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dependabot[bot]andGitHub 8ea5eb6bd1 Bump i18next-http-backend from 3.0.1 to 3.0.5 in /web
Bumps [i18next-http-backend](https://github.com/i18next/i18next-http-backend) from 3.0.1 to 3.0.5.
- [Changelog](https://github.com/i18next/i18next-http-backend/blob/master/CHANGELOG.md)
- [Commits](https://github.com/i18next/i18next-http-backend/compare/v3.0.1...v3.0.5)

---
updated-dependencies:
- dependency-name: i18next-http-backend
  dependency-version: 3.0.5
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-04-22 18:08:47 +00:00
676 changed files with 2744 additions and 27076 deletions
+1 -1
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@@ -26,7 +26,7 @@ _Please read the [contributing guidelines](https://github.com/blakeblackshear/fr
- This PR fixes or closes issue: fixes #
- This PR is related to issue:
- Link to discussion with maintainers (**required** for any large or "planned" features):
- Link to discussion with maintainers (**required** for large/pinned features):
## For new features
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@@ -13,7 +13,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Check PR description against template
uses: actions/github-script@v9
uses: actions/github-script@v7
with:
script: |
const maintainers = ['blakeblackshear', 'NickM-27', 'hawkeye217', 'dependabot[bot]', 'weblate'];
+1 -1
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@@ -72,7 +72,7 @@ jobs:
run: npm run e2e
working-directory: ./web
- name: Upload test artifacts
uses: actions/upload-artifact@v7
uses: actions/upload-artifact@v4
if: failure()
with:
name: playwright-report
+3 -3
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@@ -18,9 +18,9 @@ jobs:
close-issue-message: ""
days-before-stale: 30
days-before-close: 3
exempt-draft-pr: false
exempt-issue-labels: "planned,security"
exempt-pr-labels: "planned,security,dependencies"
exempt-draft-pr: true
exempt-issue-labels: "pinned,security"
exempt-pr-labels: "pinned,security,dependencies"
operations-per-run: 120
- name: Print outputs
env:
-5
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@@ -22,8 +22,3 @@ 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
+3 -8
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@@ -10,14 +10,11 @@ If you've found a bug and want to fix it, go for it. Link to the relevant issue
### New features
A pull request is more than just code — it's a request for the maintainers to review, integrate, and support the change long-term. We're selective about what we take on, and prioritize changes that align with the project's direction and can be responsibly maintained in the long term.
Every new feature adds scope that the maintainers must test, maintain, and support long-term. Before writing code for a new feature:
**Large or highly-requested features** raise the bar even higher. Popularity signals demand, but it doesn't pre-approve any particular implementation. The bigger the change, the higher the long-term cost, and the more important it is that we're aligned on scope and approach before any code is written. A large PR that lands without prior discussion is unlikely to be merged as-is, no matter how well it's implemented.
Before writing code for a new feature:
1. **Check for existing discussion.** Search [feature requests](https://github.com/blakeblackshear/frigate/issues) and [discussions](https://github.com/blakeblackshear/frigate/discussions) to see if it's been proposed or discussed. Feature requests tagged with "planned" are on our radar — we plan to get to them, but we don't maintain a public roadmap or timeline. Check in with us first if you have interest in contributing to one.
1. **Check for existing discussion.** Search [feature requests](https://github.com/blakeblackshear/frigate/issues) and [discussions](https://github.com/blakeblackshear/frigate/discussions) to see if it's been proposed or discussed. Pinned feature requests are on our radar — we plan to get to them, but we don't maintain a public roadmap or timeline. Check in with us first if you have interest in contributing to one.
2. **Start a discussion or feature request first.** This helps ensure your idea aligns with Frigate's direction before you invest time building it. Community interest in a feature request helps us gauge demand, though a great idea is a great idea even without a crowd behind it.
3. **Be open to "no".** We try to be thoughtful about what we take on, and sometimes that means saying no to good code if the feature isn't the right fit for the project. These calls are sometimes subjective, and we won't always get them right. We're happy to discuss and reconsider.
## AI usage policy
@@ -42,8 +39,6 @@ We're not trying to gatekeep how you write code. Use whatever tools make you pro
Some honest context: when we review a PR, we're not just evaluating whether the code works today. We're evaluating whether we can maintain it, debug it, and extend it long-term — often without the original author's involvement. Code that the author doesn't deeply understand is code that nobody understands, and that's a liability.
One more thing worth saying directly: most maintainers already have access to the same AI tools you do. A PR that's entirely AI-generated — where the author can't explain the design, debug issues independently, or engage substantively in design discussions — doesn't offer something we couldn't produce ourselves. What makes a contribution genuinely valuable is the human judgment and domain understanding behind it, as well as the engagement during review that shapes it into something we can confidently take on long-term.
## Pull request guidelines
### Before submitting
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@@ -11,7 +11,7 @@ joserfc == 1.2.*
cryptography == 44.0.*
pathvalidate == 3.3.*
markupsafe == 3.0.*
python-multipart == 0.0.26
python-multipart == 0.0.20
# Classification Model Training
tensorflow == 2.19.* ; platform_machine == 'aarch64'
tensorflow-cpu == 2.19.* ; platform_machine == 'x86_64'
+4 -11
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@@ -13,7 +13,7 @@ ARG ROCM
RUN apt update -qq && \
apt install -y wget gpg && \
wget -O rocm.deb https://repo.radeon.com/amdgpu-install/7.2.3/ubuntu/jammy/amdgpu-install_7.2.3.70203-1_all.deb && \
wget -O rocm.deb https://repo.radeon.com/amdgpu-install/7.2/ubuntu/jammy/amdgpu-install_7.2.70200-1_all.deb && \
apt install -y ./rocm.deb && \
apt update && \
apt install -qq -y rocm
@@ -32,14 +32,11 @@ RUN echo /opt/rocm/lib|tee /opt/rocm-dist/etc/ld.so.conf.d/rocm.conf
FROM deps AS deps-prelim
COPY docker/rocm/debian-backports.sources /etc/apt/sources.list.d/debian-backports.sources
# install_deps.sh upgraded libstdc++6 from trixie for Battlemage; the matching
# -dev package must also come from trixie or apt refuses to satisfy it.
RUN echo "deb http://deb.debian.org/debian trixie main" > /etc/apt/sources.list.d/trixie.list && \
apt-get update && \
RUN apt-get update && \
apt-get install -y libnuma1 && \
apt-get install -qq -y -t bookworm-backports mesa-va-drivers mesa-vulkan-drivers && \
apt-get install -qq -y -t trixie libstdc++-14-dev && \
rm -f /etc/apt/sources.list.d/trixie.list && \
# Install C++ standard library headers for HIPRTC kernel compilation fallback
apt-get install -qq -y libstdc++-12-dev && \
rm -rf /var/lib/apt/lists/*
WORKDIR /opt/frigate
@@ -78,10 +75,6 @@ ENV MIGRAPHX_DISABLE_MIOPEN_FUSION=1
ENV MIGRAPHX_DISABLE_SCHEDULE_PASS=1
ENV MIGRAPHX_DISABLE_REDUCE_FUSION=1
ENV MIGRAPHX_ENABLE_HIPRTC_WORKAROUNDS=1
ENV MIOPEN_CUSTOM_CACHE_DIR=/config/model_cache/migraphx
ENV MIOPEN_USER_DB_PATH=/config/model_cache/migraphx
ENV AMD_COMGR_CACHE=1
ENV AMD_COMGR_CACHE_DIR=/config/model_cache/migraphx
COPY --from=rocm-dist / /
+1 -1
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@@ -1 +1 @@
onnxruntime-migraphx @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v7.2.3-1/onnxruntime_migraphx-1.24.4-cp311-cp311-linux_x86_64.whl
onnxruntime-migraphx @ https://github.com/NickM-27/frigate-onnxruntime-rocm/releases/download/v7.2.0/onnxruntime_migraphx-1.23.1-cp311-cp311-linux_x86_64.whl
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@@ -1,5 +1,5 @@
variable "ROCM" {
default = "7.2.3"
default = "7.2.0"
}
variable "HSA_OVERRIDE_GFX_VERSION" {
default = ""
+2 -2
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@@ -19,7 +19,7 @@ Face recognition requires a one-time internet connection to download detection a
### Face Detection
When running a Frigate+ model (or any custom model that natively detects faces) should ensure that `face` is added to the [list of objects to track](../plus/index.md#available-label-types) either globally or for a specific camera. This will allow face detection to run at the same time as object detection and be more efficient.
When running a Frigate+ model (or any custom model that natively detects faces) should ensure that `face` is added to the [list of objects to track](../plus/#available-label-types) either globally or for a specific camera. This will allow face detection to run at the same time as object detection and be more efficient.
When running a default COCO model or another model that does not include `face` as a detectable label, face detection will run via CV2 using a lightweight DNN model that runs on the CPU. In this case, you should _not_ define `face` in your list of objects to track.
@@ -171,7 +171,7 @@ When choosing images to include in the face training set it is recommended to al
- If it is difficult to make out details in a persons face it will not be helpful in training.
- Avoid images with extreme under/over-exposure.
- Avoid blurry / pixelated images.
- Avoid training on infrared (gray-scale). The models are trained on color images and will not be able to extract features from gray-scale images.
- Avoid training on infrared (gray-scale). The models are trained on color images and will be able to extract features from gray-scale images.
- Using images of people wearing hats / sunglasses may confuse the model.
- Do not upload too many similar images at the same time, it is recommended to train no more than 4-6 similar images for each person to avoid over-fitting.
+2 -13
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@@ -201,7 +201,7 @@ Cloud Generative AI providers require an active internet connection to send imag
### Ollama Cloud
Ollama also supports [cloud models](https://ollama.com/cloud), where model inference is performed in the cloud. You can connect directly to Ollama Cloud by setting `base_url` to `https://ollama.com` and providing an API key. Alternatively, you can run Ollama locally and use a cloud model name so your local instance forwards requests to the cloud. For more details, see the Ollama cloud model [docs](https://docs.ollama.com/cloud).
Ollama also supports [cloud models](https://ollama.com/cloud), where your local Ollama instance handles requests from Frigate, but model inference is performed in the cloud. Set up Ollama locally, sign in with your Ollama account, and specify the cloud model name in your Frigate config. For more details, see the Ollama cloud model [docs](https://docs.ollama.com/cloud).
#### Configuration
@@ -210,8 +210,7 @@ Ollama also supports [cloud models](https://ollama.com/cloud), where model infer
1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
- Set **Provider** to `ollama`
- Set **Base URL** to your local Ollama address (e.g., `http://localhost:11434`) or `https://ollama.com` for direct cloud inference
- Set **API key** if required by your endpoint (e.g., when using `https://ollama.com`)
- Set **Base URL** to your local Ollama address (e.g., `http://localhost:11434`)
- Set **Model** to the cloud model name
</TabItem>
@@ -224,16 +223,6 @@ genai:
model: cloud-model-name
```
or when using Ollama Cloud directly
```yaml
genai:
provider: ollama
base_url: https://ollama.com
model: cloud-model-name
api_key: your-api-key
```
</TabItem>
</ConfigTabs>
@@ -136,32 +136,90 @@ ffmpeg:
</TabItem>
</ConfigTabs>
### Configuring Intel GPU Stats
### Configuring Intel GPU Stats in Docker
Frigate reads Intel GPU utilization directly from the kernel's per-client DRM usage counters exposed at `/proc/<pid>/fdinfo/<fd>`. This requires:
Additional configuration is needed for the Docker container to be able to access the `intel_gpu_top` command for GPU stats. There are two options:
- Linux kernel **5.19 or newer** for the `i915` driver, or any release of the `xe` driver.
- Frigate running with permission to read other processes' fdinfo. Running as root inside the container (the default) satisfies this; non-root setups may need `CAP_SYS_PTRACE`.
1. Run the container as privileged.
2. Add the `CAP_PERFMON` capability (note: you might need to set the `perf_event_paranoid` low enough to allow access to the performance event system.)
No `intel_gpu_top` binary, `CAP_PERFMON`, privileged mode, or `perf_event_paranoid` tuning is required.
#### Run as privileged
#### Stats for SR-IOV or specific devices
This method works, but it gives more permissions to the container than are actually needed.
If the host has more than one Intel GPU (e.g. an iGPU plus a discrete GPU, or SR-IOV virtual functions), pin stats collection to a specific device by setting `intel_gpu_device` to either its PCI bus address or a DRM card/render-node path:
##### Docker Compose - Privileged
```yaml
services:
frigate:
...
image: ghcr.io/blakeblackshear/frigate:stable
# highlight-next-line
privileged: true
```
##### Docker Run CLI - Privileged
```bash {4}
docker run -d \
--name frigate \
...
--privileged \
ghcr.io/blakeblackshear/frigate:stable
```
#### CAP_PERFMON
Only recent versions of Docker support the `CAP_PERFMON` capability. You can test to see if yours supports it by running: `docker run --cap-add=CAP_PERFMON hello-world`
##### Docker Compose - CAP_PERFMON
```yaml {5,6}
services:
frigate:
...
image: ghcr.io/blakeblackshear/frigate:stable
cap_add:
- CAP_PERFMON
```
##### Docker Run CLI - CAP_PERFMON
```bash {4}
docker run -d \
--name frigate \
...
--cap-add=CAP_PERFMON \
ghcr.io/blakeblackshear/frigate:stable
```
#### perf_event_paranoid
_Note: This setting must be changed for the entire system._
For more information on the various values across different distributions, see https://askubuntu.com/questions/1400874/what-does-perf-paranoia-level-four-do.
Depending on your OS and kernel configuration, you may need to change the `/proc/sys/kernel/perf_event_paranoid` kernel tunable. You can test the change by running `sudo sh -c 'echo 2 >/proc/sys/kernel/perf_event_paranoid'` which will persist until a reboot. Make it permanent by running `sudo sh -c 'echo kernel.perf_event_paranoid=2 >> /etc/sysctl.d/local.conf'`
#### Stats for SR-IOV or other devices
When using virtualized GPUs via SR-IOV, you need to specify the device path to use to gather stats from `intel_gpu_top`. This example may work for some systems using SR-IOV:
```yaml
telemetry:
stats:
intel_gpu_device: "0000:00:02.0"
intel_gpu_device: "sriov"
```
For other virtualized GPUs, try specifying the direct path to the device instead:
```yaml
telemetry:
stats:
intel_gpu_device: "/dev/dri/card1"
intel_gpu_device: "drm:/dev/dri/card0"
```
When passing a device path, make sure the device is also passed through to the container.
If you are passing in a device path, make sure you've passed the device through to the container.
## AMD-based CPUs
+24 -134
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@@ -72,7 +72,7 @@ This does not affect using hardware for accelerating other tasks such as [semant
# Officially Supported Detectors
Frigate provides a number of builtin detector types. By default, Frigate will use a single OpenVINO detector running on the CPU. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
Frigate provides a number of builtin detector types. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
## Edge TPU Detector
@@ -494,7 +494,7 @@ detectors:
| [YOLO-NAS](#yolo-nas) | ✅ | ✅ | |
| [MobileNet v2](#ssdlite-mobilenet-v2) | ✅ | ✅ | Fast and lightweight model, less accurate than larger models |
| [YOLOX](#yolox) | ✅ | ? | |
| [D-FINE / DEIMv2](#d-fine--deimv2) | ❌ | ❌ | |
| [D-FINE](#d-fine) | ❌ | ❌ | |
#### SSDLite MobileNet v2
@@ -710,13 +710,13 @@ model:
</details>
#### D-FINE / DEIMv2
#### D-FINE
[D-FINE](https://github.com/Peterande/D-FINE) and [DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) are DETR based models that share the same ONNX input/output format. The ONNX exported models are supported, but not included by default. See the models section for downloading [D-FINE](#downloading-d-fine-model) or [DEIMv2](#downloading-deimv2-model) for use in Frigate.
[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.
:::warning
Currently D-FINE / DEIMv2 models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
Currently D-FINE models only run on OpenVINO in CPU mode, GPUs currently fail to compile the model
:::
@@ -766,31 +766,6 @@ Note that the labelmap uses a subset of the complete COCO label set that has onl
</details>
<details>
<summary>DEIMv2 Setup & Config</summary>
After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
```yaml
detectors:
ov:
type: openvino
device: CPU
model:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/deimv2_hgnetv2_n.onnx
labelmap_path: /labelmap/coco-80.txt
```
Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
</details>
## Apple Silicon detector
The NPU in Apple Silicon can't be accessed from within a container, so the [Apple Silicon detector client](https://github.com/frigate-nvr/apple-silicon-detector) must first be setup. It is recommended to use the Frigate docker image with `-standard-arm64` suffix, for example `ghcr.io/blakeblackshear/frigate:stable-standard-arm64`.
@@ -972,7 +947,7 @@ The AMD GPU kernel is known problematic especially when converting models to mxr
See [ONNX supported models](#supported-models) for supported models, there are some caveats:
- D-FINE / DEIMv2 models are not supported
- D-FINE models are not supported
- YOLO-NAS models are known to not run well on integrated GPUs
## ONNX
@@ -1022,13 +997,13 @@ detectors:
### ONNX Supported Models
| Model | Nvidia GPU | AMD GPU | Notes |
| ------------------------------------ | ---------- | ------- | --------------------------------------------------- |
| [YOLOv9](#yolo-v3-v4-v7-v9-2) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [RF-DETR](#rf-detr) | ✅ | ⚠️ | Supports CUDA Graphs for optimal Nvidia performance |
| [YOLO-NAS](#yolo-nas-1) | ⚠️ | ⚠️ | Not supported by CUDA Graphs |
| [YOLOX](#yolox-1) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [D-FINE / DEIMv2](#d-fine--deimv2-1) | ⚠️ | ❌ | Not supported by CUDA Graphs |
| Model | Nvidia GPU | AMD GPU | Notes |
| ----------------------------- | ---------- | ------- | --------------------------------------------------- |
| [YOLOv9](#yolo-v3-v4-v7-v9-2) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [RF-DETR](#rf-detr) | ✅ | | Supports CUDA Graphs for optimal Nvidia performance |
| [YOLO-NAS](#yolo-nas-1) | ⚠️ | ⚠️ | Not supported by CUDA Graphs |
| [YOLOX](#yolox-1) | ✅ | ✅ | Supports CUDA Graphs for optimal Nvidia performance |
| [D-FINE](#d-fine) | ⚠️ | ❌ | Not supported by CUDA Graphs |
There is no default model provided, the following formats are supported:
@@ -1240,9 +1215,9 @@ model:
</details>
#### D-FINE / DEIMv2
#### D-FINE
[D-FINE](https://github.com/Peterande/D-FINE) and [DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) are DETR based models that share the same ONNX input/output format. The ONNX exported models are supported, but not included by default. See the models section for downloading [D-FINE](#downloading-d-fine-model) or [DEIMv2](#downloading-deimv2-model) for use in Frigate.
[D-FINE](https://github.com/Peterande/D-FINE) is a DETR based model. The ONNX exported models are supported, but not included by default. See [the models section](#downloading-d-fine-model) for more information on downloading the D-FINE model for use in Frigate.
<details>
<summary>D-FINE Setup & Config</summary>
@@ -1287,28 +1262,6 @@ model:
</details>
<details>
<summary>DEIMv2 Setup & Config</summary>
After placing the downloaded onnx model in your `config/model_cache` folder, you can use the following configuration:
```yaml
detectors:
onnx:
type: onnx
model:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/deimv2_hgnetv2_n.onnx
labelmap_path: /labelmap/coco-80.txt
```
</details>
Note that the labelmap uses a subset of the complete COCO label set that has only 80 objects.
## CPU Detector (not recommended)
@@ -1452,7 +1405,7 @@ MemryX `.dfp` models are automatically downloaded at runtime, if enabled, to the
#### YOLO-NAS
The [YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) model included in this detector is downloaded from the [Models Section](#downloading-yolo-nas-model) and compiled to DFP with [mx_nc](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage).
The [YOLO-NAS](https://github.com/Deci-AI/super-gradients/blob/master/YOLONAS.md) model included in this detector is downloaded from the [Models Section](#downloading-yolo-nas-model) and compiled to DFP with [mx_nc](https://developer.memryx.com/tools/neural_compiler.html#usage).
**Note:** The default model for the MemryX detector is YOLO-NAS 320x320.
@@ -1506,7 +1459,7 @@ model:
#### YOLOv9
The YOLOv9s model included in this detector is downloaded from [the original GitHub](https://github.com/WongKinYiu/yolov9) like in the [Models Section](#yolov9-1) and compiled to DFP with [mx_nc](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage).
The YOLOv9s model included in this detector is downloaded from [the original GitHub](https://github.com/WongKinYiu/yolov9) like in the [Models Section](#yolov9-1) and compiled to DFP with [mx_nc](https://developer.memryx.com/tools/neural_compiler.html#usage).
##### Configuration
@@ -1648,39 +1601,19 @@ model:
#### Using a Custom Model
To use your own custom model, first compile it into a [.dfp](https://developer.memryx.com/2p1/specs/files.html#dataflow-program) file, which is the format used by MemryX.
To use your own model:
#### Compile the Model
1. Package your compiled model into a `.zip` file.
Custom models must be compiled using **MemryX SDK 2.1**.
2. The `.zip` must contain the compiled `.dfp` file.
Before compiling your model, install the MemryX Neural Compiler tools from the
[Install Tools](https://developer.memryx.com/2p1/get_started/install_tools.html) page on the **host**.
3. Depending on the model, the compiler may also generate a cropped post-processing network. If present, it will be named with the suffix `_post.onnx`.
> **Note:** It is recommended to compile the model on the host machine, or on another separate machine, rather than inside the Frigate Docker container. Installing the compiler inside Docker may conflict with container packages. It is recommended to create a Python virtual environment and install the compiler there.
4. Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.
Once the SDK 2.1 environment is set up, follow the
[MemryX Compiler](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage) documentation to compile your model.
5. Update the `labelmap_path` to match your custom model's labels.
Example:
```bash
mx_nc -m yolonas.onnx -c 4 --autocrop -v --dfp_fname yolonas.dfp
```
For detailed instructions on compiling models, refer to the [MemryX Compiler](https://developer.memryx.com/2p1/tools/neural_compiler.html#usage) docs and [Tutorials](https://developer.memryx.com/2p1/tutorials/tutorials.html).
#### Package the Compiled Model
1. Package your compiled model into a `.zip` file.
2. The `.zip` file must contain the compiled `.dfp` file.
3. Depending on the model, the compiler may also generate a cropped post-processing network. If present, it will be named with the suffix `_post.onnx`.
4. Bind-mount the `.zip` file into the container and specify its path using `model.path` in your config.
5. Update `labelmap_path` to match your custom model's labels.
For detailed instructions on compiling models, refer to the [MemryX Compiler](https://developer.memryx.com/tools/neural_compiler.html#usage) docs and [Tutorials](https://developer.memryx.com/tutorials/tutorials.html).
```yaml
# The detector automatically selects the default model if nothing is provided in the config.
@@ -2341,49 +2274,6 @@ COPY --from=build /dfine/output/dfine_${MODEL_SIZE}_obj2coco.onnx /dfine-${MODEL
EOF
```
### Downloading DEIMv2 Model
[DEIMv2](https://github.com/Intellindust-AI-Lab/DEIMv2) can be exported as ONNX by running the command below. Pretrained weights are available on Hugging Face for two backbone families:
- **HGNetv2** (smaller/faster): `atto`, `femto`, `pico`, `n`
- **DINOv3** (larger/more accurate): `s`, `m`, `l`, `x`
Set `BACKBONE` and `MODEL_SIZE` in the first line to match your desired variant. Hugging Face model names use uppercase (e.g. `HGNetv2_N`, `DINOv3_S`), while config files use lowercase (e.g. `hgnetv2_n`, `dinov3_s`).
```sh
docker build . --rm --build-arg BACKBONE=hgnetv2 --build-arg MODEL_SIZE=n --output . -f- <<'EOF'
FROM python:3.11-slim AS build
RUN apt-get update && apt-get install --no-install-recommends -y git libgl1 libglib2.0-0 && rm -rf /var/lib/apt/lists/*
COPY --from=ghcr.io/astral-sh/uv:0.8.0 /uv /bin/
WORKDIR /deimv2
RUN git clone https://github.com/Intellindust-AI-Lab/DEIMv2.git .
# Install CPU-only PyTorch first to avoid pulling CUDA variant
RUN uv pip install --no-cache --system torch torchvision --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --no-cache --system -r requirements.txt
RUN uv pip install --no-cache --system onnx safetensors huggingface_hub
RUN mkdir -p output
ARG BACKBONE
ARG MODEL_SIZE
# Download from Hugging Face and convert safetensors to pth
RUN python3 -c "\
from huggingface_hub import hf_hub_download; \
from safetensors.torch import load_file; \
import torch; \
backbone = '${BACKBONE}'.replace('hgnetv2','HGNetv2').replace('dinov3','DINOv3'); \
size = '${MODEL_SIZE}'.upper(); \
st = load_file(hf_hub_download('Intellindust/DEIMv2_' + backbone + '_' + size + '_COCO', 'model.safetensors')); \
torch.save({'model': st}, 'output/deimv2.pth')"
RUN sed -i "s/data = torch.rand(2/data = torch.rand(1/" tools/deployment/export_onnx.py
# HuggingFace safetensors omits frozen constants that the model constructor initializes
RUN sed -i "s/cfg.model.load_state_dict(state)/cfg.model.load_state_dict(state, strict=False)/" tools/deployment/export_onnx.py
RUN python3 tools/deployment/export_onnx.py -c configs/deimv2/deimv2_${BACKBONE}_${MODEL_SIZE}_coco.yml -r output/deimv2.pth
FROM scratch
ARG BACKBONE
ARG MODEL_SIZE
COPY --from=build /deimv2/output/deimv2.onnx /deimv2_${BACKBONE}_${MODEL_SIZE}.onnx
EOF
```
### Downloading RF-DETR Model
RF-DETR can be exported as ONNX by running the command below. You can copy and paste the whole thing to your terminal and execute, altering `MODEL_SIZE=Nano` in the first line to `Nano`, `Small`, or `Medium` size.
+1 -1
View File
@@ -195,7 +195,7 @@ Pre and post capture footage is included in the **recording timeline**, visible
## Will Frigate delete old recordings if my storage runs out?
If there is less than an hour left of storage, the oldest hour of recordings will be deleted and a message will be printed in the Frigate logs. This emergency cleanup deletes the oldest recordings first regardless of retention settings to reclaim space as quickly as possible.
As of Frigate 0.12 if there is less than an hour left of storage, the oldest 2 hours of recordings will be deleted.
## Configuring Recording Retention
+8 -3
View File
@@ -236,7 +236,7 @@ Enabling arbitrary exec sources allows execution of arbitrary commands through g
## Advanced Restream Configurations
The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-exec) source in go2rtc can be used for custom ffmpeg commands and other applications. An example is below:
The [exec](https://github.com/AlexxIT/go2rtc/tree/v1.9.13#source-exec) source in go2rtc can be used for custom ffmpeg commands. An example is below:
:::warning
@@ -244,11 +244,16 @@ The `exec:`, `echo:`, and `expr:` sources are disabled by default for security.
:::
NOTE: RTSP output will need to be passed with two curly braces `{{output}}`, whereas pipe output must be passed without curly braces.
:::warning
The `exec:`, `echo:`, and `expr:` sources are disabled by default for security. You must set `GO2RTC_ALLOW_ARBITRARY_EXEC=true` to use them. See [Security: Restricted Stream Sources](#security-restricted-stream-sources) for more information.
:::
NOTE: The output will need to be passed with two curly braces `{{output}}`
```yaml
go2rtc:
streams:
stream1: exec:ffmpeg -hide_banner -re -stream_loop -1 -i /media/BigBuckBunny.mp4 -c copy -rtsp_transport tcp -f rtsp {{output}}
stream2: exec:rpicam-vid -t 0 --libav-format h264 -o -
```
+4 -5
View File
@@ -223,11 +223,10 @@ Apple Silicon can not run within a container, so a ZMQ proxy is utilized to comm
With the [ROCm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many discrete AMD GPUs.
| Name | YOLOv9 Inference Time | YOLO-NAS Inference Time | RF-DETR Inference Time |
| -------------- | --------------------------- | ------------------------- | ---------------------- |
| AMD 780M | t-320: ~ 14 ms s-320: 20 ms | 320: ~ 25 ms 640: ~ 50 ms | |
| AMD 8700G | | 320: ~ 20 ms 640: ~ 40 ms | |
| AMD 9060XT 16G | t-320: ~ 4 ms s-320: 5 ms | 320: ~ 6 ms | Nano-320: ~ 90 ms |
| Name | YOLOv9 Inference Time | YOLO-NAS Inference Time |
| --------- | --------------------------- | ------------------------- |
| AMD 780M | t-320: ~ 14 ms s-320: 20 ms | 320: ~ 25 ms 640: ~ 50 ms |
| AMD 8700G | | 320: ~ 20 ms 640: ~ 40 ms |
## Community Supported Detectors
+2 -25
View File
@@ -4,15 +4,12 @@ title: Installation
---
import ShmCalculator from '@site/src/components/ShmCalculator'
import DockerComposeGenerator from '@site/src/components/DockerComposeGenerator'
import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';
Frigate is a Docker container that can be run on any Docker host including as a [Home Assistant App](https://www.home-assistant.io/apps/). Note that the Home Assistant App is **not** the same thing as the integration. The [integration](/integrations/home-assistant) is required to integrate Frigate into Home Assistant, whether you are running Frigate as a standalone Docker container or as a Home Assistant App.
:::tip
If you already have Frigate installed as a Home Assistant App, check out the [getting started guide](../guides/getting_started.md#configuring-frigate) to configure Frigate.
If you already have Frigate installed as a Home Assistant App, check out the [getting started guide](../guides/getting_started#configuring-frigate) to configure Frigate.
:::
@@ -289,7 +286,7 @@ The MemryX MX3 Accelerator is available in the M.2 2280 form factor (like an NVM
#### Installation
To get started with MX3 hardware setup for your system, refer to the [Hardware Setup Guide](https://developer.memryx.com/2p1/get_started/install_hardware.html).
To get started with MX3 hardware setup for your system, refer to the [Hardware Setup Guide](https://developer.memryx.com/get_started/hardware_setup.html).
Then follow these steps for installing the correct driver/runtime configuration:
@@ -298,12 +295,6 @@ Then follow these steps for installing the correct driver/runtime configuration:
3. Run the script with `./user_installation.sh`
4. **Restart your computer** to complete driver installation.
:::warning
For manual setup, use **MemryX SDK 2.1** only. Other SDK versions are not supported for this setup. See the [SDK 2.1 documentation](https://developer.memryx.com/2p1/index.html)
:::
#### Setup
To set up Frigate, follow the default installation instructions, for example: `ghcr.io/blakeblackshear/frigate:stable`
@@ -477,16 +468,6 @@ Finally, configure [hardware object detection](/configuration/object_detectors#a
Running through Docker with Docker Compose is the recommended install method.
<Tabs>
<TabItem value="domestic" label="Docker Compose Generator" default>
Generate a Frigate Docker Compose configuration based on your hardware and requirements.
<DockerComposeGenerator/>
</TabItem>
<TabItem value="original" label="Example Docker Compose File">
```yaml
services:
frigate:
@@ -520,10 +501,6 @@ services:
environment:
FRIGATE_RTSP_PASSWORD: "password"
```
</TabItem>
</Tabs>
**Docker CLI**
If you can't use Docker Compose, you can run the container with something similar to this:
+1 -1
View File
@@ -192,7 +192,7 @@ cameras:
### Step 4: Configure detectors
By default, Frigate will use a single OpenVINO detector running on the CPU.
By default, Frigate will use a single CPU detector.
In many cases, the integrated graphics on Intel CPUs provides sufficient performance for typical Frigate setups. If you have an Intel processor, you can follow the configuration below.
@@ -39,10 +39,6 @@ This is a fork (with fixed errors and new features) of [original Double Take](ht
[Frigate telegram](https://github.com/OldTyT/frigate-telegram) makes it possible to send events from Frigate to Telegram. Events are sent as a message with a text description, video, and thumbnail.
## [kiosk-monitor](https://github.com/extremeshok/kiosk-monitor)
[kiosk-monitor](https://github.com/extremeshok/kiosk-monitor) is a Raspberry Pi watchdog that runs Chromium fullscreen on a Frigate dashboard (optionally with VLC on a second monitor for an RTSP camera stream), auto-restarts on frozen screens or unreachable URLs, and ships a Birdseye-aware Chromium helper that auto-sizes the grid to the display.
## [Periscope](https://github.com/maksz42/periscope)
[Periscope](https://github.com/maksz42/periscope) is a lightweight Android app that turns old devices into live viewers for Frigate. It works on Android 2.2 and above, including Android TV. It supports authentication and HTTPS.
+7 -14
View File
@@ -14,11 +14,9 @@
"@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",
@@ -5749,11 +5747,6 @@
"@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",
@@ -10904,9 +10897,9 @@
"license": "MIT"
},
"node_modules/express/node_modules/path-to-regexp": {
"version": "0.1.13",
"resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.13.tgz",
"integrity": "sha512-A/AGNMFN3c8bOlvV9RreMdrv7jsmF9XIfDeCd87+I8RNg6s78BhJxMu69NEMHBSJFxKidViTEdruRwEk/WIKqA==",
"version": "0.1.12",
"resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-0.1.12.tgz",
"integrity": "sha512-RA1GjUVMnvYFxuqovrEqZoxxW5NUZqbwKtYz/Tt7nXerk0LbLblQmrsgdeOxV5SFHf0UDggjS/bSeOZwt1pmEQ==",
"license": "MIT"
},
"node_modules/express/node_modules/range-parser": {
@@ -10971,9 +10964,9 @@
"license": "MIT"
},
"node_modules/fast-uri": {
"version": "3.1.2",
"resolved": "https://registry.npmjs.org/fast-uri/-/fast-uri-3.1.2.tgz",
"integrity": "sha512-rVjf7ArG3LTk+FS6Yw81V1DLuZl1bRbNrev6Tmd/9RaroeeRRJhAt7jg/6YFxbvAQXUCavSoZhPPj6oOx+5KjQ==",
"version": "3.1.0",
"resolved": "https://registry.npmjs.org/fast-uri/-/fast-uri-3.1.0.tgz",
"integrity": "sha512-iPeeDKJSWf4IEOasVVrknXpaBV0IApz/gp7S2bb7Z4Lljbl2MGJRqInZiUrQwV16cpzw/D3S5j5Julj/gT52AA==",
"funding": [
{
"type": "github",
@@ -12890,7 +12883,7 @@
},
"node_modules/js-yaml": {
"version": "4.1.1",
"resolved": "https://mirrors.tencent.com/npm/js-yaml/-/js-yaml-4.1.1.tgz",
"resolved": "https://registry.npmjs.org/js-yaml/-/js-yaml-4.1.1.tgz",
"integrity": "sha512-qQKT4zQxXl8lLwBtHMWwaTcGfFOZviOJet3Oy/xmGk2gZH677CJM9EvtfdSkgWcATZhj/55JZ0rmy3myCT5lsA==",
"license": "MIT",
"dependencies": {
+2 -5
View File
@@ -3,10 +3,9 @@
"version": "0.0.0",
"private": true,
"scripts": {
"build:config": "node scripts/build-config.mjs",
"docusaurus": "docusaurus",
"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",
"start": "npm run regen-docs && docusaurus start --host 0.0.0.0",
"build": "npm run regen-docs && docusaurus build",
"swizzle": "docusaurus swizzle",
"deploy": "docusaurus deploy",
"clear": "docusaurus clear",
@@ -24,11 +23,9 @@
"@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",
-64
View File
@@ -1,64 +0,0 @@
#!/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!");
@@ -1,108 +0,0 @@
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>
);
}
@@ -1,147 +0,0 @@
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>
);
}
@@ -1,60 +0,0 @@
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>
);
}
@@ -1,62 +0,0 @@
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} ${disabled ? styles.checkboxDisabled : ""}`}>
<input type="checkbox" checked={checked} onChange={onToggle} disabled={disabled} />
<span>{hw.label}</span>
</label>
{checked && hw.description && (
<div className={styles.hardwareDescription}>{renderDescription(hw.description)}</div>
)}
</div>
);
}
export default function HardwareOptions({ deviceId, hardwareEnabled, onToggle, isDisabled }: Props) {
return (
<div className={styles.formSection}>
<h4>Generic Hardware Devices</h4>
{deviceId !== "stable" && (
<p className={styles.helpText}>
Some options have been auto-configured based on your device type.
</p>
)}
<div className={styles.checkboxGrid}>
{hardwareOptions.map((hw) => {
const disabled = isDisabled(hw.id);
const checked = disabled ? false : !!hardwareEnabled[hw.id];
return (
<HardwareCheckbox key={hw.id} hw={hw} disabled={disabled} checked={checked} onToggle={() => onToggle(hw.id)} />
);
})}
</div>
</div>
);
}
@@ -1,64 +0,0 @@
import React from "react";
import styles from "../styles.module.css";
interface Props {
gpuCount: string;
gpuDeviceId: string;
gpuDeviceIdError: boolean;
onGpuCountChange: (value: string) => void;
onGpuDeviceIdChange: (value: string) => void;
}
export default function NvidiaGpuConfig({
gpuCount,
gpuDeviceId,
gpuDeviceIdError,
onGpuCountChange,
onGpuDeviceIdChange,
}: Props) {
const showDeviceId = gpuCount !== "";
return (
<div className={styles.nvidiaConfig}>
<div className={styles.formGroup}>
<label htmlFor="dcg-gpu-count" className={styles.label}>
GPU count:
</label>
<input
id="dcg-gpu-count"
type="text"
inputMode="numeric"
pattern="[0-9]*"
className={styles.input}
value={gpuCount}
placeholder="all"
onChange={(e) => onGpuCountChange(e.target.value.replace(/\D/g, ""))}
/>
</div>
{showDeviceId && (
<div className={styles.formGroup}>
<label htmlFor="dcg-gpu-device-id" className={styles.label}>
GPU device IDs (required, comma-separated):
</label>
<input
id="dcg-gpu-device-id"
type="text"
className={`${styles.input} ${gpuDeviceIdError ? styles.inputError : ""}`}
value={gpuDeviceId}
placeholder="0"
onChange={(e) => onGpuDeviceIdChange(e.target.value)}
/>
{gpuDeviceIdError ? (
<p className={styles.helpText}>
GPU device IDs are required when GPU count is a number
</p>
) : (
<p className={styles.helpText}>
Single GPU: 0 &nbsp;|&nbsp; Multiple GPUs: 0,1,2
</p>
)}
</div>
)}
</div>
);
}
@@ -1,122 +0,0 @@
import React, { useMemo } from "react";
import CodeInline from "@theme/CodeInline";
import styles from "../styles.module.css";
const AUTO_TIMEZONE_VALUE = "__auto__";
function getTimezoneList(): string[] {
if (typeof Intl !== "undefined") {
const intl = Intl as typeof Intl & {
supportedValuesOf?: (key: string) => string[];
};
const supported = intl.supportedValuesOf?.("timeZone");
if (supported && supported.length > 0) {
return [...supported].sort();
}
}
const fallback = Intl.DateTimeFormat().resolvedOptions().timeZone;
return fallback ? [fallback] : ["UTC"];
}
interface Props {
rtspPassword: string;
timezone: string;
shmSize: string;
shmSizeError: boolean;
onRtspPasswordChange: (value: string) => void;
onTimezoneChange: (value: string) => void;
onShmSizeChange: (value: string) => void;
}
export default function OtherOptions({
rtspPassword,
timezone,
shmSize,
shmSizeError,
onRtspPasswordChange,
onTimezoneChange,
onShmSizeChange,
}: Props) {
const timezones = useMemo(() => getTimezoneList(), []);
const systemTimezone =
Intl.DateTimeFormat().resolvedOptions().timeZone || "Etc/UTC";
const selectedValue = timezone || AUTO_TIMEZONE_VALUE;
return (
<div className={styles.formSection}>
<h4>Other Options</h4>
<div className={styles.formGrid}>
<div className={styles.formGroup}>
<label htmlFor="dcg-timezone" className={styles.label}>
Timezone:
</label>
<select
id="dcg-timezone"
className={`${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} ${shmSizeError ? styles.inputError : ""}`}
value={shmSize}
placeholder="512mb"
onChange={(e) => onShmSizeChange(e.target.value)}
/>
{shmSizeError ? (
<p className={styles.helpText}>
Invalid format. Use a number followed by a unit (e.g. 512mb, 1gb)
</p>
) : (
<p className={styles.helpText}>
See{" "}
<a href="/frigate/installation#calculating-required-shm-size">
calculating required SHM size
</a>{" "}
for the correct value.
</p>
)}
</div>
<div className={styles.formGroup}>
<label htmlFor="dcg-rtsp-password" className={styles.label}>
RTSP password:
</label>
<input
id="dcg-rtsp-password"
type="text"
className={styles.input}
value={rtspPassword}
placeholder="password"
onChange={(e) => onRtspPasswordChange(e.target.value)}
/>
<p className={styles.helpText}>
Optional. You can specify{" "}
<CodeInline>{"{FRIGATE_RTSP_PASSWORD}"}</CodeInline>{" "}
in the config file to reference camera stream passwords. This is NOT
the Frigate login password.
</p>
</div>
</div>
</div>
);
}
@@ -1,71 +0,0 @@
import React from "react";
import Admonition from "@theme/Admonition";
import { ports } from "../config";
import styles from "../styles.module.css";
interface Props {
portEnabled: Record<string, boolean>;
onTogglePort: (portId: string) => void;
}
function PortItem({
port,
enabled,
onToggle,
}: {
port: typeof ports[number];
enabled: boolean;
onToggle: () => void;
}) {
const showWarning = port.warningContent && (
port.warningWhen === "checked" ? enabled :
port.warningWhen === "unchecked" ? !enabled : enabled
);
return (
<div className={styles.hardwareItem}>
<label className={`${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>
);
}
@@ -1,66 +0,0 @@
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>
);
}
File diff suppressed because one or more lines are too long
@@ -1,12 +0,0 @@
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";
@@ -1,154 +0,0 @@
/**
* 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";
}
@@ -1,250 +0,0 @@
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");
}
@@ -1,195 +0,0 @@
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,
};
}
@@ -1 +0,0 @@
export { default } from "./DockerComposeGenerator";
@@ -1,381 +0,0 @@
/* ===================================================================
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);
}
+2 -13
View File
@@ -5997,10 +5997,7 @@ paths:
tags:
- App
summary: Start debug replay
description:
Start a debug replay session from camera recordings. Returns
immediately while clip generation runs as a background job; subscribe
to the 'debug_replay' job_state WS topic to track progress.
description: Start a debug replay session from camera recordings.
operationId: start_debug_replay_debug_replay_start_post
requestBody:
required: true
@@ -6009,16 +6006,12 @@ paths:
schema:
$ref: "#/components/schemas/DebugReplayStartBody"
responses:
"202":
"200":
description: Successful Response
content:
application/json:
schema:
$ref: "#/components/schemas/DebugReplayStartResponse"
"400":
description: Invalid camera, time range, or no recordings
"409":
description: A replay session is already active
"422":
description: Validation Error
content:
@@ -6279,14 +6272,10 @@ components:
replay_camera:
type: string
title: Replay Camera
job_id:
type: string
title: Job Id
type: object
required:
- success
- replay_camera
- job_id
title: DebugReplayStartResponse
description: Response for starting a debug replay session.
DebugReplayStatusResponse:
+1 -44
View File
@@ -146,13 +146,8 @@ def config(request: Request):
for name, detector in config_obj.detectors.items()
}
# remove environment_vars for non-admin users
if request.headers.get("remote-role") != "admin":
config.pop("environment_vars", None)
# remove mqtt credentials
# remove the mqtt password
config["mqtt"].pop("password", None)
config["mqtt"].pop("user", None)
# remove the proxy secret
config["proxy"].pop("auth_secret", None)
@@ -499,40 +494,6 @@ def config_save(save_option: str, body: Any = Body(media_type="text/plain")):
)
def _restore_masked_camera_paths(config_data: dict, config: FrigateConfig) -> None:
"""Substitute incoming `*:*` masked credentials with the in-memory ones.
The /config response masks ffmpeg input credentials, so the settings UI
sends the masked path back when sibling fields (e.g. hwaccel_args) are
edited. Without this we'd write `rtsp://*:*@host` into YAML and lose
the real credentials. Mutates `config_data` in place.
"""
cameras = config_data.get("cameras")
if not isinstance(cameras, dict):
return
for camera_name, camera_data in cameras.items():
if not isinstance(camera_data, dict):
continue
inputs = camera_data.get("ffmpeg", {}).get("inputs")
if not isinstance(inputs, list):
continue
existing = config.cameras.get(camera_name)
if existing is None:
continue
existing_paths = [inp.path for inp in existing.ffmpeg.inputs]
for index, input_obj in enumerate(inputs):
if not isinstance(input_obj, dict):
continue
path = input_obj.get("path")
if not isinstance(path, str):
continue
if ("://*:*@" in path or "user=*&password=*" in path) and index < len(
existing_paths
):
input_obj["path"] = existing_paths[index]
def _config_set_in_memory(request: Request, body: AppConfigSetBody) -> JSONResponse:
"""Apply config changes in-memory only, without writing to YAML.
@@ -543,7 +504,6 @@ def _config_set_in_memory(request: Request, body: AppConfigSetBody) -> JSONRespo
try:
updates = {}
if body.config_data:
_restore_masked_camera_paths(body.config_data, request.app.frigate_config)
updates = flatten_config_data(body.config_data)
updates = {k: ("" if v is None else v) for k, v in updates.items()}
@@ -650,9 +610,6 @@ def config_set(request: Request, body: AppConfigSetBody):
if query_string:
updates = process_config_query_string(query_string)
elif body.config_data:
_restore_masked_camera_paths(
body.config_data, request.app.frigate_config
)
updates = flatten_config_data(body.config_data)
# Convert None values to empty strings for deletion (e.g., when deleting masks)
updates = {k: ("" if v is None else v) for k, v in updates.items()}
+10 -29
View File
@@ -26,7 +26,6 @@ from frigate.api.defs.request.app_body import (
AppPutRoleBody,
)
from frigate.api.defs.tags import Tags
from frigate.api.media_auth import check_camera_access, deny_response_for_media_uri
from frigate.config import AuthConfig, NetworkingConfig, ProxyConfig
from frigate.const import CONFIG_DIR, JWT_SECRET_ENV_VAR, PASSWORD_HASH_ALGORITHM
from frigate.models import User
@@ -634,9 +633,6 @@ def auth(request: Request):
logger.debug("X-Proxy-Secret header does not match configured secret value")
return fail_response
original_url = request.headers.get("x-original-url")
frigate_config = request.app.frigate_config
# if auth is disabled, just apply the proxy header map and return success
if not auth_config.enabled:
# pass the user header value from the upstream proxy if a mapping is specified
@@ -653,11 +649,6 @@ def auth(request: Request):
role = resolve_role(request.headers, proxy_config, config_roles_set)
success_response.headers["remote-role"] = role
deny_status = deny_response_for_media_uri(original_url, role, frigate_config)
if deny_status is not None:
return Response("", status_code=deny_status)
return success_response
# now apply authentication
@@ -752,11 +743,6 @@ def auth(request: Request):
success_response.headers["remote-user"] = user
success_response.headers["remote-role"] = role
deny_status = deny_response_for_media_uri(original_url, role, frigate_config)
if deny_status is not None:
return Response("", status_code=deny_status)
return success_response
except Exception as e:
logger.error(f"Error parsing jwt: {e}")
@@ -826,11 +812,6 @@ limiter = Limiter(key_func=get_remote_addr)
)
@limiter.limit(limit_value=rateLimiter.get_limit)
def login(request: Request, body: AppPostLoginBody):
if not request.app.frigate_config.auth.enabled:
return JSONResponse(
content={"message": "Authentication is disabled"}, status_code=404
)
JWT_COOKIE_NAME = request.app.frigate_config.auth.cookie_name
JWT_COOKIE_SECURE = request.app.frigate_config.auth.cookie_secure
JWT_SESSION_LENGTH = request.app.frigate_config.auth.session_length
@@ -1083,19 +1064,19 @@ async def require_camera_access(
raise HTTPException(status_code=current_user.status_code, detail=detail)
role = current_user["role"]
frigate_config = request.app.frigate_config
all_camera_names = set(request.app.frigate_config.cameras.keys())
roles_dict = request.app.frigate_config.auth.roles
allowed_cameras = User.get_allowed_cameras(role, roles_dict, all_camera_names)
if check_camera_access(role, camera_name, frigate_config):
# Admin or full access bypasses
if role == "admin" or not roles_dict.get(role):
return
all_camera_names = set(frigate_config.cameras.keys())
allowed_cameras = User.get_allowed_cameras(
role, frigate_config.auth.roles, all_camera_names
)
raise HTTPException(
status_code=403,
detail=f"Access denied to camera '{camera_name}'. Allowed: {allowed_cameras}",
)
if camera_name not in allowed_cameras:
raise HTTPException(
status_code=403,
detail=f"Access denied to camera '{camera_name}'. Allowed: {allowed_cameras}",
)
def _get_stream_owner_cameras(request: Request, stream_name: str) -> set[str]:
+3 -63
View File
@@ -36,8 +36,6 @@ from frigate.api.defs.response.chat_response import (
)
from frigate.api.defs.tags import Tags
from frigate.api.event import events
from frigate.config import FrigateConfig
from frigate.config.ui import UnitSystemEnum
from frigate.genai.utils import build_assistant_message_for_conversation
from frigate.jobs.vlm_watch import (
get_vlm_watch_job,
@@ -403,38 +401,9 @@ def get_tools() -> JSONResponse:
return JSONResponse(content={"tools": tools})
def _resolve_zones(
zones: List[str],
config: FrigateConfig,
target_cameras: List[str],
) -> List[str]:
"""Map zone names to their canonical config keys, case-insensitively.
LLMs frequently echo a user's casing ("Front Yard") instead of the
configured key ("front_yard"). The downstream zone filter is a SQLite GLOB
over the JSON-encoded zones column, which is case-sensitive — so an
unnormalized name silently returns zero matches. Build a lookup over the
relevant cameras' configured zones and substitute when we find a match;
unknown names pass through so behavior matches what the model asked for.
"""
if not zones:
return zones
lookup: Dict[str, str] = {}
for camera_id in target_cameras:
camera_config = config.cameras.get(camera_id)
if camera_config is None:
continue
for zone_name in camera_config.zones.keys():
lookup.setdefault(zone_name.lower(), zone_name)
return [lookup.get(z.lower(), z) for z in zones]
async def _execute_search_objects(
arguments: Dict[str, Any],
allowed_cameras: List[str],
config: FrigateConfig,
) -> JSONResponse:
"""
Execute the search_objects tool.
@@ -468,11 +437,6 @@ async def _execute_search_objects(
# Convert zones array to comma-separated string if provided
zones = arguments.get("zones")
if isinstance(zones, list):
camera_arg = arguments.get("camera")
target_cameras = (
[camera_arg] if camera_arg and camera_arg != "all" else allowed_cameras
)
zones = _resolve_zones(zones, config, target_cameras)
zones = ",".join(zones)
elif zones is None:
zones = "all"
@@ -564,11 +528,6 @@ async def _execute_find_similar_objects(
sub_labels = arguments.get("sub_labels")
zones = arguments.get("zones")
if zones:
zones = _resolve_zones(
zones, request.app.frigate_config, cameras or list(allowed_cameras)
)
similarity_mode = arguments.get("similarity_mode", "fused")
if similarity_mode not in ("visual", "semantic", "fused"):
similarity_mode = "fused"
@@ -696,9 +655,7 @@ async def execute_tool(
logger.debug(f"Executing tool: {tool_name} with arguments: {arguments}")
if tool_name == "search_objects":
return await _execute_search_objects(
arguments, allowed_cameras, request.app.frigate_config
)
return await _execute_search_objects(arguments, allowed_cameras)
if tool_name == "find_similar_objects":
result = await _execute_find_similar_objects(
@@ -878,9 +835,7 @@ async def _execute_tool_internal(
This is used by the chat completion endpoint to execute tools.
"""
if tool_name == "search_objects":
response = await _execute_search_objects(
arguments, allowed_cameras, request.app.frigate_config
)
response = await _execute_search_objects(arguments, allowed_cameras)
try:
if hasattr(response, "body"):
body_str = response.body.decode("utf-8")
@@ -944,9 +899,6 @@ async def _execute_start_camera_watch(
await require_camera_access(camera, request=request)
if zones:
zones = _resolve_zones(zones, config, [camera])
genai_manager = request.app.genai_manager
chat_client = genai_manager.chat_client
if chat_client is None or not chat_client.supports_vision:
@@ -1302,7 +1254,6 @@ async def chat_completion(
cameras_info = []
config = request.app.frigate_config
has_speed_zone = False
for camera_id in allowed_cameras:
if camera_id not in config.cameras:
continue
@@ -1313,10 +1264,6 @@ async def chat_completion(
else camera_id.replace("_", " ").title()
)
zone_names = list(camera_config.zones.keys())
if not has_speed_zone:
has_speed_zone = any(
zone.distances for zone in camera_config.zones.values()
)
if zone_names:
cameras_info.append(
f" - {friendly_name} (ID: {camera_id}, zones: {', '.join(zone_names)})"
@@ -1332,13 +1279,6 @@ async def chat_completion(
+ "\n\nWhen users refer to cameras by their friendly name (e.g., 'Back Deck Camera'), use the corresponding camera ID (e.g., 'back_deck_cam') in tool calls."
)
speed_units_section = ""
if has_speed_zone:
speed_unit = (
"mph" if config.ui.unit_system == UnitSystemEnum.imperial else "km/h"
)
speed_units_section = f"\n\nReport object speeds to the user in {speed_unit}."
system_prompt = f"""You are a helpful assistant for Frigate, a security camera NVR system. You help users answer questions about their cameras, detected objects, and events.
Current server local date and time: {current_date_str} at {current_time_str}
@@ -1350,7 +1290,7 @@ When users ask about "today", "yesterday", "this week", etc., use the current da
When searching for objects or events, use ISO 8601 format for dates (e.g., {current_date_str}T00:00:00Z for the start of today).
Always be accurate with time calculations based on the current date provided.
When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{cameras_section}{speed_units_section}"""
When a user refers to a specific object they have seen or describe with identifying details ("that green car", "the person in the red jacket", "a package left today"), prefer the find_similar_objects tool over search_objects. Use search_objects first only to locate the anchor event, then pass its id to find_similar_objects. For generic queries like "show me all cars today", keep using search_objects. If a user message begins with [attached_event:<id>], treat that event id as the anchor for any similarity or "tell me more" request in the same message and call find_similar_objects with that id.{cameras_section}"""
conversation.append(
{
+30 -44
View File
@@ -10,7 +10,6 @@ from pydantic import BaseModel, Field
from frigate.api.auth import require_role
from frigate.api.defs.tags import Tags
from frigate.jobs.debug_replay import start_debug_replay_job
logger = logging.getLogger(__name__)
@@ -30,17 +29,10 @@ class DebugReplayStartResponse(BaseModel):
success: bool
replay_camera: str
job_id: str
class DebugReplayStatusResponse(BaseModel):
"""Response for debug replay status.
Returns only session-presence fields. Startup progress and error
details flow through the job_state WebSocket topic via the
debug_replay job (see frigate.jobs.debug_replay); the
Replay page subscribes there with useJobStatus("debug_replay").
"""
"""Response for debug replay status."""
active: bool
replay_camera: str | None = None
@@ -59,32 +51,15 @@ class DebugReplayStopResponse(BaseModel):
@router.post(
"/debug_replay/start",
response_model=DebugReplayStartResponse,
status_code=202,
responses={
400: {"description": "Invalid camera, time range, or no recordings"},
409: {"description": "A replay session is already active"},
},
dependencies=[Depends(require_role(["admin"]))],
summary="Start debug replay",
description="Start a debug replay session from camera recordings. Returns "
"immediately while clip generation runs as a background job; subscribe "
"to the 'debug_replay' job_state WS topic to track progress.",
description="Start a debug replay session from camera recordings.",
)
async def start_debug_replay(request: Request, body: DebugReplayStartBody):
"""Start a debug replay session asynchronously."""
"""Start a debug replay session."""
replay_manager = request.app.replay_manager
try:
job_id = await asyncio.to_thread(
start_debug_replay_job,
source_camera=body.camera,
start_ts=body.start_time,
end_ts=body.end_time,
frigate_config=request.app.frigate_config,
config_publisher=request.app.config_publisher,
replay_manager=replay_manager,
)
except RuntimeError:
if replay_manager.active:
return JSONResponse(
content={
"success": False,
@@ -92,23 +67,38 @@ async def start_debug_replay(request: Request, body: DebugReplayStartBody):
},
status_code=409,
)
try:
replay_camera = await asyncio.to_thread(
replay_manager.start,
source_camera=body.camera,
start_ts=body.start_time,
end_ts=body.end_time,
frigate_config=request.app.frigate_config,
config_publisher=request.app.config_publisher,
)
except ValueError:
logger.exception("Rejected debug replay start request")
logger.exception("Invalid parameters for debug replay start request")
return JSONResponse(
content={
"success": False,
"message": "Invalid debug replay parameters",
"message": "Invalid debug replay request parameters",
},
status_code=400,
)
except RuntimeError:
logger.exception("Error while starting debug replay session")
return JSONResponse(
content={
"success": False,
"message": "An internal error occurred while starting debug replay",
},
status_code=500,
)
return JSONResponse(
content={
"success": True,
"replay_camera": replay_manager.replay_camera_name,
"job_id": job_id,
},
status_code=202,
return DebugReplayStartResponse(
success=True,
replay_camera=replay_camera,
)
@@ -128,16 +118,12 @@ def get_debug_replay_status(request: Request):
if replay_manager.active and replay_camera:
frame_processor = request.app.detected_frames_processor
frame = (
frame_processor.get_current_frame(replay_camera)
if frame_processor is not None
else None
)
frame = frame_processor.get_current_frame(replay_camera)
if frame is not None:
frame_time = frame_processor.get_current_frame_time(replay_camera)
camera_config = request.app.frigate_config.cameras.get(replay_camera)
retry_interval = 10.0
retry_interval = 10
if camera_config is not None:
retry_interval = float(camera_config.ffmpeg.retry_interval or 10)
-9
View File
@@ -754,15 +754,6 @@ def events_search(
status_code=404,
)
if search_event.camera not in allowed_cameras:
return JSONResponse(
content={
"success": False,
"message": "Event not found",
},
status_code=404,
)
thumb_result = context.search_thumbnail(search_event)
thumb_ids = {result[0]: result[1] for result in thumb_result}
search_results = {
+3 -135
View File
@@ -5,15 +5,13 @@ import logging
import random
import string
import time
import zipfile
from collections import deque
from pathlib import Path
from typing import Iterator, List, Optional
from typing import List, Optional
import psutil
from fastapi import APIRouter, Depends, Query, Request
from fastapi.responses import JSONResponse, StreamingResponse
from pathvalidate import sanitize_filename, sanitize_filepath
from fastapi.responses import JSONResponse
from pathvalidate import sanitize_filepath
from peewee import DoesNotExist
from playhouse.shortcuts import model_to_dict
@@ -363,136 +361,6 @@ def get_export_case(case_id: str):
)
_ZIP_STREAM_CHUNK_SIZE = 1024 * 1024 # 1 MiB
class _StreamingZipBuffer:
"""File-like sink for ZipFile that exposes written bytes via drain().
ZipFile writes synchronously into this buffer; the generator drains the
queue between writes so StreamingResponse can yield bytes without
materializing the whole archive in memory.
"""
def __init__(self) -> None:
self._queue: deque[bytes] = deque()
self._offset = 0
def write(self, data: bytes) -> int:
if data:
self._queue.append(bytes(data))
self._offset += len(data)
return len(data)
def tell(self) -> int:
return self._offset
def flush(self) -> None:
pass
def drain(self) -> Iterator[bytes]:
while self._queue:
yield self._queue.popleft()
def _unique_archive_name(export: Export, used: set[str]) -> str:
base = sanitize_filename(export.name) if export.name else None
if not base:
base = f"{export.camera}_{int(datetime.datetime.timestamp(export.date))}"
candidate = f"{base}.mp4"
counter = 1
while candidate in used:
candidate = f"{base}_{counter}.mp4"
counter += 1
used.add(candidate)
return candidate
def _stream_case_archive(exports: List[Export]) -> Iterator[bytes]:
"""Yield bytes of a zip archive built from the given exports' mp4 files."""
buffer = _StreamingZipBuffer()
used_names: set[str] = set()
# ZIP_STORED: mp4 is already compressed, recompressing wastes CPU for ~0% size win.
with zipfile.ZipFile(
buffer,
mode="w",
compression=zipfile.ZIP_STORED,
allowZip64=True,
) as archive:
for export in exports:
source = Path(export.video_path)
if not source.exists():
continue
arcname = _unique_archive_name(export, used_names)
with (
archive.open(arcname, mode="w", force_zip64=True) as entry,
source.open("rb") as src,
):
while True:
chunk = src.read(_ZIP_STREAM_CHUNK_SIZE)
if not chunk:
break
entry.write(chunk)
yield from buffer.drain()
yield from buffer.drain()
yield from buffer.drain()
@router.get(
"/cases/{case_id}/download",
dependencies=[Depends(allow_any_authenticated())],
summary="Download export case as zip",
description="Streams a zip archive containing every completed export's mp4 for the given case.",
)
def download_export_case(
case_id: str,
allowed_cameras: List[str] = Depends(get_allowed_cameras_for_filter),
):
try:
case = ExportCase.get(ExportCase.id == case_id)
except DoesNotExist:
return JSONResponse(
content={"success": False, "message": "Export case not found"},
status_code=404,
)
exports = list(
Export.select()
.where(
Export.export_case == case_id,
~Export.in_progress,
Export.camera << allowed_cameras,
)
.order_by(Export.date.asc())
)
if not exports:
return JSONResponse(
content={"success": False, "message": "No exports available to download."},
status_code=404,
)
archive_base = sanitize_filename(case.name) if case.name else ""
if not archive_base:
archive_base = case_id
return StreamingResponse(
_stream_case_archive(exports),
media_type="application/zip",
headers={
"Content-Disposition": f'attachment; filename="{archive_base}.zip"',
},
)
@router.patch(
"/cases/{case_id}",
response_model=GenericResponse,
+13 -21
View File
@@ -174,10 +174,12 @@ async def latest_frame(
}
quality_params = get_image_quality_params(extension.value, params.quality)
camera_config = request.app.frigate_config.cameras.get(camera_name)
if camera_config is not None:
if camera_name in request.app.frigate_config.cameras:
frame = frame_processor.get_current_frame(camera_name, draw_options)
retry_interval = float(camera_config.ffmpeg.retry_interval or 10)
retry_interval = float(
request.app.frigate_config.cameras.get(camera_name).ffmpeg.retry_interval
or 10
)
is_offline = False
if frame is None or datetime.now().timestamp() > (
@@ -1366,17 +1368,12 @@ def preview_gif(
file_start = f"preview_{camera_name}-"
start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
camera_files = [
entry.name
for entry in os.scandir(preview_dir)
if entry.name.startswith(file_start)
]
camera_files.sort()
selected_previews = []
for file in camera_files:
for file in sorted(os.listdir(preview_dir)):
if not file.startswith(file_start):
continue
if file < start_file:
continue
@@ -1553,17 +1550,12 @@ def preview_mp4(
file_start = f"preview_{camera_name}-"
start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
camera_files = [
entry.name
for entry in os.scandir(preview_dir)
if entry.name.startswith(file_start)
]
camera_files.sort()
selected_previews = []
for file in camera_files:
for file in sorted(os.listdir(preview_dir)):
if not file.startswith(file_start):
continue
if file < start_file:
continue
-291
View File
@@ -1,291 +0,0 @@
"""URI-aware authorization for nginx-served static media.
The `/auth` endpoint (used as nginx `auth_request` target) calls into this
module to classify the requested URI from the `X-Original-URL` header and, for
camera-scoped resources, decide whether the current role may access them.
Without this, `auth_request` only verifies the JWT every authenticated user
could read clips, recordings, and exports for *any* camera, bypassing the
per-camera authorization the regular API enforces via `require_camera_access`.
"""
from __future__ import annotations
import logging
import os
from enum import Enum
from typing import Optional
from urllib.parse import unquote, urlparse
from peewee import DoesNotExist
from frigate.config import FrigateConfig
from frigate.const import EXPORT_DIR
from frigate.models import Export, User
logger = logging.getLogger(__name__)
class MediaAuthResolution(str, Enum):
"""Classification of an `X-Original-URL` path for media-auth purposes."""
CAMERA = "camera"
ADMIN_ONLY = "admin_only"
LISTING_MULTI_CAMERA = "listing_multi_camera"
LISTING_NEUTRAL = "listing_neutral"
# Under a recognized media root (/clips, /recordings, /exports) but
# unclassifiable (unknown subtree, no matching DB row, DB error).
# Restricted users are denied; admins/full-access roles are allowed
# (nginx will likely return 404 if the file genuinely doesn't exist).
UNRESOLVED_MEDIA = "unresolved_media"
# Not a media URI at all (e.g. /api/events, /login).
UNKNOWN = "unknown"
def extract_path(original_url: Optional[str]) -> Optional[str]:
"""Return the decoded path component of nginx's `X-Original-URL` header.
nginx forwards the *raw* request URI (with `..` segments intact) via
`$request_uri`. nginx normalizes the path before serving the file, so a
request like `/recordings/.../allowed_cam/../forbidden_cam/file.mp4`
would (1) parse as the allowed camera in our auth check, (2) be served
as the forbidden camera by nginx. To close the bypass we reject any URI
whose path contains `.` or `..` segments outright.
"""
if not original_url:
return None
parsed = urlparse(original_url)
raw_path = parsed.path or original_url
decoded = unquote(raw_path)
if not decoded:
return None
if not decoded.startswith("/"):
decoded = "/" + decoded
segments = decoded.split("/")
if ".." in segments or "." in segments:
return None
return decoded
def resolve_media_uri(
uri: str, frigate_config: Optional[FrigateConfig] = None
) -> tuple[MediaAuthResolution, Optional[str]]:
"""Classify a URI and return the owning camera if applicable.
`frigate_config` is used to disambiguate clip/review filenames whose
camera name contains hyphens by matching against the longest configured
camera-name prefix.
"""
if not uri:
return MediaAuthResolution.UNKNOWN, None
parts = [p for p in uri.split("/") if p]
if not parts:
return MediaAuthResolution.UNKNOWN, None
root = parts[0]
if root == "recordings":
return _resolve_recording(parts)
if root == "clips":
return _resolve_clip(parts, frigate_config)
if root == "exports":
return _resolve_export(parts)
return MediaAuthResolution.UNKNOWN, None
def _resolve_recording(
parts: list[str],
) -> tuple[MediaAuthResolution, Optional[str]]:
# /recordings → neutral
# /recordings/{date} → neutral
# /recordings/{date}/{hour} → multi-camera listing
# /recordings/{date}/{hour}/{cam}/... → camera
if len(parts) <= 2:
return MediaAuthResolution.LISTING_NEUTRAL, None
if len(parts) == 3:
return MediaAuthResolution.LISTING_MULTI_CAMERA, None
return MediaAuthResolution.CAMERA, parts[3]
def _resolve_clip(
parts: list[str], frigate_config: Optional[FrigateConfig]
) -> tuple[MediaAuthResolution, Optional[str]]:
# /clips → multi-camera listing
# /clips/thumbs/{cam}/... → camera
# /clips/previews/{cam}/... → camera
# /clips/review/thumb-{cam}-{review_id}.webp → camera (parsed)
# /clips/faces/... → admin-only
# /clips/genai-requests/... → admin-only
# /clips/preview_restart_cache/... → admin-only
# /clips/{model}/train|dataset/... → admin-only
# /clips/{cam}-{event_id}[-clean].{ext} → camera (parsed)
# other /clips/{subdir}/... → unresolved (deny restricted)
if len(parts) == 1:
return MediaAuthResolution.LISTING_MULTI_CAMERA, None
second = parts[1]
if second in ("thumbs", "previews"):
if len(parts) == 2:
return MediaAuthResolution.LISTING_MULTI_CAMERA, None
return MediaAuthResolution.CAMERA, parts[2]
if second == "review":
if len(parts) == 2:
return MediaAuthResolution.LISTING_MULTI_CAMERA, None
camera = _camera_from_thumb_filename(parts[2], frigate_config)
if camera:
return MediaAuthResolution.CAMERA, camera
return MediaAuthResolution.UNRESOLVED_MEDIA, None
if second in ("faces", "genai-requests", "preview_restart_cache"):
return MediaAuthResolution.ADMIN_ONLY, None
if len(parts) >= 3 and parts[2] in ("train", "dataset"):
return MediaAuthResolution.ADMIN_ONLY, None
if len(parts) == 2:
camera = _camera_from_clip_filename(second, frigate_config)
if camera:
return MediaAuthResolution.CAMERA, camera
return MediaAuthResolution.UNRESOLVED_MEDIA, None
return MediaAuthResolution.UNRESOLVED_MEDIA, None
def _longest_prefix_camera(
stem: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
if frigate_config is None:
return None
for cam in sorted(frigate_config.cameras.keys(), key=len, reverse=True):
if stem.startswith(cam + "-"):
return cam
return None
def _camera_from_clip_filename(
filename: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
"""Match a flat clip filename `{camera}-{event_id}[-clean].{ext}` against
configured camera names. Longest-prefix wins so camera names containing
hyphens (e.g. `front-door`) resolve correctly.
"""
dot = filename.rfind(".")
stem = filename[:dot] if dot > 0 else filename
return _longest_prefix_camera(stem, frigate_config)
def _camera_from_thumb_filename(
filename: str, frigate_config: Optional[FrigateConfig]
) -> Optional[str]:
"""Match a review thumbnail filename `thumb-{camera}-{review_id}.webp`."""
if not filename.startswith("thumb-"):
return None
dot = filename.rfind(".")
stem = filename[len("thumb-") : dot] if dot > 0 else filename[len("thumb-") :]
return _longest_prefix_camera(stem, frigate_config)
def _resolve_export(
parts: list[str],
) -> tuple[MediaAuthResolution, Optional[str]]:
# /exports → multi-camera listing
# /exports/{filename}.mp4 → camera (DB lookup by exact path)
if len(parts) == 1:
return MediaAuthResolution.LISTING_MULTI_CAMERA, None
if len(parts) != 2:
return MediaAuthResolution.UNRESOLVED_MEDIA, None
filename = parts[1]
full_path = os.path.join(EXPORT_DIR, filename)
try:
export = Export.get(Export.video_path == full_path)
return MediaAuthResolution.CAMERA, export.camera
except DoesNotExist:
return MediaAuthResolution.UNRESOLVED_MEDIA, None
except Exception as e:
logger.warning("Export DB lookup failed for %s: %s", filename, e)
return MediaAuthResolution.UNRESOLVED_MEDIA, None
def check_camera_access(role: str, camera: str, frigate_config: FrigateConfig) -> bool:
"""Return True iff `role` may access `camera`.
Mirrors the gating logic in `require_camera_access`: admin and any role
without a non-empty allow-list bypass the check.
"""
if role == "admin":
return True
roles_dict = frigate_config.auth.roles
if not roles_dict.get(role):
return True
all_camera_names = set(frigate_config.cameras.keys())
allowed = User.get_allowed_cameras(role, roles_dict, all_camera_names)
return camera in allowed
def is_role_restricted(role: str, frigate_config: FrigateConfig) -> bool:
"""True if `role` has a non-empty allow-list (i.e. not full-access)."""
if role == "admin":
return False
return bool(frigate_config.auth.roles.get(role))
def deny_response_for_media_uri(
original_url: Optional[str], role: Optional[str], frigate_config: FrigateConfig
) -> Optional[int]:
"""Decide whether the current role should be blocked from `original_url`.
Returns an HTTP status code (403) when access should be denied, or `None`
when the request is allowed.
"""
if not original_url:
return None
path = extract_path(original_url)
# `extract_path` returns None for URIs containing `.` or `..` segments.
# For media-root URIs that's a traversal attempt — deny outright. For
# non-media URIs, pass through (nginx / the backend handle them).
if path is None:
raw = urlparse(original_url).path or original_url
decoded = unquote(raw)
first = decoded.lstrip("/").split("/", 1)[0] if decoded else ""
if first in ("clips", "recordings", "exports"):
return 403
return None
resolution, camera = resolve_media_uri(path, frigate_config)
if resolution == MediaAuthResolution.UNKNOWN:
return None
if not role or role == "admin":
return None
if not is_role_restricted(role, frigate_config):
return None
if resolution == MediaAuthResolution.LISTING_NEUTRAL:
return None
if resolution in (
MediaAuthResolution.LISTING_MULTI_CAMERA,
MediaAuthResolution.ADMIN_ONLY,
MediaAuthResolution.UNRESOLVED_MEDIA,
):
return 403
if resolution == MediaAuthResolution.CAMERA:
if camera and check_camera_access(role, camera, frigate_config):
return None
return 403
return 403
+4 -9
View File
@@ -148,17 +148,12 @@ def get_preview_frames_from_cache(camera_name: str, start_ts: float, end_ts: flo
file_start = f"preview_{camera_name}-"
start_file = f"{file_start}{start_ts}.{PREVIEW_FRAME_TYPE}"
end_file = f"{file_start}{end_ts}.{PREVIEW_FRAME_TYPE}"
camera_files = [
entry.name
for entry in os.scandir(preview_dir)
if entry.name.startswith(file_start)
]
camera_files.sort()
selected_previews = []
for file in camera_files:
for file in sorted(os.listdir(preview_dir)):
if not file.startswith(file_start):
continue
if file < start_file:
continue
+1 -1
View File
@@ -35,7 +35,7 @@ logger = logging.getLogger(__name__)
router = APIRouter(tags=[Tags.recordings])
@router.get("/recordings/storage", dependencies=[Depends(require_role(["admin"]))])
@router.get("/recordings/storage", dependencies=[Depends(allow_any_authenticated())])
def get_recordings_storage_usage(request: Request):
recording_stats = request.app.stats_emitter.get_latest_stats()["service"][
"storage"
+12 -5
View File
@@ -428,11 +428,18 @@ class FrigateApp:
self.camera_maintainer.start()
def start_audio_processor(self) -> None:
self.audio_process = AudioProcessor(
self.config, self.camera_metrics, self.stop_event
)
self.audio_process.start()
self.processes["audio_detector"] = self.audio_process.pid or 0
audio_cameras = [
c
for c in self.config.cameras.values()
if c.enabled and c.audio.enabled_in_config
]
if audio_cameras:
self.audio_process = AudioProcessor(
self.config, audio_cameras, self.camera_metrics, self.stop_event
)
self.audio_process.start()
self.processes["audio_detector"] = self.audio_process.pid or 0
def start_timeline_processor(self) -> None:
self.timeline_processor = TimelineProcessor(
+1 -12
View File
@@ -429,10 +429,7 @@ class WebPushClient(Communicator):
else:
title = base_title
if payload["after"]["data"]["metadata"].get("shortSummary"):
message = payload["after"]["data"]["metadata"]["shortSummary"]
else:
message = f"Detected on {camera_name}"
message = payload["after"]["data"]["metadata"]["shortSummary"]
else:
zone_names = payload["after"]["data"]["zones"]
formatted_zone_names = []
@@ -552,14 +549,6 @@ class WebPushClient(Communicator):
logger.debug(f"Sending camera monitoring push notification for {camera_name}")
for user in self.web_pushers:
if not self._user_has_camera_access(user, camera):
logger.debug(
"Skipping notification for user %s - no access to camera %s",
user,
camera,
)
continue
self.send_push_notification(
user=user,
payload=payload,
+3 -99
View File
@@ -17,90 +17,9 @@ from ws4py.websocket import WebSocket as WebSocket_
from frigate.comms.base_communicator import Communicator
from frigate.config import FrigateConfig
from frigate.const import (
CLEAR_ONGOING_REVIEW_SEGMENTS,
EXPIRE_AUDIO_ACTIVITY,
INSERT_MANY_RECORDINGS,
INSERT_PREVIEW,
NOTIFICATION_TEST,
REQUEST_REGION_GRID,
UPDATE_AUDIO_ACTIVITY,
UPDATE_AUDIO_TRANSCRIPTION_STATE,
UPDATE_BIRDSEYE_LAYOUT,
UPDATE_CAMERA_ACTIVITY,
UPDATE_EMBEDDINGS_REINDEX_PROGRESS,
UPDATE_EVENT_DESCRIPTION,
UPDATE_MODEL_STATE,
UPDATE_REVIEW_DESCRIPTION,
UPSERT_REVIEW_SEGMENT,
)
logger = logging.getLogger(__name__)
# Internal IPC topics — NEVER allowed from WebSocket, regardless of role
_WS_BLOCKED_TOPICS = frozenset(
{
INSERT_MANY_RECORDINGS,
INSERT_PREVIEW,
REQUEST_REGION_GRID,
UPSERT_REVIEW_SEGMENT,
CLEAR_ONGOING_REVIEW_SEGMENTS,
UPDATE_CAMERA_ACTIVITY,
UPDATE_AUDIO_ACTIVITY,
EXPIRE_AUDIO_ACTIVITY,
UPDATE_EVENT_DESCRIPTION,
UPDATE_REVIEW_DESCRIPTION,
UPDATE_MODEL_STATE,
UPDATE_EMBEDDINGS_REINDEX_PROGRESS,
UPDATE_BIRDSEYE_LAYOUT,
UPDATE_AUDIO_TRANSCRIPTION_STATE,
NOTIFICATION_TEST,
}
)
# Read-only topics any authenticated user (including viewer) can send
_WS_VIEWER_TOPICS = frozenset(
{
"onConnect",
"modelState",
"audioTranscriptionState",
"birdseyeLayout",
"embeddingsReindexProgress",
}
)
def _check_ws_authorization(
topic: str,
role_header: str | None,
separator: str,
) -> bool:
"""Check if a WebSocket message is authorized.
Args:
topic: The message topic.
role_header: The HTTP_REMOTE_ROLE header value, or None.
separator: The role separator character from proxy config.
Returns:
True if authorized, False if blocked.
"""
# Block IPC-only topics unconditionally
if topic in _WS_BLOCKED_TOPICS:
return False
# No role header: default to viewer (fail-closed)
if role_header is None:
return topic in _WS_VIEWER_TOPICS
# Check if any role is admin
roles = [r.strip() for r in role_header.split(separator)]
if "admin" in roles:
return True
# Non-admin: only viewer topics allowed
return topic in _WS_VIEWER_TOPICS
class WebSocket(WebSocket_): # type: ignore[misc]
def unhandled_error(self, error: Any) -> None:
@@ -130,7 +49,6 @@ class WebSocketClient(Communicator):
class _WebSocketHandler(WebSocket):
receiver = self._dispatcher
role_separator = self.config.proxy.separator or ","
def received_message(self, message: WebSocket.received_message) -> None: # type: ignore[name-defined]
try:
@@ -145,25 +63,11 @@ class WebSocketClient(Communicator):
)
return
topic = json_message["topic"]
# Authorization check (skip when environ is None — direct internal connection)
role_header = (
self.environ.get("HTTP_REMOTE_ROLE") if self.environ else None
logger.debug(
f"Publishing mqtt message from websockets at {json_message['topic']}."
)
if self.environ is not None and not _check_ws_authorization(
topic, role_header, self.role_separator
):
logger.warning(
"Blocked unauthorized WebSocket message: topic=%s, role=%s",
topic,
role_header,
)
return
logger.debug(f"Publishing mqtt message from websockets at {topic}.")
self.receiver(
topic,
json_message["topic"],
json_message["payload"],
)
+1 -1
View File
@@ -76,7 +76,7 @@ class CameraConfig(FrigateBaseModel):
# Options with global fallback
audio: AudioConfig = Field(
default_factory=AudioConfig,
title="Audio detection",
title="Audio events",
description="Settings for audio-based event detection for this camera.",
)
audio_transcription: CameraAudioTranscriptionConfig = Field(
+2 -1
View File
@@ -41,7 +41,8 @@ class GenAIConfig(FrigateBaseModel):
title="Model",
description="The model to use from the provider for generating descriptions or summaries.",
)
provider: GenAIProviderEnum = Field(
provider: GenAIProviderEnum | None = Field(
default=None,
title="Provider",
description="The GenAI provider to use (for example: ollama, gemini, openai).",
)
-5
View File
@@ -20,7 +20,6 @@ class CameraConfigUpdateEnum(str, Enum):
ffmpeg = "ffmpeg"
live = "live"
motion = "motion" # includes motion and motion masks
mqtt = "mqtt"
notifications = "notifications"
objects = "objects"
object_genai = "object_genai"
@@ -34,7 +33,6 @@ class CameraConfigUpdateEnum(str, Enum):
lpr = "lpr"
snapshots = "snapshots"
timestamp_style = "timestamp_style"
ui = "ui"
zones = "zones"
@@ -121,10 +119,7 @@ class CameraConfigUpdateSubscriber:
elif update_type == CameraConfigUpdateEnum.objects:
config.objects = updated_config
elif update_type == CameraConfigUpdateEnum.record:
old_enabled_in_config = config.record.enabled_in_config
config.record = updated_config
if old_enabled_in_config != updated_config.enabled_in_config:
config.recreate_ffmpeg_cmds()
elif update_type == CameraConfigUpdateEnum.review:
config.review = updated_config
elif update_type == CameraConfigUpdateEnum.review_genai:
+9 -14
View File
@@ -26,11 +26,6 @@ class EnrichmentsDeviceEnum(str, Enum):
CPU = "CPU"
class ModelSizeEnum(str, Enum):
small = "small"
large = "large"
class TriggerType(str, Enum):
THUMBNAIL = "thumbnail"
DESCRIPTION = "description"
@@ -58,13 +53,13 @@ class AudioTranscriptionConfig(FrigateBaseModel):
title="Transcription language",
description="Language code used for transcription/translation (for example 'en' for English). See https://whisper-api.com/docs/languages/ for supported language codes.",
)
device: EnrichmentsDeviceEnum = Field(
device: Optional[EnrichmentsDeviceEnum] = Field(
default=EnrichmentsDeviceEnum.CPU,
title="Transcription device",
description="Device key (CPU/GPU) to run the transcription model on. Only NVIDIA CUDA GPUs are currently supported for transcription.",
)
model_size: ModelSizeEnum = Field(
default=ModelSizeEnum.small,
model_size: str = Field(
default="small",
title="Model size",
description="Model size to use for offline audio event transcription.",
)
@@ -194,8 +189,8 @@ class SemanticSearchConfig(FrigateBaseModel):
return v
return v
model_size: ModelSizeEnum = Field(
default=ModelSizeEnum.small,
model_size: str = Field(
default="small",
title="Model size",
description="Select model size; 'small' runs on CPU and 'large' typically requires GPU.",
)
@@ -258,8 +253,8 @@ class FaceRecognitionConfig(FrigateBaseModel):
title="Enable face recognition",
description="Enable or disable face recognition for all cameras; can be overridden per-camera.",
)
model_size: ModelSizeEnum = Field(
default=ModelSizeEnum.small,
model_size: str = Field(
default="small",
title="Model size",
description="Model size to use for face embeddings (small/large); larger may require GPU.",
)
@@ -340,8 +335,8 @@ class LicensePlateRecognitionConfig(FrigateBaseModel):
title="Enable LPR",
description="Enable or disable license plate recognition for all cameras; can be overridden per-camera.",
)
model_size: ModelSizeEnum = Field(
default=ModelSizeEnum.small,
model_size: str = Field(
default="small",
title="Model size",
description="Model size used for text detection/recognition. Most users should use 'small'.",
)
+5 -34
View File
@@ -1,6 +1,5 @@
from __future__ import annotations
import io
import json
import logging
import os
@@ -81,40 +80,17 @@ logger = logging.getLogger(__name__)
yaml = YAML()
DEFAULT_DETECTORS = {
"ov": {
"type": "openvino",
"device": "CPU",
}
}
DEFAULT_MODEL = {
"width": 300,
"height": 300,
"input_tensor": "nhwc",
"input_pixel_format": "bgr",
"path": "/openvino-model/ssdlite_mobilenet_v2.xml",
"labelmap_path": "/openvino-model/coco_91cl_bkgr.txt",
}
DEFAULT_DETECT_DIMENSIONS = {"width": 1280, "height": 720}
def _render_default_yaml(data: dict) -> str:
buf = io.StringIO()
_yaml_writer = YAML()
_yaml_writer.indent(mapping=2, sequence=4, offset=2)
_yaml_writer.dump(data, buf)
return buf.getvalue()
DEFAULT_CONFIG = f"""
mqtt:
enabled: False
{_render_default_yaml({"detectors": DEFAULT_DETECTORS, "model": DEFAULT_MODEL})}
cameras: {{}} # No cameras defined, UI wizard should be used
version: {CURRENT_CONFIG_VERSION}
"""
DEFAULT_DETECTORS = {"cpu": {"type": "cpu"}}
DEFAULT_DETECT_DIMENSIONS = {"width": 1280, "height": 720}
# stream info handler
stream_info_retriever = StreamInfoRetriever()
@@ -477,7 +453,7 @@ class FrigateConfig(FrigateBaseModel):
cameras: Dict[str, CameraConfig] = Field(title="Cameras", description="Cameras")
audio: AudioConfig = Field(
default_factory=AudioConfig,
title="Audio detection",
title="Audio events",
description="Settings for audio-based event detection for all cameras; can be overridden per-camera.",
)
birdseye: BirdseyeConfig = Field(
@@ -703,9 +679,6 @@ class FrigateConfig(FrigateBaseModel):
model_config["path"] = "/cpu_model.tflite"
elif detector_config.type == "edgetpu":
model_config["path"] = "/edgetpu_model.tflite"
elif detector_config.type == "openvino":
for default_key, default_value in DEFAULT_MODEL.items():
model_config.setdefault(default_key, default_value)
model = ModelConfig.model_validate(model_config)
model.check_and_load_plus_model(self.plus_api, detector_config.type)
@@ -862,9 +835,7 @@ class FrigateConfig(FrigateBaseModel):
if mask_config:
coords = mask_config.coordinates
relative_coords = get_relative_coordinates(
coords,
camera_config.frame_shape,
camera_name=camera_config.name,
coords, camera_config.frame_shape
)
# Create a new ObjectMaskConfig with raw_coordinates set
processed_global_masks[mask_id] = ObjectMaskConfig(
+2 -2
View File
@@ -25,8 +25,8 @@ class StatsConfig(FrigateBaseModel):
)
intel_gpu_device: Optional[str] = Field(
default=None,
title="Intel GPU device",
description="PCI bus address or DRM device path (e.g. /dev/dri/card1) used to pin Intel GPU stats to a specific device when multiple are present.",
title="SR-IOV device",
description="Device identifier used when treating Intel GPUs as SR-IOV to fix GPU stats.",
)
+1 -1
View File
@@ -15,7 +15,7 @@ TRIGGER_DIR = f"{CLIPS_DIR}/triggers"
BIRDSEYE_PIPE = "/tmp/cache/birdseye"
CACHE_DIR = "/tmp/cache"
REPLAY_CAMERA_PREFIX = "_replay_"
REPLAY_DIR = os.path.join(CLIPS_DIR, "replay")
REPLAY_DIR = os.path.join(CACHE_DIR, "replay")
PLUS_ENV_VAR = "PLUS_API_KEY"
PLUS_API_HOST = "https://api.frigate.video"
+2 -57
View File
@@ -133,61 +133,6 @@ class FaceRecognizer(ABC):
return 0.0
def build_class_mean(
embs: list[np.ndarray],
trim: float = 0.15,
outlier_threshold: float = 0.30,
min_keep_frac: float = 0.7,
max_iters: int = 3,
) -> np.ndarray:
"""Build a class-mean embedding with two-layer outlier protection.
Layer 1 (iterative, vector-wise): drop whole embeddings whose cosine
similarity to the current class mean is below ``outlier_threshold``.
Catches mislabeled or corrupted training samples (wrong face in the
folder, full-frame screenshots, extreme crops) that per-dimension
trimming cannot detect.
Layer 2 (per-dimension): ``scipy.stats.trim_mean`` on the retained set
to smooth per-component noise (lighting, expression, alignment jitter).
Collections with fewer than 5 images bypass outlier rejection too few
samples to establish a reliable class center.
"""
arr = np.stack(embs, axis=0)
if len(arr) < 5:
return np.asarray(stats.trim_mean(arr, trim, axis=0))
keep = np.ones(len(arr), dtype=bool)
floor = max(5, int(np.ceil(min_keep_frac * len(arr))))
for _ in range(max_iters):
mean = stats.trim_mean(arr[keep], trim, axis=0)
m_norm = mean / (np.linalg.norm(mean) + 1e-9)
e_norms = arr / (np.linalg.norm(arr, axis=1, keepdims=True) + 1e-9)
cos = e_norms @ m_norm
new_keep = cos >= outlier_threshold
if new_keep.sum() < floor:
top = np.argsort(-cos)[:floor]
new_keep = np.zeros(len(arr), dtype=bool)
new_keep[top] = True
if np.array_equal(new_keep, keep):
break
keep = new_keep
dropped = int((~keep).sum())
if dropped:
logger.debug(
f"Vector-wise outlier filter dropped {dropped}/{len(arr)} embeddings"
)
return np.asarray(stats.trim_mean(arr[keep], trim, axis=0))
def similarity_to_confidence(
cosine_similarity: float,
median: float = 0.3,
@@ -284,7 +229,7 @@ class FaceNetRecognizer(FaceRecognizer):
for name, embs in face_embeddings_map.items():
if embs:
self.mean_embs[name] = build_class_mean(embs)
self.mean_embs[name] = stats.trim_mean(embs, 0.15)
logger.debug("Finished building ArcFace model")
@@ -395,7 +340,7 @@ class ArcFaceRecognizer(FaceRecognizer):
for name, embs in face_embeddings_map.items():
if embs:
self.mean_embs[name] = build_class_mean(embs)
self.mean_embs[name] = stats.trim_mean(embs, 0.15)
logger.debug("Finished building ArcFace model")
@@ -1073,6 +1073,10 @@ class LicensePlateProcessingMixin:
top_score = score
top_box = bbox
if score > top_score:
top_score = score
top_box = bbox
# Return the top scoring bounding box if found
if top_box is not None:
# expand box by 5% to help with OCR
@@ -1088,6 +1092,9 @@ class LicensePlateProcessingMixin:
]
).clip(0, [input.shape[1], input.shape[0]] * 2)
logger.debug(
f"{camera}: Found license plate. Bounding box: {expanded_box.astype(int)}"
)
return tuple(int(x) for x in expanded_box) # type: ignore[return-value]
else:
return None # No detection above the threshold
@@ -1353,8 +1360,8 @@ class LicensePlateProcessingMixin:
)
# check that license plate is valid
# quadruple the value because we've doubled both dimensions of the car
if license_plate_area < self.config.cameras[camera].lpr.min_area * 4:
# double the value because we've doubled the size of the car
if license_plate_area < self.config.cameras[camera].lpr.min_area * 2:
logger.debug(f"{camera}: License plate is less than min_area")
return
@@ -1458,7 +1465,6 @@ class LicensePlateProcessingMixin:
license_plate_frame,
)
logger.debug(f"{camera}: Found license plate. Bounding box: {list(plate_box)}")
logger.debug(f"{camera}: Running plate recognition for id: {id}.")
# run detection, returns results sorted by confidence, best first
@@ -269,9 +269,7 @@ class ObjectDescriptionProcessor(PostProcessorApi):
if event.has_snapshot and camera_config.objects.genai.use_snapshot:
snapshot_image = self._read_and_crop_snapshot(event)
if not snapshot_image:
self.cleanup_event(event_id)
return
num_thumbnails = len(self.tracked_events.get(event_id, []))
@@ -39,8 +39,6 @@ logger = logging.getLogger(__name__)
RECORDING_BUFFER_EXTENSION_PERCENT = 0.10
MIN_RECORDING_DURATION = 10
MAX_IMAGE_TOKENS = 24000
MAX_FRAMES_PER_SECOND = 1
class ReviewDescriptionProcessor(PostProcessorApi):
@@ -62,22 +60,14 @@ class ReviewDescriptionProcessor(PostProcessorApi):
def calculate_frame_count(
self,
camera: str,
duration: float,
image_source: ImageSourceEnum = ImageSourceEnum.preview,
height: int = 480,
) -> int:
"""Calculate optimal number of frames based on event duration, context size,
image source, and resolution.
"""Calculate optimal number of frames based on context size, image source, and resolution.
Per-image token cost is asked of the GenAI provider so providers that know
their model's true cost (e.g. llama.cpp can probe the loaded mmproj) can
diverge from the default ~1-token-per-1250-pixels heuristic. The frame
budget is bounded by:
- remaining context window after prompt + response reservations
- a fixed MAX_IMAGE_TOKENS ceiling
- MAX_FRAMES_PER_SECOND x duration, to avoid drowning short events in
near-duplicate frames where the model latches onto the redundant middle
and skips the start/end action
Token usage varies by resolution: larger images (ultra-wide aspect ratios) use more tokens.
Estimates ~1 token per 1250 pixels. Targets 98% context utilization with safety margin.
Capped at 20 frames.
"""
client = self.genai_manager.description_client
@@ -115,15 +105,14 @@ class ReviewDescriptionProcessor(PostProcessorApi):
width = target_width
height = int(target_width / aspect_ratio)
tokens_per_image = client.estimate_image_tokens(width, height)
pixels_per_image = width * height
tokens_per_image = pixels_per_image / 1250
prompt_tokens = 3800
response_tokens = 300
context_budget = context_size - prompt_tokens - response_tokens
image_token_budget = min(context_budget, MAX_IMAGE_TOKENS)
max_frames_by_tokens = int(image_token_budget / tokens_per_image)
max_frames_by_duration = int(duration * MAX_FRAMES_PER_SECOND)
max_frames = min(max_frames_by_tokens, max_frames_by_duration)
return max(max_frames, 3)
available_tokens = context_size - prompt_tokens - response_tokens
max_frames = int(available_tokens / tokens_per_image)
return min(max(max_frames, 3), 20)
def process_data(
self, data: dict[str, Any], data_type: PostProcessDataEnum
@@ -366,17 +355,12 @@ class ReviewDescriptionProcessor(PostProcessorApi):
file_start = f"preview_{camera}-"
start_file = f"{file_start}{start_time}.webp"
end_file = f"{file_start}{end_time}.webp"
camera_files = [
entry.name
for entry in os.scandir(preview_dir)
if entry.name.startswith(file_start)
]
camera_files.sort()
all_frames: list[str] = []
for file in camera_files:
for file in sorted(os.listdir(preview_dir)):
if not file.startswith(file_start):
continue
if file < start_file:
if len(all_frames):
all_frames[0] = os.path.join(preview_dir, file)
@@ -392,9 +376,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
all_frames.append(os.path.join(preview_dir, file))
frame_count = len(all_frames)
desired_frame_count = self.calculate_frame_count(
camera, duration=end_time - start_time
)
desired_frame_count = self.calculate_frame_count(camera)
if frame_count <= desired_frame_count:
return all_frames
@@ -418,7 +400,7 @@ class ReviewDescriptionProcessor(PostProcessorApi):
"""Get frames from recordings at specified timestamps."""
duration = end_time - start_time
desired_frame_count = self.calculate_frame_count(
camera, duration, ImageSourceEnum.recordings, height
camera, ImageSourceEnum.recordings, height
)
# Calculate evenly spaced timestamps throughout the duration
+6 -22
View File
@@ -1,37 +1,21 @@
from typing import Annotated
from pydantic import BaseModel, ConfigDict, Field, StringConstraints
ObservationItem = Annotated[str, StringConstraints(min_length=20, max_length=200)]
from pydantic import BaseModel, ConfigDict, Field
class ReviewMetadata(BaseModel):
model_config = ConfigDict(extra="ignore", protected_namespaces=())
observations: list[ObservationItem] = Field(
...,
min_length=3,
max_length=8,
description="Enumerate the significant observations across all frames, in chronological order.",
title: str = Field(
description="A short title characterizing what took place and where, under 10 words."
)
scene: str = Field(
min_length=150,
max_length=600,
description="A chronological narrative of what happens from start to finish, drawing directly from the items in observations.",
)
title: str = Field(
max_length=80,
description="Title for the activity.",
description="A chronological narrative of what happens from start to finish."
)
shortSummary: str = Field(
min_length=70,
max_length=140,
description="A brief summary for the activity.",
description="A brief 2-sentence summary of the scene, suitable for notifications."
)
confidence: float = Field(
ge=0.0,
le=1.0,
description="Confidence in the analysis as a decimal between 0.0 and 1.0, where 0.0 means no confidence and 1.0 means complete confidence. Express ONLY as a decimal.",
description="Confidence in the analysis, from 0 to 1.",
)
potential_threat_level: int = Field(
ge=0,
+7 -3
View File
@@ -229,10 +229,9 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
logger.debug(f"No person box available for {id}")
return
# YuNet (cv2.FaceDetectorYN) is trained on BGR
bgr = cv2.cvtColor(frame, cv2.COLOR_YUV2BGR_I420)
rgb = cv2.cvtColor(frame, cv2.COLOR_YUV2RGB_I420)
left, top, right, bottom = person_box
person = bgr[top:bottom, left:right]
person = rgb[top:bottom, left:right]
face_box = self.__detect_face(person, self.face_config.detection_threshold)
if not face_box:
@@ -251,6 +250,11 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
)
return
try:
face_frame = cv2.cvtColor(face_frame, cv2.COLOR_RGB2BGR)
except Exception as e:
logger.debug(f"Failed to convert face frame color for {id}: {e}")
return
else:
# don't run for object without attributes
if not obj_data.get("current_attributes"):
+187 -83
View File
@@ -1,13 +1,9 @@
"""Debug replay camera management for replaying recordings with detection overlays.
The startup work (ffmpeg concat + camera config publish) lives in
frigate.jobs.debug_replay. This module owns only session presence
(active), session metadata, and post-session cleanup.
"""
"""Debug replay camera management for replaying recordings with detection overlays."""
import logging
import os
import shutil
import subprocess as sp
import threading
from ruamel.yaml import YAML
@@ -25,7 +21,7 @@ from frigate.const import (
REPLAY_DIR,
THUMB_DIR,
)
from frigate.jobs.debug_replay import cancel_debug_replay_job, wait_for_runner
from frigate.models import Recordings
from frigate.util.camera_cleanup import cleanup_camera_db, cleanup_camera_files
from frigate.util.config import find_config_file
@@ -33,14 +29,7 @@ logger = logging.getLogger(__name__)
class DebugReplayManager:
"""Owns the lifecycle pointers for a single debug replay session.
A session exists from the moment mark_starting is called (synchronously,
inside the API handler) until clear_session runs (on success cleanup,
failure, or stop). The active property is the source of truth that the
status bar consumes broader than the startup job, which only covers the
preparing_clip / starting_camera window.
"""
"""Manages a single debug replay session."""
def __init__(self) -> None:
self._lock = threading.Lock()
@@ -52,66 +41,144 @@ class DebugReplayManager:
@property
def active(self) -> bool:
"""True from mark_starting until clear_session."""
"""Whether a replay session is currently active."""
return self.replay_camera_name is not None
def mark_starting(
def start(
self,
source_camera: str,
replay_camera_name: str,
start_ts: float,
end_ts: float,
) -> None:
"""Synchronously claim the session before the job runner starts.
Called inside the API handler so the status bar sees active=True
immediately, before the worker thread does any ffmpeg work.
"""
with self._lock:
self.replay_camera_name = replay_camera_name
self.source_camera = source_camera
self.start_ts = start_ts
self.end_ts = end_ts
self.clip_path = None
def mark_session_ready(self, clip_path: str) -> None:
"""Record the on-disk clip path after the camera has been published."""
with self._lock:
self.clip_path = clip_path
def clear_session(self) -> None:
"""Reset session pointers without publishing camera removal.
Used by the job runner on failure paths. stop() does the camera
teardown plus this clear in one step.
"""
with self._lock:
self._clear_locked()
def _clear_locked(self) -> None:
self.replay_camera_name = None
self.source_camera = None
self.clip_path = None
self.start_ts = None
self.end_ts = None
def publish_camera(
self,
source_camera: str,
replay_name: str,
clip_path: str,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
) -> None:
"""Build the in-memory replay camera config and publish the add event.
) -> str:
"""Start a debug replay session.
Called by the job runner during the starting_camera phase.
Args:
source_camera: Name of the source camera to replay
start_ts: Start timestamp
end_ts: End timestamp
frigate_config: Current Frigate configuration
config_publisher: Publisher for camera config updates
Returns:
The replay camera name
Raises:
ValueError: If a session is already active or parameters are invalid
RuntimeError: If clip generation fails
"""
with self._lock:
return self._start_locked(
source_camera, start_ts, end_ts, frigate_config, config_publisher
)
def _start_locked(
self,
source_camera: str,
start_ts: float,
end_ts: float,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
) -> str:
if self.active:
raise ValueError("A replay session is already active")
if source_camera not in frigate_config.cameras:
raise ValueError(f"Camera '{source_camera}' not found")
if end_ts <= start_ts:
raise ValueError("End time must be after start time")
# Query recordings for the source camera in the time range
recordings = (
Recordings.select(
Recordings.path,
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(start_ts, end_ts)
| Recordings.end_time.between(start_ts, end_ts)
| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
)
.where(Recordings.camera == source_camera)
.order_by(Recordings.start_time.asc())
)
if not recordings.count():
raise ValueError(
f"No recordings found for camera '{source_camera}' in the specified time range"
)
# Create replay directory
os.makedirs(REPLAY_DIR, exist_ok=True)
# Generate replay camera name
replay_name = f"{REPLAY_CAMERA_PREFIX}{source_camera}"
# Build concat file for ffmpeg
concat_file = os.path.join(REPLAY_DIR, f"{replay_name}_concat.txt")
clip_path = os.path.join(REPLAY_DIR, f"{replay_name}.mp4")
with open(concat_file, "w") as f:
for recording in recordings:
f.write(f"file '{recording.path}'\n")
# Concatenate recordings into a single clip with -c copy (fast)
ffmpeg_cmd = [
frigate_config.ffmpeg.ffmpeg_path,
"-hide_banner",
"-y",
"-f",
"concat",
"-safe",
"0",
"-i",
concat_file,
"-c",
"copy",
"-movflags",
"+faststart",
clip_path,
]
logger.info(
"Generating replay clip for %s (%.1f - %.1f)",
source_camera,
start_ts,
end_ts,
)
try:
result = sp.run(
ffmpeg_cmd,
capture_output=True,
text=True,
timeout=120,
)
if result.returncode != 0:
logger.error("FFmpeg error: %s", result.stderr)
raise RuntimeError(
f"Failed to generate replay clip: {result.stderr[-500:]}"
)
except sp.TimeoutExpired:
raise RuntimeError("Clip generation timed out")
finally:
# Clean up concat file
if os.path.exists(concat_file):
os.remove(concat_file)
if not os.path.exists(clip_path):
raise RuntimeError("Clip file was not created")
# Build camera config dict for the replay camera
source_config = frigate_config.cameras[source_camera]
camera_dict = self._build_camera_config_dict(
source_config, replay_name, clip_path
)
# Build an in-memory config with the replay camera added
config_file = find_config_file()
yaml_parser = YAML()
with open(config_file, "r") as f:
@@ -124,48 +191,75 @@ class DebugReplayManager:
try:
new_config = FrigateConfig.parse_object(config_data)
except Exception as e:
raise RuntimeError(f"Failed to validate replay camera config: {e}") from e
raise RuntimeError(f"Failed to validate replay camera config: {e}")
# Update the running config
frigate_config.cameras[replay_name] = new_config.cameras[replay_name]
# Publish the add event
config_publisher.publish_update(
CameraConfigUpdateTopic(CameraConfigUpdateEnum.add, replay_name),
new_config.cameras[replay_name],
)
# Store session state
self.replay_camera_name = replay_name
self.source_camera = source_camera
self.clip_path = clip_path
self.start_ts = start_ts
self.end_ts = end_ts
logger.info("Debug replay started: %s -> %s", source_camera, replay_name)
return replay_name
def stop(
self,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
) -> None:
"""Cancel any in-flight startup job and tear down the active session.
"""Stop the active replay session and clean up all artifacts.
Safe to call when no session is active (no-op with a warning).
Args:
frigate_config: Current Frigate configuration
config_publisher: Publisher for camera config updates
"""
cancel_debug_replay_job()
wait_for_runner(timeout=2.0)
with self._lock:
if not self.active:
logger.warning("No active replay session to stop")
return
self._stop_locked(frigate_config, config_publisher)
replay_name = self.replay_camera_name
def _stop_locked(
self,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
) -> None:
if not self.active:
logger.warning("No active replay session to stop")
return
# Only publish remove if the camera was actually added to the live
# config (i.e. the runner reached the starting_camera phase).
if replay_name is not None and replay_name in frigate_config.cameras:
config_publisher.publish_update(
CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, replay_name),
frigate_config.cameras[replay_name],
)
replay_name = self.replay_camera_name
if replay_name is not None:
self._cleanup_db(replay_name)
self._cleanup_files(replay_name)
# Publish remove event so subscribers stop and remove from their config
if replay_name in frigate_config.cameras:
config_publisher.publish_update(
CameraConfigUpdateTopic(CameraConfigUpdateEnum.remove, replay_name),
frigate_config.cameras[replay_name],
)
# Do NOT pop here — let subscribers handle removal from the shared
# config dict when they process the ZMQ message to avoid race conditions
self._clear_locked()
# Defensive DB cleanup
self._cleanup_db(replay_name)
logger.info("Debug replay stopped and cleaned up: %s", replay_name)
# Remove filesystem artifacts
self._cleanup_files(replay_name)
# Reset state
self.replay_camera_name = None
self.source_camera = None
self.clip_path = None
self.start_ts = None
self.end_ts = None
logger.info("Debug replay stopped and cleaned up: %s", replay_name)
def _build_camera_config_dict(
self,
@@ -173,7 +267,16 @@ class DebugReplayManager:
replay_name: str,
clip_path: str,
) -> dict:
"""Build a camera config dictionary for the replay camera."""
"""Build a camera config dictionary for the replay camera.
Args:
source_config: Source camera's CameraConfig
replay_name: Name for the replay camera
clip_path: Path to the replay clip file
Returns:
Camera config as a dictionary
"""
# Extract detect config (exclude computed fields)
detect_dict = source_config.detect.model_dump(
exclude={"min_initialized", "max_disappeared", "enabled_in_config"}
@@ -208,6 +311,7 @@ class DebugReplayManager:
zone_dump = zone_config.model_dump(
exclude={"contour", "color"}, exclude_defaults=True
)
# Always include required fields
zone_dump.setdefault("coordinates", zone_config.coordinates)
zones_dict[zone_name] = zone_dump
+1
View File
@@ -132,6 +132,7 @@ class ONNXModelRunner(BaseModelRunner):
return model_type in [
EnrichmentModelTypeEnum.paddleocr.value,
EnrichmentModelTypeEnum.jina_v2.value,
EnrichmentModelTypeEnum.arcface.value,
ModelTypeEnum.rfdetr.value,
ModelTypeEnum.dfine.value,
]
-6
View File
@@ -52,12 +52,6 @@ class OvDetector(DetectionApi):
self.h = detector_config.model.height
self.w = detector_config.model.width
logger.info(
"Loading OpenVINO model %s on device %s",
detector_config.model.path,
detector_config.device,
)
self.runner = OpenVINOModelRunner(
model_path=detector_config.model.path,
device=detector_config.device,
-9
View File
@@ -4,7 +4,6 @@ import base64
import json
import logging
import os
import sys
import threading
from json.decoder import JSONDecodeError
from multiprocessing.synchronize import Event as MpEvent
@@ -53,14 +52,6 @@ class EmbeddingProcess(FrigateProcess):
self.stop_event,
)
maintainer.start()
maintainer.join()
# If the maintainer thread exited but no shutdown was requested, it
# crashed. Surface as a non-zero exit so the watchdog restarts us
# instead of treating the silent thread death as a clean shutdown.
if not self.stop_event.is_set():
logger.error("Embeddings maintainer thread exited unexpectedly")
sys.exit(1)
class EmbeddingsContext:
+2 -18
View File
@@ -60,11 +60,7 @@ from frigate.data_processing.real_time.license_plate import (
)
from frigate.data_processing.types import DataProcessorMetrics, PostProcessDataEnum
from frigate.db.sqlitevecq import SqliteVecQueueDatabase
from frigate.events.types import (
EventStateEnum,
EventTypeEnum,
RegenerateDescriptionEnum,
)
from frigate.events.types import EventTypeEnum, RegenerateDescriptionEnum
from frigate.genai import GenAIClientManager
from frigate.models import Event, Recordings, ReviewSegment, Trigger
from frigate.types import TrackedObjectUpdateTypesEnum
@@ -439,7 +435,7 @@ class EmbeddingMaintainer(threading.Thread):
if update is None:
return
source_type, event_type, camera, frame_name, data = update
source_type, _, camera, frame_name, data = update
logger.debug(
f"Received update - source_type: {source_type}, camera: {camera}, data label: {data.get('label') if data else 'None'}"
@@ -489,12 +485,6 @@ class EmbeddingMaintainer(threading.Thread):
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
# skip end events — _process_finalized handles them via event_end_subscriber.
# processing them here can re-create tracked_events entries after cleanup
# when the event_subscriber queue is backlogged behind event_end_subscriber.
if event_type == EventStateEnum.end:
continue
processor.process_data(
{
"camera": camera,
@@ -527,16 +517,10 @@ class EmbeddingMaintainer(threading.Thread):
try:
event: Event = Event.get(Event.id == event_id)
except DoesNotExist:
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
processor.cleanup_event(event_id)
continue
# Skip the event if not an object
if event.data.get("type") != "object":
for processor in self.post_processors:
if isinstance(processor, ObjectDescriptionProcessor):
processor.cleanup_event(event_id)
continue
# Extract valid thumbnail
+13 -47
View File
@@ -84,6 +84,7 @@ class AudioProcessor(FrigateProcess):
def __init__(
self,
config: FrigateConfig,
cameras: list[CameraConfig],
camera_metrics: DictProxy,
stop_event: MpEvent,
):
@@ -92,11 +93,12 @@ class AudioProcessor(FrigateProcess):
)
self.camera_metrics = camera_metrics
self.cameras = cameras
self.config = config
def run(self) -> None:
self.pre_run_setup(self.config.logger)
audio_threads: dict[str, AudioEventMaintainer] = {}
audio_threads: list[AudioEventMaintainer] = []
threading.current_thread().name = "process:audio_manager"
@@ -110,56 +112,32 @@ class AudioProcessor(FrigateProcess):
else:
self.transcription_model_runner = None
config_subscriber = CameraConfigUpdateSubscriber(
self.config,
self.config.cameras,
[
CameraConfigUpdateEnum.add,
CameraConfigUpdateEnum.audio,
CameraConfigUpdateEnum.ffmpeg,
],
)
if len(self.cameras) == 0:
return
def spawn_if_needed(camera: CameraConfig) -> None:
name = camera.name
if name is None or name in audio_threads:
return
if not camera.enabled or not camera.audio.enabled:
return
# ffmpeg update may not have arrived yet; wait for next poll
if not any("audio" in i.roles for i in camera.ffmpeg.inputs):
return
thread = AudioEventMaintainer(
for camera in self.cameras:
audio_thread = AudioEventMaintainer(
camera,
self.config,
self.camera_metrics,
self.transcription_model_runner,
self.stop_event, # type: ignore[arg-type]
)
audio_threads[name] = thread
thread.start()
self.logger.info(f"Audio maintainer started for {name}")
for camera in self.config.cameras.values():
spawn_if_needed(camera)
audio_threads.append(audio_thread)
audio_thread.start()
self.logger.info(f"Audio processor started (pid: {self.pid})")
# poll for newly added cameras or cameras flipped to audio.enabled at runtime
while not self.stop_event.wait(timeout=1.0):
config_subscriber.check_for_updates()
for camera in self.config.cameras.values():
spawn_if_needed(camera)
while not self.stop_event.wait():
pass
config_subscriber.stop()
for thread in audio_threads.values():
for thread in audio_threads:
thread.join(1)
if thread.is_alive():
self.logger.info(f"Waiting for thread {thread.name:s} to exit")
thread.join(10)
for thread in audio_threads.values():
for thread in audio_threads:
if thread.is_alive():
self.logger.warning(f"Thread {thread.name} is still alive")
@@ -227,7 +205,6 @@ class AudioEventMaintainer(threading.Thread):
self.transcription_thread.start()
self.was_enabled = camera.enabled
self.was_audio_enabled = camera.audio.enabled
def detect_audio(self, audio: np.ndarray) -> None:
if not self.camera_config.audio.enabled or self.stop_event.is_set():
@@ -386,17 +363,6 @@ class AudioEventMaintainer(threading.Thread):
time.sleep(0.1)
continue
audio_enabled = self.camera_config.audio.enabled
if audio_enabled != self.was_audio_enabled:
if not audio_enabled:
self.logger.debug(
f"Disabling audio detections for {self.camera_config.name}, ending events"
)
self.requestor.send_data(
EXPIRE_AUDIO_ACTIVITY, self.camera_config.name
)
self.was_audio_enabled = audio_enabled
self.read_audio()
if self.audio_listener:
+9 -43
View File
@@ -2,7 +2,6 @@
import datetime
import importlib
import json
import logging
import os
import re
@@ -10,7 +9,6 @@ from typing import Any, Callable, Optional
import numpy as np
from playhouse.shortcuts import model_to_dict
from pydantic import ValidationError
from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum
from frigate.const import CLIPS_DIR
@@ -108,11 +106,10 @@ When forming your description:
## Response Field Guidelines
Respond with a JSON object matching the provided schema. Field-specific guidance:
- `observations`: Include the very start of the activity for example, a vehicle entering the frame or pulling into the driveway even if it lasts only a few frames and the rest of the clip is dominated by a longer activity. Include each arrival, departure, object handled, and notable change in position or state. Each item is a single concrete fact written as a complete sentence.
- `scene`: Describe how the sequence begins, then the progression of events all significant movements and actions in order. For example, if a vehicle arrives and then a person exits, describe both sequentially. For named subjects (those with a `` separator in "Objects in Scene"), always use their name do not replace them with generic terms. For unnamed objects (e.g., "person", "car"), refer to them naturally with articles (e.g., "a person", "the car"). Your description should align with and support the threat level you assign.
- `title`: Name the primary activity across the observations, together with the location. An activity is what is being done with objects, tools, or surfaces; locomotion through the scene qualifies as the activity only when no other interaction is observed. For named subjects, always use their name. For unnamed objects, refer to them naturally with articles.
- `shortSummary`: Briefly summarize the primary activity across the observations.
- `title`: Characterize **what took place and where** interpret the overall purpose or outcome, do not simply compress the scene description into fewer words. Include the relevant location (zone, area, or entry point). For named subjects, always use their name. For unnamed objects, refer to them naturally with articles. No editorial qualifiers like "routine" or "suspicious."
- `potential_threat_level`: Must be consistent with your scene description and the activity patterns above.
{get_concern_prompt()}
## Sequence Details
@@ -154,6 +151,9 @@ Each line represents a detection state, not necessarily unique individuals. The
if "other_concerns" in schema.get("required", []):
schema["required"].remove("other_concerns")
# OpenAI strict mode requires additionalProperties: false on all objects
schema["additionalProperties"] = False
response_format = {
"type": "json_schema",
"json_schema": {
@@ -181,36 +181,7 @@ Each line represents a detection state, not necessarily unique individuals. The
try:
metadata = ReviewMetadata.model_validate_json(clean_json)
except ValidationError as ve:
# Constraint violations (length, item count, ranges) are logged
# at debug and the response is kept anyway — a slightly
# off-spec answer is still usable, and dropping the whole
# response loses the narrative content the model produced.
for err in ve.errors():
loc = ".".join(str(p) for p in err["loc"]) or "<root>"
logger.debug(
"Review metadata soft validation: %s%s (input: %r)",
loc,
err["msg"],
err.get("input"),
)
try:
raw = json.loads(clean_json)
except json.JSONDecodeError as je:
logger.error("Failed to parse review description JSON: %s", je)
return None
# observations and confidence are required on the model; fill an empty default
# if the response omitted it so attribute access stays safe.
raw.setdefault("observations", [])
raw.setdefault("confidence", 0.0)
metadata = ReviewMetadata.model_construct(**raw)
except Exception as e:
logger.error(
f"Failed to parse review description as the response did not match expected format. {e}"
)
return None
try:
# Normalize confidence if model returned a percentage (e.g. 85 instead of 0.85)
if metadata.confidence > 1.0:
metadata.confidence = min(metadata.confidence / 100.0, 1.0)
@@ -223,7 +194,10 @@ Each line represents a detection state, not necessarily unique individuals. The
metadata.time = review_data["start"]
return metadata
except Exception as e:
logger.error(f"Failed to post-process review metadata: {e}")
# rarely LLMs can fail to follow directions on output format
logger.warning(
f"Failed to parse review description as the response did not match expected format. {e}"
)
return None
else:
logger.debug(
@@ -370,14 +344,6 @@ Guidelines:
"""Get the context window size for this provider in tokens."""
return 4096
def estimate_image_tokens(self, width: int, height: int) -> float:
"""Estimate prompt tokens consumed by a single image of the given dimensions.
Default heuristic: ~1 token per 1250 pixels. Providers that can measure or
know their model's exact image-token cost should override.
"""
return (width * height) / 1250
def embed(
self,
texts: list[str] | None = None,
+20 -64
View File
@@ -136,44 +136,22 @@ class GeminiClient(GenAIClient):
)
)
elif role == "assistant":
parts: list[types.Part] = []
if content:
parts.append(types.Part.from_text(text=content))
for tc in msg.get("tool_calls") or []:
func = tc.get("function") or {}
tc_name = func.get("name") or ""
tc_args: Any = func.get("arguments")
if isinstance(tc_args, str):
try:
tc_args = json.loads(tc_args)
except (json.JSONDecodeError, TypeError):
tc_args = {}
if not isinstance(tc_args, dict):
tc_args = {}
if tc_name:
parts.append(
types.Part.from_function_call(
name=tc_name, args=tc_args
)
)
if not parts:
parts.append(types.Part.from_text(text=" "))
gemini_messages.append(types.Content(role="model", parts=parts))
gemini_messages.append(
types.Content(
role="model", parts=[types.Part.from_text(text=content)]
)
)
elif role == "tool":
# Handle tool response
response_payload = (
content if isinstance(content, dict) else {"result": content}
)
function_response = {
"name": msg.get("name", ""),
"response": content,
}
gemini_messages.append(
types.Content(
role="function",
parts=[
types.Part.from_function_response(
name=msg.get("name")
or msg.get("tool_call_id")
or "",
response=response_payload,
)
types.Part.from_function_response(function_response) # type: ignore[misc,call-arg,arg-type]
],
)
)
@@ -365,44 +343,22 @@ class GeminiClient(GenAIClient):
)
)
elif role == "assistant":
parts: list[types.Part] = []
if content:
parts.append(types.Part.from_text(text=content))
for tc in msg.get("tool_calls") or []:
func = tc.get("function") or {}
tc_name = func.get("name") or ""
tc_args: Any = func.get("arguments")
if isinstance(tc_args, str):
try:
tc_args = json.loads(tc_args)
except (json.JSONDecodeError, TypeError):
tc_args = {}
if not isinstance(tc_args, dict):
tc_args = {}
if tc_name:
parts.append(
types.Part.from_function_call(
name=tc_name, args=tc_args
)
)
if not parts:
parts.append(types.Part.from_text(text=" "))
gemini_messages.append(types.Content(role="model", parts=parts))
gemini_messages.append(
types.Content(
role="model", parts=[types.Part.from_text(text=content)]
)
)
elif role == "tool":
# Handle tool response
response_payload = (
content if isinstance(content, dict) else {"result": content}
)
function_response = {
"name": msg.get("name", ""),
"response": content,
}
gemini_messages.append(
types.Content(
role="function",
parts=[
types.Part.from_function_response(
name=msg.get("name")
or msg.get("tool_call_id")
or "",
response=response_payload,
)
types.Part.from_function_response(function_response) # type: ignore[misc,call-arg,arg-type]
],
)
)
+36 -204
View File
@@ -18,17 +18,6 @@ from frigate.genai.utils import parse_tool_calls_from_message
logger = logging.getLogger(__name__)
def _parse_launch_arg(args: list[str], flag: str) -> str | None:
"""Return the value following `flag` in a positional argv list, or None."""
try:
idx = args.index(flag)
except ValueError:
return None
if idx + 1 >= len(args):
return None
return args[idx + 1]
def _to_jpeg(img_bytes: bytes) -> bytes | None:
"""Convert image bytes to JPEG. llama.cpp/STB does not support WebP."""
try:
@@ -53,9 +42,6 @@ class LlamaCppClient(GenAIClient):
_supports_vision: bool
_supports_audio: bool
_supports_tools: bool
_image_token_cache: dict[tuple[int, int], int]
_text_baseline_tokens: int | None
_media_marker: str
def _init_provider(self) -> str | None:
"""Initialize the client and query model metadata from the server."""
@@ -66,9 +52,6 @@ class LlamaCppClient(GenAIClient):
self._supports_vision = False
self._supports_audio = False
self._supports_tools = False
self._image_token_cache = {}
self._text_baseline_tokens = None
self._media_marker = "<__media__>"
base_url = (
self.genai_config.base_url.rstrip("/")
@@ -78,73 +61,28 @@ class LlamaCppClient(GenAIClient):
if base_url is None:
return None
else:
base_url = base_url.replace("/v1", "") # Strip /v1 if included in base_url
configured_model = self.genai_config.model
info = self._get_model_info(base_url, configured_model)
if info is None:
return None
self._context_size = info["context_size"]
self._supports_vision = info["supports_vision"]
self._supports_audio = info["supports_audio"]
self._supports_tools = info["supports_tools"]
self._media_marker = info["media_marker"]
logger.info(
"llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s",
configured_model,
self._context_size or "unknown",
self._supports_vision,
self._supports_audio,
self._supports_tools,
)
return base_url
def _get_model_info(
self, base_url: str, configured_model: str
) -> dict[str, Any] | None:
"""Resolve model metadata from /v1/models with /props fallback.
Returns a dict of capability fields, or None if the server's model
registry was reachable and reported the configured model as missing.
A reachable-but-unparseable /v1/models is treated as soft-pass and
falls through to /props, matching prior behavior.
After ggml-org/llama.cpp#22952, /v1/models exposes per-model
`architecture.input_modalities` (text/image/audio) the primary
source. When proxied through llama-swap, the same entry carries
`status.args` (server launch argv) and, for the loaded model,
`meta.n_ctx`. /props remains the only source for `media_marker`,
which the server randomizes per startup unless LLAMA_MEDIA_MARKER
is set.
"""
info: dict[str, Any] = {
"context_size": None,
"supports_vision": False,
"supports_audio": False,
"supports_tools": False,
"media_marker": "<__media__>",
}
model_entry: dict[str, Any] | None = None
# Query /v1/models to validate the configured model exists
try:
response = requests.get(f"{base_url}/v1/models", timeout=10)
response = requests.get(
f"{base_url}/v1/models",
timeout=10,
)
response.raise_for_status()
models_data = response.json()
model_found = False
for model in models_data.get("data", []):
model_ids = {model.get("id")}
for alias in model.get("aliases", []):
model_ids.add(alias)
if configured_model in model_ids:
model_entry = model
model_found = True
break
if model_entry is None:
if not model_found:
available = []
for m in models_data.get("data", []):
available.append(m.get("id", "unknown"))
@@ -163,35 +101,10 @@ class LlamaCppClient(GenAIClient):
e,
)
if model_entry is not None:
architecture = model_entry.get("architecture") or {}
input_modalities = architecture.get("input_modalities") or []
if isinstance(input_modalities, list):
info["supports_vision"] = "image" in input_modalities
info["supports_audio"] = "audio" in input_modalities
status = model_entry.get("status") or {}
launch_args = status.get("args") if isinstance(status, dict) else None
if not isinstance(launch_args, list):
launch_args = []
meta = model_entry.get("meta") if isinstance(model_entry, dict) else None
n_ctx = meta.get("n_ctx") if isinstance(meta, dict) else None
if not n_ctx:
n_ctx = _parse_launch_arg(launch_args, "--ctx-size")
if n_ctx:
try:
info["context_size"] = int(n_ctx)
except (TypeError, ValueError):
pass
# Tool calling on llama-server requires --jinja.
if "--jinja" in launch_args:
info["supports_tools"] = True
# Query /props for context size, modalities, and tool support.
# The standard /props?model=<name> endpoint works with llama-server.
# If it fails, try the llama-swap per-model passthrough endpoint which
# returns props for a specific model without requiring it to be loaded.
try:
try:
response = requests.get(
@@ -209,32 +122,37 @@ class LlamaCppClient(GenAIClient):
response.raise_for_status()
props = response.json()
if info["context_size"] is None:
default_settings = props.get("default_generation_settings", {})
n_ctx = default_settings.get("n_ctx")
if n_ctx:
info["context_size"] = int(n_ctx)
# Context size from server runtime config
default_settings = props.get("default_generation_settings", {})
n_ctx = default_settings.get("n_ctx")
if n_ctx:
self._context_size = int(n_ctx)
if not (info["supports_vision"] or info["supports_audio"]):
modalities = props.get("modalities", {})
info["supports_vision"] = bool(modalities.get("vision", False))
info["supports_audio"] = bool(modalities.get("audio", False))
# Modalities (vision, audio)
modalities = props.get("modalities", {})
self._supports_vision = modalities.get("vision", False)
self._supports_audio = modalities.get("audio", False)
if not info["supports_tools"]:
chat_caps = props.get("chat_template_caps", {})
info["supports_tools"] = bool(chat_caps.get("supports_tools", False))
# Tool support from chat template capabilities
chat_caps = props.get("chat_template_caps", {})
self._supports_tools = chat_caps.get("supports_tools", False)
media_marker = props.get("media_marker")
if isinstance(media_marker, str) and media_marker:
info["media_marker"] = media_marker
logger.info(
"llama.cpp model '%s' initialized — context: %s, vision: %s, audio: %s, tools: %s",
configured_model,
self._context_size or "unknown",
self._supports_vision,
self._supports_audio,
self._supports_tools,
)
except Exception as e:
logger.warning(
"Failed to query llama.cpp /props endpoint: %s. "
"Image embeddings may fail if the server randomized its media marker.",
"Using defaults for context size and capabilities.",
e,
)
return info
return base_url
def _send(
self,
@@ -354,91 +272,6 @@ class LlamaCppClient(GenAIClient):
return self._context_size
return 4096
def estimate_image_tokens(self, width: int, height: int) -> float:
"""Probe the llama.cpp server to learn the model's image-token cost at the
requested dimensions.
llama.cpp's image tokenization is a deterministic function of dimensions and
the loaded mmproj, so the result is cached per (width, height) for the
lifetime of the process. Falls back to the base pixel heuristic if the
server is unreachable or the response is malformed.
"""
if self.provider is None:
return super().estimate_image_tokens(width, height)
cached = self._image_token_cache.get((width, height))
if cached is not None:
return cached
try:
baseline = self._probe_baseline_tokens()
with_image = self._probe_image_prompt_tokens(width, height)
tokens = max(1, with_image - baseline)
except Exception as e:
logger.debug(
"llama.cpp image-token probe failed for %dx%d (%s); using heuristic",
width,
height,
e,
)
return super().estimate_image_tokens(width, height)
self._image_token_cache[(width, height)] = tokens
logger.debug(
"llama.cpp model '%s' uses ~%d tokens for %dx%d images",
self.genai_config.model,
tokens,
width,
height,
)
return tokens
def _probe_baseline_tokens(self) -> int:
"""Return prompt_tokens for a minimal text-only request. Cached after first call."""
if self._text_baseline_tokens is not None:
return self._text_baseline_tokens
self._text_baseline_tokens = self._probe_prompt_tokens(
[{"type": "text", "text": "."}]
)
return self._text_baseline_tokens
def _probe_image_prompt_tokens(self, width: int, height: int) -> int:
"""Return prompt_tokens for a single synthetic image plus minimal text."""
img = Image.new("RGB", (width, height), (128, 128, 128))
buf = io.BytesIO()
img.save(buf, format="JPEG", quality=60)
encoded = base64.b64encode(buf.getvalue()).decode("utf-8")
return self._probe_prompt_tokens(
[
{"type": "text", "text": "."},
{
"type": "image_url",
"image_url": {"url": f"data:image/jpeg;base64,{encoded}"},
},
]
)
def _probe_prompt_tokens(self, content: list[dict[str, Any]]) -> int:
"""POST a 1-token chat completion and return reported prompt_tokens.
Uses a generous timeout to absorb a cold model load on the first probe
when the server lazily loads models on demand (e.g. llama-swap).
"""
payload = {
"model": self.genai_config.model,
"messages": [{"role": "user", "content": content}],
"max_tokens": 1,
}
response = requests.post(
f"{self.provider}/v1/chat/completions",
json=payload,
timeout=60,
)
response.raise_for_status()
return int(response.json()["usage"]["prompt_tokens"])
def _build_payload(
self,
messages: list[dict[str, Any]],
@@ -543,11 +376,10 @@ class LlamaCppClient(GenAIClient):
jpeg_bytes = _to_jpeg(img)
to_encode = jpeg_bytes if jpeg_bytes is not None else img
encoded = base64.b64encode(to_encode).decode("utf-8")
# prompt_string must contain the server's media marker placeholder.
# The marker is randomized per server startup (read from /props).
# prompt_string must contain <__media__> placeholder for image tokenization
content.append(
{
"prompt_string": f"{self._media_marker}\n",
"prompt_string": "<__media__>\n",
"multimodal_data": [encoded], # type: ignore[dict-item]
}
)
+4 -58
View File
@@ -1,7 +1,5 @@
"""Ollama Provider for Frigate AI."""
import base64
import binascii
import json
import logging
from typing import Any, AsyncGenerator, Optional
@@ -18,41 +16,6 @@ from frigate.genai.utils import parse_tool_calls_from_message
logger = logging.getLogger(__name__)
def _normalize_multimodal_content(
content: Any,
) -> tuple[Optional[str], Optional[list[bytes]]]:
"""Convert OpenAI-style multimodal content to Ollama's (text, images) shape.
The chat API constructs user messages with content as a list of
``{"type": "text"}`` and ``{"type": "image_url"}`` parts when a tool
returns a live frame. Ollama's SDK requires content to be a string and
images to be passed in a separate field, so we extract each.
"""
if not isinstance(content, list):
return content, None
text_parts: list[str] = []
images: list[bytes] = []
for part in content:
if not isinstance(part, dict):
continue
part_type = part.get("type")
if part_type == "text":
text = part.get("text")
if text:
text_parts.append(str(text))
elif part_type == "image_url":
url = (part.get("image_url") or {}).get("url", "")
if isinstance(url, str) and url.startswith("data:"):
try:
encoded = url.split(",", 1)[1]
images.append(base64.b64decode(encoded, validate=True))
except (ValueError, IndexError, binascii.Error) as e:
logger.debug("Failed to decode multimodal image url: %s", e)
return ("\n".join(text_parts) if text_parts else None), (images or None)
@register_genai_provider(GenAIProviderEnum.ollama)
class OllamaClient(GenAIClient):
"""Generative AI client for Frigate using Ollama."""
@@ -68,12 +31,6 @@ class OllamaClient(GenAIClient):
provider: ApiClient | None
provider_options: dict[str, Any]
def _auth_headers(self) -> dict | None:
if self.genai_config.api_key:
return {"Authorization": "Bearer " + self.genai_config.api_key}
return None
def _init_provider(self) -> ApiClient | None:
"""Initialize the client."""
self.provider_options = {
@@ -82,11 +39,7 @@ class OllamaClient(GenAIClient):
}
try:
client = ApiClient(
host=self.genai_config.base_url,
timeout=self.timeout,
headers=self._auth_headers(),
)
client = ApiClient(host=self.genai_config.base_url, timeout=self.timeout)
# ensure the model is available locally
response = client.show(self.genai_config.model)
if response.get("error"):
@@ -213,9 +166,7 @@ class OllamaClient(GenAIClient):
return []
try:
client = ApiClient(
host=self.genai_config.base_url,
timeout=self.timeout,
headers=self._auth_headers(),
host=self.genai_config.base_url, timeout=self.timeout
)
except Exception:
return []
@@ -244,13 +195,10 @@ class OllamaClient(GenAIClient):
"""Build request_messages and params for chat (sync or stream)."""
request_messages = []
for msg in messages:
content, images = _normalize_multimodal_content(msg.get("content", ""))
msg_dict: dict[str, Any] = {
msg_dict = {
"role": msg.get("role"),
"content": content if content is not None else "",
"content": msg.get("content", ""),
}
if images:
msg_dict["images"] = images
if msg.get("tool_call_id"):
msg_dict["tool_call_id"] = msg["tool_call_id"]
if msg.get("name"):
@@ -396,7 +344,6 @@ class OllamaClient(GenAIClient):
async_client = OllamaAsyncClient(
host=self.genai_config.base_url,
timeout=self.timeout,
headers=self._auth_headers(),
)
response = await async_client.chat(**request_params)
result = self._message_from_response(response)
@@ -412,7 +359,6 @@ class OllamaClient(GenAIClient):
async_client = OllamaAsyncClient(
host=self.genai_config.base_url,
timeout=self.timeout,
headers=self._auth_headers(),
)
content_parts: list[str] = []
final_message: dict[str, Any] | None = None
-9
View File
@@ -73,17 +73,8 @@ 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")
-386
View File
@@ -1,386 +0,0 @@
"""Debug replay startup job: ffmpeg concat + camera config publish.
The runner orchestrates the async portion of starting a debug replay
session. The DebugReplayManager (in frigate.debug_replay) owns session
presence so the status bar can keep reading a single `active` flag from
/debug_replay/status for the entire session window which is broader
than this job's lifetime.
"""
import logging
import os
import subprocess as sp
import threading
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING, Any, Optional, cast
from peewee import ModelSelect
from frigate.config import FrigateConfig
from frigate.config.camera.updater import CameraConfigUpdatePublisher
from frigate.const import REPLAY_CAMERA_PREFIX, REPLAY_DIR
from frigate.jobs.export import JobStatePublisher
from frigate.jobs.job import Job
from frigate.jobs.manager import job_is_running, set_current_job
from frigate.models import Recordings
from frigate.types import JobStatusTypesEnum
from frigate.util.ffmpeg import run_ffmpeg_with_progress
if TYPE_CHECKING:
from frigate.debug_replay import DebugReplayManager
logger = logging.getLogger(__name__)
# Coalesce frequent ffmpeg progress callbacks so the WS isn't flooded.
PROGRESS_BROADCAST_MIN_INTERVAL = 1.0
JOB_TYPE = "debug_replay"
STEP_PREPARING_CLIP = "preparing_clip"
STEP_STARTING_CAMERA = "starting_camera"
_active_runner: Optional["DebugReplayJobRunner"] = None
_runner_lock = threading.Lock()
def _set_active_runner(runner: Optional["DebugReplayJobRunner"]) -> None:
global _active_runner
with _runner_lock:
_active_runner = runner
def get_active_runner() -> Optional["DebugReplayJobRunner"]:
with _runner_lock:
return _active_runner
@dataclass
class DebugReplayJob(Job):
"""Job state for a debug replay startup."""
job_type: str = JOB_TYPE
source_camera: str = ""
replay_camera_name: str = ""
start_ts: float = 0.0
end_ts: float = 0.0
current_step: Optional[str] = None
progress_percent: float = 0.0
def to_dict(self) -> dict[str, Any]:
"""Whitelisted payload for the job_state WS topic.
Replay-specific fields land in results so the frontend's
generic Job<TResults> type can be parameterised cleanly.
"""
return {
"id": self.id,
"job_type": self.job_type,
"status": self.status,
"start_time": self.start_time,
"end_time": self.end_time,
"error_message": self.error_message,
"results": {
"current_step": self.current_step,
"progress_percent": self.progress_percent,
"source_camera": self.source_camera,
"replay_camera_name": self.replay_camera_name,
"start_ts": self.start_ts,
"end_ts": self.end_ts,
},
}
def query_recordings(source_camera: str, start_ts: float, end_ts: float) -> ModelSelect:
"""Return the Recordings query for the time range.
Module-level so tests can patch it without instantiating a runner.
"""
query = (
Recordings.select(
Recordings.path,
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(start_ts, end_ts)
| Recordings.end_time.between(start_ts, end_ts)
| ((start_ts > Recordings.start_time) & (end_ts < Recordings.end_time))
)
.where(Recordings.camera == source_camera)
.order_by(Recordings.start_time.asc())
)
return cast(ModelSelect, query)
class DebugReplayJobRunner(threading.Thread):
"""Worker thread that drives the startup job to completion.
Owns the live ffmpeg Popen reference for cancellation. Cancellation
is two-step (threading.Event + proc.terminate()) so the runner
both knows it should stop and is unblocked from its blocking subprocess
wait.
"""
def __init__(
self,
job: DebugReplayJob,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
replay_manager: "DebugReplayManager",
publisher: Optional[JobStatePublisher] = None,
) -> None:
super().__init__(daemon=True, name=f"debug_replay_{job.id}")
self.job = job
self.frigate_config = frigate_config
self.config_publisher = config_publisher
self.replay_manager = replay_manager
self.publisher = publisher if publisher is not None else JobStatePublisher()
self._cancel_event = threading.Event()
self._active_process: sp.Popen | None = None
self._proc_lock = threading.Lock()
self._last_broadcast_monotonic: float = 0.0
def cancel(self) -> None:
"""Request cancellation. Idempotent."""
self._cancel_event.set()
with self._proc_lock:
proc = self._active_process
if proc is not None:
try:
proc.terminate()
except Exception as exc:
logger.warning("Failed to terminate ffmpeg subprocess: %s", exc)
def is_cancelled(self) -> bool:
return self._cancel_event.is_set()
def _record_proc(self, proc: sp.Popen) -> None:
with self._proc_lock:
self._active_process = proc
# Race: cancel arrived between Popen and _record_proc.
if self._cancel_event.is_set():
try:
proc.terminate()
except Exception:
pass
def _broadcast(self, force: bool = False) -> None:
now = time.monotonic()
if (
not force
and now - self._last_broadcast_monotonic < PROGRESS_BROADCAST_MIN_INTERVAL
):
return
self._last_broadcast_monotonic = now
try:
self.publisher.publish(self.job.to_dict())
except Exception as err:
logger.warning("Publisher raised during job state broadcast: %s", err)
def run(self) -> None:
replay_name = self.job.replay_camera_name
os.makedirs(REPLAY_DIR, exist_ok=True)
concat_file = os.path.join(REPLAY_DIR, f"{replay_name}_concat.txt")
clip_path = os.path.join(REPLAY_DIR, f"{replay_name}.mp4")
self.job.status = JobStatusTypesEnum.running
self.job.start_time = time.time()
self.job.current_step = STEP_PREPARING_CLIP
self._broadcast(force=True)
try:
recordings = query_recordings(
self.job.source_camera, self.job.start_ts, self.job.end_ts
)
with open(concat_file, "w") as f:
for recording in recordings:
f.write(f"file '{recording.path}'\n")
ffmpeg_cmd = [
self.frigate_config.ffmpeg.ffmpeg_path,
"-hide_banner",
"-y",
"-f",
"concat",
"-safe",
"0",
"-i",
concat_file,
"-c",
"copy",
"-movflags",
"+faststart",
clip_path,
]
logger.info(
"Generating replay clip for %s (%.1f - %.1f)",
self.job.source_camera,
self.job.start_ts,
self.job.end_ts,
)
def _on_progress(percent: float) -> None:
self.job.progress_percent = percent
self._broadcast()
try:
returncode, stderr = run_ffmpeg_with_progress(
ffmpeg_cmd,
expected_duration_seconds=max(
0.0, self.job.end_ts - self.job.start_ts
),
on_progress=_on_progress,
process_started=self._record_proc,
use_low_priority=True,
)
finally:
with self._proc_lock:
self._active_process = None
if self._cancel_event.is_set():
self._finalize_cancelled(clip_path)
return
if returncode != 0:
raise RuntimeError(f"FFmpeg failed: {stderr[-500:]}")
if not os.path.exists(clip_path):
raise RuntimeError("Clip file was not created")
self.job.current_step = STEP_STARTING_CAMERA
self.job.progress_percent = 100.0
self._broadcast(force=True)
if self._cancel_event.is_set():
self._finalize_cancelled(clip_path)
return
self.replay_manager.publish_camera(
source_camera=self.job.source_camera,
replay_name=replay_name,
clip_path=clip_path,
frigate_config=self.frigate_config,
config_publisher=self.config_publisher,
)
self.replay_manager.mark_session_ready(clip_path)
self.job.status = JobStatusTypesEnum.success
self.job.end_time = time.time()
self._broadcast(force=True)
logger.info(
"Debug replay started: %s -> %s",
self.job.source_camera,
replay_name,
)
except Exception as exc:
logger.exception("Debug replay startup failed")
self.job.status = JobStatusTypesEnum.failed
self.job.error_message = str(exc)
self.job.end_time = time.time()
self._broadcast(force=True)
self.replay_manager.clear_session()
_remove_silent(clip_path)
finally:
_remove_silent(concat_file)
_set_active_runner(None)
def _finalize_cancelled(self, clip_path: str) -> None:
logger.info("Debug replay startup cancelled")
self.job.status = JobStatusTypesEnum.cancelled
self.job.end_time = time.time()
self._broadcast(force=True)
# The caller of cancel_debug_replay_job (DebugReplayManager.stop) owns
# session cleanup — db rows, filesystem artifacts, clear_session. We
# only clean up the partial concat output we created.
_remove_silent(clip_path)
def _remove_silent(path: str) -> None:
try:
if os.path.exists(path):
os.remove(path)
except OSError:
pass
def start_debug_replay_job(
*,
source_camera: str,
start_ts: float,
end_ts: float,
frigate_config: FrigateConfig,
config_publisher: CameraConfigUpdatePublisher,
replay_manager: "DebugReplayManager",
) -> str:
"""Validate, create job, start runner. Returns the job id.
Raises ValueError for bad params (camera missing, time range
invalid, no recordings) and RuntimeError if a session is already
active.
"""
if job_is_running(JOB_TYPE) or replay_manager.active:
raise RuntimeError("A replay session is already active")
if source_camera not in frigate_config.cameras:
raise ValueError(f"Camera '{source_camera}' not found")
if end_ts <= start_ts:
raise ValueError("End time must be after start time")
recordings = query_recordings(source_camera, start_ts, end_ts)
if not recordings.count():
raise ValueError(
f"No recordings found for camera '{source_camera}' in the specified time range"
)
replay_name = f"{REPLAY_CAMERA_PREFIX}{source_camera}"
replay_manager.mark_starting(
source_camera=source_camera,
replay_camera_name=replay_name,
start_ts=start_ts,
end_ts=end_ts,
)
job = DebugReplayJob(
source_camera=source_camera,
replay_camera_name=replay_name,
start_ts=start_ts,
end_ts=end_ts,
)
set_current_job(job)
runner = DebugReplayJobRunner(
job=job,
frigate_config=frigate_config,
config_publisher=config_publisher,
replay_manager=replay_manager,
)
_set_active_runner(runner)
runner.start()
return job.id
def cancel_debug_replay_job() -> bool:
"""Signal the active runner to cancel.
Returns True if a runner was signalled, False if no job was active.
"""
runner = get_active_runner()
if runner is None:
return False
runner.cancel()
return True
def wait_for_runner(timeout: float = 2.0) -> bool:
"""Join the active runner. Returns True if the runner ended in time."""
runner = get_active_runner()
if runner is None:
return True
runner.join(timeout=timeout)
return not runner.is_alive()
+9 -21
View File
@@ -8,6 +8,7 @@ import os
import queue
import subprocess as sp
import threading
import time
import traceback
from multiprocessing.synchronize import Event as MpEvent
from typing import Any, Optional
@@ -18,7 +19,6 @@ import numpy as np
from frigate.comms.inter_process import InterProcessRequestor
from frigate.config import BirdseyeModeEnum, FfmpegConfig, FrigateConfig
from frigate.const import BASE_DIR, BIRDSEYE_PIPE, INSTALL_DIR, UPDATE_BIRDSEYE_LAYOUT
from frigate.output.ws_auth import ws_has_camera_access
from frigate.util.image import (
SharedMemoryFrameManager,
copy_yuv_to_position,
@@ -62,10 +62,8 @@ def get_canvas_shape(width: int, height: int) -> tuple[int, int]:
if round(a_w / a_h, 2) != round(width / height, 2):
canvas_width = int(width // 4 * 4)
canvas_height = int((canvas_width / a_w * a_h) // 4 * 4)
logger.error(
f"Birdseye resolution {width}x{height} is not a supported aspect ratio "
f"and may cause visual distortion; falling back to {canvas_width}x{canvas_height}. "
f"Set width and height to a supported aspect ratio (16:9, 20:10, 16:6, 32:9, 12:9, 22:15, 9:16, 9:12, 16:3, or 1:1)"
logger.warning(
f"The birdseye resolution is a non-standard aspect ratio, forcing birdseye resolution to {canvas_width} x {canvas_height}"
)
return (canvas_width, canvas_height)
@@ -238,14 +236,12 @@ class BroadcastThread(threading.Thread):
converter: FFMpegConverter,
websocket_server: Any,
stop_event: MpEvent,
config: FrigateConfig,
):
super().__init__()
self.camera = camera
self.converter = converter
self.websocket_server = websocket_server
self.stop_event = stop_event
self.config = config
def run(self) -> None:
while not self.stop_event.is_set():
@@ -260,7 +256,6 @@ class BroadcastThread(threading.Thread):
if (
not ws.terminated
and ws.environ["PATH_INFO"] == f"/{self.camera}"
and ws_has_camera_access(ws, self.camera, self.config)
):
try:
ws.send(buf, binary=True)
@@ -798,27 +793,20 @@ class Birdseye:
websocket_server: Any,
) -> None:
self.config = config
canvas_width, canvas_height = get_canvas_shape(
config.birdseye.width, config.birdseye.height
)
self.input: queue.Queue[bytes] = queue.Queue(maxsize=10)
self.converter = FFMpegConverter(
config.ffmpeg,
self.input,
stop_event,
canvas_width,
canvas_height,
canvas_width,
canvas_height,
config.birdseye.width,
config.birdseye.height,
config.birdseye.width,
config.birdseye.height,
config.birdseye.quality,
config.birdseye.restream,
)
self.broadcaster = BroadcastThread(
"birdseye",
self.converter,
websocket_server,
stop_event,
config,
"birdseye", self.converter, websocket_server, stop_event
)
self.birdseye_manager = BirdsEyeFrameManager(self.config, stop_event)
self.frame_manager = SharedMemoryFrameManager()
@@ -886,7 +874,7 @@ class Birdseye:
coordinates = self.birdseye_manager.get_camera_coordinates()
self.requestor.send_data(UPDATE_BIRDSEYE_LAYOUT, coordinates)
if self._idle_interval:
now = datetime.datetime.now().timestamp()
now = time.monotonic()
is_idle = len(self.birdseye_manager.camera_layout) == 0
if (
is_idle
+3 -15
View File
@@ -7,8 +7,7 @@ import threading
from multiprocessing.synchronize import Event as MpEvent
from typing import Any
from frigate.config import CameraConfig, FfmpegConfig, FrigateConfig
from frigate.output.ws_auth import ws_has_camera_access
from frigate.config import CameraConfig, FfmpegConfig
logger = logging.getLogger(__name__)
@@ -103,14 +102,12 @@ class BroadcastThread(threading.Thread):
converter: FFMpegConverter,
websocket_server: Any,
stop_event: MpEvent,
config: FrigateConfig,
):
super().__init__()
self.camera = camera
self.converter = converter
self.websocket_server = websocket_server
self.stop_event = stop_event
self.config = config
def run(self) -> None:
while not self.stop_event.is_set():
@@ -125,7 +122,6 @@ class BroadcastThread(threading.Thread):
if (
not ws.terminated
and ws.environ["PATH_INFO"] == f"/{self.camera}"
and ws_has_camera_access(ws, self.camera, self.config)
):
try:
ws.send(buf, binary=True)
@@ -139,11 +135,7 @@ class BroadcastThread(threading.Thread):
class JsmpegCamera:
def __init__(
self,
config: CameraConfig,
frigate_config: FrigateConfig,
stop_event: MpEvent,
websocket_server: Any,
self, config: CameraConfig, stop_event: MpEvent, websocket_server: Any
) -> None:
self.config = config
self.input: queue.Queue[bytes] = queue.Queue(maxsize=config.detect.fps)
@@ -162,11 +154,7 @@ class JsmpegCamera:
config.live.quality,
)
self.broadcaster = BroadcastThread(
config.name or "",
self.converter,
websocket_server,
stop_event,
frigate_config,
config.name or "", self.converter, websocket_server, stop_event
)
self.converter.start()
+1 -11
View File
@@ -32,7 +32,6 @@ from frigate.const import (
from frigate.output.birdseye import Birdseye
from frigate.output.camera import JsmpegCamera
from frigate.output.preview import PreviewRecorder
from frigate.output.ws_auth import ws_has_camera_access
from frigate.util.image import SharedMemoryFrameManager, get_blank_yuv_frame
from frigate.util.process import FrigateProcess
@@ -103,7 +102,7 @@ class OutputProcess(FrigateProcess):
) -> None:
camera_config = self.config.cameras[camera]
jsmpeg_cameras[camera] = JsmpegCamera(
camera_config, self.config, self.stop_event, websocket_server
camera_config, self.stop_event, websocket_server
)
preview_recorders[camera] = PreviewRecorder(camera_config)
preview_write_times[camera] = 0
@@ -263,7 +262,6 @@ class OutputProcess(FrigateProcess):
# send camera frame to ffmpeg process if websockets are connected
if any(
ws.environ["PATH_INFO"].endswith(camera)
and ws_has_camera_access(ws, camera, self.config)
for ws in websocket_server.manager
):
# write to the converter for the camera if clients are listening to the specific camera
@@ -277,7 +275,6 @@ class OutputProcess(FrigateProcess):
self.config.birdseye.restream
or any(
ws.environ["PATH_INFO"].endswith("birdseye")
and ws_has_camera_access(ws, "birdseye", self.config)
for ws in websocket_server.manager
)
)
@@ -349,13 +346,6 @@ def move_preview_frames(loc: str) -> None:
if not os.path.exists(preview_holdover):
return
if not os.access(preview_holdover, os.R_OK | os.W_OK):
logger.error(
"Insufficient permissions on preview restart cache at %s",
preview_holdover,
)
return
shutil.move(preview_holdover, preview_cache)
except shutil.Error:
logger.error("Failed to restore preview cache.")
+3 -6
View File
@@ -361,17 +361,14 @@ class PreviewRecorder:
small_frame,
cv2.COLOR_YUV2BGR_I420,
)
cache_path = get_cache_image_name(self.camera_name, frame_time)
if not cv2.imwrite(
cache_path,
cv2.imwrite(
get_cache_image_name(self.camera_name, frame_time),
small_frame,
[
int(cv2.IMWRITE_WEBP_QUALITY),
PREVIEW_QUALITY_WEBP[self.config.record.preview.quality],
],
):
logger.error("Failed to write preview frame to %s", cache_path)
)
def write_data(
self,
-43
View File
@@ -1,43 +0,0 @@
"""Authorization helpers for JSMPEG websocket clients."""
from typing import Any
from frigate.config import FrigateConfig
from frigate.models import User
def _get_valid_ws_roles(ws: Any, config: FrigateConfig) -> list[str]:
role_header = ws.environ.get("HTTP_REMOTE_ROLE", "")
roles = [
role.strip()
for role in role_header.split(config.proxy.separator)
if role.strip()
]
return [role for role in roles if role in config.auth.roles]
def ws_has_camera_access(ws: Any, camera_name: str, config: FrigateConfig) -> bool:
"""Return True when a websocket client is authorized for the camera path."""
roles = _get_valid_ws_roles(ws, config)
if not roles:
return False
roles_dict = config.auth.roles
# Birdseye is a composite stream, so only users with unrestricted access
# should receive it.
if camera_name == "birdseye":
return any(role == "admin" or not roles_dict.get(role) for role in roles)
all_camera_names = set(config.cameras.keys())
for role in roles:
if role == "admin" or not roles_dict.get(role):
return True
allowed_cameras = User.get_allowed_cameras(role, roles_dict, all_camera_names)
if camera_name in allowed_cameras:
return True
return False
+3 -5
View File
@@ -351,11 +351,9 @@ class RecordingCleanup(threading.Thread):
)
.where(
ReviewSegment.camera == camera,
# candidate recordings can extend up to continuous_expire_date
# (the no-motion no-audio branch of the recordings query),
# so reviews must cover that full range to avoid deleting
# segments that overlap recent alerts/detections.
ReviewSegment.start_time < continuous_expire_date,
# need to ensure segments for all reviews starting
# before the expire date are included
ReviewSegment.start_time < motion_expire_date,
)
.order_by(ReviewSegment.start_time)
.namedtuples()
+111 -190
View File
@@ -13,7 +13,6 @@ from enum import Enum
from pathlib import Path
from typing import Callable, Optional
import pytz # type: ignore[import-untyped]
from peewee import DoesNotExist
from frigate.config import FfmpegConfig, FrigateConfig
@@ -23,13 +22,13 @@ from frigate.const import (
EXPORT_DIR,
MAX_PLAYLIST_SECONDS,
PREVIEW_FRAME_TYPE,
PROCESS_PRIORITY_LOW,
)
from frigate.ffmpeg_presets import (
EncodeTypeEnum,
parse_preset_hardware_acceleration_encode,
)
from frigate.models import Export, Previews, Recordings, ReviewSegment
from frigate.util.ffmpeg import run_ffmpeg_with_progress
from frigate.models import Export, Previews, Recordings
from frigate.util.time import is_current_hour
logger = logging.getLogger(__name__)
@@ -243,176 +242,110 @@ class RecordingExporter(threading.Thread):
return total
def _inject_progress_flags(self, ffmpeg_cmd: list[str]) -> list[str]:
"""Insert FFmpeg progress reporting flags before the output path.
``-progress pipe:2`` writes structured key=value lines to stderr,
``-nostats`` suppresses the noisy default stats output.
"""
if not ffmpeg_cmd:
return ffmpeg_cmd
return ffmpeg_cmd[:-1] + ["-progress", "pipe:2", "-nostats", ffmpeg_cmd[-1]]
def _run_ffmpeg_with_progress(
self,
ffmpeg_cmd: list[str],
playlist_lines: str | list[str],
step: str = "encoding",
) -> tuple[int, str]:
"""Delegate to the shared helper, mapping percent → (step, percent).
"""Run an FFmpeg export command, parsing progress events from stderr.
Returns ``(returncode, captured_stderr)``.
Returns ``(returncode, captured_stderr)``. Stdout is left attached to
the parent process so we don't have to drain it (and risk a deadlock
if the buffer fills). Progress percent is computed against the
expected output duration; values are clamped to [0, 100] inside
:py:meth:`_emit_progress`.
"""
cmd = ["nice", "-n", str(PROCESS_PRIORITY_LOW)] + self._inject_progress_flags(
ffmpeg_cmd
)
if isinstance(playlist_lines, list):
stdin_payload = "\n".join(playlist_lines)
else:
stdin_payload = playlist_lines
return run_ffmpeg_with_progress(
ffmpeg_cmd,
expected_duration_seconds=self._expected_output_duration_seconds(),
on_progress=lambda percent: self._emit_progress(step, percent),
stdin_payload=stdin_payload,
use_low_priority=True,
expected_duration = self._expected_output_duration_seconds()
self._emit_progress(step, 0.0)
proc = sp.Popen(
cmd,
stdin=sp.PIPE,
stderr=sp.PIPE,
text=True,
encoding="ascii",
errors="replace",
)
def get_datetime_from_timestamp(self, timestamp: int) -> str:
# return in iso format using the configured ui.timezone when set,
# so the auto-generated export name reflects local time rather
# than the container's UTC clock
tz_name = self.config.ui.timezone
if tz_name:
assert proc.stdin is not None
assert proc.stderr is not None
try:
proc.stdin.write(stdin_payload)
except (BrokenPipeError, OSError):
# FFmpeg may have rejected the input early; still wait for it
# to terminate so the returncode is meaningful.
pass
finally:
try:
tz = pytz.timezone(tz_name)
except pytz.UnknownTimeZoneError:
tz = None
if tz is not None:
return datetime.datetime.fromtimestamp(timestamp, tz=tz).strftime(
"%Y-%m-%d %H:%M:%S"
)
return datetime.datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")
proc.stdin.close()
except (BrokenPipeError, OSError):
pass
def _chapter_metadata_path(self) -> str:
return os.path.join(CACHE_DIR, f"export_chapters_{self.export_id}.txt")
def _build_chapter_metadata_file(self, recordings: list) -> Optional[str]:
"""Write an FFmpeg metadata file with chapters for review items in range.
Chapter offsets are computed in *output time*: the VOD endpoint
concatenates recording clips back-to-back, so wall-clock gaps
between recordings collapse in the produced video. We walk the
same recording rows that feed the playlist and convert each
review item's wall-clock boundaries into output-time offsets.
Returns ``None`` when there are no recordings, no review items,
or any chapter would have zero output duration.
"""
if not recordings:
return None
windows: list[tuple[float, float, float]] = []
output_offset = 0.0
for rec in recordings:
clipped_start = max(float(rec.start_time), float(self.start_time))
clipped_end = min(float(rec.end_time), float(self.end_time))
if clipped_end <= clipped_start:
continue
windows.append((clipped_start, clipped_end, output_offset))
output_offset += clipped_end - clipped_start
if not windows:
return None
captured: list[str] = []
try:
review_rows = list(
ReviewSegment.select(
ReviewSegment.start_time,
ReviewSegment.end_time,
ReviewSegment.severity,
ReviewSegment.data,
)
.where(
ReviewSegment.start_time.between(self.start_time, self.end_time)
| ReviewSegment.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > ReviewSegment.start_time)
& (self.end_time < ReviewSegment.end_time)
)
)
.where(ReviewSegment.camera == self.camera)
.order_by(ReviewSegment.start_time.asc())
.iterator()
)
for raw_line in proc.stderr:
captured.append(raw_line)
line = raw_line.strip()
if not line:
continue
if line.startswith("out_time_us="):
if expected_duration <= 0:
continue
try:
out_time_us = int(line.split("=", 1)[1])
except (ValueError, IndexError):
continue
if out_time_us < 0:
continue
out_seconds = out_time_us / 1_000_000.0
percent = (out_seconds / expected_duration) * 100.0
self._emit_progress(step, percent)
elif line == "progress=end":
self._emit_progress(step, 100.0)
break
except Exception:
logger.exception(
"Failed to query review segments for export %s", self.export_id
)
return None
logger.exception("Failed reading FFmpeg progress for %s", self.export_id)
if not review_rows:
return None
proc.wait()
total_output = windows[-1][2] + (windows[-1][1] - windows[-1][0])
last_recorded_end = windows[-1][1]
def wall_to_output(t: float) -> float:
t = max(float(self.start_time), min(float(self.end_time), t))
for w_start, w_end, w_offset in windows:
if t < w_start:
return w_offset
if t <= w_end:
return w_offset + (t - w_start)
return total_output
chapter_blocks: list[str] = []
for review in review_rows:
if review.start_time is None:
continue
# In-progress segments have a NULL end_time until the activity
# closes; clamp to the last recorded second so the chapter never
# extends past the actual video.
review_end = (
float(review.end_time)
if review.end_time is not None
else last_recorded_end
)
start_out = wall_to_output(float(review.start_time))
end_out = wall_to_output(review_end)
# Drop chapters that fall entirely in a recording gap, or are
# too short to be navigable in a player.
if end_out - start_out < 1.0:
continue
data = review.data or {}
labels: list[str] = []
for obj in data.get("objects") or []:
label = str(obj).split("-")[0]
if label and label not in labels:
labels.append(label)
metadata = data.get("metadata") or {}
title = metadata.get("title")
if not title:
title = str(review.severity).capitalize()
if labels:
title = f"{title}: {', '.join(labels)}"
chapter_blocks.append(
"[CHAPTER]\n"
"TIMEBASE=1/1000\n"
f"START={int(start_out * 1000)}\n"
f"END={int(end_out * 1000)}\n"
f"title={title}"
)
if not chapter_blocks:
return None
meta_path = self._chapter_metadata_path()
# Drain any remaining stderr so callers can log it on failure.
try:
with open(meta_path, "w", encoding="utf-8") as f:
f.write(";FFMETADATA1\n")
f.write("\n".join(chapter_blocks))
f.write("\n")
except OSError:
logger.exception(
"Failed to write chapter metadata file for export %s", self.export_id
)
return None
remaining = proc.stderr.read()
if remaining:
captured.append(remaining)
except Exception:
pass
return meta_path
return proc.returncode, "".join(captured)
def get_datetime_from_timestamp(self, timestamp: int) -> str:
# return in iso format
return datetime.datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")
def save_thumbnail(self, id: str) -> str:
thumb_path = os.path.join(CLIPS_DIR, f"export/{id}.webp")
@@ -454,14 +387,16 @@ class RecordingExporter(threading.Thread):
except DoesNotExist:
return ""
diff = max(0.0, float(self.start_time) - float(preview.start_time))
diff = self.start_time - preview.start_time
minutes = int(diff / 60)
seconds = int(diff % 60)
ffmpeg_cmd = [
"/usr/lib/ffmpeg/7.0/bin/ffmpeg", # hardcode path for exports thumbnail due to missing libwebp support
"-hide_banner",
"-loglevel",
"warning",
"-ss",
f"{diff:.3f}",
f"00:{minutes}:{seconds}",
"-i",
preview.path,
"-frames",
@@ -487,18 +422,12 @@ class RecordingExporter(threading.Thread):
start_file = f"{file_start}{self.start_time}.{PREVIEW_FRAME_TYPE}"
end_file = f"{file_start}{self.end_time}.{PREVIEW_FRAME_TYPE}"
selected_preview = None
# Preview frames are written at most 1-2 fps during activity
# and as little as one every 30s during quiet periods, so a
# short export window can contain zero frames. Track the most
# recent frame before the window as a fallback.
fallback_preview = None
for file in sorted(os.listdir(preview_dir)):
if not file.startswith(file_start):
continue
if file < start_file:
fallback_preview = os.path.join(preview_dir, file)
continue
if file > end_file:
@@ -507,9 +436,6 @@ class RecordingExporter(threading.Thread):
selected_preview = os.path.join(preview_dir, file)
break
if not selected_preview:
selected_preview = fallback_preview
if not selected_preview:
return ""
@@ -525,24 +451,6 @@ class RecordingExporter(threading.Thread):
if type(internal_port) is str:
internal_port = int(internal_port.split(":")[-1])
recordings = list(
Recordings.select(
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(self.start_time, self.end_time)
| Recordings.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > Recordings.start_time)
& (self.end_time < Recordings.end_time)
)
)
.where(Recordings.camera == self.camera)
.order_by(Recordings.start_time.asc())
.iterator()
)
playlist_lines: list[str] = []
if (self.end_time - self.start_time) <= MAX_PLAYLIST_SECONDS:
playlist_url = f"http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{self.start_time}/end/{self.end_time}/index.m3u8"
@@ -550,13 +458,32 @@ class RecordingExporter(threading.Thread):
f"-y -protocol_whitelist pipe,file,http,tcp -i {playlist_url}"
)
else:
# Chunk the recording rows into pages so each playlist line
# references a bounded sub-range rather than the full export.
# get full set of recordings
export_recordings = (
Recordings.select(
Recordings.start_time,
Recordings.end_time,
)
.where(
Recordings.start_time.between(self.start_time, self.end_time)
| Recordings.end_time.between(self.start_time, self.end_time)
| (
(self.start_time > Recordings.start_time)
& (self.end_time < Recordings.end_time)
)
)
.where(Recordings.camera == self.camera)
.order_by(Recordings.start_time.asc())
)
# Use pagination to process records in chunks
page_size = 1000
for i in range(0, len(recordings), page_size):
chunk = recordings[i : i + page_size]
num_pages = (export_recordings.count() + page_size - 1) // page_size
for page in range(1, num_pages + 1):
playlist = export_recordings.paginate(page, page_size)
playlist_lines.append(
f"file 'http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{float(chunk[0].start_time)}/end/{float(chunk[-1].end_time)}/index.m3u8'"
f"file 'http://127.0.0.1:{internal_port}/vod/{self.camera}/start/{float(playlist[0].start_time)}/end/{float(playlist[-1].end_time)}/index.m3u8'"
)
ffmpeg_input = "-y -protocol_whitelist pipe,file,http,tcp -f concat -safe 0 -i /dev/stdin"
@@ -577,12 +504,8 @@ class RecordingExporter(threading.Thread):
)
).split(" ")
else:
chapters_path = self._build_chapter_metadata_file(recordings)
chapter_args = (
f" -i {chapters_path} -map 0 -map_metadata 1" if chapters_path else ""
)
ffmpeg_cmd = (
f"{self.config.ffmpeg.ffmpeg_path} -hide_banner {ffmpeg_input}{chapter_args} -c copy -movflags +faststart"
f"{self.config.ffmpeg.ffmpeg_path} -hide_banner {ffmpeg_input} -c copy -movflags +faststart"
).split(" ")
# add metadata
@@ -768,8 +691,6 @@ class RecordingExporter(threading.Thread):
ffmpeg_cmd, playlist_lines, step="encoding_retry"
)
Path(self._chapter_metadata_path()).unlink(missing_ok=True)
if returncode != 0:
logger.error(
f"Failed to export {self.playback_source.value} for command {' '.join(ffmpeg_cmd)}"
@@ -1,123 +0,0 @@
"""Tests for /debug_replay API endpoints."""
from unittest.mock import patch
from frigate.models import Event, Recordings, ReviewSegment
from frigate.test.http_api.base_http_test import AuthTestClient, BaseTestHttp
class TestDebugReplayAPI(BaseTestHttp):
def setUp(self):
super().setUp([Event, Recordings, ReviewSegment])
self.app = self.create_app()
def test_start_returns_202_with_job_id(self):
# Stub the factory to skip validation/threading and just record the
# name on the manager the way the real factory's mark_starting would.
def fake_start(**kwargs):
kwargs["replay_manager"].mark_starting(
source_camera=kwargs["source_camera"],
replay_camera_name="_replay_front",
start_ts=kwargs["start_ts"],
end_ts=kwargs["end_ts"],
)
return "job-1234"
with patch(
"frigate.api.debug_replay.start_debug_replay_job",
side_effect=fake_start,
):
with AuthTestClient(self.app) as client:
resp = client.post(
"/debug_replay/start",
json={
"camera": "front",
"start_time": 100,
"end_time": 200,
},
)
self.assertEqual(resp.status_code, 202)
body = resp.json()
self.assertTrue(body["success"])
self.assertEqual(body["job_id"], "job-1234")
self.assertEqual(body["replay_camera"], "_replay_front")
def test_start_returns_400_on_validation_error(self):
with patch(
"frigate.api.debug_replay.start_debug_replay_job",
side_effect=ValueError("Camera 'missing' not found"),
):
with AuthTestClient(self.app) as client:
resp = client.post(
"/debug_replay/start",
json={
"camera": "missing",
"start_time": 100,
"end_time": 200,
},
)
self.assertEqual(resp.status_code, 400)
body = resp.json()
self.assertFalse(body["success"])
# Message is hard-coded so we don't echo exception text back to clients
# (CodeQL: information exposure through an exception).
self.assertEqual(body["message"], "Invalid debug replay parameters")
def test_start_returns_409_when_session_already_active(self):
with patch(
"frigate.api.debug_replay.start_debug_replay_job",
side_effect=RuntimeError("A replay session is already active"),
):
with AuthTestClient(self.app) as client:
resp = client.post(
"/debug_replay/start",
json={
"camera": "front",
"start_time": 100,
"end_time": 200,
},
)
self.assertEqual(resp.status_code, 409)
body = resp.json()
self.assertFalse(body["success"])
def test_status_inactive_when_no_session(self):
with AuthTestClient(self.app) as client:
resp = client.get("/debug_replay/status")
self.assertEqual(resp.status_code, 200)
body = resp.json()
self.assertFalse(body["active"])
self.assertIsNone(body["replay_camera"])
self.assertIsNone(body["source_camera"])
self.assertIsNone(body["start_time"])
self.assertIsNone(body["end_time"])
self.assertFalse(body["live_ready"])
# Make sure deprecated fields are gone
self.assertNotIn("state", body)
self.assertNotIn("progress_percent", body)
self.assertNotIn("error_message", body)
def test_status_active_after_mark_starting(self):
manager = self.app.replay_manager
manager.mark_starting(
source_camera="front",
replay_camera_name="_replay_front",
start_ts=100.0,
end_ts=200.0,
)
with AuthTestClient(self.app) as client:
resp = client.get("/debug_replay/status")
self.assertEqual(resp.status_code, 200)
body = resp.json()
self.assertTrue(body["active"])
self.assertEqual(body["replay_camera"], "_replay_front")
self.assertEqual(body["source_camera"], "front")
self.assertEqual(body["start_time"], 100.0)
self.assertEqual(body["end_time"], 200.0)
self.assertFalse(body["live_ready"])
-20
View File
@@ -23,26 +23,6 @@ class TestHttpApp(BaseTestHttp):
response_json = response.json()
assert response_json == self.test_stats
def test_recordings_storage_requires_admin(self):
stats = Mock(spec=StatsEmitter)
stats.get_latest_stats.return_value = self.test_stats
app = super().create_app(stats)
app.storage_maintainer = Mock()
app.storage_maintainer.calculate_camera_usages.return_value = {
"front_door": {"usage": 2.0},
}
with AuthTestClient(app) as client:
response = client.get(
"/recordings/storage",
headers={"remote-user": "viewer", "remote-role": "viewer"},
)
assert response.status_code == 403
response = client.get("/recordings/storage")
assert response.status_code == 200
assert response.json()["front_door"]["usage_percent"] == 25.0
def test_config_set_in_memory_replaces_objects_track_list(self):
self.minimal_config["cameras"]["front_door"]["objects"] = {
"track": ["person", "car"],
-19
View File
@@ -219,25 +219,6 @@ class TestHttpApp(BaseTestHttp):
assert len(events) == 1
assert events[0]["id"] == event_id
def test_similarity_search_hides_unauthorized_anchor_event(self):
mock_embeddings = Mock()
self.app.frigate_config.semantic_search.enabled = True
self.app.embeddings = mock_embeddings
with AuthTestClient(self.app) as client:
super().insert_mock_event("hidden.anchor", camera="back_door")
response = client.get(
"/events/search",
params={
"search_type": "similarity",
"event_id": "hidden.anchor",
},
)
assert response.status_code == 404
assert response.json()["message"] == "Event not found"
mock_embeddings.search_thumbnail.assert_not_called()
def test_get_good_event(self):
id = "123456.random"
@@ -145,12 +145,9 @@ class TestExecuteFindSimilarObjects(unittest.TestCase):
embeddings=embeddings,
frigate_config=SimpleNamespace(
semantic_search=SimpleNamespace(enabled=semantic_enabled),
cameras={"driveway": object()},
auth=SimpleNamespace(roles={"admin": [], "viewer": ["driveway"]}),
proxy=SimpleNamespace(separator=","),
),
)
return SimpleNamespace(app=app, headers={})
return SimpleNamespace(app=app)
def test_semantic_search_disabled_returns_error(self):
req = self._make_request(semantic_enabled=False)
@@ -183,7 +180,7 @@ class TestExecuteFindSimilarObjects(unittest.TestCase):
_execute_find_similar_objects(
req,
{"event_id": "anchor", "cameras": ["nonexistent_cam"]},
allowed_cameras=["driveway"],
allowed_cameras=["nonexistent_cam"],
)
)
self.assertEqual(result["results"], [])
+3 -4
View File
@@ -64,9 +64,9 @@ class TestConfig(unittest.TestCase):
def test_config_class(self):
frigate_config = FrigateConfig(**self.minimal)
assert "ov" in frigate_config.detectors.keys()
assert frigate_config.detectors["ov"].type == DetectorTypeEnum.openvino
assert frigate_config.detectors["ov"].model.width == 300
assert "cpu" in frigate_config.detectors.keys()
assert frigate_config.detectors["cpu"].type == DetectorTypeEnum.cpu
assert frigate_config.detectors["cpu"].model.width == 320
@patch("frigate.detectors.detector_config.load_labels")
def test_detector_custom_model_path(self, mock_labels):
@@ -1005,7 +1005,6 @@ class TestConfig(unittest.TestCase):
config = {
"mqtt": {"host": "mqtt"},
"detectors": {"cpu": {"type": "cpu"}},
"model": {"path": "plus://test"},
"cameras": {
"back": {
-242
View File
@@ -1,242 +0,0 @@
"""Tests for the simplified DebugReplayManager.
Startup orchestration lives in ``frigate.jobs.debug_replay`` (covered by
``test_debug_replay_job``). The manager owns only session presence and
cleanup.
"""
import unittest
import unittest.mock
from unittest.mock import MagicMock, patch
class TestDebugReplayManagerSession(unittest.TestCase):
def test_inactive_by_default(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
self.assertFalse(manager.active)
self.assertIsNone(manager.replay_camera_name)
self.assertIsNone(manager.source_camera)
self.assertIsNone(manager.clip_path)
self.assertIsNone(manager.start_ts)
self.assertIsNone(manager.end_ts)
def test_mark_starting_sets_session_pointers_and_active(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting(
source_camera="front",
replay_camera_name="_replay_front",
start_ts=100.0,
end_ts=200.0,
)
self.assertTrue(manager.active)
self.assertEqual(manager.replay_camera_name, "_replay_front")
self.assertEqual(manager.source_camera, "front")
self.assertEqual(manager.start_ts, 100.0)
self.assertEqual(manager.end_ts, 200.0)
self.assertIsNone(manager.clip_path)
def test_mark_session_ready_sets_clip_path(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting("front", "_replay_front", 100.0, 200.0)
manager.mark_session_ready(clip_path="/tmp/replay/_replay_front.mp4")
self.assertEqual(manager.clip_path, "/tmp/replay/_replay_front.mp4")
self.assertTrue(manager.active)
def test_clear_session_resets_all_pointers(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting("front", "_replay_front", 100.0, 200.0)
manager.mark_session_ready("/tmp/replay/clip.mp4")
manager.clear_session()
self.assertFalse(manager.active)
self.assertIsNone(manager.replay_camera_name)
self.assertIsNone(manager.source_camera)
self.assertIsNone(manager.clip_path)
self.assertIsNone(manager.start_ts)
self.assertIsNone(manager.end_ts)
class TestDebugReplayManagerStop(unittest.TestCase):
def test_stop_when_inactive_is_a_noop(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
frigate_config = MagicMock()
frigate_config.cameras = {}
publisher = MagicMock()
# Should not raise; should not publish any events.
manager.stop(frigate_config=frigate_config, config_publisher=publisher)
publisher.publish_update.assert_not_called()
def test_stop_publishes_remove_when_camera_was_published(self) -> None:
from frigate.config.camera.updater import CameraConfigUpdateEnum
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting("front", "_replay_front", 100.0, 200.0)
manager.mark_session_ready("/tmp/replay/_replay_front.mp4")
camera_config = MagicMock()
frigate_config = MagicMock()
frigate_config.cameras = {"_replay_front": camera_config}
publisher = MagicMock()
with (
patch.object(manager, "_cleanup_db"),
patch.object(manager, "_cleanup_files"),
patch("frigate.debug_replay.cancel_debug_replay_job", return_value=False),
):
manager.stop(frigate_config=frigate_config, config_publisher=publisher)
# One publish_update call with a remove topic.
self.assertEqual(publisher.publish_update.call_count, 1)
topic_arg = publisher.publish_update.call_args.args[0]
self.assertEqual(topic_arg.update_type, CameraConfigUpdateEnum.remove)
self.assertFalse(manager.active)
def test_stop_skips_remove_publish_when_camera_not_in_config(self) -> None:
"""Cancellation during preparing_clip: no camera was published yet."""
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting("front", "_replay_front", 100.0, 200.0)
# clip_path stays None because we cancelled before camera publish.
frigate_config = MagicMock()
frigate_config.cameras = {} # _replay_front not present
publisher = MagicMock()
with (
patch.object(manager, "_cleanup_db"),
patch.object(manager, "_cleanup_files"),
patch("frigate.debug_replay.cancel_debug_replay_job", return_value=True),
):
manager.stop(frigate_config=frigate_config, config_publisher=publisher)
publisher.publish_update.assert_not_called()
self.assertFalse(manager.active)
def test_stop_calls_cancel_debug_replay_job(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
manager.mark_starting("front", "_replay_front", 100.0, 200.0)
frigate_config = MagicMock()
frigate_config.cameras = {}
publisher = MagicMock()
with (
patch.object(manager, "_cleanup_db"),
patch.object(manager, "_cleanup_files"),
patch(
"frigate.debug_replay.cancel_debug_replay_job",
return_value=True,
) as mock_cancel,
):
manager.stop(frigate_config=frigate_config, config_publisher=publisher)
mock_cancel.assert_called_once()
class TestDebugReplayManagerPublishCamera(unittest.TestCase):
def test_publish_camera_invokes_publisher_with_add_topic(self) -> None:
from frigate.config.camera.updater import CameraConfigUpdateEnum
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
source_config = MagicMock()
new_camera_config = MagicMock()
frigate_config = MagicMock()
frigate_config.cameras = {"front": source_config}
publisher = MagicMock()
with (
patch.object(
manager,
"_build_camera_config_dict",
return_value={"enabled": True},
),
patch("frigate.debug_replay.find_config_file", return_value="/cfg.yml"),
patch("frigate.debug_replay.YAML") as yaml_cls,
patch("frigate.debug_replay.FrigateConfig.parse_object") as parse_object,
patch("builtins.open", unittest.mock.mock_open(read_data="cameras:\n")),
):
yaml_instance = yaml_cls.return_value
yaml_instance.load.return_value = {"cameras": {}}
parsed = MagicMock()
parsed.cameras = {"_replay_front": new_camera_config}
parse_object.return_value = parsed
manager.publish_camera(
source_camera="front",
replay_name="_replay_front",
clip_path="/tmp/clip.mp4",
frigate_config=frigate_config,
config_publisher=publisher,
)
# Camera registered into the live config dict
self.assertIn("_replay_front", frigate_config.cameras)
# Publisher invoked with an add topic
self.assertEqual(publisher.publish_update.call_count, 1)
topic_arg = publisher.publish_update.call_args.args[0]
self.assertEqual(topic_arg.update_type, CameraConfigUpdateEnum.add)
def test_publish_camera_wraps_parse_failure_in_runtime_error(self) -> None:
from frigate.debug_replay import DebugReplayManager
manager = DebugReplayManager()
frigate_config = MagicMock()
frigate_config.cameras = {"front": MagicMock()}
publisher = MagicMock()
with (
patch.object(
manager,
"_build_camera_config_dict",
return_value={"enabled": True},
),
patch("frigate.debug_replay.find_config_file", return_value="/cfg.yml"),
patch("frigate.debug_replay.YAML") as yaml_cls,
patch(
"frigate.debug_replay.FrigateConfig.parse_object",
side_effect=ValueError("zone foo has invalid coordinates"),
),
patch("builtins.open", unittest.mock.mock_open(read_data="cameras:\n")),
):
yaml_cls.return_value.load.return_value = {"cameras": {}}
with self.assertRaises(RuntimeError) as ctx:
manager.publish_camera(
source_camera="front",
replay_name="_replay_front",
clip_path="/tmp/clip.mp4",
frigate_config=frigate_config,
config_publisher=publisher,
)
self.assertIn("replay camera config", str(ctx.exception))
self.assertIn("invalid coordinates", str(ctx.exception))
publisher.publish_update.assert_not_called()
if __name__ == "__main__":
unittest.main()
-460
View File
@@ -1,460 +0,0 @@
"""Tests for the debug replay job runner and factory."""
import threading
import time
import unittest
import unittest.mock
from unittest.mock import MagicMock, patch
from frigate.debug_replay import DebugReplayManager
from frigate.jobs.debug_replay import (
DebugReplayJob,
cancel_debug_replay_job,
get_active_runner,
start_debug_replay_job,
)
from frigate.jobs.export import JobStatePublisher
from frigate.jobs.manager import _completed_jobs, _current_jobs
from frigate.types import JobStatusTypesEnum
def _reset_job_manager() -> None:
"""Clear the global job manager state between tests."""
_current_jobs.clear()
_completed_jobs.clear()
def _patch_publisher(test_case: unittest.TestCase) -> None:
"""Replace JobStatePublisher.publish with a no-op to avoid hanging on IPC."""
publisher_patch = patch.object(
JobStatePublisher, "publish", lambda self, payload: None
)
publisher_patch.start()
test_case.addCleanup(publisher_patch.stop)
class TestDebugReplayJob(unittest.TestCase):
def test_default_fields(self) -> None:
job = DebugReplayJob()
self.assertEqual(job.job_type, "debug_replay")
self.assertEqual(job.status, JobStatusTypesEnum.queued)
self.assertIsNone(job.current_step)
self.assertEqual(job.progress_percent, 0.0)
def test_to_dict_whitelist(self) -> None:
job = DebugReplayJob(
source_camera="front",
replay_camera_name="_replay_front",
start_ts=100.0,
end_ts=200.0,
)
job.current_step = "preparing_clip"
job.progress_percent = 42.5
payload = job.to_dict()
# Top-level matches the standard Job<TResults> shape.
for key in (
"id",
"job_type",
"status",
"start_time",
"end_time",
"error_message",
"results",
):
self.assertIn(key, payload, f"missing top-level field: {key}")
results = payload["results"]
self.assertEqual(results["source_camera"], "front")
self.assertEqual(results["replay_camera_name"], "_replay_front")
self.assertEqual(results["current_step"], "preparing_clip")
self.assertEqual(results["progress_percent"], 42.5)
self.assertEqual(results["start_ts"], 100.0)
self.assertEqual(results["end_ts"], 200.0)
class TestStartDebugReplayJob(unittest.TestCase):
def setUp(self) -> None:
_reset_job_manager()
_patch_publisher(self)
self.manager = DebugReplayManager()
self.frigate_config = MagicMock()
self.frigate_config.cameras = {"front": MagicMock()}
self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
self.publisher = MagicMock()
self.recordings_qs = MagicMock()
self.recordings_qs.count.return_value = 1
self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
def tearDown(self) -> None:
runner = get_active_runner()
if runner is not None:
runner.cancel()
runner.join(timeout=2.0)
_reset_job_manager()
def test_rejects_unknown_camera(self) -> None:
with self.assertRaises(ValueError):
start_debug_replay_job(
source_camera="missing",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
def test_rejects_invalid_time_range(self) -> None:
with self.assertRaises(ValueError):
start_debug_replay_job(
source_camera="front",
start_ts=200.0,
end_ts=100.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
def test_rejects_when_no_recordings(self) -> None:
empty_qs = MagicMock()
empty_qs.count.return_value = 0
with patch("frigate.jobs.debug_replay.query_recordings", return_value=empty_qs):
with self.assertRaises(ValueError):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
def test_returns_job_id_and_marks_session_starting(self) -> None:
block = threading.Event()
def slow_helper(cmd, **kwargs):
block.wait(timeout=5)
return 0, ""
with (
patch(
"frigate.jobs.debug_replay.query_recordings",
return_value=self.recordings_qs,
),
patch(
"frigate.jobs.debug_replay.run_ffmpeg_with_progress",
side_effect=slow_helper,
),
patch.object(self.manager, "publish_camera"),
patch("os.path.exists", return_value=True),
patch("os.makedirs"),
patch("builtins.open", unittest.mock.mock_open()),
):
job_id = start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
self.assertIsInstance(job_id, str)
self.assertTrue(self.manager.active)
self.assertEqual(self.manager.replay_camera_name, "_replay_front")
self.assertEqual(self.manager.source_camera, "front")
block.set()
def test_rejects_concurrent_calls(self) -> None:
block = threading.Event()
def slow_helper(cmd, **kwargs):
block.wait(timeout=5)
return 0, ""
with (
patch(
"frigate.jobs.debug_replay.query_recordings",
return_value=self.recordings_qs,
),
patch(
"frigate.jobs.debug_replay.run_ffmpeg_with_progress",
side_effect=slow_helper,
),
patch.object(self.manager, "publish_camera"),
patch("os.path.exists", return_value=True),
patch("os.makedirs"),
patch("builtins.open", unittest.mock.mock_open()),
):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
with self.assertRaises(RuntimeError):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
block.set()
class TestRunnerHappyPath(unittest.TestCase):
def setUp(self) -> None:
_reset_job_manager()
_patch_publisher(self)
self.manager = DebugReplayManager()
self.frigate_config = MagicMock()
self.frigate_config.cameras = {"front": MagicMock()}
self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
self.publisher = MagicMock()
self.recordings_qs = MagicMock()
self.recordings_qs.count.return_value = 1
self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
def tearDown(self) -> None:
runner = get_active_runner()
if runner is not None:
runner.cancel()
runner.join(timeout=2.0)
_reset_job_manager()
def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
deadline = time.time() + timeout
while time.time() < deadline:
if predicate():
return True
time.sleep(0.02)
return False
def test_progress_callback_updates_job_percent(self) -> None:
captured: list[float] = []
def fake_helper(cmd, *, on_progress=None, **kwargs):
on_progress(0.0)
on_progress(50.0)
on_progress(100.0)
return 0, ""
with (
patch(
"frigate.jobs.debug_replay.query_recordings",
return_value=self.recordings_qs,
),
patch(
"frigate.jobs.debug_replay.run_ffmpeg_with_progress",
side_effect=fake_helper,
),
patch.object(
self.manager,
"publish_camera",
side_effect=lambda *a, **kw: captured.append("published"),
),
patch("os.path.exists", return_value=True),
patch("os.makedirs"),
patch("builtins.open", unittest.mock.mock_open()),
):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
self.assertTrue(
self._wait_for(lambda: get_active_runner() is None),
"runner did not finish",
)
from frigate.jobs.manager import get_current_job
job = get_current_job("debug_replay")
self.assertIsNotNone(job)
self.assertEqual(job.status, JobStatusTypesEnum.success)
self.assertEqual(job.progress_percent, 100.0)
self.assertEqual(captured, ["published"])
# Manager should have been told the session is ready with the clip path.
self.assertIsNotNone(self.manager.clip_path)
class TestRunnerFailurePath(unittest.TestCase):
def setUp(self) -> None:
_reset_job_manager()
_patch_publisher(self)
self.manager = DebugReplayManager()
self.frigate_config = MagicMock()
self.frigate_config.cameras = {"front": MagicMock()}
self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
self.publisher = MagicMock()
self.recordings_qs = MagicMock()
self.recordings_qs.count.return_value = 1
self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
def tearDown(self) -> None:
runner = get_active_runner()
if runner is not None:
runner.cancel()
runner.join(timeout=2.0)
_reset_job_manager()
def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
deadline = time.time() + timeout
while time.time() < deadline:
if predicate():
return True
time.sleep(0.02)
return False
def test_ffmpeg_failure_marks_job_failed_and_clears_session(self) -> None:
def failing_helper(cmd, **kwargs):
return 1, "ffmpeg exploded"
with (
patch(
"frigate.jobs.debug_replay.query_recordings",
return_value=self.recordings_qs,
),
patch(
"frigate.jobs.debug_replay.run_ffmpeg_with_progress",
side_effect=failing_helper,
),
patch("os.path.exists", return_value=True),
patch("os.makedirs"),
patch("os.remove"),
patch("builtins.open", unittest.mock.mock_open()),
):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
self.assertTrue(
self._wait_for(lambda: get_active_runner() is None),
"runner did not finish",
)
from frigate.jobs.manager import get_current_job
job = get_current_job("debug_replay")
self.assertIsNotNone(job)
self.assertEqual(job.status, JobStatusTypesEnum.failed)
self.assertIsNotNone(job.error_message)
self.assertIn("ffmpeg", job.error_message.lower())
# Session cleared so a new /start is allowed
self.assertFalse(self.manager.active)
class TestRunnerCancellation(unittest.TestCase):
def setUp(self) -> None:
_reset_job_manager()
_patch_publisher(self)
self.manager = DebugReplayManager()
self.frigate_config = MagicMock()
self.frigate_config.cameras = {"front": MagicMock()}
self.frigate_config.ffmpeg.ffmpeg_path = "/bin/true"
self.publisher = MagicMock()
self.recordings_qs = MagicMock()
self.recordings_qs.count.return_value = 1
self.recordings_qs.__iter__.return_value = iter([MagicMock(path="/tmp/r1.mp4")])
def tearDown(self) -> None:
runner = get_active_runner()
if runner is not None:
runner.cancel()
runner.join(timeout=2.0)
_reset_job_manager()
def _wait_for(self, predicate, timeout: float = 5.0) -> bool:
deadline = time.time() + timeout
while time.time() < deadline:
if predicate():
return True
time.sleep(0.02)
return False
def test_cancel_terminates_ffmpeg_and_marks_cancelled(self) -> None:
terminated = threading.Event()
fake_proc = MagicMock()
fake_proc.terminate = MagicMock(side_effect=lambda: terminated.set())
def fake_helper(cmd, *, process_started=None, **kwargs):
if process_started is not None:
process_started(fake_proc)
terminated.wait(timeout=5)
return -15, "killed"
with (
patch(
"frigate.jobs.debug_replay.query_recordings",
return_value=self.recordings_qs,
),
patch(
"frigate.jobs.debug_replay.run_ffmpeg_with_progress",
side_effect=fake_helper,
),
patch("os.path.exists", return_value=True),
patch("os.makedirs"),
patch("os.remove"),
patch("builtins.open", unittest.mock.mock_open()),
):
start_debug_replay_job(
source_camera="front",
start_ts=100.0,
end_ts=200.0,
frigate_config=self.frigate_config,
config_publisher=self.publisher,
replay_manager=self.manager,
)
# Wait for the runner to register the active process.
self.assertTrue(
self._wait_for(
lambda: (
get_active_runner() is not None
and get_active_runner()._active_process is fake_proc
)
)
)
cancelled = cancel_debug_replay_job()
self.assertTrue(cancelled)
self.assertTrue(fake_proc.terminate.called)
self.assertTrue(
self._wait_for(lambda: get_active_runner() is None),
"runner did not finish",
)
from frigate.jobs.manager import get_current_job
job = get_current_job("debug_replay")
self.assertEqual(job.status, JobStatusTypesEnum.cancelled)
# Runner must not clear the manager session on cancellation —
# that belongs to the caller of cancel_debug_replay_job (stop()).
# If the runner cleared it, stop() would log "no active session"
# and skip its cleanup_db / cleanup_files calls.
self.assertTrue(self.manager.active)
if __name__ == "__main__":
unittest.main()
+5 -173
View File
@@ -1,9 +1,6 @@
"""Tests for export progress tracking, broadcast, and FFmpeg parsing."""
import io
import os
import shutil
import tempfile
import unittest
from unittest.mock import MagicMock, patch
@@ -14,7 +11,6 @@ from frigate.jobs.export import (
)
from frigate.record.export import PlaybackSourceEnum, RecordingExporter
from frigate.types import JobStatusTypesEnum
from frigate.util.ffmpeg import inject_progress_flags
def _make_exporter(
@@ -119,9 +115,10 @@ class TestExpectedOutputDuration(unittest.TestCase):
class TestProgressFlagInjection(unittest.TestCase):
def test_inserts_before_output_path(self) -> None:
exporter = _make_exporter()
cmd = ["ffmpeg", "-i", "input.m3u8", "-c", "copy", "/tmp/output.mp4"]
result = inject_progress_flags(cmd)
result = exporter._inject_progress_flags(cmd)
assert result == [
"ffmpeg",
@@ -136,7 +133,8 @@ class TestProgressFlagInjection(unittest.TestCase):
]
def test_handles_empty_cmd(self) -> None:
assert inject_progress_flags([]) == []
exporter = _make_exporter()
assert exporter._inject_progress_flags([]) == []
class TestFfmpegProgressParsing(unittest.TestCase):
@@ -166,7 +164,7 @@ class TestFfmpegProgressParsing(unittest.TestCase):
fake_proc.returncode = 0
fake_proc.wait = MagicMock(return_value=0)
with patch("frigate.util.ffmpeg.sp.Popen", return_value=fake_proc):
with patch("frigate.record.export.sp.Popen", return_value=fake_proc):
returncode, _stderr = exporter._run_ffmpeg_with_progress(
["ffmpeg", "-i", "x.m3u8", "/tmp/out.mp4"], "playlist", step="encoding"
)
@@ -365,121 +363,6 @@ class TestBroadcastAggregation(unittest.TestCase):
assert job.progress_percent == 33.0
class TestGetDatetimeFromTimestamp(unittest.TestCase):
"""Auto-generated export name should honor config.ui.timezone, not
fall back to the container's UTC clock when a timezone is configured.
"""
def test_uses_configured_ui_timezone(self) -> None:
exporter = _make_exporter()
exporter.config.ui.timezone = "America/New_York"
# 2025-01-15 12:00:00 UTC is 07:00:00 EST
assert exporter.get_datetime_from_timestamp(1736942400) == "2025-01-15 07:00:00"
def test_falls_back_to_local_when_timezone_unset(self) -> None:
exporter = _make_exporter()
exporter.config.ui.timezone = None
# No assertion on the exact wall-clock value — just confirm no
# exception and that pytz isn't required when the field is unset.
assert isinstance(exporter.get_datetime_from_timestamp(1736942400), str)
def test_invalid_timezone_falls_back_to_local(self) -> None:
exporter = _make_exporter()
exporter.config.ui.timezone = "Not/A_Real_Zone"
assert isinstance(exporter.get_datetime_from_timestamp(1736942400), str)
class TestSaveThumbnailFromPreviewFrames(unittest.TestCase):
"""Short exports in the current hour can fall between preview frame
writes (1-2 fps during activity, every 30s otherwise). When no frame
falls inside the export window, save_thumbnail should fall back to
the most recent prior frame instead of returning no thumbnail."""
def setUp(self) -> None:
self.tmp_root = tempfile.mkdtemp(prefix="frigate_thumb_test_")
self.preview_dir = os.path.join(self.tmp_root, "cache", "preview_frames")
self.export_clips = os.path.join(self.tmp_root, "clips", "export")
os.makedirs(self.preview_dir, exist_ok=True)
os.makedirs(self.export_clips, exist_ok=True)
def tearDown(self) -> None:
shutil.rmtree(self.tmp_root, ignore_errors=True)
def _write_frame(self, camera: str, frame_time: float) -> str:
path = os.path.join(self.preview_dir, f"preview_{camera}-{frame_time}.webp")
with open(path, "wb") as f:
f.write(b"fake-webp-bytes")
return path
def _make_short_current_hour_exporter(self) -> RecordingExporter:
# Use a "now-ish" timestamp so save_thumbnail's start-of-hour
# comparison takes the current-hour branch (preview frames).
import datetime
now = datetime.datetime.now(datetime.timezone.utc).timestamp()
exporter = _make_exporter()
exporter.export_id = "thumb_short"
exporter.start_time = now
exporter.end_time = now + 3
return exporter
def test_short_export_falls_back_to_prior_preview_frame(self) -> None:
exporter = self._make_short_current_hour_exporter()
# Most recent preview frame is 10s before the export window
prior = self._write_frame(exporter.camera, exporter.start_time - 10.0)
thumb_target = os.path.join(self.export_clips, f"{exporter.export_id}.webp")
with (
patch(
"frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
),
patch(
"frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
),
):
result = exporter.save_thumbnail(exporter.export_id)
assert result == thumb_target
assert os.path.isfile(thumb_target)
with open(thumb_target, "rb") as f, open(prior, "rb") as src:
assert f.read() == src.read()
def test_returns_empty_when_no_preview_frames_exist(self) -> None:
exporter = self._make_short_current_hour_exporter()
with (
patch(
"frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
),
patch(
"frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
),
):
result = exporter.save_thumbnail(exporter.export_id)
assert result == ""
def test_prefers_in_window_frame_over_prior_frame(self) -> None:
exporter = self._make_short_current_hour_exporter()
self._write_frame(exporter.camera, exporter.start_time - 10.0)
in_window = self._write_frame(exporter.camera, exporter.start_time + 1.0)
thumb_target = os.path.join(self.export_clips, f"{exporter.export_id}.webp")
with (
patch(
"frigate.record.export.CACHE_DIR", os.path.join(self.tmp_root, "cache")
),
patch(
"frigate.record.export.CLIPS_DIR", os.path.join(self.tmp_root, "clips")
),
):
result = exporter.save_thumbnail(exporter.export_id)
assert result == thumb_target
with open(thumb_target, "rb") as f, open(in_window, "rb") as src:
assert f.read() == src.read()
class TestSchedulesCleanup(unittest.TestCase):
def test_schedule_job_cleanup_removes_after_delay(self) -> None:
config = MagicMock()
@@ -498,56 +381,5 @@ class TestSchedulesCleanup(unittest.TestCase):
assert job.id not in manager.jobs
class TestChapterMetadataInProgressReview(unittest.TestCase):
"""Regression: in-progress review segments have end_time=NULL until the
activity closes. The chapter builder must clamp the chapter end to the
last recorded second instead of crashing on float(None)."""
def _fake_select_returning(self, rows: list) -> MagicMock:
mock_query = MagicMock()
mock_query.where.return_value = mock_query
mock_query.order_by.return_value = mock_query
mock_query.iterator.return_value = iter(rows)
return mock_query
def test_in_progress_review_does_not_crash_and_clamps_to_last_recording(
self,
) -> None:
exporter = _make_exporter(end_minus_start=200)
# Recordings cover [1000, 1150]; export window is [1000, 1200] so
# the last recorded second is 1150 (a 50s gap at the tail).
recordings = [
MagicMock(start_time=1000.0, end_time=1150.0),
]
in_progress = MagicMock(
start_time=1100.0,
end_time=None,
severity="alert",
data={"objects": ["person"]},
)
with tempfile.TemporaryDirectory() as tmpdir:
chapter_path = os.path.join(tmpdir, "chapters.txt")
exporter._chapter_metadata_path = lambda: chapter_path # type: ignore[method-assign]
with patch(
"frigate.record.export.ReviewSegment.select",
return_value=self._fake_select_returning([in_progress]),
):
result = exporter._build_chapter_metadata_file(recordings)
assert result == chapter_path
with open(chapter_path) as f:
content = f.read()
# Output time is windows[-1][1] - windows[-1][0] = 150s.
# Review starts at wall=1100, output offset = 100s -> 100000ms.
# Clamped end = last_recorded_end (1150) -> output offset = 150s -> 150000ms.
assert "[CHAPTER]" in content
assert "START=100000" in content
assert "END=150000" in content
assert "title=Alert: person" in content
if __name__ == "__main__":
unittest.main()
-111
View File
@@ -1,111 +0,0 @@
"""Tests for the shared ffmpeg progress helper."""
import unittest
from unittest.mock import MagicMock, patch
from frigate.util.ffmpeg import inject_progress_flags, run_ffmpeg_with_progress
class TestInjectProgressFlags(unittest.TestCase):
def test_inserts_flags_before_output_path(self):
cmd = ["ffmpeg", "-i", "in.mp4", "-c", "copy", "out.mp4"]
result = inject_progress_flags(cmd)
self.assertEqual(
result,
[
"ffmpeg",
"-i",
"in.mp4",
"-c",
"copy",
"-progress",
"pipe:2",
"-nostats",
"out.mp4",
],
)
def test_empty_cmd_returns_empty(self):
self.assertEqual(inject_progress_flags([]), [])
class TestRunFfmpegWithProgress(unittest.TestCase):
def _make_fake_proc(self, stderr_lines, returncode=0):
proc = MagicMock()
proc.stderr = iter(stderr_lines)
proc.stdin = MagicMock()
proc.returncode = returncode
proc.wait = MagicMock()
return proc
def test_emits_percent_from_out_time_us_lines(self):
captured: list[float] = []
def on_progress(percent: float) -> None:
captured.append(percent)
stderr_lines = [
"out_time_us=1000000\n",
"out_time_us=5000000\n",
"progress=end\n",
]
proc = self._make_fake_proc(stderr_lines)
proc.stderr = MagicMock()
proc.stderr.__iter__ = lambda self: iter(stderr_lines)
proc.stderr.read = MagicMock(return_value="")
with patch("subprocess.Popen", return_value=proc):
returncode, _stderr = run_ffmpeg_with_progress(
["ffmpeg", "-i", "in", "out"],
expected_duration_seconds=10.0,
on_progress=on_progress,
use_low_priority=False,
)
self.assertEqual(returncode, 0)
self.assertEqual(len(captured), 4) # initial 0.0 + two parsed + final 100.0
self.assertAlmostEqual(captured[0], 0.0)
self.assertAlmostEqual(captured[1], 10.0)
self.assertAlmostEqual(captured[2], 50.0)
self.assertAlmostEqual(captured[3], 100.0)
def test_passes_started_process_to_callback(self):
proc = self._make_fake_proc([])
proc.stderr = MagicMock()
proc.stderr.__iter__ = lambda self: iter([])
proc.stderr.read = MagicMock(return_value="")
seen: list = []
with patch("subprocess.Popen", return_value=proc):
run_ffmpeg_with_progress(
["ffmpeg", "out"],
expected_duration_seconds=1.0,
process_started=lambda p: seen.append(p),
use_low_priority=False,
)
self.assertEqual(seen, [proc])
def test_clamps_percent_to_0_100(self):
captured: list[float] = []
def on_progress(percent: float) -> None:
captured.append(percent)
stderr_lines = ["out_time_us=999999999999\n"]
proc = self._make_fake_proc(stderr_lines)
proc.stderr = MagicMock()
proc.stderr.__iter__ = lambda self: iter(stderr_lines)
proc.stderr.read = MagicMock(return_value="")
with patch("subprocess.Popen", return_value=proc):
run_ffmpeg_with_progress(
["ffmpeg", "out"],
expected_duration_seconds=10.0,
on_progress=on_progress,
use_low_priority=False,
)
# initial 0.0 then a clamped reading
self.assertEqual(captured[-1], 100.0)
+27 -69
View File
@@ -7,6 +7,8 @@ from frigate.util.services import get_amd_gpu_stats, get_intel_gpu_stats
class TestGpuStats(unittest.TestCase):
def setUp(self):
self.amd_results = "Unknown Radeon card. <= R500 won't work, new cards might.\nDumping to -, line limit 1.\n1664070990.607556: bus 10, gpu 4.17%, ee 0.00%, vgt 0.00%, ta 0.00%, tc 0.00%, sx 0.00%, sh 0.00%, spi 0.83%, smx 0.00%, cr 0.00%, sc 0.00%, pa 0.00%, db 0.00%, cb 0.00%, vram 60.37% 294.04mb, gtt 0.33% 52.21mb, mclk 100.00% 1.800ghz, sclk 26.65% 0.533ghz\n"
self.intel_results = """{"period":{"duration":1.194033,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":3349.991164,"unit":"irq/s"},"rc6":{"value":47.844741,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":4.533124,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":6.194385,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}},{"period":{"duration":1.189291,"unit":"ms"},"frequency":{"requested":0.000000,"actual":0.000000,"unit":"MHz"},"interrupts":{"count":0.000000,"unit":"irq/s"},"rc6":{"value":100.000000,"unit":"%"},"engines":{"Render/3D/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Blitter/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"Video/1":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"},"VideoEnhance/0":{"busy":0.000000,"sema":0.000000,"wait":0.000000,"unit":"%"}}}"""
self.nvidia_results = "name, utilization.gpu [%], memory.used [MiB], memory.total [MiB]\nNVIDIA GeForce RTX 3050, 42 %, 5036 MiB, 8192 MiB\n"
@patch("subprocess.run")
def test_amd_gpu_stats(self, sp):
@@ -17,76 +19,32 @@ class TestGpuStats(unittest.TestCase):
amd_stats = get_amd_gpu_stats()
assert amd_stats == {"gpu": "4.17%", "mem": "60.37%"}
@patch("frigate.util.services.time.sleep")
@patch("frigate.util.services.time.monotonic")
@patch("frigate.util.services._read_intel_drm_fdinfo")
def test_intel_gpu_stats_fdinfo(self, read_fdinfo, monotonic, sleep):
# 1 second of wall clock between snapshots
monotonic.side_effect = [0.0, 1.0]
# @patch("subprocess.run")
# def test_nvidia_gpu_stats(self, sp):
# process = MagicMock()
# process.returncode = 0
# process.stdout = self.nvidia_results
# sp.return_value = process
# nvidia_stats = get_nvidia_gpu_stats()
# assert nvidia_stats == {
# "name": "NVIDIA GeForce RTX 3050",
# "gpu": "42 %",
# "mem": "61.5 %",
# }
# Two i915 clients on the same iGPU. Engine values are cumulative ns.
# Deltas over the 1s window:
# client A (pid 100): render +200_000_000 (20%), video +500_000_000 (50%),
# video-enhance +100_000_000 (10%)
# client B (pid 200): compute +100_000_000 (10%)
# Engine totals → render 20, video 50, video-enhance 10, compute 10
# → compute = render + compute = 30
# → dec = video + video-enhance = 60
# → gpu = compute + dec = 90
snapshot_a = {
("0000:00:02.0", "1", "100"): {
"driver": "i915",
"pid": "100",
"engines": {
"render": (1_000_000_000, 0),
"video": (5_000_000_000, 0),
"video-enhance": (200_000_000, 0),
"compute": (0, 0),
},
},
("0000:00:02.0", "2", "200"): {
"driver": "i915",
"pid": "200",
"engines": {
"render": (0, 0),
"compute": (2_000_000_000, 0),
},
},
}
snapshot_b = {
("0000:00:02.0", "1", "100"): {
"driver": "i915",
"pid": "100",
"engines": {
"render": (1_200_000_000, 0),
"video": (5_500_000_000, 0),
"video-enhance": (300_000_000, 0),
"compute": (0, 0),
},
},
("0000:00:02.0", "2", "200"): {
"driver": "i915",
"pid": "200",
"engines": {
"render": (0, 0),
"compute": (2_100_000_000, 0),
},
},
}
read_fdinfo.side_effect = [snapshot_a, snapshot_b]
intel_stats = get_intel_gpu_stats(None)
sleep.assert_called_once()
@patch("subprocess.run")
def test_intel_gpu_stats(self, sp):
process = MagicMock()
process.returncode = 124
process.stdout = self.intel_results
sp.return_value = process
intel_stats = get_intel_gpu_stats(False)
# rc6 values: 47.844741 and 100.0 → avg 73.92 → gpu = 100 - 73.92 = 26.08%
# Render/3D/0: 0.0 and 0.0 → enc = 0.0%
# Video/0: 4.533124 and 0.0 → dec = 2.27%
assert intel_stats == {
"gpu": "90.0%",
"gpu": "26.08%",
"mem": "-%",
"compute": "30.0%",
"dec": "60.0%",
"clients": {"100": "80.0%", "200": "10.0%"},
"compute": "0.0%",
"dec": "2.27%",
}
@patch("frigate.util.services._read_intel_drm_fdinfo")
def test_intel_gpu_stats_no_clients(self, read_fdinfo):
read_fdinfo.return_value = {}
assert get_intel_gpu_stats(None) is None
-381
View File
@@ -1,381 +0,0 @@
"""Unit tests for `frigate.api.media_auth`.
Covers URI classification, the role-vs-camera decision matrix, and the export
DB-lookup path. These are pure functions/DB lookups no HTTP stack involved.
"""
import datetime
import logging
import os
import unittest
from peewee_migrate import Router
from playhouse.sqlite_ext import SqliteExtDatabase
from playhouse.sqliteq import SqliteQueueDatabase
from frigate.api.media_auth import (
MediaAuthResolution,
deny_response_for_media_uri,
extract_path,
resolve_media_uri,
)
from frigate.config import FrigateConfig
from frigate.models import Event, Export, Recordings, ReviewSegment
from frigate.test.const import TEST_DB, TEST_DB_CLEANUPS
_CONFIG = {
"mqtt": {"host": "mqtt"},
"auth": {"roles": {"limited_user": ["front_door"]}},
"cameras": {
"front_door": {
"ffmpeg": {
"inputs": [{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
"back_door": {
"ffmpeg": {
"inputs": [{"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]}]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
# Camera name with a hyphen — exercises longest-prefix match.
"back-yard": {
"ffmpeg": {
"inputs": [{"path": "rtsp://10.0.0.3:554/video", "roles": ["detect"]}]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
},
}
class TestExtractPath(unittest.TestCase):
def test_full_url(self):
self.assertEqual(
extract_path("http://host:8971/clips/front_door-1.jpg"),
"/clips/front_door-1.jpg",
)
def test_strips_query_string(self):
self.assertEqual(
extract_path("http://h/recordings/2026-05-11/14/front_door/00.00.mp4?t=1"),
"/recordings/2026-05-11/14/front_door/00.00.mp4",
)
def test_path_only(self):
self.assertEqual(extract_path("/exports/x.mp4"), "/exports/x.mp4")
def test_percent_decoded(self):
self.assertEqual(
extract_path("http://h/clips/front%20door-1.jpg"),
"/clips/front door-1.jpg",
)
def test_empty(self):
self.assertIsNone(extract_path(None))
self.assertIsNone(extract_path(""))
class TestResolveMediaUri(unittest.TestCase):
def setUp(self):
self.config = FrigateConfig(**_CONFIG)
def _assert(self, uri, resolution, camera=None):
got_resolution, got_camera = resolve_media_uri(uri, self.config)
self.assertEqual(got_resolution, resolution, uri)
self.assertEqual(got_camera, camera, uri)
def test_unknown_paths(self):
self._assert("/api/events", MediaAuthResolution.UNKNOWN)
self._assert("/", MediaAuthResolution.UNKNOWN)
self._assert("", MediaAuthResolution.UNKNOWN)
def test_recordings(self):
self._assert("/recordings/", MediaAuthResolution.LISTING_NEUTRAL)
self._assert("/recordings/2026-05-11/", MediaAuthResolution.LISTING_NEUTRAL)
self._assert(
"/recordings/2026-05-11/14/", MediaAuthResolution.LISTING_MULTI_CAMERA
)
self._assert(
"/recordings/2026-05-11/14/front_door/",
MediaAuthResolution.CAMERA,
camera="front_door",
)
self._assert(
"/recordings/2026-05-11/14/back_door/00.00.mp4",
MediaAuthResolution.CAMERA,
camera="back_door",
)
def test_clip_flat_filename_resolves_camera(self):
self._assert(
"/clips/front_door-1234.jpg",
MediaAuthResolution.CAMERA,
camera="front_door",
)
self._assert(
"/clips/back_door-1234-clean.webp",
MediaAuthResolution.CAMERA,
camera="back_door",
)
def test_clip_filename_with_hyphenated_camera_name(self):
# Camera name "back-yard" itself contains a hyphen; longest-prefix
# match must pick `back-yard`, not the bogus `back` prefix.
self._assert(
"/clips/back-yard-1234.jpg",
MediaAuthResolution.CAMERA,
camera="back-yard",
)
def test_clip_filename_no_matching_camera(self):
# Looks like a media path but couldn't classify — fail closed for
# restricted users (UNRESOLVED_MEDIA), not pass-through.
self._assert(
"/clips/nonexistent-1234.jpg", MediaAuthResolution.UNRESOLVED_MEDIA
)
def test_clip_thumbs(self):
self._assert("/clips/thumbs/", MediaAuthResolution.LISTING_MULTI_CAMERA)
self._assert(
"/clips/thumbs/front_door/",
MediaAuthResolution.CAMERA,
camera="front_door",
)
self._assert(
"/clips/thumbs/back_door/abc.webp",
MediaAuthResolution.CAMERA,
camera="back_door",
)
def test_clip_previews(self):
self._assert("/clips/previews/", MediaAuthResolution.LISTING_MULTI_CAMERA)
self._assert(
"/clips/previews/front_door/",
MediaAuthResolution.CAMERA,
camera="front_door",
)
self._assert(
"/clips/previews/back_door/segment.mp4",
MediaAuthResolution.CAMERA,
camera="back_door",
)
def test_clip_review_thumbs(self):
# Format: /clips/review/thumb-{camera}-{review_id}.webp (frigate/review/maintainer.py).
self._assert(
"/clips/review/thumb-front_door-abc123.webp",
MediaAuthResolution.CAMERA,
camera="front_door",
)
# Hyphenated camera name — longest-prefix match.
self._assert(
"/clips/review/thumb-back-yard-abc123.webp",
MediaAuthResolution.CAMERA,
camera="back-yard",
)
# Unknown camera prefix → unresolved, not allowed for restricted users.
self._assert(
"/clips/review/thumb-unknown-cam-abc123.webp",
MediaAuthResolution.UNRESOLVED_MEDIA,
)
def test_clip_admin_only_subtrees(self):
self._assert("/clips/faces/train/foo.webp", MediaAuthResolution.ADMIN_ONLY)
self._assert("/clips/faces/", MediaAuthResolution.ADMIN_ONLY)
self._assert("/clips/genai-requests/x/0.webp", MediaAuthResolution.ADMIN_ONLY)
self._assert(
"/clips/preview_restart_cache/x.mp4", MediaAuthResolution.ADMIN_ONLY
)
self._assert("/clips/some_model/train/x.jpg", MediaAuthResolution.ADMIN_ONLY)
self._assert("/clips/some_model/dataset/x.jpg", MediaAuthResolution.ADMIN_ONLY)
def test_clip_unknown_subtree_is_unresolved(self):
# Unknown /clips/{x}/{y}/... subtree falls through as unresolved (not
# admin-only) so restricted users get 403 without admins being denied
# access to legitimate but unrecognized resources.
self._assert("/clips/random_dir/foo.jpg", MediaAuthResolution.UNRESOLVED_MEDIA)
def test_clip_top_level_listing(self):
self._assert("/clips/", MediaAuthResolution.LISTING_MULTI_CAMERA)
def test_exports_listing(self):
self._assert("/exports/", MediaAuthResolution.LISTING_MULTI_CAMERA)
class TestExportResolution(unittest.TestCase):
"""Export resolution requires a DB lookup."""
def setUp(self):
migrate_db = SqliteExtDatabase("test.db")
del logging.getLogger("peewee_migrate").handlers[:]
Router(migrate_db).run()
migrate_db.close()
self.db = SqliteQueueDatabase(TEST_DB)
self.db.bind([Event, ReviewSegment, Recordings, Export])
self.config = FrigateConfig(**_CONFIG)
def tearDown(self):
if not self.db.is_closed():
self.db.close()
for f in TEST_DB_CLEANUPS:
try:
os.remove(f)
except OSError:
pass
def _insert_export(self, export_id, camera, filename):
Export.insert(
id=export_id,
camera=camera,
name=f"export-{export_id}",
date=datetime.datetime.now(),
video_path=f"/media/frigate/exports/{filename}",
thumb_path=f"/media/frigate/exports/{filename}.jpg",
in_progress=False,
).execute()
def test_export_resolves_camera(self):
self._insert_export(
"exp1", "back_door", "back_door_20260511_140000-20260511_150000_abc123.mp4"
)
resolution, camera = resolve_media_uri(
"/exports/back_door_20260511_140000-20260511_150000_abc123.mp4",
self.config,
)
self.assertEqual(resolution, MediaAuthResolution.CAMERA)
self.assertEqual(camera, "back_door")
def test_unknown_export_is_unresolved(self):
# No matching row → UNRESOLVED_MEDIA (fail closed for restricted users),
# not UNKNOWN (which would pass-through).
resolution, camera = resolve_media_uri(
"/exports/does_not_exist.mp4", self.config
)
self.assertEqual(resolution, MediaAuthResolution.UNRESOLVED_MEDIA)
self.assertIsNone(camera)
def test_export_anchored_match_not_endswith(self):
# Anchored exact-path equality must NOT match by filename suffix.
# A request like /exports/clip.mp4 must not authorize against a row at
# /media/frigate/exports/back_door_clip.mp4 just because the suffix matches.
self._insert_export("exp_bd", "back_door", "back_door_clip.mp4")
self._insert_export("exp_fd", "front_door", "front_door_clip.mp4")
resolution, _ = resolve_media_uri("/exports/clip.mp4", self.config)
self.assertEqual(resolution, MediaAuthResolution.UNRESOLVED_MEDIA)
class TestDenyResponseForMediaUri(unittest.TestCase):
"""End-to-end decision check used by /auth."""
def setUp(self):
self.config = FrigateConfig(**_CONFIG)
def _deny(self, url, role):
return deny_response_for_media_uri(url, role, self.config)
def test_admin_always_allowed(self):
self.assertIsNone(self._deny("/clips/back_door-1.jpg", "admin"))
self.assertIsNone(self._deny("/clips/", "admin"))
self.assertIsNone(self._deny("/clips/faces/x.webp", "admin"))
self.assertIsNone(
self._deny("/recordings/2026-05-11/14/back_door/00.00.mp4", "admin")
)
def test_unrestricted_role_allowed(self):
# "viewer" role has no entry in roles_dict → full access (matches the
# behavior of require_camera_access).
self.assertIsNone(self._deny("/clips/back_door-1.jpg", "viewer"))
self.assertIsNone(self._deny("/clips/", "viewer"))
def test_restricted_role_allowed_camera(self):
self.assertIsNone(self._deny("/clips/front_door-1.jpg", "limited_user"))
self.assertIsNone(
self._deny("/recordings/2026-05-11/14/front_door/00.00.mp4", "limited_user")
)
self.assertIsNone(
self._deny("/clips/thumbs/front_door/abc.webp", "limited_user")
)
def test_restricted_role_blocked_other_camera(self):
self.assertEqual(self._deny("/clips/back_door-1.jpg", "limited_user"), 403)
self.assertEqual(
self._deny("/recordings/2026-05-11/14/back_door/00.00.mp4", "limited_user"),
403,
)
self.assertEqual(
self._deny("/clips/thumbs/back_door/abc.webp", "limited_user"), 403
)
def test_restricted_role_blocked_admin_only(self):
self.assertEqual(self._deny("/clips/faces/train/foo.webp", "limited_user"), 403)
def test_restricted_role_blocked_multi_camera_listing(self):
self.assertEqual(self._deny("/clips/", "limited_user"), 403)
self.assertEqual(self._deny("/exports/", "limited_user"), 403)
self.assertEqual(self._deny("/recordings/2026-05-11/14/", "limited_user"), 403)
def test_restricted_role_allowed_neutral_listing(self):
self.assertIsNone(self._deny("/recordings/", "limited_user"))
self.assertIsNone(self._deny("/recordings/2026-05-11/", "limited_user"))
def test_non_media_uri_passes_through(self):
self.assertIsNone(self._deny("/api/events", "limited_user"))
self.assertIsNone(self._deny("http://h/login", "limited_user"))
def test_missing_header(self):
self.assertIsNone(self._deny(None, "limited_user"))
self.assertIsNone(self._deny("", "limited_user"))
def test_traversal_in_media_uri_denied_for_all_roles(self):
# Bypass attempt: parts[3] looks like an allowed camera, but the
# normalized path nginx would serve points at a forbidden camera.
# Both restricted and admin should be denied — the URI is malformed
# and we refuse to make an auth decision against it.
traversal_uris = [
"/recordings/2026-05-11/14/front_door/../back_door/00.00.mp4",
"/clips/front_door-1.jpg/../back_door-1.jpg",
"/exports/../recordings/2026-05-11/14/back_door/00.00.mp4",
"/clips/./back_door-1.jpg",
]
for uri in traversal_uris:
self.assertEqual(self._deny(uri, "limited_user"), 403, uri)
self.assertEqual(self._deny(uri, "admin"), 403, uri)
self.assertEqual(self._deny(uri, "viewer"), 403, uri)
def test_traversal_outside_media_passes_through(self):
# `..` in non-media URIs is not our problem; the backend handles it.
self.assertIsNone(self._deny("/api/foo/../bar", "limited_user"))
def test_percent_encoded_traversal_denied(self):
# nginx may decode percent-encoded `%2E%2E` to `..` before serving;
# we must apply the same denial after percent-decoding.
self.assertEqual(
self._deny(
"/recordings/2026-05-11/14/front_door/%2E%2E/back_door/00.mp4",
"limited_user",
),
403,
)
def test_unresolved_media_fails_closed_for_restricted(self):
# Restricted user requesting a media URI we can't classify (no DB row,
# unknown clip prefix, unknown clip subtree) must be denied.
self.assertEqual(self._deny("/clips/nonexistent-1.jpg", "limited_user"), 403)
self.assertEqual(self._deny("/clips/random_dir/foo.jpg", "limited_user"), 403)
self.assertEqual(
self._deny("/clips/review/thumb-unknown_cam-1.webp", "limited_user"),
403,
)
def test_unresolved_media_allowed_for_admin(self):
# Admin and full-access roles are *not* denied on UNRESOLVED_MEDIA —
# nginx returns 404 if the file doesn't exist on disk anyway, and we
# don't want a stale DB to lock out admins.
self.assertIsNone(self._deny("/clips/nonexistent-1.jpg", "admin"))
self.assertIsNone(self._deny("/clips/nonexistent-1.jpg", "viewer"))
if __name__ == "__main__":
unittest.main()
-57
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@@ -1,57 +0,0 @@
"""Tests for JSMPEG websocket authorization."""
import unittest
from types import SimpleNamespace
from frigate.config import FrigateConfig
from frigate.output.ws_auth import ws_has_camera_access
class TestWsHasCameraAccess(unittest.TestCase):
def setUp(self):
self.config = FrigateConfig(
mqtt={"host": "mqtt"},
auth={"roles": {"limited_user": ["front_door"]}},
cameras={
"front_door": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.1:554/video", "roles": ["detect"]}
]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
"back_door": {
"ffmpeg": {
"inputs": [
{"path": "rtsp://10.0.0.2:554/video", "roles": ["detect"]}
]
},
"detect": {"height": 1080, "width": 1920, "fps": 5},
},
},
)
def _make_ws(self, role: str):
return SimpleNamespace(environ={"HTTP_REMOTE_ROLE": role})
def test_restricted_role_only_gets_allowed_camera(self):
ws = self._make_ws("limited_user")
self.assertTrue(ws_has_camera_access(ws, "front_door", self.config))
self.assertFalse(ws_has_camera_access(ws, "back_door", self.config))
def test_unrestricted_role_can_access_any_camera(self):
ws = self._make_ws("viewer")
self.assertTrue(ws_has_camera_access(ws, "front_door", self.config))
self.assertTrue(ws_has_camera_access(ws, "back_door", self.config))
def test_birdseye_requires_unrestricted_access(self):
self.assertTrue(
ws_has_camera_access(self._make_ws("admin"), "birdseye", self.config)
)
self.assertTrue(
ws_has_camera_access(self._make_ws("viewer"), "birdseye", self.config)
)
self.assertFalse(
ws_has_camera_access(self._make_ws("limited_user"), "birdseye", self.config)
)
@@ -1,29 +0,0 @@
"""Tests for camera monitoring notification authorization."""
import unittest
from types import SimpleNamespace
from unittest.mock import MagicMock
from frigate.comms.webpush import WebPushClient
class TestCameraMonitoringNotifications(unittest.TestCase):
def test_send_camera_monitoring_filters_by_camera_access(self):
client = WebPushClient.__new__(WebPushClient)
client.config = SimpleNamespace(
cameras={"front_door": SimpleNamespace(friendly_name=None)}
)
client.web_pushers = {"allowed": [], "denied": []}
client.user_cameras = {"allowed": {"front_door"}, "denied": set()}
client.check_registrations = MagicMock()
client.cleanup_registrations = MagicMock()
client.send_push_notification = MagicMock()
client.send_camera_monitoring(
{"camera": "front_door", "message": "Monitoring condition met"}
)
self.assertEqual(client.send_push_notification.call_count, 1)
self.assertEqual(
client.send_push_notification.call_args.kwargs["user"], "allowed"
)
-166
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@@ -1,166 +0,0 @@
"""Tests for WebSocket authorization checks."""
import unittest
from frigate.comms.ws import _check_ws_authorization
from frigate.const import INSERT_MANY_RECORDINGS, UPDATE_CAMERA_ACTIVITY
class TestCheckWsAuthorization(unittest.TestCase):
"""Tests for the _check_ws_authorization pure function."""
DEFAULT_SEPARATOR = ","
# --- IPC topic blocking (unconditional, regardless of role) ---
def test_ipc_topic_blocked_for_admin(self):
self.assertFalse(
_check_ws_authorization(
INSERT_MANY_RECORDINGS, "admin", self.DEFAULT_SEPARATOR
)
)
def test_ipc_topic_blocked_for_viewer(self):
self.assertFalse(
_check_ws_authorization(
UPDATE_CAMERA_ACTIVITY, "viewer", self.DEFAULT_SEPARATOR
)
)
def test_ipc_topic_blocked_when_no_role(self):
self.assertFalse(
_check_ws_authorization(
INSERT_MANY_RECORDINGS, None, self.DEFAULT_SEPARATOR
)
)
# --- Viewer allowed topics ---
def test_viewer_can_send_on_connect(self):
self.assertTrue(
_check_ws_authorization("onConnect", "viewer", self.DEFAULT_SEPARATOR)
)
def test_viewer_can_send_model_state(self):
self.assertTrue(
_check_ws_authorization("modelState", "viewer", self.DEFAULT_SEPARATOR)
)
def test_viewer_can_send_audio_transcription_state(self):
self.assertTrue(
_check_ws_authorization(
"audioTranscriptionState", "viewer", self.DEFAULT_SEPARATOR
)
)
def test_viewer_can_send_birdseye_layout(self):
self.assertTrue(
_check_ws_authorization("birdseyeLayout", "viewer", self.DEFAULT_SEPARATOR)
)
def test_viewer_can_send_embeddings_reindex_progress(self):
self.assertTrue(
_check_ws_authorization(
"embeddingsReindexProgress", "viewer", self.DEFAULT_SEPARATOR
)
)
# --- Viewer blocked from admin topics ---
def test_viewer_blocked_from_restart(self):
self.assertFalse(
_check_ws_authorization("restart", "viewer", self.DEFAULT_SEPARATOR)
)
def test_viewer_blocked_from_camera_detect_set(self):
self.assertFalse(
_check_ws_authorization(
"front_door/detect/set", "viewer", self.DEFAULT_SEPARATOR
)
)
def test_viewer_blocked_from_camera_ptz(self):
self.assertFalse(
_check_ws_authorization("front_door/ptz", "viewer", self.DEFAULT_SEPARATOR)
)
def test_viewer_blocked_from_global_notifications_set(self):
self.assertFalse(
_check_ws_authorization(
"notifications/set", "viewer", self.DEFAULT_SEPARATOR
)
)
def test_viewer_blocked_from_camera_notifications_suspend(self):
self.assertFalse(
_check_ws_authorization(
"front_door/notifications/suspend", "viewer", self.DEFAULT_SEPARATOR
)
)
def test_viewer_blocked_from_arbitrary_unknown_topic(self):
self.assertFalse(
_check_ws_authorization(
"some_random_topic", "viewer", self.DEFAULT_SEPARATOR
)
)
# --- Admin access ---
def test_admin_can_send_restart(self):
self.assertTrue(
_check_ws_authorization("restart", "admin", self.DEFAULT_SEPARATOR)
)
def test_admin_can_send_camera_detect_set(self):
self.assertTrue(
_check_ws_authorization(
"front_door/detect/set", "admin", self.DEFAULT_SEPARATOR
)
)
def test_admin_can_send_camera_ptz(self):
self.assertTrue(
_check_ws_authorization("front_door/ptz", "admin", self.DEFAULT_SEPARATOR)
)
# --- Comma-separated roles ---
def test_comma_separated_admin_viewer_grants_admin(self):
self.assertTrue(
_check_ws_authorization("restart", "admin,viewer", self.DEFAULT_SEPARATOR)
)
def test_comma_separated_viewer_admin_grants_admin(self):
self.assertTrue(
_check_ws_authorization("restart", "viewer,admin", self.DEFAULT_SEPARATOR)
)
def test_comma_separated_with_spaces(self):
self.assertTrue(
_check_ws_authorization("restart", "viewer, admin", self.DEFAULT_SEPARATOR)
)
# --- Custom separator ---
def test_pipe_separator(self):
self.assertTrue(_check_ws_authorization("restart", "viewer|admin", "|"))
def test_pipe_separator_no_admin(self):
self.assertFalse(_check_ws_authorization("restart", "viewer|editor", "|"))
# --- No role header (fail-closed) ---
def test_no_role_header_blocks_admin_topics(self):
self.assertFalse(
_check_ws_authorization("restart", None, self.DEFAULT_SEPARATOR)
)
def test_no_role_header_allows_viewer_topics(self):
self.assertTrue(
_check_ws_authorization("onConnect", None, self.DEFAULT_SEPARATOR)
)
if __name__ == "__main__":
unittest.main()

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