Merge remote-tracking branch 'origin/master' into dev

2026-10-19 01:41:31 +10:00 · 2026-03-22 17:34:11 -05:00
parent ec7040bed5 416a9b7692
commit 59f570f436
76 changed files with 1315 additions and 381 deletions
@@ -44,13 +44,21 @@ go2rtc:

 ### `environment_vars`

-This section can be used to set environment variables for those unable to modify the environment of the container, like within Home Assistant OS.
+This section can be used to set environment variables for those unable to modify the environment of the container, like within Home Assistant OS. Docker users should set environment variables in their `docker run` command (`-e FRIGATE_MQTT_PASSWORD=secret`) or `docker-compose.yml` file (`environment:` section) instead. Note that values set here are stored in plain text in your config file, so if the goal is to keep credentials out of your configuration, use Docker environment variables or Docker secrets instead.
+
+Variables prefixed with `FRIGATE_` can be referenced in config fields that support environment variable substitution (such as MQTT host and credentials, camera stream URLs, and ONVIF host and credentials) using the `{FRIGATE_VARIABLE_NAME}` syntax.

 Example:

 ```yaml
 environment_vars:
-  VARIABLE_NAME: variable_value
+  FRIGATE_MQTT_USER: my_mqtt_user
+  FRIGATE_MQTT_PASSWORD: my_mqtt_password
+
+mqtt:
+  host: "{FRIGATE_MQTT_HOST}"
+  user: "{FRIGATE_MQTT_USER}"
+  password: "{FRIGATE_MQTT_PASSWORD}"
 ```

 #### TensorFlow Thread Configuration
@@ -86,7 +86,7 @@ Frigate looks for a JWT token secret in the following order:

 1. An environment variable named `FRIGATE_JWT_SECRET`
 2. A file named `FRIGATE_JWT_SECRET` in the directory specified by the `CREDENTIALS_DIRECTORY` environment variable (defaults to the Docker Secrets directory: `/run/secrets/`)
-3. A `jwt_secret` option from the Home Assistant Add-on options
+3. A `jwt_secret` option from the Home Assistant App options
 4. A `.jwt_secret` file in the config directory

 If no secret is found on startup, Frigate generates one and stores it in a `.jwt_secret` file in the config directory.
@@ -232,7 +232,7 @@ The viewer role provides read-only access to all cameras in the UI and API. Cust

 ### Role Configuration Example

-```yaml
+```yaml {11-16}
 cameras:
  front_door:
    # ... camera config
@@ -24,7 +24,7 @@ A custom icon can be added to the birdseye background by providing a 180x180 ima

 If you want to include a camera in Birdseye view only for specific circumstances, or just don't include it at all, the Birdseye setting can be set at the camera level.

-```yaml
+```yaml {8-10,12-14}
 # Include all cameras by default in Birdseye view
 birdseye:
  enabled: True
@@ -48,6 +48,7 @@ By default birdseye shows all cameras that have had the configured activity in t
 ```yaml
 birdseye:
  enabled: True
+  # highlight-next-line
  inactivity_threshold: 15
 ```

@@ -78,9 +79,11 @@ birdseye:
 cameras:
  front:
    birdseye:
+      # highlight-next-line
      order: 1
  back:
    birdseye:
+      # highlight-next-line
      order: 2
 ```

@@ -92,7 +95,7 @@ It is possible to limit the number of cameras shown on birdseye at one time. Whe

 For example, this can be configured to only show the most recently active camera.

-```yaml
+```yaml {3-4}
 birdseye:
  enabled: True
  layout:
@@ -103,7 +106,7 @@ birdseye:

 By default birdseye tries to fit 2 cameras in each row and then double in size until a suitable layout is found. The scaling can be configured with a value between 1.0 and 5.0 depending on use case.

-```yaml
+```yaml {3-4}
 birdseye:
  enabled: True
  layout:
@@ -23,6 +23,7 @@ Some cameras support h265 with different formats, but Safari only supports the a
 cameras:
  h265_cam: # <------ Doesn't matter what the camera is called
    ffmpeg:
+      # highlight-next-line
      apple_compatibility: true # <- Adds compatibility with MacOS and iPhone
 ```

@@ -30,7 +31,7 @@ cameras:

 Note that mjpeg cameras require encoding the video into h264 for recording, and restream roles. This will use significantly more CPU than if the cameras supported h264 feeds directly. It is recommended to use the restream role to create an h264 restream and then use that as the source for ffmpeg.

-```yaml
+```yaml {3,10}
 go2rtc:
  streams:
    mjpeg_cam: "ffmpeg:http://your_mjpeg_stream_url#video=h264#hardware" # <- use hardware acceleration to create an h264 stream usable for other components.
@@ -96,6 +97,7 @@ This camera is H.265 only. To be able to play clips on some devices (like MacOs
 cameras:
  annkec800: # <------ Name the camera
    ffmpeg:
+      # highlight-next-line
      apple_compatibility: true # <- Adds compatibility with MacOS and iPhone
      output_args:
        record: preset-record-generic-audio-aac
@@ -274,7 +276,7 @@ To use a USB camera (webcam) with Frigate, the recommendation is to use go2rtc's

 - In your Frigate Configuration File, add the go2rtc stream and roles as appropriate:

-```
+```yaml {4,11-12}
 go2rtc:
  streams:
    usb_camera:
@@ -66,7 +66,7 @@ Not every PTZ supports ONVIF, which is the standard protocol Frigate uses to com

 Add the onvif section to your camera in your configuration file:

-```yaml
+```yaml {4-8}
 cameras:
  back:
    ffmpeg: ...
@@ -7,11 +7,11 @@ Object classification allows you to train a custom MobileNetV2 classification mo

 ## Minimum System Requirements

-Object classification models are lightweight and run very fast on CPU. Inference should be usable on virtually any machine that can run Frigate.
+Object classification models are lightweight and run very fast on CPU.

 Training the model does briefly use a high amount of system resources for about 1–3 minutes per training run. On lower-power devices, training may take longer.

-A CPU with AVX instructions is required for training and inference.
+A CPU with AVX + AVX2 instructions is required for training and inference.

 ## Classes

@@ -27,7 +27,6 @@ For object classification:
 ### Classification Type

 - **Sub label**:
-
  - Applied to the object’s `sub_label` field.
  - Ideal for a single, more specific identity or type.
  - Example: `cat` → `Leo`, `Charlie`, `None`.
@@ -119,6 +118,7 @@ Enable debug logs for classification models by adding `frigate.data_processing.r
 logger:
  default: info
  logs:
+    # highlight-next-line
    frigate.data_processing.real_time.custom_classification: debug
 ```

@@ -7,11 +7,11 @@ State classification allows you to train a custom MobileNetV2 classification mod

 ## Minimum System Requirements

-State classification models are lightweight and run very fast on CPU. Inference should be usable on virtually any machine that can run Frigate.
+State classification models are lightweight and run very fast on CPU.

 Training the model does briefly use a high amount of system resources for about 1–3 minutes per training run. On lower-power devices, training may take longer.

-A CPU with AVX instructions is required for training and inference.
+A CPU with AVX + AVX2 instructions is required for training and inference.

 ## Classes

@@ -85,6 +85,7 @@ Enable debug logs for classification models by adding `frigate.data_processing.r
 logger:
  default: info
  logs:
+    # highlight-next-line
    frigate.data_processing.real_time.custom_classification: debug
 ```

@@ -32,6 +32,8 @@ All of these features run locally on your system.

 ## Minimum System Requirements

+A CPU with AVX + AVX2 instructions is required to run Face Recognition.
+
 The `small` model is optimized for efficiency and runs on the CPU, most CPUs should run the model efficiently.

 The `large` model is optimized for accuracy, an integrated or discrete GPU / NPU is required. See the [Hardware Accelerated Enrichments](/configuration/hardware_acceleration_enrichments.md) documentation.
@@ -143,17 +145,14 @@ Start with the [Usage](#usage) section and re-read the [Model Requirements](#mod
 1. Ensure `person` is being _detected_. A `person` will automatically be scanned by Frigate for a face. Any detected faces will appear in the Recent Recognitions tab in the Frigate UI's Face Library.

   If you are using a Frigate+ or `face` detecting model:
-
   - Watch the debug view (Settings --> Debug) to ensure that `face` is being detected along with `person`.
   - You may need to adjust the `min_score` for the `face` object if faces are not being detected.

   If you are **not** using a Frigate+ or `face` detecting model:
-
   - Check your `detect` stream resolution and ensure it is sufficiently high enough to capture face details on `person` objects.
   - You may need to lower your `detection_threshold` if faces are not being detected.

 2. Any detected faces will then be _recognized_.
-
   - Make sure you have trained at least one face per the recommendations above.
   - Adjust `recognition_threshold` settings per the suggestions [above](#advanced-configuration).

@@ -187,7 +187,7 @@ genai:

 To use a different Gemini-compatible API endpoint, set the `provider_options` with the `base_url` key to your provider's API URL. For example:

-```
+```yaml {4,5}
 genai:
  provider: gemini
  ...
@@ -220,6 +220,29 @@ genai:
  model: gpt-4o
 ```

+:::note
+
+To use a different OpenAI-compatible API endpoint, set the `OPENAI_BASE_URL` environment variable to your provider's API URL.
+
+:::
+
+:::tip
+
+For OpenAI-compatible servers (such as llama.cpp) that don't expose the configured context size in the API response, you can manually specify the context size in `provider_options`:
+
+```yaml {5,6}
+genai:
+  provider: openai
+  base_url: http://your-llama-server
+  model: your-model-name
+  provider_options:
+    context_size: 8192 # Specify the configured context size
+```
+
+This ensures Frigate uses the correct context window size when generating prompts.
+
+:::
+
 ### Azure OpenAI

 Microsoft offers several vision models through Azure OpenAI. A subscription is required.
@@ -80,6 +80,7 @@ By default, review summaries use preview images (cached preview frames) which ha
 review:
  genai:
    enabled: true
+    # highlight-next-line
    image_source: recordings # Options: "preview" (default) or "recordings"
 ```

@@ -104,7 +105,7 @@ If recordings are not available for a given time period, the system will automat

 Along with the concern of suspicious activity or immediate threat, you may have concerns such as animals in your garden or a gate being left open. These concerns can be configured so that the review summaries will make note of them if the activity requires additional review. For example:

-```yaml
+```yaml {4,5}
 review:
  genai:
    enabled: true
@@ -116,7 +117,7 @@ review:

 By default, review summaries are generated in English. You can configure Frigate to generate summaries in your preferred language by setting the `preferred_language` option:

-```yaml
+```yaml {4}
 review:
  genai:
    enabled: true
@@ -10,6 +10,7 @@ import CommunityBadge from '@site/src/components/CommunityBadge';
 It is highly recommended to use an integrated or discrete GPU for hardware acceleration video decoding in Frigate.

 Some types of hardware acceleration are detected and used automatically, but you may need to update your configuration to enable hardware accelerated decoding in ffmpeg. To verify that hardware acceleration is working:
+
 - Check the logs: A message will either say that hardware acceleration was automatically detected, or there will be a warning that no hardware acceleration was automatically detected
 - If hardware acceleration is specified in the config, verification can be done by ensuring the logs are free from errors. There is no CPU fallback for hardware acceleration.

@@ -67,7 +68,7 @@ Frigate can utilize most Intel integrated GPUs and Arc GPUs to accelerate video

 :::note

-The default driver is `iHD`. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `config.yml` for HA Add-on users](advanced.md#environment_vars).
+The default driver is `iHD`. You may need to change the driver to `i965` by adding the following environment variable `LIBVA_DRIVER_NAME=i965` to your docker-compose file or [in the `config.yml` for HA App users](advanced.md#environment_vars).

 See [The Intel Docs](https://www.intel.com/content/www/us/en/support/articles/000005505/processors.html) to figure out what generation your CPU is.

@@ -116,12 +117,13 @@ services:
  frigate:
    ...
    image: ghcr.io/blakeblackshear/frigate:stable
+    # highlight-next-line
    privileged: true
 ```

 ##### Docker Run CLI - Privileged

-```bash
+```bash {4}
 docker run -d \
  --name frigate \
  ...
@@ -135,7 +137,7 @@ Only recent versions of Docker support the `CAP_PERFMON` capability. You can tes

 ##### Docker Compose - CAP_PERFMON

-```yaml
+```yaml {5,6}
 services:
  frigate:
    ...
@@ -146,7 +148,7 @@ services:

 ##### Docker Run CLI - CAP_PERFMON

-```bash
+```bash {4}
 docker run -d \
  --name frigate \
  ...
@@ -188,7 +190,7 @@ Frigate can utilize modern AMD integrated GPUs and AMD GPUs to accelerate video

 ### Configuring Radeon Driver

-You need to change the driver to `radeonsi` by adding the following environment variable `LIBVA_DRIVER_NAME=radeonsi` to your docker-compose file or [in the `config.yml` for HA Add-on users](advanced.md#environment_vars).
+You need to change the driver to `radeonsi` by adding the following environment variable `LIBVA_DRIVER_NAME=radeonsi` to your docker-compose file or [in the `config.yml` for HA App users](advanced.md#environment_vars).

 ### Via VAAPI

@@ -213,7 +215,7 @@ Additional configuration is needed for the Docker container to be able to access

 #### Docker Compose - Nvidia GPU

-```yaml
+```yaml {5-12}
 services:
  frigate:
    ...
@@ -230,7 +232,7 @@ services:

 #### Docker Run CLI - Nvidia GPU

-```bash
+```bash {4}
 docker run -d \
  --name frigate \
  ...
@@ -292,7 +294,7 @@ These instructions were originally based on the [Jellyfin documentation](https:/
 ## Raspberry Pi 3/4

 Ensure you increase the allocated RAM for your GPU to at least 128 (`raspi-config` > Performance Options > GPU Memory).
-If you are using the HA Add-on, you may need to use the full access variant and turn off _Protection mode_ for hardware acceleration.
+If you are using the HA App, you may need to use the full access variant and turn off _Protection mode_ for hardware acceleration.

 ```yaml
 # if you want to decode a h264 stream
@@ -309,7 +311,7 @@ ffmpeg:
 If running Frigate through Docker, you either need to run in privileged mode or
 map the `/dev/video*` devices to Frigate. With Docker Compose add:

-```yaml
+```yaml {4-5}
 services:
  frigate:
    ...
@@ -319,7 +321,7 @@ services:

 Or with `docker run`:

-```bash
+```bash {4}
 docker run -d \
  --name frigate \
  ...
@@ -351,7 +353,7 @@ You will need to use the image with the nvidia container runtime:

 ### Docker Run CLI - Jetson

-```bash
+```bash {3}
 docker run -d \
  ...
  --runtime nvidia
@@ -360,7 +362,7 @@ docker run -d \

 ### Docker Compose - Jetson

-```yaml
+```yaml {5}
 services:
  frigate:
    ...
@@ -451,14 +453,14 @@ Restarting ffmpeg...

 you should try to uprade to FFmpeg 7. This can be done using this config option:

-```
+```yaml
 ffmpeg:
  path: "7.0"
 ```

 You can set this option globally to use FFmpeg 7 for all cameras or on camera level to use it only for specific cameras. Do not confuse this option with:

-```
+```yaml
 cameras:
  name:
    ffmpeg:
@@ -480,7 +482,7 @@ Make sure to follow the [Synaptics specific installation instructions](/frigate/

 Add one of the following FFmpeg presets to your `config.yml` to enable hardware video processing:

-```yaml
+```yaml {2}
 ffmpeg:
  hwaccel_args: -c:v h264_v4l2m2m
  input_args: preset-rtsp-restream
@@ -3,7 +3,7 @@ id: index
 title: Frigate Configuration
 ---

-For Home Assistant Add-on installations, the config file should be at `/addon_configs/<addon_directory>/config.yml`, where `<addon_directory>` is specific to the variant of the Frigate Add-on you are running. See the list of directories [here](#accessing-add-on-config-dir).
+For Home Assistant App installations, the config file should be at `/addon_configs/<addon_directory>/config.yml`, where `<addon_directory>` is specific to the variant of the Frigate App you are running. See the list of directories [here](#accessing-app-config-dir).

 For all other installation types, the config file should be mapped to `/config/config.yml` inside the container.

@@ -25,11 +25,11 @@ cameras:
            - detect
 ```

-## Accessing the Home Assistant Add-on configuration directory {#accessing-add-on-config-dir}
+## Accessing the Home Assistant App configuration directory {#accessing-app-config-dir}

-When running Frigate through the HA Add-on, the Frigate `/config` directory is mapped to `/addon_configs/<addon_directory>` in the host, where `<addon_directory>` is specific to the variant of the Frigate Add-on you are running.
+When running Frigate through the HA App, the Frigate `/config` directory is mapped to `/addon_configs/<addon_directory>` in the host, where `<addon_directory>` is specific to the variant of the Frigate App you are running.

-| Add-on Variant             | Configuration directory                   |
+| App Variant                | Configuration directory                   |
 | -------------------------- | ----------------------------------------- |
 | Frigate                    | `/addon_configs/ccab4aaf_frigate`         |
 | Frigate (Full Access)      | `/addon_configs/ccab4aaf_frigate-fa`      |
@@ -38,11 +38,11 @@ When running Frigate through the HA Add-on, the Frigate `/config` directory is m

 **Whenever you see `/config` in the documentation, it refers to this directory.**

-If for example you are running the standard Add-on variant and use the [VS Code Add-on](https://github.com/hassio-addons/addon-vscode) to browse your files, you can click _File_ > _Open folder..._ and navigate to `/addon_configs/ccab4aaf_frigate` to access the Frigate `/config` directory and edit the `config.yaml` file. You can also use the built-in file editor in the Frigate UI to edit the configuration file.
+If for example you are running the standard App variant and use the [VS Code App](https://github.com/hassio-addons/addon-vscode) to browse your files, you can click _File_ > _Open folder..._ and navigate to `/addon_configs/ccab4aaf_frigate` to access the Frigate `/config` directory and edit the `config.yaml` file. You can also use the built-in file editor in the Frigate UI to edit the configuration file.

 ## VS Code Configuration Schema

-VS Code supports JSON schemas for automatically validating configuration files. You can enable this feature by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema.json` to the beginning of the configuration file. Replace `frigate_host` with the IP address or hostname of your Frigate server. If you're using both VS Code and Frigate as an Add-on, you should use `ccab4aaf-frigate` instead. Make sure to expose the internal unauthenticated port `5000` when accessing the config from VS Code on another machine.
+VS Code supports JSON schemas for automatically validating configuration files. You can enable this feature by adding `# yaml-language-server: $schema=http://frigate_host:5000/api/config/schema.json` to the beginning of the configuration file. Replace `frigate_host` with the IP address or hostname of your Frigate server. If you're using both VS Code and Frigate as an App, you should use `ccab4aaf-frigate` instead. Make sure to expose the internal unauthenticated port `5000` when accessing the config from VS Code on another machine.

 ## Environment Variable Substitution

@@ -50,6 +50,7 @@ Frigate supports the use of environment variables starting with `FRIGATE_` **onl

 ```yaml
 mqtt:
+  host: "{FRIGATE_MQTT_HOST}"
  user: "{FRIGATE_MQTT_USER}"
  password: "{FRIGATE_MQTT_PASSWORD}"
 ```
@@ -60,7 +61,7 @@ mqtt:

 ```yaml
 onvif:
-  host: 10.0.10.10
+  host: "192.168.1.12"
  port: 8000
  user: "{FRIGATE_RTSP_USER}"
  password: "{FRIGATE_RTSP_PASSWORD}"
@@ -82,10 +83,10 @@ genai:

 Here are some common starter configuration examples. Refer to the [reference config](./reference.md) for detailed information about all the config values.

-### Raspberry Pi Home Assistant Add-on with USB Coral
+### Raspberry Pi Home Assistant App with USB Coral

 - Single camera with 720p, 5fps stream for detect
- MQTT connected to the Home Assistant Mosquitto Add-on
+- MQTT connected to the Home Assistant Mosquitto App
 - Hardware acceleration for decoding video
 - USB Coral detector
 - Save all video with any detectable motion for 7 days regardless of whether any objects were detected or not
@@ -30,7 +30,7 @@ In the default mode, Frigate's LPR needs to first detect a `car` or `motorcycle`

 ## Minimum System Requirements

-License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM is required.
+License plate recognition works by running AI models locally on your system. The YOLOv9 plate detector model and the OCR models ([PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)) are relatively lightweight and can run on your CPU or GPU, depending on your configuration. At least 4GB of RAM and a CPU with AVX + AVX2 instructions is required.

 ## Configuration

@@ -43,7 +43,7 @@ lpr:

 Like other enrichments in Frigate, LPR **must be enabled globally** to use the feature. You should disable it for specific cameras at the camera level if you don't want to run LPR on cars on those cameras:

-```yaml
+```yaml {4,5}
 cameras:
  garage:
    ...
@@ -375,7 +375,6 @@ Use `match_distance` to allow small character mismatches. Alternatively, define
 Start with ["Why isn't my license plate being detected and recognized?"](#why-isnt-my-license-plate-being-detected-and-recognized). If you are still having issues, work through these steps.

 1. Start with a simplified LPR config.
-
   - Remove or comment out everything in your LPR config, including `min_area`, `min_plate_length`, `format`, `known_plates`, or `enhancement` values so that the only values left are `enabled` and `debug_save_plates`. This will run LPR with Frigate's default values.

     ```yaml
@@ -386,31 +385,28 @@ Start with ["Why isn't my license plate being detected and recognized?"](#why-is
     ```

 2. Enable debug logs to see exactly what Frigate is doing.
-
   - Enable debug logs for LPR by adding `frigate.data_processing.common.license_plate: debug` to your `logger` configuration. These logs are _very_ verbose, so only keep this enabled when necessary. Restart Frigate after this change.

     ```yaml
     logger:
       default: info
       logs:
+        # highlight-next-line
         frigate.data_processing.common.license_plate: debug
     ```

 3. Ensure your plates are being _detected_.

   If you are using a Frigate+ or `license_plate` detecting model:
-
   - Watch the debug view (Settings --> Debug) to ensure that `license_plate` is being detected.
   - View MQTT messages for `frigate/events` to verify detected plates.
   - You may need to adjust your `min_score` and/or `threshold` for the `license_plate` object if your plates are not being detected.

   If you are **not** using a Frigate+ or `license_plate` detecting model:
-
   - Watch the debug logs for messages from the YOLOv9 plate detector.
   - You may need to adjust your `detection_threshold` if your plates are not being detected.

 4. Ensure the characters on detected plates are being _recognized_.
-
   - Enable `debug_save_plates` to save images of detected text on plates to the clips directory (`/media/frigate/clips/lpr`). Ensure these images are readable and the text is clear.
   - Watch the debug view to see plates recognized in real-time. For non-dedicated LPR cameras, the `car` or `motorcycle` label will change to the recognized plate when LPR is enabled and working.
   - Adjust `recognition_threshold` settings per the suggestions [above](#advanced-configuration).
@@ -15,7 +15,7 @@ The jsmpeg live view will use more browser and client GPU resources. Using go2rt
 | ------ | ------------------------------------- | ---------- | ---------------------------- | --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
 | jsmpeg | same as `detect -> fps`, capped at 10 | 720p       | no                           | no              | Resolution is configurable, but go2rtc is recommended if you want higher resolutions and better frame rates. jsmpeg is Frigate's default without go2rtc configured. |
 | mse    | native                                | native     | yes (depends on audio codec) | yes             | iPhone requires iOS 17.1+, Firefox is h.264 only. This is Frigate's default when go2rtc is configured.                                                              |
-| webrtc | native                                | native     | yes (depends on audio codec) | yes             | Requires extra configuration. Frigate attempts to use WebRTC when MSE fails or when using a camera's two-way talk feature.                   |
+| webrtc | native                                | native     | yes (depends on audio codec) | yes             | Requires extra configuration. Frigate attempts to use WebRTC when MSE fails or when using a camera's two-way talk feature.                                          |

 ### Camera Settings Recommendations

@@ -77,7 +77,7 @@ Configure the `streams` option with a "friendly name" for your stream followed b

 Using Frigate's internal version of go2rtc is required to use this feature. You cannot specify paths in the `streams` configuration, only go2rtc stream names.

-```yaml
+```yaml {3,6,8,25-29}
 go2rtc:
  streams:
    test_cam:
@@ -114,9 +114,9 @@ cameras:
 WebRTC works by creating a TCP or UDP connection on port `8555`. However, it requires additional configuration:

 - For external access, over the internet, setup your router to forward port `8555` to port `8555` on the Frigate device, for both TCP and UDP.
- For internal/local access, unless you are running through the HA Add-on, you will also need to set the WebRTC candidates list in the go2rtc config. For example, if `192.168.1.10` is the local IP of the device running Frigate:
+- For internal/local access, unless you are running through the HA App, you will also need to set the WebRTC candidates list in the go2rtc config. For example, if `192.168.1.10` is the local IP of the device running Frigate:

-  ```yaml title="config.yml"
+  ```yaml title="config.yml" {4-7}
  go2rtc:
    streams:
      test_cam: ...
@@ -128,13 +128,13 @@ WebRTC works by creating a TCP or UDP connection on port `8555`. However, it req

 - For access through Tailscale, the Frigate system's Tailscale IP must be added as a WebRTC candidate. Tailscale IPs all start with `100.`, and are reserved within the `100.64.0.0/10` CIDR block.

- Note that some browsers may not support H.265 (HEVC). You can check your browser's current version for H.265 compatibility [here](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness). 
+- Note that some browsers may not support H.265 (HEVC). You can check your browser's current version for H.265 compatibility [here](https://github.com/AlexxIT/go2rtc?tab=readme-ov-file#codecs-madness).

 :::tip

-This extra configuration may not be required if Frigate has been installed as a Home Assistant Add-on, as Frigate uses the Supervisor's API to generate a WebRTC candidate.
+This extra configuration may not be required if Frigate has been installed as a Home Assistant App, as Frigate uses the Supervisor's API to generate a WebRTC candidate.

-However, it is recommended if issues occur to define the candidates manually. You should do this if the Frigate Add-on fails to generate a valid candidate. If an error occurs you will see some warnings like the below in the Add-on logs page during the initialization:
+However, it is recommended if issues occur to define the candidates manually. You should do this if the Frigate App fails to generate a valid candidate. If an error occurs you will see some warnings like the below in the App logs page during the initialization:

 ```log
 [WARN] Failed to get IP address from supervisor
@@ -154,7 +154,7 @@ If not running in host mode, port 8555 will need to be mapped for the container:

 docker-compose.yml

-```yaml
+```yaml {4-6}
 services:
  frigate:
    ...
@@ -222,34 +222,28 @@ Note that disabling a camera through the config file (`enabled: False`) removes
 When your browser runs into problems playing back your camera streams, it will log short error messages to the browser console. They indicate playback, codec, or network issues on the client/browser side, not something server side with Frigate itself. Below are the common messages you may see and simple actions you can take to try to resolve them.

 - **startup**
-
  - What it means: The player failed to initialize or connect to the live stream (network or startup error).
  - What to try: Reload the Live view or click _Reset_. Verify `go2rtc` is running and the camera stream is reachable. Try switching to a different stream from the Live UI dropdown (if available) or use a different browser.

  - Possible console messages from the player code:
-
    - `Error opening MediaSource.`
    - `Browser reported a network error.`
    - `Max error count ${errorCount} exceeded.` (the numeric value will vary)

 - **mse-decode**
-
  - What it means: The browser reported a decoding error while trying to play the stream, which usually is a result of a codec incompatibility or corrupted frames.
  - What to try: Check the browser console for the supported and negotiated codecs. Ensure your camera/restream is using H.264 video and AAC audio (these are the most compatible). If your camera uses a non-standard audio codec, configure `go2rtc` to transcode the stream to AAC. Try another browser (some browsers have stricter MSE/codec support) and, for iPhone, ensure you're on iOS 17.1 or newer.

  - Possible console messages from the player code:
-
    - `Safari cannot open MediaSource.`
    - `Safari reported InvalidStateError.`
    - `Safari reported decoding errors.`

 - **stalled**
-
  - What it means: Playback has stalled because the player has fallen too far behind live (extended buffering or no data arriving).
  - What to try: This is usually indicative of the browser struggling to decode too many high-resolution streams at once. Try selecting a lower-bandwidth stream (substream), reduce the number of live streams open, improve the network connection, or lower the camera resolution. Also check your camera's keyframe (I-frame) interval — shorter intervals make playback start and recover faster. You can also try increasing the timeout value in the UI pane of Frigate's settings.

  - Possible console messages from the player code:
-
    - `Buffer time (10 seconds) exceeded, browser may not be playing media correctly.`
    - `Media playback has stalled after <n> seconds due to insufficient buffering or a network interruption.` (the seconds value will vary)

@@ -270,21 +264,18 @@ When your browser runs into problems playing back your camera streams, it will l
   If you are using continuous streaming or you are loading more than a few high resolution streams at once on the dashboard, your browser may struggle to begin playback of your streams before the timeout. Frigate always prioritizes showing a live stream as quickly as possible, even if it is a lower quality jsmpeg stream. You can use the "Reset" link/button to try loading your high resolution stream again.

   Errors in stream playback (e.g., connection failures, codec issues, or buffering timeouts) that cause the fallback to low bandwidth mode (jsmpeg) are logged to the browser console for easier debugging. These errors may include:
-
   - Network issues (e.g., MSE or WebRTC network connection problems).
   - Unsupported codecs or stream formats (e.g., H.265 in WebRTC, which is not supported in some browsers).
   - Buffering timeouts or low bandwidth conditions causing fallback to jsmpeg.
   - Browser compatibility problems (e.g., iOS Safari limitations with MSE).

   To view browser console logs:
-
   1. Open the Frigate Live View in your browser.
   2. Open the browser's Developer Tools (F12 or right-click > Inspect > Console tab).
   3. Reproduce the error (e.g., load a problematic stream or simulate network issues).
   4. Look for messages prefixed with the camera name.

   These logs help identify if the issue is player-specific (MSE vs. WebRTC) or related to camera configuration (e.g., go2rtc streams, codecs). If you see frequent errors:
-
   - Verify your camera's H.264/AAC settings (see [Frigate's camera settings recommendations](#camera_settings_recommendations)).
   - Check go2rtc configuration for transcoding (e.g., audio to AAC/OPUS).
   - Test with a different stream via the UI dropdown (if `live -> streams` is configured).
@@ -324,9 +315,7 @@ When your browser runs into problems playing back your camera streams, it will l
   To prevent this, make the `detect` stream match the go2rtc live stream's aspect ratio (resolution does not need to match, just the aspect ratio). You can either adjust the camera's output resolution or set the `width` and `height` values in your config's `detect` section to a resolution with an aspect ratio that matches.

   Example: Resolutions from two streams
-
   - Mismatched (may cause aspect ratio switching on the dashboard):
-
     - Live/go2rtc stream: 1920x1080 (16:9)
     - Detect stream: 640x352 (~1.82:1, not 16:9)

@@ -166,7 +166,7 @@ YOLOv9 models that are compiled for TensorFlow Lite and properly quantized are s

 :::tip

-**Frigate+ Users:** Follow the [instructions](../integrations/plus#use-models) to set a model ID in your config file.
+**Frigate+ Users:** Follow the [instructions](/integrations/plus#use-models) to set a model ID in your config file.

 :::

@@ -577,7 +577,7 @@ $ docker run --device=/dev/kfd --device=/dev/dri  \

 When using Docker Compose:

-```yaml
+```yaml {4-6}
 services:
  frigate:
    ...
@@ -608,7 +608,7 @@ $ docker run -e HSA_OVERRIDE_GFX_VERSION=10.0.0 \

 When using Docker Compose:

-```yaml
+```yaml {4-5}
 services:
  frigate:
    ...
@@ -130,7 +130,7 @@ When exporting a time-lapse the default speed-up is 25x with 30 FPS. This means

 To configure the speed-up factor, the frame rate and further custom settings, the configuration parameter `timelapse_args` can be used. The below configuration example would change the time-lapse speed to 60x (for fitting 1 hour of recording into 1 minute of time-lapse) with 25 FPS:

-```yaml
+```yaml {3-4}
 record:
  enabled: True
  export:
@@ -16,6 +16,8 @@ mqtt:
  # Optional: Enable mqtt server (default: shown below)
  enabled: True
  # Required: host name
+  # NOTE: MQTT host can be specified with an environment variable or docker secrets that must begin with 'FRIGATE_'.
+  #       e.g. host: '{FRIGATE_MQTT_HOST}'
  host: mqtt.server.com
  # Optional: port (default: shown below)
  port: 1883
@@ -949,6 +951,8 @@ cameras:
    onvif:
      # Required: host of the camera being connected to.
      # NOTE: HTTP is assumed by default; HTTPS is supported if you specify the scheme, ex: "https://0.0.0.0".
+      # NOTE: ONVIF user, and password can be specified with environment variables or docker secrets
+      #       that must begin with 'FRIGATE_'. e.g. host: '{FRIGATE_ONVIF_USERNAME}'
      host: 0.0.0.0
      # Optional: ONVIF port for device (default: shown below).
      port: 8000
@@ -34,7 +34,7 @@ To improve connection speed when using Birdseye via restream you can enable a sm

 The go2rtc restream can be secured with RTSP based username / password authentication. Ex:

-```yaml
+```yaml {2-4}
 go2rtc:
  rtsp:
    username: "admin"
@@ -147,6 +147,7 @@ For example:
 ```yaml
 go2rtc:
  streams:
+    # highlight-error-line
    my_camera: rtsp://username:$@foo%@192.168.1.100
 ```

@@ -155,6 +156,7 @@ becomes
 ```yaml
 go2rtc:
  streams:
+    # highlight-next-line
    my_camera: rtsp://username:$%40foo%25@192.168.1.100
 ```

@@ -71,7 +71,7 @@ To exclude a specific camera from alerts or detections, simply provide an empty

 For example, to exclude objects on the camera _gatecamera_ from any detections, include this in your config:

-```yaml
+```yaml {3-5}
 cameras:
  gatecamera:
    review:
@@ -13,7 +13,7 @@ Semantic Search is accessed via the _Explore_ view in the Frigate UI.

 Semantic Search works by running a large AI model locally on your system. Small or underpowered systems like a Raspberry Pi will not run Semantic Search reliably or at all.

-A minimum of 8GB of RAM is required to use Semantic Search. A GPU is not strictly required but will provide a significant performance increase over CPU-only systems.
+A minimum of 8GB of RAM is required to use Semantic Search. A CPU with AVX + AVX2 instructions is required to run Semantic Search. A GPU is not strictly required but will provide a significant performance increase over CPU-only systems.

 For best performance, 16GB or more of RAM and a dedicated GPU are recommended.

@@ -20,7 +20,7 @@ tls:

 TLS certificates can be mounted at `/etc/letsencrypt/live/frigate` using a bind mount or docker volume.

-```yaml
+```yaml {3-4}
 frigate:
  ...
  volumes:
@@ -32,7 +32,7 @@ Within the folder, the private key is expected to be named `privkey.pem` and the

 Note that certbot uses symlinks, and those can't be followed by the container unless it has access to the targets as well, so if using certbot you'll also have to mount the `archive` folder for your domain, e.g.:

-```yaml
+```yaml {3-5}
 frigate:
  ...
  volumes:
@@ -46,7 +46,7 @@ Frigate automatically compares the fingerprint of the certificate at `/etc/letse

 If you issue Frigate valid certificates you will likely want to configure it to run on port 443 so you can access it without a port number like `https://your-frigate-domain.com` by mapping 8971 to 443.

-```yaml
+```yaml {3-4}
 frigate:
  ...
  ports:
@@ -22,7 +22,7 @@ To create a zone, follow [the steps for a "Motion mask"](masks.md), but use the

 Often you will only want alerts to be created when an object enters areas of interest. This is done using zones along with setting required_zones. Let's say you only want to have an alert created when an object enters your entire_yard zone, the config would be:

-```yaml
+```yaml {6,8}
 cameras:
  name_of_your_camera:
    review:
@@ -108,6 +108,7 @@ cameras:
  name_of_your_camera:
    zones:
      sidewalk:
+        # highlight-next-line
        loitering_time: 4 # unit is in seconds
        objects:
          - person
@@ -122,6 +123,7 @@ cameras:
  name_of_your_camera:
    zones:
      front_yard:
+        # highlight-next-line
        inertia: 3
        objects:
          - person
@@ -134,6 +136,7 @@ cameras:
  name_of_your_camera:
    zones:
      driveway_entrance:
+        # highlight-next-line
        inertia: 1
        objects:
          - car
@@ -196,5 +199,6 @@ cameras:
        coordinates: ...
        distances: ...
        inertia: 1
+        # highlight-next-line
        speed_threshold: 20 # unit is in kph or mph, depending on how unit_system is set (see above)
 ```