Merge a2b92caab0 into d036061e3f

Add an `atlas` GenAI provider backed by Atlas Cloud, an OpenAI-compatible
inference platform serving vision-capable models. The provider subclasses
the existing OpenAIClient and only defaults the base_url to the Atlas
endpoint, reusing all vision, streaming, reasoning, and tool-calling logic.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

README.md

@@ -12,6 +12,44 @@
 
 \[English\] | [简体中文](https://github.com/blakeblackshear/frigate/blob/dev/README_CN.md)
 
+---
+
+<p align="center">
+  <a href="https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=frigate">
+    <img src="docs/static/img/branding/atlas-cloud-logo.png" alt="Atlas Cloud" width="200">
+  </a>
+</p>
+
+<p align="center">
+  <b><a href="https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=frigate">Atlas Cloud</a></b> is an OpenAI-compatible inference platform that can power Frigate's
+  <a href="https://docs.frigate.video/configuration/genai/">Generative AI</a> features as a drop-in multimodal LLM backend.
+  Point the <code>atlas</code> provider at Atlas Cloud and use a vision-capable model
+  (such as <code>qwen/qwen3-vl-235b-a22b-thinking</code> or <code>Qwen/Qwen3-VL-235B-A22B-Instruct</code>)
+  to generate natural-language object and review descriptions from detection frames —
+  no local GPU required. See the <a href="https://docs.frigate.video/configuration/genai/">GenAI configuration docs</a>
+  to get started, or grab a <a href="https://www.atlascloud.ai/console/coding-plan">coding plan</a>.
+</p>
+
+<details>
+<summary>Vision-capable Atlas Cloud models for GenAI descriptions</summary>
+
+Frigate's GenAI features require a **vision-capable** model. Good multimodal choices on Atlas Cloud include:
+
+- `qwen/qwen3-vl-235b-a22b-thinking`
+- `Qwen/Qwen3-VL-235B-A22B-Instruct`
+- `qwen/qwen3-vl-30b-a3b-instruct`
+- `qwen/qwen3-vl-30b-a3b-thinking`
+- `qwen/qwen3-vl-8b-instruct`
+- `google/gemini-3.5-flash`
+- `google/gemini-3.1-pro-preview`
+
+The full, always-current model catalog is available at the
+[Atlas Cloud console](https://www.atlascloud.ai/console).
+
+</details>
+
+---
+
 A complete and local NVR designed for [Home Assistant](https://www.home-assistant.io) with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras.
 
 Use of a GPU or AI accelerator is highly recommended. AI accelerators will outperform even the best CPUs with very little overhead. See Frigate's supported [object detectors](https://docs.frigate.video/configuration/object_detectors/).

README_CN.md

@@ -12,6 +12,43 @@
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
+---
+
+<p align="center">
+  <a href="https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=frigate">
+    <img src="docs/static/img/branding/atlas-cloud-logo.png" alt="Atlas Cloud" width="200">
+  </a>
+</p>
+
+<p align="center">
+  <b><a href="https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=frigate">Atlas Cloud</a></b> 是一个兼容 OpenAI 接口的推理平台，可作为即插即用的多模态 LLM 后端，
+  为 Frigate 的<a href="https://docs.frigate.video/configuration/genai/">生成式 AI（Generative AI）</a>功能提供算力支持。
+  只需将 <code>atlas</code> provider 指向 Atlas Cloud，并选用一个支持视觉的模型
+  （例如 <code>qwen/qwen3-vl-235b-a22b-thinking</code> 或 <code>Qwen/Qwen3-VL-235B-A22B-Instruct</code>），
+  即可基于检测帧画面生成自然语言的物体描述与审查摘要，无需本地 GPU。
+  请参阅 <a href="https://docs.frigate.video/configuration/genai/">GenAI 配置文档</a>开始使用，
+  或了解 <a href="https://www.atlascloud.ai/console/coding-plan">coding plan</a>。
+</p>
+
+<details>
+<summary>适合做 GenAI 描述的 Atlas Cloud 多模态模型</summary>
+
+Frigate 的 GenAI 功能要求使用**支持视觉**的模型。Atlas Cloud 上推荐的多模态模型包括：
+
+- `qwen/qwen3-vl-235b-a22b-thinking`
+- `Qwen/Qwen3-VL-235B-A22B-Instruct`
+- `qwen/qwen3-vl-30b-a3b-instruct`
+- `qwen/qwen3-vl-30b-a3b-thinking`
+- `qwen/qwen3-vl-8b-instruct`
+- `google/gemini-3.5-flash`
+- `google/gemini-3.1-pro-preview`
+
+完整且实时更新的模型列表请见 [Atlas Cloud 控制台](https://www.atlascloud.ai/console)。
+
+</details>
+
+---
+
 一个完整的本地网络视频录像机（NVR），专为[Home Assistant](https://www.home-assistant.io)设计，具备 AI 目标/物体检测功能。使用 OpenCV 和 TensorFlow 在本地为 IP 摄像头执行实时物体检测。
 
 强烈推荐使用 GPU 或者 AI 加速器（例如[Google Coral 加速器](https://coral.ai/products/) 或者 [Hailo](https://hailo.ai/)等）。它们的运行效率远远高于现在的顶级 CPU，并且功耗也极低。

docs/docs/configuration/genai/config.md

@@ -386,3 +386,44 @@ genai:
 
 </TabItem>
 </ConfigTabs>
+
+### Atlas Cloud
+
+[Atlas Cloud](https://www.atlascloud.ai/?utm_source=github&utm_medium=link&utm_campaign=frigate) is an OpenAI-compatible inference platform that serves a range of vision-capable models, so it can act as a drop-in multimodal backend for Frigate's Generative AI features. The `atlas` provider defaults its base URL to the Atlas Cloud endpoint, so a minimal config only needs your API key and a model.
+
+#### Supported Models
+
+You must use a vision capable model with Frigate. Recommended multimodal models on Atlas Cloud include `qwen/qwen3-vl-235b-a22b-thinking`, `Qwen/Qwen3-VL-235B-A22B-Instruct`, `qwen/qwen3-vl-30b-a3b-instruct`, and `google/gemini-3.5-flash`. The full, always-current catalog is available in the [Atlas Cloud console](https://www.atlascloud.ai/console).
+
+#### Get API Key
+
+To start using Atlas Cloud, create an API key from the [Atlas Cloud console](https://www.atlascloud.ai/console/api-keys).
+
+#### Configuration
+
+<ConfigTabs>
+<TabItem value="ui">
+
+1. Navigate to <NavPath path="Settings > Enrichments > Generative AI" />.
+   - Set **Provider** to `atlas`
+   - Set **API key** to your Atlas Cloud API key (or use an environment variable such as `{FRIGATE_ATLAS_API_KEY}`)
+   - Set **Model** to a vision-capable model (e.g., `qwen/qwen3-vl-235b-a22b-thinking`)
+
+</TabItem>
+<TabItem value="yaml">
+
+```yaml
+genai:
+  provider: atlas
+  api_key: "{FRIGATE_ATLAS_API_KEY}"
+  model: qwen/qwen3-vl-235b-a22b-thinking
+```
+
+</TabItem>
+</ConfigTabs>
+
+:::note
+
+The `atlas` provider points to `https://api.atlascloud.ai/v1` by default. To target a different OpenAI-compatible endpoint, set `base_url` explicitly.
+
+:::

frigate/api/preview.py

@@ -1,7 +1,9 @@
 """Preview apis."""
 
+import bisect
 import logging
 import os
+import threading
 from datetime import datetime, timedelta, timezone
 
 import pytz
@@ -133,6 +135,32 @@ def preview_hour(
     return preview_ts(camera_name, start_ts, end_ts, allowed_cameras)
 
 
+# cache one sorted listing of the shared preview_frames dir
+_preview_listing_lock = threading.Lock()
+_preview_listing_cache: tuple[float, list[str]] = (-1.0, [])
+
+
+def _get_preview_frame_listing(preview_dir: str) -> list[str]:
+    """Return the sorted preview_frames listing, cached until the dir changes."""
+    global _preview_listing_cache
+
+    # mtime bumps when a frame is added or removed, invalidating the cache
+    mtime = os.stat(preview_dir).st_mtime
+    cached_mtime, files = _preview_listing_cache
+    if mtime == cached_mtime:
+        return files
+
+    with _preview_listing_lock:
+        # another thread may have refreshed the cache while we waited
+        cached_mtime, files = _preview_listing_cache
+        if mtime == cached_mtime:
+            return files
+
+        files = sorted(entry.name for entry in os.scandir(preview_dir))
+        _preview_listing_cache = (mtime, files)
+        return files
+
+
 @router.get(
     "/preview/{camera_name}/start/{start_ts}/end/{end_ts}/frames",
     response_model=PreviewFramesResponse,
@@ -149,23 +177,15 @@ def get_preview_frames_from_cache(camera_name: str, start_ts: float, end_ts: flo
     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)
+    files = _get_preview_frame_listing(preview_dir)
+
+    # a camera's frames form a contiguous slice of the sorted listing;
+    # bisect locates it without scanning the whole directory
+    left = bisect.bisect_left(files, start_file)
+    right = bisect.bisect_right(files, end_file)
+    selected_previews = [
+        file for file in files[left:right] if file.startswith(file_start)
     ]
-    camera_files.sort()
-
-    selected_previews = []
-
-    for file in camera_files:
-        if file < start_file:
-            continue
-
-        if file > end_file:
-            break
-
-        selected_previews.append(file)
 
     return JSONResponse(
         content=selected_previews,

frigate/config/camera/genai.py

@@ -12,6 +12,7 @@ __all__ = ["GenAIConfig", "GenAIProviderEnum", "GenAIRoleEnum"]
 class GenAIProviderEnum(str, Enum):
     openai = "openai"
     azure_openai = "azure_openai"
+    atlas = "atlas"
     gemini = "gemini"
     ollama = "ollama"
     llamacpp = "llamacpp"

frigate/genai/plugins/atlas.py

@@ -0,0 +1,71 @@
+"""Atlas Cloud Provider for Frigate AI.
+
+Atlas Cloud (https://www.atlascloud.ai) is an OpenAI-compatible inference
+platform that serves a range of vision-capable models. Because its chat
+completions API follows the OpenAI standard, this provider inherits all
+transport, vision, streaming, reasoning, and tool-calling logic from
+:class:`OpenAIClient` and only overrides what is Atlas-specific:
+
+- Client construction: defaults ``base_url`` to the Atlas Cloud endpoint
+  when the user has not set one explicitly, so a minimal config (provider +
+  api_key + model) works out of the box. A user-supplied ``base_url`` still
+  takes precedence.
+- Context size: the Atlas ``/models`` endpoint does not reliably surface a
+  per-model context window, so we fall back to a conservative default rather
+  than the model-name heuristic used by OpenAI. It can be overridden via
+  ``provider_options.context_size``.
+"""
+
+import logging
+from typing import Optional
+
+from openai import OpenAI
+
+from frigate.config import GenAIProviderEnum
+from frigate.genai import register_genai_provider
+from frigate.genai.plugins.openai import OpenAIClient
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_BASE_URL = "https://api.atlascloud.ai/v1"
+
+# Atlas serves large-context models, but its model listing does not expose a
+# per-model context window; default conservatively and let users override via
+# provider_options.context_size when they know their model's window.
+DEFAULT_CONTEXT_SIZE = 32000
+
+
+@register_genai_provider(GenAIProviderEnum.atlas)
+class AtlasClient(OpenAIClient):
+    """Generative AI client for Frigate using Atlas Cloud."""
+
+    def _init_provider(self) -> OpenAI:
+        """Initialize the OpenAI client pointed at Atlas Cloud.
+
+        Defaults ``base_url`` to the Atlas endpoint when the user has not set
+        one, then defers to the OpenAI implementation for everything else.
+        """
+        if not self.genai_config.base_url:
+            self.genai_config.base_url = DEFAULT_BASE_URL
+
+        return super()._init_provider()
+
+    def get_context_size(self) -> int:
+        """Return the context window for Atlas models.
+
+        A manually specified ``context_size`` in ``provider_options`` always
+        wins; otherwise fall back to a conservative default since Atlas does
+        not reliably surface per-model context windows.
+        """
+        if self.context_size is not None:
+            return self.context_size
+
+        provider_context_size: Optional[int] = self.genai_config.provider_options.get(
+            "context_size"
+        )
+        if provider_context_size is not None:
+            self.context_size = provider_context_size
+            return self.context_size
+
+        self.context_size = DEFAULT_CONTEXT_SIZE
+        return self.context_size

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

@@ -70,6 +70,13 @@
       "selectFromTimeline": "Select from Timeline",
       "cameraSelection": "Cameras",
       "cameraSelectionHelp": "Cameras with tracked objects in this time range are pre-selected",
+      "searchOrSelectGroup": "Search, or select a camera group...",
+      "selectAll": "Select all cameras",
+      "clearSelection": "Clear selection",
+      "selectWithActivity": "Cameras with tracked objects",
+      "selectGroup": "Select group",
+      "noMatchingCameras": "No cameras match your search",
+      "selectedCount": "{{selected}} / {{total}} selected",
       "checkingActivity": "Checking camera activity...",
       "noCameras": "No cameras available",
       "detectionCount_one": "1 tracked object",

web/src/components/overlay/ExportDialog.tsx

@@ -39,6 +39,16 @@ import {
   TooltipContent,
   TooltipTrigger,
 } from "@/components/ui/tooltip";
+import {
+  Command,
+  CommandGroup,
+  CommandInput,
+  CommandItem,
+  CommandList,
+  CommandSeparator,
+} from "../ui/command";
+import { IconRenderer } from "../icons/IconPicker";
+import * as LuIcons from "react-icons/lu";
 import { isDesktop, isMobile } from "react-device-detect";
 import { Drawer, DrawerContent, DrawerTrigger } from "../ui/drawer";
 import SaveExportOverlay from "./SaveExportOverlay";
@@ -376,6 +386,9 @@ export function ExportContent({
   const [newCaseName, setNewCaseName] = useState("");
   const [newCaseDescription, setNewCaseDescription] = useState("");
   const [isStartingBatchExport, setIsStartingBatchExport] = useState(false);
+  const [cameraSearch, setCameraSearch] = useState("");
+  const [cameraMenuOpen, setCameraMenuOpen] = useState(false);
+  const cameraMenuRef = useRef<HTMLDivElement>(null);
   const multiRangeKey = useMemo(() => {
     if (activeTab !== "multi" || !range) {
       return undefined;
@@ -577,6 +590,75 @@ export function ExportContent({
     );
   }, []);
 
+  const availableCameraIds = useMemo(
+    () => cameraActivities.map((activity) => activity.camera),
+    [cameraActivities],
+  );
+
+  const activeCameraIds = useMemo(
+    () =>
+      cameraActivities
+        .filter((activity) => activity.hasDetections)
+        .map((activity) => activity.camera),
+    [cameraActivities],
+  );
+
+  const cameraGroups = useMemo(
+    () =>
+      Object.entries(config?.camera_groups ?? {})
+        .map(([name, group]) => ({
+          name,
+          icon: group.icon,
+          order: group.order,
+          cameras: group.cameras.filter((cameraId) =>
+            availableCameraIds.includes(cameraId),
+          ),
+        }))
+        .filter((group) => group.cameras.length > 0)
+        .sort((a, b) => a.order - b.order),
+    [config?.camera_groups, availableCameraIds],
+  );
+
+  // Filter the rendered camera cards by the search query
+  const filteredCameraActivities = useMemo(() => {
+    const query = cameraSearch.trim().toLowerCase();
+    if (!query) {
+      return cameraActivities;
+    }
+    return cameraActivities.filter((activity) => {
+      const friendlyName = resolveCameraName(config, activity.camera);
+      return (
+        activity.camera.toLowerCase().includes(query) ||
+        friendlyName.toLowerCase().includes(query)
+      );
+    });
+  }, [cameraActivities, cameraSearch, config]);
+
+  // Group/all/activity selection replaces the current selection
+  const applyCameraSelection = useCallback((cameraIds: string[]) => {
+    setHasManualCameraSelection(true);
+    setSelectedCameraIds(cameraIds);
+    setCameraMenuOpen(false);
+  }, []);
+
+  // Close the dropdown when focus leaves the camera selection control entirely
+  const handleCameraInputBlur = useCallback((event: React.FocusEvent) => {
+    if (
+      cameraMenuRef.current &&
+      !cameraMenuRef.current.contains(event.relatedTarget as Node)
+    ) {
+      setCameraMenuOpen(false);
+    }
+  }, []);
+
+  // Reset the search and dropdown when leaving the multi-camera tab
+  useEffect(() => {
+    if (activeTab !== "multi") {
+      setCameraSearch("");
+      setCameraMenuOpen(false);
+    }
+  }, [activeTab]);
+
   const startBatchExport = useCallback(async () => {
     if (isStartingBatchExport) {
       return;
@@ -802,7 +884,7 @@ export function ExportContent({
 
           {isAdmin && (
             <div className="space-y-2">
-              <Label className="text-sm text-secondary-foreground">
+              <Label className="text-sm text-primary">
                 {t("export.case.label")}
               </Label>
               <Select
@@ -859,7 +941,7 @@ export function ExportContent({
           )}
         >
           <div className="space-y-2">
-            <Label className="text-sm text-secondary-foreground">
+            <Label className="text-sm text-primary">
               {t("export.multiCamera.timeRange")}
             </Label>
             <div className="flex items-center gap-2">
@@ -902,16 +984,109 @@ export function ExportContent({
           </div>
 
           <div className="space-y-2">
-            <Label className="text-sm text-secondary-foreground">
-              {t("export.multiCamera.cameraSelection")}
-            </Label>
+            <div className="flex items-center justify-between gap-2">
+              <Label className="text-sm text-primary">
+                {t("export.multiCamera.cameraSelection")}
+              </Label>
+              {availableCameraIds.length > 0 && (
+                <span className="text-xs text-muted-foreground">
+                  {t("export.multiCamera.selectedCount", {
+                    selected: selectedCameraCount,
+                    total: availableCameraIds.length,
+                  })}
+                </span>
+              )}
+            </div>
             <div className="text-xs text-muted-foreground">
               {t("export.multiCamera.cameraSelectionHelp")}
             </div>
+            {!isEventsLoading && availableCameraIds.length > 0 && (
+              <div className="relative" ref={cameraMenuRef}>
+                <Command
+                  shouldFilter={false}
+                  className="overflow-visible rounded-md border bg-secondary/40"
+                >
+                  <CommandInput
+                    value={cameraSearch}
+                    onValueChange={setCameraSearch}
+                    onFocus={() => setCameraMenuOpen(true)}
+                    onBlur={handleCameraInputBlur}
+                    placeholder={t("export.multiCamera.searchOrSelectGroup")}
+                  />
+                  {/* Hide the actions/groups menu while a search query is
+                      active so it doesn't cover the filtered camera cards. */}
+                  {cameraMenuOpen && cameraSearch.trim().length === 0 && (
+                    <CommandList className="absolute top-full z-10 mt-1 max-h-72 w-full rounded-md border bg-background shadow-md">
+                      <CommandGroup>
+                        <CommandItem
+                          value="action:select-all"
+                          className="cursor-pointer"
+                          onSelect={() =>
+                            applyCameraSelection(availableCameraIds)
+                          }
+                        >
+                          <span>{t("export.multiCamera.selectAll")}</span>
+                          <span className="ml-auto text-xs text-muted-foreground">
+                            {availableCameraIds.length}
+                          </span>
+                        </CommandItem>
+                        <CommandItem
+                          value="action:clear"
+                          className="cursor-pointer"
+                          onSelect={() => applyCameraSelection([])}
+                        >
+                          {t("export.multiCamera.clearSelection")}
+                        </CommandItem>
+                        <CommandItem
+                          value="action:activity"
+                          className="cursor-pointer"
+                          onSelect={() => applyCameraSelection(activeCameraIds)}
+                        >
+                          <span>
+                            {t("export.multiCamera.selectWithActivity")}
+                          </span>
+                          <span className="ml-auto text-xs text-muted-foreground">
+                            {activeCameraIds.length}
+                          </span>
+                        </CommandItem>
+                      </CommandGroup>
+                      {cameraGroups.length > 0 && (
+                        <>
+                          <CommandSeparator />
+                          <CommandGroup
+                            heading={t("export.multiCamera.selectGroup")}
+                          >
+                            {cameraGroups.map((group) => (
+                              <CommandItem
+                                key={group.name}
+                                value={`group:${group.name}`}
+                                className="cursor-pointer"
+                                onSelect={() =>
+                                  applyCameraSelection(group.cameras)
+                                }
+                              >
+                                <IconRenderer
+                                  icon={LuIcons[group.icon]}
+                                  className="mr-2 size-4 text-secondary-foreground"
+                                />
+                                <span className="truncate">{group.name}</span>
+                                <span className="ml-auto text-xs text-muted-foreground">
+                                  {group.cameras.length}
+                                </span>
+                              </CommandItem>
+                            ))}
+                          </CommandGroup>
+                        </>
+                      )}
+                    </CommandList>
+                  )}
+                </Command>
+              </div>
+            )}
             <div
               className={cn(
                 "scrollbar-container space-y-2",
-                isDesktop && "max-h-64 overflow-y-auto pr-1",
+                isDesktop && "max-h-64 overflow-y-auto p-0.5 pr-1",
               )}
             >
               {isEventsLoading && (
@@ -924,7 +1099,14 @@ export function ExportContent({
                   {t("export.multiCamera.noCameras")}
                 </div>
               )}
-              {cameraActivities.map((activity) => {
+              {!isEventsLoading &&
+                cameraActivities.length > 0 &&
+                filteredCameraActivities.length === 0 && (
+                  <div className="px-2 py-4 text-sm text-muted-foreground">
+                    {t("export.multiCamera.noMatchingCameras")}
+                  </div>
+                )}
+              {filteredCameraActivities.map((activity) => {
                 const isSelected = selectedCameraIds.includes(activity.camera);
 
                 return (
@@ -981,7 +1163,7 @@ export function ExportContent({
           </div>
 
           <div className="space-y-2">
-            <Label className="text-sm text-secondary-foreground">
+            <Label className="text-sm text-primary">
               {t("export.multiCamera.nameLabel")}
             </Label>
             <Input
@@ -994,7 +1176,7 @@ export function ExportContent({
 
           {isAdmin && (
             <div className="space-y-2">
-              <Label className="text-sm text-secondary-foreground">
+              <Label className="text-sm text-primary">
                 {t("export.case.label")}
               </Label>
               <Select