholung)",
+    "finalizing": "Abschließen"
+  },
+  "caseView": {
+    "noDescription": "keine Beschreibung",
+    "createdAt": "Erstellt {{value}}",
+    "exportCount_one": "1 Export",
+    "exportCount_other": "{{count}} Exports",
+    "cameraCount_one": "1 Kamera",
+    "cameraCount_other": "{{count}} Kameras",
+    "showMore": "Mehr anzeigen",
+    "showLess": "Weniger Anzeigen",
+    "emptyTitle": "Der Fall ist leer",
+    "emptyDescription": "Fügen Sie vorhandene, nicht kategorisierte Exporte hinzu, um den Fall übersichtlich zu halten.",
+    "emptyDescriptionNoExports": "Es sind noch keine nicht kategorisierten Exporte zum Hinzufügen verfügbar."
+  },
+  "caseEditor": {
+    "createTitle": "Fall erstellen",
+    "editTitle": "Fall bearbeiten",
+    "namePlaceholder": "Fall Name",
+    "descriptionPlaceholder": "Fügen Sie Anmerkungen oder Kontext zu diesem Fall hinzu"
+  },
+  "addExportDialog": {
+    "title": "Export zum {{caseName}} hinzufügen",
+    "searchPlaceholder": "Suche nach nicht kategorisierten Exporten",
+    "empty": "Es wurden keine nicht kategorisierten Exporte gefunden, die dieser Suche entsprechen.",
+    "addButton_one": "1 Export hinzufügen",
+    "addButton_other": "Fügen Sie {{count}} Exporte hinzu",
+    "adding": "Hinzufügen..."
+  },
+  "selected_one": "{{count}} ausgewählt",
+  "selected_other": "{{count}} ausgewählt",
+  "bulkActions": {
+    "addToCase": "Zum Fall hinzufügen",
+    "moveToCase": "Zum Fall wechseln",
+    "removeFromCase": "Aus dem Fall nehmen",
+    "delete": "löschen",
+    "deleteNow": "jetzt löschen"
+  },
+  "bulkDelete": {
+    "title": "Exporte löschen",
+    "desc_one": "Möchten Sie den Export {{count}} wirklich löschen?",
+    "desc_other": "Möchten Sie wirklich {{count}} Exporte löschen?"
+  },
+  "bulkRemoveFromCase": {
+    "title": "Aus dem Fall nehmen",
+    "desc_one": "{{count}}-Export aus diesem Fall entfernen?",
+    "desc_other": "{{count}} Exporte aus diesem Fall entfernen?",
+    "descKeepExports": "Die Exporte werden in die Kategorie „Nicht kategorisiert“ verschoben.",
+    "descDeleteExports": "Exporte werden endgültig gelöscht.",
+    "deleteExports": "Löschen Sie stattdessen Exporte"
+  },
+  "bulkToast": {
+    "success": {
+      "delete": "Exporte erfolgreich gelöscht",
+      "reassign": "Fallzuweisung erfolgreich aktualisiert",
+      "remove": "Exporte erfolgreich aus dem Fall entfernt"
+    },
+    "error": {
+      "deleteFailed": "Fehler beim Löschen der Exporte: {{errorMessage}}",
+      "reassignFailed": "Fehler beim Aktualisieren der Fallzuordnung: {{errorMessage}}"
+    }
   }
 }

web/public/locales/de/views/settings.json

@@ -345,6 +345,10 @@
           "zone": "Zone",
           "motion_mask": "Bewegungsmaske",
           "object_mask": "Objektmaske"
+        },
+        "revertOverride": {
+          "title": "Basis Konfiguration wiederherstellen",
+          "desc": "Dadurch wird die Profilüberschreibung für {{type}}<em>{{name}}</em> aufgehoben und die Grundkonfiguration wiederhergestellt."
         }
       },
       "speed": {
@@ -507,7 +511,8 @@
         "title": "Aktiviert",
         "description": "Ob diese Maske in der Konfigurationsdatei aktiviert ist. Ist sie deaktiviert, kann sie nicht über MQTT aktiviert werden. Deaktivierte Masken werden zur Laufzeit ignoriert."
       }
-    }
+    },
+    "addDisabledProfile": "Fügen Sie es zuerst der Basiskonfiguration hinzu und überschreiben Sie es dann im Profil"
   },
   "debug": {
     "objectShapeFilterDrawing": {
@@ -1647,7 +1652,8 @@
       "keyDuplicate": "Der Name des Detektors ist bereits vorhanden.",
       "noSchema": "Es sind keine Detektorschemata verfügbar.",
       "none": "Es sind keine Detektorinstanzen konfiguriert.",
-      "add": "Detektor hinzufügen"
+      "add": "Detektor hinzufügen",
+      "addCustomKey": "Benutzerdefinierten Schlüssel hinzufügen"
     },
     "record": {
       "title": "Aufnahmeeinstellungen"
@@ -1718,7 +1724,16 @@
       "title": "Einstellungen für Zeitstempel"
     },
     "searchPlaceholder": "Suche...",
-    "addCustomLabel": "Benutzerdefiniertes Etikett hinzufügen..."
+    "addCustomLabel": "Benutzerdefiniertes Etikett hinzufügen...",
+    "knownPlates": {
+      "namePlaceholder": "z.B. das Auto der Frau",
+      "platePlaceholder": "Kennzeichen oder regulärer Ausdruck"
+    },
+    "genaiModel": {
+      "placeholder": "Modell auswählen…",
+      "search": "Modell suchen…",
+      "noModels": "Keine Modelle verfügbar"
+    }
   },
   "globalConfig": {
     "title": "Globale Konfiguration",
@@ -1876,6 +1891,10 @@
     },
     "snapshots": {
       "detectDisabled": "Die Objekterkennung ist deaktiviert. Es werden keine Momentaufnahmen von verfolgten Objekten erstellt."
+    },
+    "detectors": {
+      "mixedTypes": "Alle Detektoren müssen von gleichem Typ sein, Entferne bestehende Detektoren um einen anderen Typ zu benutzen.",
+      "mixedTypesSuggestion": "Alle Detektoren müssen vom gleichem Typ sein. Entferne bestehende oder wähle {{type}}."
     }
   }
 }

web/public/locales/el/config/global.json

@@ -1 +1,14 @@
-{}
+{
+    "version": {
+        "label": "Τρέχουσα έκδοση διαμόρφωσης"
+    },
+    "safe_mode": {
+        "label": "Ασφαλής λειτουργία"
+    },
+    "auth": {
+        "reset_admin_password": {
+            "label": "Επανέφερε κωδικού πρόσβασης για τον διαχειριστή admin",
+            "description": "Άμα είναι αλήθεια, επαναφέρει τον κωδικό πρόσβασης του χρήστη διαχειριστή(admin) κατά την εκκίνηση και εκτύπωση του νέου κωδικού πρόσβασης στα αρχείο καταγραφής(logs)"
+        }
+    }
+}

web/public/locales/en/views/replay.json

@@ -19,26 +19,31 @@
     "startLabel": "Start",
     "endLabel": "End",
     "toast": {
-      "success": "Debug replay started successfully",
       "error": "Failed to start debug replay: {{error}}",
       "alreadyActive": "A replay session is already active",
-      "stopped": "Debug replay stopped",
       "stopError": "Failed to stop debug replay: {{error}}",
       "goToReplay": "Go to Replay"
     }
   },
   "page": {
-    "noSession": "No Active Replay Session",
-    "noSessionDesc": "Start a debug replay from the History view by clicking the Debug Replay button in the toolbar.",
+    "noSession": "No Active Debug Replay Session",
+    "noSessionDesc": "Start a Debug Replay from History view by clicking the Actions button in the toolbar and choosing Debug Replay.",
     "goToRecordings": "Go to History",
+    "preparingClip": "Preparing clip…",
+    "preparingClipDesc": "Frigate is stitching together recordings for the selected time range. This can take a minute for longer ranges.",
+    "startingCamera": "Starting Debug Replay…",
+    "startError": {
+      "title": "Failed to start Debug Replay",
+      "back": "Back to History"
+    },
     "sourceCamera": "Source Camera",
     "replayCamera": "Replay Camera",
-    "initializingReplay": "Initializing replay...",
-    "stoppingReplay": "Stopping replay...",
+    "initializingReplay": "Initializing Debug Replay...",
+    "stoppingReplay": "Stopping Debug Replay...",
     "stopReplay": "Stop Replay",
     "confirmStop": {
       "title": "Stop Debug Replay?",
-      "description": "This will stop the replay session and clean up all temporary data. Are you sure?",
+      "description": "This will stop the session and clean up all temporary data. Are you sure?",
       "confirm": "Stop Replay",
       "cancel": "Cancel"
     },
@@ -49,6 +54,6 @@
     "activeTracking": "Active tracking",
     "noActiveTracking": "No active tracking",
     "configuration": "Configuration",
-    "configurationDesc": "Fine tune motion detection and object tracking settings for the debug replay camera. No changes are saved to your Frigate configuration file."
+    "configurationDesc": "Fine tune motion detection and object tracking settings for the Debug Replay camera. No changes are saved to your Frigate configuration file."
   }
 }

web/public/locales/es/common.json

@@ -195,7 +195,8 @@
     "explore": "Explorar",
     "uiPlayground": "Zona de pruebas de la interfaz de usuario",
     "faceLibrary": "Biblioteca de rostros",
-    "classification": "Clasificación"
+    "classification": "Clasificación",
+    "profiles": "Perfiles"
   },
   "unit": {
     "speed": {

web/public/locales/es/components/dialog.json

@@ -77,7 +77,11 @@
       "saveExport": "Guardar exportación",
       "previewExport": "Vista previa de la exportación"
     },
-    "selectOrExport": "Seleccionar o exportar"
+    "selectOrExport": "Seleccionar o exportar",
+    "case": {
+      "label": "Caso",
+      "newCaseDescriptionPlaceholder": "Descripción de caso"
+    }
   },
   "streaming": {
     "restreaming": {
@@ -124,6 +128,9 @@
       "markAsReviewed": "Marcar como revisado",
       "deleteNow": "Eliminar ahora",
       "markAsUnreviewed": "Marcar como no revisado"
+    },
+    "shareTimestamp": {
+      "description": "Comparta una URL con marca de tiempo de la posición actual del reproductor o elija una marca de tiempo personalizada. Tenga en cuenta que esta no es una URL pública para compartir y solo es accesible para los usuarios que tienen acceso a Frigate y a esta cámara."
     }
   },
   "imagePicker": {

web/public/locales/es/components/player.json

@@ -3,7 +3,8 @@
   "noPreviewFoundFor": "No se encontró vista previa para {{cameraName}}",
   "submitFrigatePlus": {
     "submit": "Enviar",
-    "title": "¿Enviar este fotograma a Frigate+?"
+    "title": "¿Enviar este fotograma a Frigate+?",
+    "previewError": "No se pudo cargar la vista previa de la instantánea. Es posible que la grabación no esté disponible en este momento."
   },
   "streamOffline": {
     "desc": "No se han recibido fotogramas en la transmisión <code>detect</code> de {{cameraName}}, revisa los registros de errores",

web/public/locales/es/config/cameras.json

@@ -42,10 +42,32 @@
         "label": "Nombre descriptivo",
         "description": "Nombre descriptivo de la cámara utilizado en la interfaz de usuario de Frigate"
     },
-    "label": "Configuración de Cámara",
+    "label": "Configuración de cámara",
     "onvif": {
         "profile": {
-            "label": "Perfil ONVIF"
+            "label": "Perfil ONVIF",
+            "description": "Perfil multimedia ONVIF específico que se utilizará para el control PTZ, identificado por token o nombre. Si no se especifica, se selecciona automáticamente el primer perfil con una configuración PTZ válida."
+        },
+        "autotracking": {
+            "zoom_factor": {
+                "description": "Controla el nivel de zoom en los objetos rastreados. Los valores más bajos mantienen una mayor parte de la escena a la vista; los valores más altos acercan la imagen, pero pueden provocar la pérdida del rastreo. Valores entre 0.1 y 0.75."
+            },
+            "calibrate_on_startup": {
+                "description": "Mida la velocidad de los motores PTZ al encenderlos para mejorar la precisión del seguimiento. Frigate actualizará la configuración con los `movement_weights` tras la calibración."
+            },
+            "description": "Realice un seguimiento automático de objetos en movimiento y manténgalos centrados en el encuadre mediante movimientos de cámara PTZ.",
+            "zooming": {
+                "description": "Control del comportamiento del zoom: deshabilitado (solo panorámica/inclinación), absoluto (mayor compatibilidad) o relativo (panorámica/inclinación/zoom simultáneos)."
+            },
+            "return_preset": {
+                "description": "Nombre del preajuste ONVIF configurado en el firmware de la cámara al que regresar una vez finalizado el seguimiento."
+            },
+            "timeout": {
+                "description": "Espere esta cantidad de segundos después de perder el seguimiento antes de devolver la cámara a la posición preestablecida."
+            }
+        },
+        "tls_insecure": {
+            "description": "Omitir la verificación TLS y deshabilitar la autenticación digest para ONVIF (no seguro; usar solo en redes seguras)."
         }
     },
     "zones": {
@@ -83,7 +105,24 @@
             "max_area": {
                 "description": "Área máxima del cuadro delimitador (píxeles o porcentaje) permitida para este tipo de objeto. Puede expresarse en píxeles (entero) o como porcentaje (decimal entre 0,000001 y 0,99).",
                 "label": "Área máxima del objeto"
-            }
+            },
+            "description": "Filtros para aplicar a los objetos dentro de esta zona. Se utilizan para reducir los falsos positivos o restringir qué objetos se consideran presentes en la zona."
+        },
+        "objects": {
+            "description": "Lista de tipos de objetos (del mapa de etiquetas) que pueden activar esta zona. Puede ser una cadena de texto o una lista de cadenas. Si está vacío, se consideran todos los objetos."
+        },
+        "description": "Las zonas le permiten definir un área específica del fotograma, de modo que pueda determinar si un objeto se encuentra o no dentro de un área determinada.",
+        "speed_threshold": {
+            "description": "Velocidad mínima (en unidades del mundo real, si se han configurado distancias) requerida para que un objeto se considere presente en la zona. Se utiliza para los disparadores de zona basados en la velocidad."
+        },
+        "friendly_name": {
+            "description": "Un nombre fácil de usar para la zona, que se muestra en la interfaz de usuario de Frigate. Si no se especifica, se utilizará una versión formateada del nombre de la zona."
+        },
+        "inertia": {
+            "description": "Número de fotogramas consecutivos en los que se debe detectar un objeto dentro de la zona antes de considerarlo presente. Ayuda a filtrar las detecciones transitorias."
+        },
+        "loitering_time": {
+            "description": "Número de segundos que un objeto debe permanecer en la zona para ser considerado como merodeo. Establezca en 0 para desactivar la detección de merodeo."
         }
     },
     "objects": {
@@ -100,7 +139,151 @@
             "use_snapshot": {
                 "label": "Usar instantáneas",
                 "description": "Usar instantáneas de objetos en lugar de miniaturas para la generación de descripciones de GenAI."
+            },
+            "send_triggers": {
+                "after_significant_updates": {
+                    "description": "Envía una solicitud a GenAI tras un número especificado de actualizaciones significativas del objeto rastreado."
+                },
+                "description": "Define cuándo se deben enviar los fotogramas a GenAI (al finalizar, después de las actualizaciones, etc.)."
+            },
+            "required_zones": {
+                "description": "Zonas en las que deben ubicarse los objetos para ser elegibles para la generación de descripciones con GenAI."
             }
         }
+    },
+    "mqtt": {
+        "label": "MQTT",
+        "required_zones": {
+            "description": "Zonas en las que debe entrar un objeto para que se publique una imagen MQTT."
+        }
+    },
+    "notifications": {
+        "email": {
+            "label": "Email de notificacion"
+        }
+    },
+    "audio_transcription": {
+        "description": "Configuración para la transcripción de audio en vivo y de voz, utilizada para eventos y subtítulos en tiempo real.",
+        "enabled": {
+            "label": "Habilitar transcripción"
+        }
+    },
+    "motion": {
+        "skip_motion_threshold": {
+            "description": "Si se establece en un valor entre 0,0 y 1,0, y más de esta fracción de la imagen cambia en un solo fotograma, el detector no devolverá cuadros de movimiento y se recalibrará inmediatamente. Esto puede ahorrar recursos de CPU y reducir los falsos positivos durante tormentas eléctricas, tempestades, etc., aunque podría pasar por alto eventos reales, como el seguimiento automático de un objeto por parte de una cámara PTZ. La disyuntiva está entre descartar unos cuantos megabytes de grabaciones o revisar un par de clips cortos. Deje este parámetro sin establecer (None) para desactivar esta función."
+        },
+        "lightning_threshold": {
+            "description": "Umbral para detectar e ignorar breves picos de luz (un valor menor indica mayor sensibilidad; valores entre 0,3 y 1,0). Esto no impide por completo la detección de movimiento; Simplemente provoca que el detector deje de analizar fotogramas adicionales una vez que se supera el umbral. Durante estos eventos aún se realizan grabaciones basadas en el movimiento."
+        },
+        "threshold": {
+            "description": "Umbral de diferencia de píxeles utilizado por el detector de movimiento; los valores más altos reducen la sensibilidad (rango 1-255)."
+        }
+    },
+    "lpr": {
+        "enhancement": {
+            "description": "Nivel de mejora (0-10) que se aplicará a los recortes de matrículas antes del OCR; los valores más altos no siempre mejoran los resultados, y los niveles superiores a 5 podrían funcionar únicamente con matrículas capturadas de noche, por lo que deben utilizarse con precaución."
+        },
+        "expire_time": {
+            "description": "Tiempo en segundos tras el cual una matrícula no detectada caduca en el sistema de seguimiento (solo para cámaras LPR dedicadas)."
+        }
+    },
+    "detect": {
+        "fps": {
+            "description": "Fotogramas por segundo deseados para ejecutar la detección; los valores más bajos reducen el uso de la CPU (el valor recomendado es 5; establezca un valor superior —como máximo de 10— únicamente si realiza el seguimiento de objetos que se mueven con extrema rapidez)."
+        },
+        "min_initialized": {
+            "description": "Número de detecciones consecutivas requeridas antes de crear un objeto rastreado. Auméntelo para reducir las inicializaciones falsas. El valor predeterminado es los FPS divididos por 2."
+        },
+        "height": {
+            "description": "Altura (en píxeles) de los fotogramas utilizados para la transmisión de detección; déjelo vacío para utilizar la resolución nativa de la transmisión."
+        },
+        "width": {
+            "description": "Ancho (en píxeles) de los fotogramas utilizados para la transmisión de detección; déjelo vacío para utilizar la resolución nativa de la transmisión."
+        },
+        "stationary": {
+            "description": "Configuración para detectar y gestionar objetos que permanecen inmóviles durante un periodo de tiempo."
+        }
+    },
+    "record": {
+        "motion": {
+            "description": "Número de días para conservar las grabaciones activadas por movimiento, independientemente de los objetos rastreados. Establézcalo en 0 si solo desea conservar las grabaciones de alertas y detecciones."
+        },
+        "continuous": {
+            "description": "Número de días para conservar las grabaciones, independientemente de los objetos rastreados o del movimiento. Establézcalo en 0 si solo desea conservar las grabaciones de alertas y detecciones."
+        },
+        "detections": {
+            "pre_capture": {
+                "description": "Número de segundos antes del evento de detección que se incluirán en la grabación."
+            },
+            "post_capture": {
+                "description": "Número de segundos después del evento de detección que se incluirán en la grabación."
+            }
+        },
+        "alerts": {
+            "pre_capture": {
+                "description": "Número de segundos antes del evento de detección que se incluirán en la grabación."
+            },
+            "post_capture": {
+                "description": "Número de segundos después del evento de detección que se incluirán en la grabación."
+            }
+        }
+    },
+    "ui": {
+        "dashboard": {
+            "description": "Alterna si esta cámara es visible en toda la interfaz de usuario de Frigate. Desactivar esta opción requerirá editar manualmente la configuración para volver a visualizar esta cámara en la interfaz."
+        }
+    },
+    "live": {
+        "height": {
+            "description": "Altura (en píxeles) para renderizar la transmisión en vivo de jsmpeg en la interfaz web; debe ser <= a la altura de la transmisión de detección."
+        },
+        "description": "Configuraciones utilizadas por la interfaz web para controlar la selección, la resolución y la calidad de transmisiónes en vivo."
+    },
+    "review": {
+        "description": "Configuraciones que controlan las alertas, las detecciones y los resúmenes de revisión de GenAI utilizados por la interfaz de usuario y el almacenamiento de esta cámara.",
+        "alerts": {
+            "required_zones": {
+                "description": "Zonas en las que debe entrar un objeto para ser considerado una alerta; dejar vacío para permitir cualquier zona."
+            },
+            "labels": {
+                "description": "Lista de etiquetas de objetos que califican como alertas (por ejemplo: car, person)."
+            }
+        },
+        "detections": {
+            "required_zones": {
+                "description": "Zonas en las que debe entrar un objeto para ser considerado detectado; dejar vacío para permitir cualquier zona."
+            },
+            "description": "Configuración para determinar qué objetos rastreados generan detecciones (no alertas) y cómo se retienen dichas detecciones."
+        },
+        "genai": {
+            "image_source": {
+                "description": "Fuente de las imágenes enviadas a GenAI ('preview' o 'recordings'); La opción 'recordings' utiliza fotogramas de mayor calidad, pero requiere más tokens."
+            },
+            "additional_concerns": {
+                "description": "Una lista de preocupaciones o notas adicionales que GenAI debería tener en cuenta al evaluar la actividad en esta cámara."
+            },
+            "activity_context_prompt": {
+                "description": "Instrucción personalizada que describe qué constituye y qué no una actividad sospechosa, con el fin de proporcionar contexto para los resúmenes generados por GenAI."
+            },
+            "description": "Controla el uso de IA generativa (GenAI) para la elaboración de descripciones y resúmenes de elementos de revisión.",
+            "debug_save_thumbnails": {
+                "description": "Guarde las miniaturas que se envían al proveedor de GenAI para su depuración y revisión."
+            }
+        }
+    },
+    "birdseye": {
+        "description": "Configuración para la vista compuesta Birdseye, que combina las transmisiones de múltiples cámaras en una sola vista."
+    },
+    "ffmpeg": {
+        "retry_interval": {
+            "description": "Segundos de espera antes de intentar reconectar la transmisión de una cámara tras un fallo. El valor predeterminado es 10."
+        },
+        "path": {
+            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"5.0\" o \"7.0\")."
+        },
+        "output_args": {
+            "description": "Argumentos de salida predeterminados utilizados para diferentes roles de FFmpeg, tales como detección y grabación."
+        },
+        "description": "Configuración de FFmpeg, incluyendo la ruta del binario, argumentos, opciones de aceleración por hardware y argumentos de salida por rol."
     }
 }

web/public/locales/es/config/global.json

@@ -70,11 +70,45 @@
         "cookie_secure": {
             "label": "Flag de cookie segura",
             "description": "Establece el flag de seguridad en la cookie de autenticación; debe ser 'true' cuando se utilice TLS."
+        },
+        "failed_login_rate_limit": {
+            "label": "Limite de intento de acceso fallidos"
+        },
+        "session_length": {
+            "description": "Duración de la sesión en segundos para sesiones de JWT."
+        },
+        "admin_first_time_login": {
+            "description": "Cuando se establece en true, la interfaz de usuario puede mostrar un enlace de ayuda en la página de inicio de sesión, informando a los usuarios sobre cómo iniciar sesión tras el restablecimiento de la contraseña de administrador. "
+        },
+        "refresh_time": {
+            "description": "Cuando a una sesión le queden menos de esta cantidad de segundos para expirar, actualícela para restablecer su duración completa."
         }
     },
     "onvif": {
         "profile": {
-            "label": "Perfil ONVIF"
+            "label": "Perfil ONVIF",
+            "description": "Perfil multimedia ONVIF específico que se utilizará para el control PTZ, identificado por token o nombre. Si no se especifica, se selecciona automáticamente el primer perfil con una configuración PTZ válida."
+        },
+        "autotracking": {
+            "zoom_factor": {
+                "description": "Controla el nivel de zoom en los objetos rastreados. Los valores más bajos mantienen una mayor parte de la escena a la vista; los valores más altos acercan la imagen, pero pueden provocar la pérdida del rastreo. Valores entre 0.1 y 0.75."
+            },
+            "calibrate_on_startup": {
+                "description": "Mida la velocidad de los motores PTZ al encenderlos para mejorar la precisión del seguimiento. Frigate actualizará la configuración con los `movement_weights` tras la calibración."
+            },
+            "description": "Realice un seguimiento automático de objetos en movimiento y manténgalos centrados en el encuadre mediante movimientos de cámara PTZ.",
+            "zooming": {
+                "description": "Control del comportamiento del zoom: deshabilitado (solo panorámica/inclinación), absoluto (mayor compatibilidad) o relativo (panorámica/inclinación/zoom simultáneos)."
+            },
+            "return_preset": {
+                "description": "Nombre del preajuste ONVIF configurado en el firmware de la cámara al que regresar una vez finalizado el seguimiento."
+            },
+            "timeout": {
+                "description": "Espere esta cantidad de segundos después de perder el seguimiento antes de devolver la cámara a la posición preestablecida."
+            }
+        },
+        "tls_insecure": {
+            "description": "Omitir la verificación TLS y deshabilitar la autenticación digest para ONVIF (no seguro; usar solo en redes seguras)."
         }
     },
     "objects": {
@@ -91,7 +125,19 @@
             "use_snapshot": {
                 "label": "Usar instantáneas",
                 "description": "Usar instantáneas de objetos en lugar de miniaturas para la generación de descripciones de GenAI."
+            },
+            "send_triggers": {
+                "after_significant_updates": {
+                    "description": "Envía una solicitud a GenAI tras un número especificado de actualizaciones significativas del objeto rastreado."
+                },
+                "description": "Define cuándo se deben enviar los fotogramas a GenAI (al finalizar, después de las actualizaciones, etc.)."
+            },
+            "required_zones": {
+                "description": "Zonas en las que deben ubicarse los objetos para ser elegibles para la generación de descripciones con GenAI."
             }
+        },
+        "track": {
+            "description": "Lista de etiquetas de objetos a rastrear para todas las cámaras; puede anularse por cámara."
         }
     },
     "detectors": {
@@ -107,6 +153,310 @@
             "api_key": {
                 "label": "Clave de API de DeepStack (si es necesaria)"
             }
+        },
+        "type": {
+            "label": "Tipo"
+        },
+        "label": "Detector de hardware",
+        "cpu": {
+            "label": "CPU",
+            "num_threads": {
+                "label": "Número de hilos para detección"
+            },
+            "description": "Detector TFLite de CPU que ejecuta modelos de TensorFlow Lite en la CPU del host sin aceleración por hardware. No recomendado."
+        },
+        "axengine": {
+            "label": "Motor AX NPU"
+        },
+        "teflon_tfl": {
+            "description": "Detector de delegados Teflon para TFLite, que utiliza la biblioteca de delegados Mesa Teflon para acelerar la inferencia en las GPU compatibles."
+        },
+        "synaptics": {
+            "description": "Detector NPU de Synaptics para modelos en formato .synap, utilizando el Synap SDK en hardware de Synaptics."
+        },
+        "zmq": {
+            "description": "Detector ZMQ IPC que descarga la inferencia a un proceso externo a través de un punto de conexión IPC de ZeroMQ."
+        },
+        "hailo8l": {
+            "description": "Detector Hailo-8/Hailo-8L que utiliza modelos HEF y el SDK HailoRT para la inferencia en hardware Hailo."
+        },
+        "onnx": {
+            "description": "Detector ONNX para ejecutar modelos ONNX; utilizará los backends de aceleración disponibles (CUDA/ROCm/OpenVINO) cuando estén disponibles."
+        },
+        "description": "Configuración para detectores de objetos (backends de CPU, GPU y ONNX) y cualquier ajuste del modelo específico del detector.",
+        "openvino": {
+            "description": "Detector OpenVINO para CPU AMD e Intel, GPU Intel y hardware VPU Intel."
+        },
+        "tensorrt": {
+            "description": "Detector TensorRT para dispositivos Nvidia Jetson que utiliza motores TensorRT serializados para una inferencia acelerada."
+        },
+        "degirum": {
+            "description": "Detector DeGirum para ejecutar modelos a través de la nube de DeGirum o servicios de inferencia local."
+        },
+        "rknn": {
+            "description": "Detector RKNN para NPUs de Rockchip; ejecuta modelos compilados para RKNN en hardware de Rockchip."
+        }
+    },
+    "database": {
+        "label": "Base de datos",
+        "description": "Configuración de la base de datos SQLite utilizada por Frigate para almacenar los metadatos de los objetos rastreados y las grabaciones."
+    },
+    "mqtt": {
+        "label": "MQTT",
+        "port": {
+            "label": "Puerto MQTT"
+        },
+        "tls_client_cert": {
+            "label": "Certificado cliente"
+        },
+        "description": "Configuración para conectar y publicar telemetría, instantáneas y detalles de eventos en un broker MQTT.",
+        "topic_prefix": {
+            "description": "Prefijo del tema MQTT para todos los temas de Frigate; debe ser único si se ejecutan múltiples instancias."
+        },
+        "client_id": {
+            "description": "Identificador de cliente utilizado al conectarse al broker MQTT; debe ser único para cada instancia."
+        }
+    },
+    "notifications": {
+        "email": {
+            "label": "Email de notificacion"
+        }
+    },
+    "networking": {
+        "ipv6": {
+            "label": "Configuración IPV6"
+        },
+        "listen": {
+            "internal": {
+                "label": "Puerto interno"
+            },
+            "external": {
+                "label": "Puerto externo",
+                "description": "Puerto externo de escucha para Frigate (por defecto 8791)."
+            },
+            "description": "Configuración de los puertos de escucha internos y externos. Esto es para usuarios avanzados. Para la mayoría de los casos de uso, se recomienda modificar la sección de puertos de su configuración de Docker Compose."
+        }
+    },
+    "proxy": {
+        "label": "Proxy",
+        "separator": {
+            "label": "Carácter de separación"
+        },
+        "default_role": {
+            "description": "Rol predeterminado asignado a los usuarios autenticados por proxy cuando no se aplica ningún mapeo de roles (administrador o espectador)."
+        },
+        "description": "Configuración para integrar Frigate detrás de un proxy inverso que transmite encabezados de usuario autenticados.",
+        "header_map": {
+            "description": "Mapear los encabezados de proxy entrantes a los campos de usuario y rol de Frigate para la autenticación basada en proxy.",
+            "role": {
+                "description": "Encabezado que contiene el rol o los grupos del usuario autenticado provenientes del proxy ascendente."
+            }
+        }
+    },
+    "telemetry": {
+        "label": "Telemetria",
+        "stats": {
+            "intel_gpu_stats": {
+                "label": "Estadísticas GPU Intel",
+                "description": "Habilitar la recopilación de estadísticas de la GPU Intel si hay una GPU Intel presente."
+            },
+            "network_bandwidth": {
+                "label": "Ancho de banda"
+            },
+            "amd_gpu_stats": {
+                "label": "Estadísticas GPU Amd",
+                "description": "Habilitar la recopilación de estadísticas de la GPU AMD si hay una GPU AMD presente."
+            },
+            "intel_gpu_device": {
+                "description": "Identificador de dispositivo utilizado al tratar las GPU Intel como SR-IOV para corregir las estadísticas de la GPU."
+            }
+        },
+        "version_check": {
+            "description": "Habilite una verificación saliente para detectar si hay disponible una versión más reciente de Frigate."
+        }
+    },
+    "ui": {
+        "timezone": {
+            "label": "Uso horario",
+            "description": "Zona horaria opcional que se mostrará en la interfaz de usuario (si no se especifica, se utilizará la hora local del navegador)."
+        },
+        "unit_system": {
+            "label": "Unidad de sistema",
+            "description": "Sistema de unidades para la visualización (métrico o imperial) utilizado en la interfaz de usuario y en MQTT."
+        }
+    },
+    "audio_transcription": {
+        "description": "Configuración para la transcripción de audio en vivo y de voz, utilizada para eventos y subtítulos en tiempo real.",
+        "language": {
+            "description": "Código de idioma utilizado para la transcripción/traducción (por ejemplo, 'es' para Español). Consulte https://whisper-api.com/docs/languages/ para ver los códigos de idioma compatibles."
+        },
+        "enabled": {
+            "description": "Habilitar o deshabilitar la transcripción automática de audio para todas las cámaras; puede anularse por cámara."
+        }
+    },
+    "motion": {
+        "skip_motion_threshold": {
+            "description": "Si se establece en un valor entre 0,0 y 1,0, y más de esta fracción de la imagen cambia en un solo fotograma, el detector no devolverá cuadros de movimiento y se recalibrará inmediatamente. Esto puede ahorrar recursos de CPU y reducir los falsos positivos durante tormentas eléctricas, tempestades, etc., aunque podría pasar por alto eventos reales, como el seguimiento automático de un objeto por parte de una cámara PTZ. La disyuntiva está entre descartar unos cuantos megabytes de grabaciones o revisar un par de clips cortos. Deje este parámetro sin establecer (None) para desactivar esta función."
+        },
+        "lightning_threshold": {
+            "description": "Umbral para detectar e ignorar breves picos de luz (un valor menor indica mayor sensibilidad; valores entre 0,3 y 1,0). Esto no impide por completo la detección de movimiento; Simplemente provoca que el detector deje de analizar fotogramas adicionales una vez que se supera el umbral. Durante estos eventos aún se realizan grabaciones basadas en el movimiento."
+        },
+        "threshold": {
+            "description": "Umbral de diferencia de píxeles utilizado por el detector de movimiento; los valores más altos reducen la sensibilidad (rango 1-255)."
+        },
+        "enabled": {
+            "description": "Habilitar o deshabilitar la detección de movimiento para todas las cámaras; puede anularse para cada cámara individualmente."
+        }
+    },
+    "lpr": {
+        "enhancement": {
+            "description": "Nivel de mejora (0-10) que se aplicará a los recortes de matrículas antes del OCR; los valores más altos no siempre mejoran los resultados, y los niveles superiores a 5 podrían funcionar únicamente con matrículas capturadas de noche, por lo que deben utilizarse con precaución."
+        },
+        "expire_time": {
+            "description": "Tiempo en segundos tras el cual una matrícula no detectada caduca en el sistema de seguimiento (solo para cámaras LPR dedicadas)."
+        },
+        "enabled": {
+            "description": "Habilitar o deshabilitar el reconocimiento de matrículas para todas las cámaras; puede anularse por cámara."
+        },
+        "min_plate_length": {
+            "description": "Número mínimo de caracteres que debe contener una matrícula reconocida para ser considerada válida."
+        }
+    },
+    "detect": {
+        "fps": {
+            "description": "Fotogramas por segundo deseados para ejecutar la detección; los valores más bajos reducen el uso de la CPU (el valor recomendado es 5; establezca un valor superior —como máximo de 10— únicamente si realiza el seguimiento de objetos que se mueven con extrema rapidez)."
+        },
+        "min_initialized": {
+            "description": "Número de detecciones consecutivas requeridas antes de crear un objeto rastreado. Auméntelo para reducir las inicializaciones falsas. El valor predeterminado es los FPS divididos por 2."
+        },
+        "height": {
+            "description": "Altura (en píxeles) de los fotogramas utilizados para la transmisión de detección; déjelo vacío para utilizar la resolución nativa de la transmisión."
+        },
+        "width": {
+            "description": "Ancho (en píxeles) de los fotogramas utilizados para la transmisión de detección; déjelo vacío para utilizar la resolución nativa de la transmisión."
+        },
+        "stationary": {
+            "description": "Configuración para detectar y gestionar objetos que permanecen inmóviles durante un periodo de tiempo."
+        },
+        "enabled": {
+            "description": "Habilitar o deshabilitar la detección de objetos para todas las cámaras; puede anularse para cada cámara individualmente."
+        }
+    },
+    "record": {
+        "motion": {
+            "description": "Número de días para conservar las grabaciones activadas por movimiento, independientemente de los objetos rastreados. Establézcalo en 0 si solo desea conservar las grabaciones de alertas y detecciones."
+        },
+        "continuous": {
+            "description": "Número de días para conservar las grabaciones, independientemente de los objetos rastreados o del movimiento. Establézcalo en 0 si solo desea conservar las grabaciones de alertas y detecciones."
+        },
+        "detections": {
+            "pre_capture": {
+                "description": "Número de segundos antes del evento de detección que se incluirán en la grabación."
+            },
+            "post_capture": {
+                "description": "Número de segundos después del evento de detección que se incluirán en la grabación."
+            }
+        },
+        "alerts": {
+            "pre_capture": {
+                "description": "Número de segundos antes del evento de detección que se incluirán en la grabación."
+            },
+            "post_capture": {
+                "description": "Número de segundos después del evento de detección que se incluirán en la grabación."
+            }
+        }
+    },
+    "camera_ui": {
+        "dashboard": {
+            "description": "Alterna si esta cámara es visible en toda la interfaz de usuario de Frigate. Desactivar esta opción requerirá editar manualmente la configuración para volver a visualizar esta cámara en la interfaz."
+        }
+    },
+    "live": {
+        "description": "Configuración para controlar la resolución y la calidad de la transmisión en vivo de jsmpeg. Esto no afecta a las cámaras retransmitidas que utilizan go2rtc para la visualización en vivo.",
+        "height": {
+            "description": "Altura (en píxeles) para renderizar la transmisión en vivo de jsmpeg en la interfaz web; debe ser <= a la altura de la transmisión de detección."
+        }
+    },
+    "semantic_search": {
+        "model": {
+            "description": "El modelo de embeddings a utilizar para la búsqueda semántica (por ejemplo, 'jinav1'), o el nombre de un proveedor de GenAI con el rol de embeddings."
+        }
+    },
+    "review": {
+        "alerts": {
+            "required_zones": {
+                "description": "Zonas en las que debe entrar un objeto para ser considerado una alerta; dejar vacío para permitir cualquier zona."
+            },
+            "labels": {
+                "description": "Lista de etiquetas de objetos que califican como alertas (por ejemplo: car, person)."
+            }
+        },
+        "detections": {
+            "required_zones": {
+                "description": "Zonas en las que debe entrar un objeto para ser considerado detectado; dejar vacío para permitir cualquier zona."
+            },
+            "description": "Configuración para determinar qué objetos rastreados generan detecciones (no alertas) y cómo se retienen dichas detecciones."
+        },
+        "genai": {
+            "image_source": {
+                "description": "Fuente de las imágenes enviadas a GenAI ('preview' o 'recordings'); La opción 'recordings' utiliza fotogramas de mayor calidad, pero requiere más tokens."
+            },
+            "additional_concerns": {
+                "description": "Una lista de preocupaciones o notas adicionales que GenAI debería tener en cuenta al evaluar la actividad en esta cámara."
+            },
+            "activity_context_prompt": {
+                "description": "Instrucción personalizada que describe qué constituye y qué no una actividad sospechosa, con el fin de proporcionar contexto para los resúmenes generados por GenAI."
+            },
+            "description": "Controla el uso de IA generativa (GenAI) para la elaboración de descripciones y resúmenes de elementos de revisión.",
+            "debug_save_thumbnails": {
+                "description": "Guarde las miniaturas que se envían al proveedor de GenAI para su depuración y revisión."
+            }
+        }
+    },
+    "birdseye": {
+        "description": "Configuración para la vista compuesta Birdseye, que combina las transmisiones de múltiples cámaras en una sola vista.",
+        "restream": {
+            "description": "Retransmita la salida de video de Birdseye como una transmisión en vivo RTSP; al habilitar esta opción, Birdseye se mantendrá en ejecución de forma continua."
+        },
+        "layout": {
+            "max_cameras": {
+                "description": "Número máximo de cámaras a mostrar simultáneamente en Birdseye; muestra las cámaras más recientes."
+            }
+        }
+    },
+    "ffmpeg": {
+        "retry_interval": {
+            "description": "Segundos de espera antes de intentar reconectar la transmisión de una cámara tras un fallo. El valor predeterminado es 10."
+        },
+        "path": {
+            "description": "Ruta al binario de FFmpeg que se va a utilizar o un alias de versión (\"5.0\" o \"7.0\")."
+        },
+        "output_args": {
+            "description": "Argumentos de salida predeterminados utilizados para diferentes roles de FFmpeg, tales como detección y grabación."
+        },
+        "description": "Configuración de FFmpeg, incluyendo la ruta del binario, argumentos, opciones de aceleración por hardware y argumentos de salida por rol."
+    },
+    "go2rtc": {
+        "description": "Configuración del servicio integrado de retransmisión go2rtc, utilizado para el relevo y la traducción de transmisiones en vivo."
+    },
+    "genai": {
+        "description": "Configuración para los proveedores integrados de IA generativa (GenAI) utilizados para generar descripciones de objetos y resúmenes de reseñas.",
+        "api_key": {
+            "description": "Clave de API requerida por algunos proveedores (también puede configurarse mediante variables de entorno)."
+        },
+        "base_url": {
+            "description": "URL base para proveedores autoalojados o compatibles (por ejemplo, una instancia de Ollama)."
+        },
+        "model": {
+            "description": "El modelo del proveedor que se utilizará para generar descripciones o resúmenes."
+        }
+    },
+    "face_recognition": {
+        "description": "Configuración para la detección y el reconocimiento facial en todas las cámaras; puede anularse por cámara."
+    },
+    "camera_mqtt": {
+        "required_zones": {
+            "description": "Zonas en las que debe entrar un objeto para que se publique una imagen MQTT."
         }
     }
 }

web/public/locales/es/config/groups.json

@@ -59,6 +59,15 @@
         "global": {
             "retention": "Retención global",
             "events": "Eventos globales"
+        },
+        "cameras": {
+            "events": "Evento",
+            "retention": "Retención"
+        }
+    },
+    "ffmpeg": {
+        "cameras": {
+            "cameraFfmpeg": "Argumentos de FFmpeg específicos de la cámara"
         }
     }
 }

web/public/locales/es/config/validation.json

@@ -19,7 +19,8 @@
     "ffmpeg": {
         "inputs": {
             "rolesUnique": "Cada rol solo puede asignarse a un flujo de entrada.",
-            "detectRequired": "Al menos un flujo de entrada debe tener asignado el rol 'detect'."
+            "detectRequired": "Al menos un flujo de entrada debe tener asignado el rol 'detect'.",
+            "hwaccelDetectOnly": "Solo el flujo de entrada con la función \"detect\" puede definir argumentos de aceleración por hardware."
         }
     },
     "anyOf": "Debe coincidir con al menos uno de los esquemas permitidos",

web/public/locales/es/objects.json

@@ -47,7 +47,7 @@
   "carrot": "Zanahoria",
   "hot_dog": "Perrito caliente",
   "pizza": "Pizza",
-  "donut": "Donut",
+  "donut": "Rosquilla",
   "chair": "Silla",
   "couch": "Sofá",
   "potted_plant": "Planta en maceta",

web/public/locales/es/views/classificationModel.json

@@ -12,12 +12,12 @@
   },
   "toast": {
     "success": {
-      "deletedCategory_one": "Clase Borrada",
-      "deletedCategory_many": "",
-      "deletedCategory_other": "",
-      "deletedImage_one": "Imágenes Borradas",
-      "deletedImage_many": "",
-      "deletedImage_other": "",
+      "deletedCategory_one": "Se eliminó {{count}} clase",
+      "deletedCategory_many": "Se eliminaron {{count}} clases",
+      "deletedCategory_other": "Se eliminaron {{count}} clases",
+      "deletedImage_one": "Se eliminó {{count}} imagen",
+      "deletedImage_many": "Se eliminaron {{count}} imágenes",
+      "deletedImage_other": "Se eliminaron {{count}} imágenes",
       "deletedModel_one": "Borrado con éxito {{count}} modelo",
       "deletedModel_many": "Borrados con éxito {{count}} modelos",
       "deletedModel_other": "Borrados con éxito {{count}} modelos",
@@ -68,7 +68,7 @@
   "details": {
     "scoreInfo": "La puntuación representa la confianza media de clasificación en todas las detecciones de este objeto.",
     "unknown": "Desconocido",
-    "none": "Ninguna"
+    "none": "Ninguno"
   },
   "categorizeImage": "Clasificar Imagen",
   "menu": {

web/public/locales/es/views/exports.json

@@ -22,17 +22,26 @@
     "downloadVideo": "Descargar video",
     "editName": "Editar nombre",
     "deleteExport": "Eliminar exportación",
-    "assignToCase": "Añadir al caso"
+    "assignToCase": "Añadir al caso",
+    "removeFromCase": "Remover del contenedor"
   },
   "headings": {
     "cases": "Casos",
-    "uncategorizedExports": "Exportaciones sin categorizar"
+    "uncategorizedExports": "Exportaciones sin Categorizar"
   },
   "caseDialog": {
     "title": "Añadir al caso",
     "newCaseOption": "Crear nuevo caso",
     "nameLabel": "Nombre del caso",
     "description": "Elige un caso existente o crea uno nuevo.",
-    "selectLabel": "Caso"
+    "selectLabel": "Caso",
+    "descriptionLabel": "Descripción"
+  },
+  "toolbar": {
+    "addExport": "Añadir Exportación"
+  },
+  "deleteCase": {
+    "label": "Eliminar caso",
+    "desc": "¿Estás seguro de que quieres eliminar {{caseName}}?"
   }
 }

web/public/locales/es/views/live.json

@@ -17,7 +17,7 @@
         "label": "Haz clic en el marco para centrar la cámara",
         "enable": "Habilitar clic para mover",
         "disable": "Deshabilitar clic para mover",
-        "enableWithZoom": "Activar clic para mover / arrastrar para hacer zoom"
+        "enableWithZoom": "Habilitar clic para mover / arrastrar para aumentar"
       },
       "up": {
         "label": "Mover la cámara PTZ hacia arriba"

web/public/locales/es/views/settings.json

@@ -21,7 +21,7 @@
   "menu": {
     "cameras": "Configuración de Cámara",
     "debug": "Depuración",
-    "ui": "Interfaz de usuario",
+    "ui": "Interfaz de Usuario",
     "classification": "Clasificación",
     "motionTuner": "Ajuste de movimiento",
     "masksAndZones": "Máscaras / Zonas",
@@ -35,7 +35,22 @@
     "cameraReview": "Revisar",
     "general": "General",
     "globalConfig": "Configuración Global",
-    "system": "Sistema"
+    "system": "Sistema",
+    "integrations": "Integraciones",
+    "uiSettings": "Configuración de Interfaz de Usuario",
+    "profiles": "Perfiles",
+    "globalDetect": "Detección de Objetos",
+    "globalRecording": "Grabación",
+    "globalSnapshots": "Instantáneas",
+    "globalFfmpeg": "FFmpeg",
+    "globalMotion": "Detección de Movimiento",
+    "globalObjects": "Objetos",
+    "globalReview": "Revisión",
+    "globalAudioEvents": "Eventos de Audio",
+    "globalLivePlayback": "Reproducción en Vivo",
+    "globalTimestampStyle": "Estilo de Marca de Tiempo",
+    "systemDatabase": "Base de Datos",
+    "systemAuthentication": "Autenticación"
   },
   "dialog": {
     "unsavedChanges": {
@@ -353,6 +368,9 @@
       "allObjects": "Todos los objetos",
       "toast": {
         "success": "La zona ({{zoneName}}) ha sido guardada."
+      },
+      "enabled": {
+        "description": "Indica si esta zona está activa y habilitada en la configuración. Si está deshabilitado, no puede ser habilitado por MQTT. Las zonas deshabilitadas se ignoran durante la ejecución."
       }
     },
     "toast": {
@@ -697,7 +715,7 @@
         "cleanCopySnapshots": "<code>clean_copy</code> Instantáneas"
       },
       "desc": "Enviar a Frigate+ requiere que tanto las capturas instantáneas como las capturas <code>clean_copy</code> estén habilitadas en tu configuración.",
-      "cleanCopyWarning": "Algunas cámaras tienen las instantáneas habilitadas pero tienen la copia limpia desactivada. Necesitas habilitar <code>clean_copy</code> en tu configuración de instantáneas para poder enviar imágenes de estas cámaras a Frigate+."
+      "cleanCopyWarning": "Algunas cámaras tienen las instantáneas deshabilitadas"
     },
     "modelInfo": {
       "title": "Información del modelo",
@@ -722,7 +740,8 @@
       "error": "No se pudieron guardar los cambios en la configuración: {{errorMessage}}"
     },
     "restart_required": "Es necesario reiniciar (se ha cambiado el modelo Frigate+)",
-    "unsavedChanges": "Cambios en la configuración de Frigate+ no guardados"
+    "unsavedChanges": "Cambios en la configuración de Frigate+ no guardados",
+    "description": "Frigate+ es un servicio de suscripción que proporciona acceso a funciones y capacidades adicionales para su instancia de Frigate, incluida la posibilidad de utilizar modelos de detección de objetos personalizados entrenados con sus propios datos. Puede gestionar la configuración de sus modelos de Frigate+ aquí."
   },
   "enrichments": {
     "title": "Configuración de Enriquecimientos",
@@ -1172,7 +1191,8 @@
     "backToSettings": "Volver a configuración de la cámara",
     "streams": {
       "title": "Habilitar/deshabilitar cámaras",
-      "desc": "Desactiva temporalmente una cámara hasta que Frigate se reinicie. Desactivar una cámara detiene por completo el procesamiento de las transmisiones de Frigate. La detección, la grabación y la depuración no estarán disponibles.<br /> <em>Nota: Esto no desactiva las retransmisiones de go2rtc.</em>"
+      "desc": "Desactiva temporalmente una cámara hasta que Frigate se reinicie. Desactivar una cámara detiene por completo el procesamiento de las transmisiones de Frigate. La detección, la grabación y la depuración no estarán disponibles.<br /> <em>Nota: Esto no desactiva las retransmisiones de go2rtc.</em>",
+      "enableDesc": "Deshabilita temporalmente una cámara habilitada hasta que Frigate se reinicie. Deshabilitar una cámara detiene por completo el procesamiento de las transmisiones de esa cámara por parte de Frigate. La detección, la grabación y la depuración no estarán disponibles.<br /> <em>Nota: Esto no deshabilita las retransmisiones de go2rtc.</em>"
     },
     "cameraConfig": {
       "add": "Añadir cámara",
@@ -1202,6 +1222,9 @@
       "toast": {
         "success": "Cámara {{cameraName}} guardada correctamente"
       }
+    },
+    "deleteCameraDialog": {
+      "description": "Eliminar una cámara borrará permanentemente todas las grabaciones, los objetos rastreados y la configuración de esa cámara. Es posible que sea necesario eliminar manualmente cualquier transmisión go2rtc asociada a esta cámara."
     }
   },
   "cameraReview": {
@@ -1253,12 +1276,133 @@
   "maintenance": {
     "sync": {
       "verboseDesc": "Escribe una lista completa de archivos huérfanos en el disco para su revisión.",
-      "verbose": "Detallado"
+      "verbose": "Detallado",
+      "desc": "Frigate limpiará periódicamente los archivos multimedia según un cronograma regular, de acuerdo con su configuración de retención. Es normal ver algunos archivos huérfanos mientras Frigate se ejecuta. Utilice esta función para eliminar del disco los archivos multimedia huérfanos que ya no se referencian en la base de datos.",
+      "forceDesc": "Omitir el umbral de seguridad y completar la sincronización incluso si se eliminara más del 50% de los archivos."
+    },
+    "regionGrid": {
+      "clearConfirmDesc": "No se recomienda borrar la cuadrícula de la región a menos que haya cambiado recientemente el tamaño del modelo de su detector o la posición física de su cámara y esté experimentando problemas de seguimiento de objetos. La cuadrícula se reconstruirá automáticamente con el tiempo a medida que se realice el seguimiento de los objetos. Es necesario reiniciar Frigate para que los cambios surtan efecto.",
+      "desc": "La cuadrícula de regiones es una optimización que aprende dónde suelen aparecer los objetos de diferentes tamaños en el campo de visión de cada cámara. Frigate utiliza estos datos para dimensionar de forma eficiente las regiones de detección. La cuadrícula se construye automáticamente a lo largo del tiempo a partir de los datos de los objetos rastreados."
     }
   },
   "configForm": {
     "camera": {
-      "noCameras": "No hay cámaras disponibles"
+      "noCameras": "No hay cámaras disponibles",
+      "description": "Estos ajustes se aplican únicamente a esta cámara y anulan los ajustes globales."
+    },
+    "genaiModel": {
+      "noModels": "No hay modelos disponibles"
+    },
+    "global": {
+      "description": "Estos ajustes se aplican a todas las cámaras, a menos que se anulen en los ajustes específicos de cada cámara."
+    }
+  },
+  "globalConfig": {
+    "title": "Configuración global",
+    "description": "Configura los ajustes globales que se aplican a todas las cámaras, a menos que se sobrescriban.",
+    "toast": {
+      "success": "Ajustes globales guardados con éxito",
+      "error": "Error al guardar los ajustes globales",
+      "validationError": "Error de validación"
+    }
+  },
+  "cameraConfig": {
+    "title": "Configuración de cámara",
+    "description": "Configura los ajustes de cámaras individuales. Estos ajustes sobrescriben los valores globales predeterminados.",
+    "overriddenBadge": "Sobrescrito",
+    "resetToGlobal": "Restablecer al valor global",
+    "toast": {
+      "success": "Ajustes de cámara guardados con éxito",
+      "error": "Error al guardar los ajustes de cámara"
+    }
+  },
+  "toast": {
+    "success": "Ajustes guardados con éxito",
+    "applied": "Ajustes aplicados con éxito",
+    "successRestartRequired": "Ajustes guardados con éxito. Reinicia Frigate para aplicar los cambios.",
+    "error": "Error al guardar los ajustes",
+    "validationError": "Error de validación: {{message}}",
+    "resetSuccess": "Restablecido a los valores globales predeterminados",
+    "resetError": "Error al restablecer los ajustes",
+    "saveAllSuccess_one": "Se ha guardado {{count}} sección con éxito.",
+    "saveAllSuccess_many": "Se han guardado las {{count}} secciones con éxito.",
+    "saveAllSuccess_other": "Se han guardado {{count}} secciones con éxito.",
+    "saveAllPartial_one": "Se ha guardado {{successCount}} de {{totalCount}} sección. {{failCount}} ha fallado.",
+    "saveAllPartial_many": "Se han guardado {{successCount}} de {{totalCount}} secciones. {{failCount}} han fallado.",
+    "saveAllPartial_other": "Se han guardado {{successCount}} de {{totalCount}} secciones. {{failCount}} han fallado.",
+    "saveAllFailure": "Error al guardar todas las secciones."
+  },
+  "profiles": {
+    "title": "Perfiles",
+    "activeProfile": "Perfil activo",
+    "noActiveProfile": "Sin perfil activo",
+    "active": "Activo",
+    "activated": "Perfil '{{profile}}' activado",
+    "activateFailed": "Error al establecer el perfil",
+    "deactivated": "Perfil desactivado",
+    "noProfiles": "No hay perfiles definidos.",
+    "noOverrides": "Sin sobrescripciones",
+    "cameraCount_one": "{{count}} cámara",
+    "cameraCount_many": "{{count}} de cámaras",
+    "cameraCount_other": "{{count}} cámaras",
+    "columnCamera": "Cámara",
+    "columnOverrides": "Sobrescripciones del perfil",
+    "baseConfig": "Configuración base",
+    "addProfile": "Añadir perfil",
+    "newProfile": "Nuevo perfil",
+    "profileNamePlaceholder": "ej. Armado, Fuera de casa, Modo noche",
+    "friendlyNameLabel": "Nombre del perfil",
+    "profileIdLabel": "ID del perfil",
+    "profileIdDescription": "Identificador interno utilizado en la configuración y automatizaciones",
+    "nameInvalid": "Solo se permiten letras minúsculas, números y guiones bajos",
+    "nameDuplicate": "Ya existe un perfil con este nombre",
+    "error": {
+      "mustBeAtLeastTwoCharacters": "Debe tener al menos 2 caracteres",
+      "mustNotContainPeriod": "No debe contener puntos",
+      "alreadyExists": "Ya existe un perfil con este ID"
+    },
+    "renameProfile": "Renombrar perfil",
+    "renameSuccess": "Perfil renombrado a '{{profile}}'",
+    "enabledDescription": "Los perfiles están habilitados. Cree un nuevo perfil a continuación, navegue a una sección de configuración de cámara para realizar sus cambios y guarde para que estos surtan efecto.",
+    "disabledDescription": "Los perfiles le permiten definir conjuntos con nombre de anulaciones de configuración de la cámara (por ejemplo: armado, fuera, noche) que pueden activarse bajo demanda."
+  },
+  "go2rtcStreams": {
+    "renameStreamDesc": "Introduce un nuevo nombre para esta transmisión. Cambiar el nombre de una transmisión puede provocar fallos en las cámaras u otras transmisiones que hagan referencia a ella por su nombre.",
+    "addStreamDesc": "Introduce un nombre para la nueva transmisión. Este nombre se utilizará para hacer referencia a la transmisión en la configuración de su cámara.",
+    "description": "Gestione las configuraciones de transmisión de go2rtc para la retransmisión de cámaras. Cada transmisión tiene un nombre y una o más URL de origen.",
+    "deleteStreamConfirm": "¿Está seguro de que desea eliminar la transmisión \"{{streamName}}\"? Las cámaras que hagan referencia a esta transmisión podrían dejar de funcionar."
+  },
+  "configMessages": {
+    "birdseye": {
+      "objectsModeDetectDisabled": "Birdseye está configurado en modo 'objects', pero la detección de objetos está desactivada para esta cámara. La cámara no aparecerá en Birdseye."
+    },
+    "lpr": {
+      "globalDisabled": "El reconocimiento de matrículas no está habilitado a nivel global. Habilítelo en la configuración global para que funcione el reconocimiento de matrículas a nivel de cámara."
+    },
+    "audio": {
+      "noAudioRole": "Ninguna transmisión tiene definido el rol de audio. Debe habilitar el rol de audio para que funcione la detección de audio."
+    },
+    "faceRecognition": {
+      "personNotTracked": "El reconocimiento facial requiere que se realice el seguimiento del objeto 'person'. Asegúrese de que 'person' se encuentre en la lista de seguimiento de objetos."
+    },
+    "audioTranscription": {
+      "audioDetectionDisabled": "La detección de audio no está habilitada para esta cámara. La transcripción de audio requiere que la detección de audio esté activa."
+    },
+    "snapshots": {
+      "detectDisabled": "La detección de objetos está desactivada. Las instantáneas se generan a partir de los objetos rastreados y no se crearán."
+    },
+    "detectors": {
+      "mixedTypes": "Todos los detectores deben ser del mismo tipo. Retire los detectores existentes para utilizar un tipo diferente."
+    },
+    "review": {
+      "detectDisabled": "La detección de objetos está desactivada. Los elementos de revisión requieren objetos detectados para categorizar las alertas y detecciones."
+    }
+  },
+  "resetToDefaultDescription": "Esto restablecerá todos los ajustes de esta sección a sus valores predeterminados. Esta acción no se puede deshacer.",
+  "resetToGlobalDescription": "Esto restablecerá la configuración de esta sección a los valores predeterminados globales. Esta acción no se puede deshacer.",
+  "detectionModel": {
+    "plusActive": {
+      "description": "Esta instancia está ejecutando un modelo de Frigate+. Seleccione o cambie su modelo en la configuración de Frigate+."
     }
   }
 }

web/public/locales/es/views/system.json

@@ -45,10 +45,17 @@
         "reviews": "Revisiones",
         "face_recognition": "Reconocimiento facial",
         "camera_activity": "Actividad de cámara",
-        "classification": "Clasificación"
+        "classification": "Clasificación",
+        "system": "Sistema",
+        "camera": "Cámara",
+        "all_cameras": "Todas las cámaras",
+        "cameras_count_one": "{{count}} Cámara",
+        "cameras_count_other": "{{count}} Cámaras",
+        "lpr": "Reconocimiento de matriculas"
       },
       "count_other": "{{count}} mensajes",
-      "count_one": "{{count}} mensaje"
+      "count_one": "{{count}} mensaje",
+      "empty": "No se han capturado mensaje aún"
     }
   },
   "title": "Sistema",
@@ -99,7 +106,10 @@
         "title": "Aviso de estadísticas Intel GPU",
         "message": "Estadísticas de GPU no disponibles",
         "description": "Este es un error conocido en las herramientas de informes de estadísticas de GPU de Intel (intel_gpu_top). El error se produce y muestra repetidamente un uso de GPU del 0 %, incluso cuando la aceleración de hardware y la detección de objetos se ejecutan correctamente en la (i)GPU. No se trata de un error de Frigate. Puede reiniciar el host para solucionar el problema temporalmente y confirmar que la GPU funciona correctamente. Esto no afecta al rendimiento."
-      }
+      },
+      "npuTemperature": "Temperatura NPU",
+      "gpuCompute": "Cálculo GPU / Codificación",
+      "gpuTemperature": "Temperatura GPU"
     },
     "otherProcesses": {
       "title": "Otros Procesos",
@@ -136,7 +146,11 @@
     },
     "shm": {
       "title": "Asignación de SHM (memoria compartida)",
-      "warning": "El tamaño actual de SHM de {{total}}MB es muy pequeño. Aumente al menos a {{min_shm}}MB."
+      "warning": "El tamaño actual de SHM de {{total}}MB es muy pequeño. Aumente al menos a {{min_shm}}MB.",
+      "frameLifetime": {
+        "title": "Tiempo de vida del fotograma",
+        "description": "Cada cámara tiene espacio en la memoria compartida para {{frames}} cuadros. Si la velocidad de cuadros de la cámara es alta, cada cuadro se guarda aproximadamente {{lifetime}} antes de ser sobreescrito."
+      }
     }
   },
   "cameras": {
@@ -174,7 +188,8 @@
       "cameraDetect": "{{camName}} detectar",
       "cameraFramesPerSecond": "{{camName}} cuadros por segundo",
       "cameraDetectionsPerSecond": "{{camName}} detecciones por segundo",
-      "overallSkippedDetectionsPerSecond": "detecciones omitidas por segundo totales"
+      "overallSkippedDetectionsPerSecond": "detecciones omitidas por segundo totales",
+      "cameraGpu": "{{camName}} GPU"
     },
     "toast": {
       "success": {
@@ -183,6 +198,17 @@
       "error": {
         "unableToProbeCamera": "No se pudo sondear la cámara: {{errorMessage}}"
       }
+    },
+    "connectionQuality": {
+      "excellent": "Excelente",
+      "poor": "Debil",
+      "title": "Calidad de la conexión",
+      "fps": "Cuadros por segundo",
+      "expectedFps": "Cuadros por segundo esperados",
+      "reconnectsLastHour": "Reconexiones (última hora)",
+      "unusable": "No usable",
+      "fair": "Normal",
+      "stallsLastHour": "Bloqueos (última hora)"
     }
   },
   "lastRefreshed": "Última actualización: ",
@@ -221,6 +247,7 @@
     "detectIsSlow": "{{detect}} es lento ({{speed}} ms)",
     "cameraIsOffline": "{{camera}} está desconectada",
     "detectIsVerySlow": "{{detect}} es muy lento ({{speed}} ms)",
-    "shmTooLow": "Asignación de /dev/shm ({{total}} MB) debe aumentarse al menos a {{min}} MB."
+    "shmTooLow": "Asignación de /dev/shm ({{total}} MB) debe aumentarse al menos a {{min}} MB.",
+    "debugReplayActive": "Sesión de depuración activa"
   }
 }

web/public/locales/et/audio.json

@@ -113,5 +113,165 @@
   "quack": "Prääksumine",
   "goose": "Hani",
   "honk": "Kaagatamine",
-  "wild_animals": "Metsloomad"
+  "wild_animals": "Metsloomad",
+  "roaring_cats": "Möirgavad kassid",
+  "roar": "Möirgamine",
+  "chirp": "Sirisemine",
+  "squawk": "Prääksatamine",
+  "pigeon": "Tuvi",
+  "coo": "Kudrutamine",
+  "crow": "Vares",
+  "caw": "Kraaksumine",
+  "owl": "Öökull",
+  "hoot": "Huikamine",
+  "flapping_wings": "Tiibade laperdamine",
+  "buzz": "Sumisemine",
+  "frog": "Konn",
+  "croak": "Krooksumine",
+  "snake": "Madu",
+  "rattle": "Kõristamine/lõgistamine",
+  "whale_vocalization": "Vaalaskala häälitsused",
+  "music": "Muusika",
+  "musical_instrument": "Pill",
+  "plucked_string_instrument": "Keelpill",
+  "guitar": "Kitarr",
+  "electric_guitar": "Elektrikitarr",
+  "bass_guitar": "Basskitarr",
+  "acoustic_guitar": "Akustiline kitarr",
+  "sitar": "Sitar",
+  "mandolin": "Mandoliin",
+  "banjo": "Bändžo",
+  "zither": "Kannel/tsitter",
+  "ukulele": "Ukulele",
+  "piano": "Klaver",
+  "electric_piano": "Elektriklaver",
+  "organ": "Orel",
+  "electronic_organ": "Elektriorel",
+  "hammond_organ": "Hammond-orel",
+  "synthesizer": "Süntesaator",
+  "sampler": "Sämpler",
+  "harpsichord": "Klavessiin",
+  "percussion": "Löökriistad",
+  "drum_kit": "Trummikomplekt",
+  "bass_drum": "Basstrumm",
+  "tambourine": "Tamburiin",
+  "glockenspiel": "Ksülofon",
+  "vibraphone": "Vibrafon (metalltorudega ksülofon)",
+  "marimba": "Marimbafon",
+  "tubular_bells": "Torukellad",
+  "gong": "Gong",
+  "orchestra": "Orkester",
+  "cello": "Tšello",
+  "pizzicato": "Pizzicato (poogenpilli sõrmega mängimine)",
+  "violin": "Viiul",
+  "string_section": "Keelpillid",
+  "trombone": "Tromboon",
+  "trumpet": "Trompet",
+  "french_horn": "Metsasarv",
+  "brass_instrument": "Puhkpillid",
+  "double_bass": "Kontrabass",
+  "wind_instrument": "Puhkpill",
+  "flute": "Flööt",
+  "saxophone": "Saksofon",
+  "clarinet": "Klarnet",
+  "harp": "Harf",
+  "bell": "Kellad",
+  "church_bell": "Kirikukell",
+  "jingle_bell": "Aisakell",
+  "bicycle_bell": "Rattakell",
+  "tuning_fork": "Helihark/kammertoon",
+  "bagpipes": "Torupillid",
+  "didgeridoo": "Didžeriduu",
+  "pop_music": "Popmuusika",
+  "hip_hop_music": "Hiphop muusika",
+  "rock_music": "Rokkmuusika",
+  "beatboxing": "Beatbox",
+  "heavy_metal": "Hevimuusika",
+  "punk_rock": "Punkrokk",
+  "grunge": "Grunge",
+  "progressive_rock": "Progressiivne rokk",
+  "rhythm_and_blues": "Rütmibluus",
+  "soul_music": "Soulmuusika",
+  "reggae": "Reggae",
+  "country": "Kantrimuusika",
+  "funk": "Funkmuusika",
+  "folk_music": "Rahvamuusika",
+  "middle_eastern_music": "Lähis-Ida muusika",
+  "jazz": "Džäss",
+  "disco": "Disko",
+  "classical_music": "Klassikaline muusika",
+  "opera": "Ooper",
+  "electronic_music": "Elektrooniline muusika",
+  "house_music": "House-muusika",
+  "techno": "Tekno",
+  "dubstep": "Dubstep",
+  "drum_and_bass": "Drum and Bass",
+  "electronic_dance_music": "Elektrooniline tantsumuusika",
+  "music_of_latin_america": "Ladina-Ameerika muusika",
+  "salsa_music": "Salsa",
+  "flamenco": "Flamenko",
+  "blues": "Bluus",
+  "music_for_children": "Lastemuusika",
+  "new-age_music": "New Age muusika",
+  "vocal_music": "Laulmine",
+  "a_capella": "A Capella",
+  "music_of_africa": "Aafrika muusika",
+  "afrobeat": "Afrobeat",
+  "christian_music": "Kristlik muusika",
+  "gospel_music": "Gospelmuusika",
+  "music_of_asia": "Aasia muusika",
+  "music_of_bollywood": "Bollywoodi muusika",
+  "ska": "Ska",
+  "carnatic_music": "Karnataka muusika",
+  "trance_music": "Trance muusika",
+  "ambient_music": "Ambient muusika",
+  "electronica": "Electronica",
+  "swing_music": "Svingmuusika",
+  "bluegrass": "Bluegrass",
+  "psychedelic_rock": "Psühhedeelne rokk",
+  "rock_and_roll": "Rock'n'roll",
+  "scratching": "Kriipimine/kraapimine",
+  "theremin": "Teremin",
+  "accordion": "Akordion",
+  "harmonica": "Suupill",
+  "wind_chime": "Tuulekell",
+  "chime": "Kelluke",
+  "traditional_music": "Traditsiooniline muusika",
+  "independent_music": "Sõltumatu muusika",
+  "song": "Laul",
+  "background_music": "Taustamuusika",
+  "lullaby": "Hällilaul",
+  "christmas_music": "Jõulumuusika",
+  "video_game_music": "Videomängude muusika",
+  "dance_music": "Tantsumuusika",
+  "wedding_music": "Pulmamuusika",
+  "happy_music": "Rõõmus muusika",
+  "sad_music": "Kurb muusika",
+  "tender_music": "Tundeline muusika",
+  "angry_music": "Vihane muusika",
+  "exciting_music": "Põnev muusika",
+  "scary_music": "Hirmutav muusika",
+  "wind": "Tuul",
+  "thunderstorm": "Äikesetorm",
+  "thunder": "Kõu/äike",
+  "water": "Vesi",
+  "rain": "Vihm",
+  "raindrop": "Vihmapiisk",
+  "spray": "Pritsimine",
+  "pump": "Pumpamine",
+  "stir": "Segamine/nihelemine",
+  "boiling": "Keemine",
+  "sonar": "Kajalood",
+  "arrow": "Nool",
+  "whoosh": "Vuhh/vuhisemine",
+  "thump": "Potsatus/mütsatus",
+  "thunk": "Põmakas",
+  "doorbell": "Uksekell",
+  "traffic_noise": "Liiklusmüra",
+  "rail_transport": "Raudteetransport",
+  "train_whistle": "Rongivile",
+  "sailboat": "Purjekas",
+  "soundtrack_music": "Filmimuusika",
+  "jingle": "Kõlisemine/tilisemine",
+  "theme_music": "Tunnusmuusika"
 }

web/public/locales/et/common.json

@@ -181,7 +181,8 @@
     "classification": "Klassifikatsioon",
     "chat": "Vestlus",
     "actions": "Tegevused",
-    "profiles": "Profiilid"
+    "profiles": "Profiilid",
+    "features": "Funktsionaalsused"
   },
   "unit": {
     "speed": {

web/public/locales/et/components/filter.json

@@ -4,13 +4,16 @@
     "toast": {
       "error": "Jälgitavate objektide kustutamine ei õnnestunud: {{errorMessage}}",
       "success": "Jälgitavate objektide kustutamine õnnestus."
-    }
+    },
+    "title": "Kinnita kustutamine",
+    "desc": "Nende {{objectLength}} jälgitava objekti kustutamine eemaldab tõmmise salvestuse, kõik seotud salvestatud sissekanded ja kõik seotud objekti elutsükli kirjed. Ajaloo vaates salvestatud videomaterjali nende jälgitavate objektide kohta <em>EI</em> kustutata.<br /><br/>Kas soovid kindlasti jätkata?<br/><br/>Hoia <em>Shift</em>-klahvi all, et seda teateakent tulevikus vahele jätta."
   },
   "cameras": {
     "all": {
       "title": "Kõik kaamerad",
       "short": "Kaamerad"
-    }
+    },
+    "label": "Kaamerate filter"
   },
   "labels": {
     "all": {
@@ -38,7 +41,8 @@
       "defaultView": {
         "title": "Vaikimisi vaade",
         "summary": "Kokkuvõte",
-        "unfilteredGrid": "Filtreerimata ruudustik"
+        "unfilteredGrid": "Filtreerimata ruudustik",
+        "desc": "Kui filtreid pole valitud, näita viimaste jälgitud objektide kokkuvõtet sildi kohta või näita filtreerimata ruudustikuvaadet."
       },
       "gridColumns": {
         "title": "Ruudustiku veerud",
@@ -48,16 +52,26 @@
         "options": {
           "thumbnailImage": "Pisipilt",
           "description": "Kirjeldus"
-        }
+        },
+        "label": "Otsinguallikas",
+        "desc": "Vali, kas soovid otsida sinu jälgitavate objektide pisipilte või kirjeldusi."
+      }
+    },
+    "date": {
+      "selectDateBy": {
+        "label": "Vali kuupäev, mille alusel tahad filtreerida"
       }
     }
   },
   "logSettings": {
     "loading": {
-      "title": "Laadin"
+      "title": "Laadin",
+      "desc": "Kui logipaneeli vaade on keritud lõpuni, siis kuvatakse lisanduvad logikirjed automaatselt kohe."
     },
     "disableLogStreaming": "Keela logi voogedastus",
-    "allLogs": "Kõik logid"
+    "allLogs": "Kõik logid",
+    "label": "Logimistase filtri jaoks",
+    "filterBySeverity": "Kriitilisus filtri jaoks"
   },
   "classes": {
     "label": "Klassid",
@@ -83,6 +97,44 @@
   "estimatedSpeed": "Hinnanguline kiirus: ({{unit}})",
   "features": {
     "label": "Omadused",
-    "hasSnapshot": "Leidub hetkvõte"
+    "hasSnapshot": "Leidub hetkvõte",
+    "hasVideoClip": "Videoklipp on olemas",
+    "submittedToFrigatePlus": {
+      "label": "Saadetud teenusesse Frigate+",
+      "tips": "Sa pead filtreerima jälgitavaid objekte, millel on tõmmis.<br /><br />Kui jälgitaval objektil pole tõmmist, siis teda Frigate+ teenusesse saata ei saa."
+    }
+  },
+  "attributes": {
+    "label": "Klassifitseerimisatribuudid",
+    "all": "Kõik atribuudid"
+  },
+  "sort": {
+    "label": "Järjestus",
+    "dateAsc": "Kuupäev (kasvavalt)",
+    "dateDesc": "Kuupäev (kahanevalt)",
+    "scoreAsc": "Objekti punktiskoor (kasvavalt)",
+    "scoreDesc": "Objekti punktiskoor (kahanevalt)",
+    "speedAsc": "Hinnanguline kiirus (kasvavalt)",
+    "speedDesc": "Hinnanguline kiirus (kahanevalt)",
+    "relevance": "Teemakohasus"
+  },
+  "review": {
+    "showReviewed": "Näita ülevaadatuid"
+  },
+  "motion": {
+    "showMotionOnly": "Näita vaid liikumisega klippe"
+  },
+  "zoneMask": {
+    "filterBy": "Tsoonimask filtri jaoks"
+  },
+  "recognizedLicensePlates": {
+    "title": "Tuvastatud sõiduki numbrimärgid",
+    "loadFailed": "Tuvastatud sõiduki numbrimärkide laadimine ei õnnestunud.",
+    "loading": "Laadin tuvastatud sõiduki numbrimärke…",
+    "placeholder": "Sõidukite numbrimärkide otsimiseks kirjuta midagi…",
+    "noLicensePlatesFound": "Sõidukite numbrimärke ei leidu.",
+    "selectPlatesFromList": "Vali loendist üks või enam sõiduki numbrimärki.",
+    "selectAll": "Vali kõik",
+    "clearAll": "Eemalda kõik"
   }
 }

web/public/locales/et/components/player.json

@@ -4,7 +4,8 @@
   "noPreviewFoundFor": "{{cameraName}} kaamera eelvaadet ei leidu",
   "submitFrigatePlus": {
     "submit": "Saada",
-    "title": "Kas saadad selle kaadri Frigate+ teenusesse?"
+    "title": "Kas saadad selle kaadri Frigate+ teenusesse?",
+    "previewError": "Hetktõmmise eelvaate laadimine ei õnnestu. Salvestus ei pruugi olla hetkel saadaval."
   },
   "cameraDisabled": "Kaamera on kasutuselt eemaldatud",
   "stats": {

web/public/locales/et/config/cameras.json

@@ -2,5 +2,21 @@
     "name": {
         "label": "Kaamera nimi",
         "description": "Kaamera nimi on nõutav"
+    },
+    "friendly_name": {
+        "label": "Sõbralik nimi",
+        "description": "Frigate UI-s kasutatud kaamerasõbralik nimi"
+    },
+    "enabled": {
+        "label": "Kasutusel",
+        "description": "Kasutusel"
+    },
+    "audio": {
+        "label": "Helisündmused"
+    },
+    "birdseye": {
+        "mode": {
+            "label": "Jälgimisrežiim"
+        }
     }
 }