Increase mypy coverage and fixes (#22632)

frigate/genai/__init__.py

@@ -5,7 +5,7 @@ import importlib
 import logging
 import os
 import re
-from typing import Any, Optional
+from typing import Any, Callable, Optional
 
 import numpy as np
 from playhouse.shortcuts import model_to_dict
@@ -31,10 +31,10 @@ __all__ = [
 PROVIDERS = {}
 
 
-def register_genai_provider(key: GenAIProviderEnum):
+def register_genai_provider(key: GenAIProviderEnum) -> Callable:
     """Register a GenAI provider."""
 
-    def decorator(cls):
+    def decorator(cls: type) -> type:
         PROVIDERS[key] = cls
         return cls
 
@@ -297,7 +297,7 @@ Guidelines:
         """Generate a description for the frame."""
         try:
             prompt = camera_config.objects.genai.object_prompts.get(
-                event.label,
+                str(event.label),
                 camera_config.objects.genai.prompt,
             ).format(**model_to_dict(event))
         except KeyError as e:
@@ -307,7 +307,7 @@ Guidelines:
         logger.debug(f"Sending images to genai provider with prompt: {prompt}")
         return self._send(prompt, thumbnails)
 
-    def _init_provider(self):
+    def _init_provider(self) -> Any:
         """Initialize the client."""
         return None
 
@@ -402,7 +402,7 @@ Guidelines:
         }
 
 
-def load_providers():
+def load_providers() -> None:
     package_dir = os.path.dirname(__file__)
     for filename in os.listdir(package_dir):
         if filename.endswith(".py") and filename != "__init__.py":

frigate/genai/azure-openai.py

@@ -3,7 +3,7 @@
 import base64
 import json
 import logging
-from typing import Any, Optional
+from typing import Any, AsyncGenerator, Optional
 from urllib.parse import parse_qs, urlparse
 
 from openai import AzureOpenAI
@@ -20,10 +20,10 @@ class OpenAIClient(GenAIClient):
 
     provider: AzureOpenAI
 
-    def _init_provider(self):
+    def _init_provider(self) -> AzureOpenAI | None:
         """Initialize the client."""
         try:
-            parsed_url = urlparse(self.genai_config.base_url)
+            parsed_url = urlparse(self.genai_config.base_url or "")
             query_params = parse_qs(parsed_url.query)
             api_version = query_params.get("api-version", [None])[0]
             azure_endpoint = f"{parsed_url.scheme}://{parsed_url.netloc}/"
@@ -79,7 +79,7 @@ class OpenAIClient(GenAIClient):
             logger.warning("Azure OpenAI returned an error: %s", str(e))
             return None
         if len(result.choices) > 0:
-            return result.choices[0].message.content.strip()
+            return str(result.choices[0].message.content.strip())
         return None
 
     def get_context_size(self) -> int:
@@ -113,7 +113,7 @@ class OpenAIClient(GenAIClient):
                 if openai_tool_choice is not None:
                     request_params["tool_choice"] = openai_tool_choice
 
-            result = self.provider.chat.completions.create(**request_params)
+            result = self.provider.chat.completions.create(**request_params)  # type: ignore[call-overload]
 
             if (
                 result is None
@@ -181,7 +181,7 @@ class OpenAIClient(GenAIClient):
         messages: list[dict[str, Any]],
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
-    ):
+    ) -> AsyncGenerator[tuple[str, Any], None]:
         """
         Stream chat with tools; yields content deltas then final message.
 
@@ -214,7 +214,7 @@ class OpenAIClient(GenAIClient):
             tool_calls_by_index: dict[int, dict[str, Any]] = {}
             finish_reason = "stop"
 
-            stream = self.provider.chat.completions.create(**request_params)
+            stream = self.provider.chat.completions.create(**request_params)  # type: ignore[call-overload]
 
             for chunk in stream:
                 if not chunk or not chunk.choices:

frigate/genai/gemini.py

@@ -2,10 +2,11 @@
 
 import json
 import logging
-from typing import Any, Optional
+from typing import Any, AsyncGenerator, Optional
 
 from google import genai
 from google.genai import errors, types
+from google.genai.types import FunctionCallingConfigMode
 
 from frigate.config import GenAIProviderEnum
 from frigate.genai import GenAIClient, register_genai_provider
@@ -19,10 +20,10 @@ class GeminiClient(GenAIClient):
 
     provider: genai.Client
 
-    def _init_provider(self):
+    def _init_provider(self) -> genai.Client:
         """Initialize the client."""
         # Merge provider_options into HttpOptions
-        http_options_dict = {
+        http_options_dict: dict[str, Any] = {
             "timeout": int(self.timeout * 1000),  # requires milliseconds
             "retry_options": types.HttpRetryOptions(
                 attempts=3,
@@ -54,7 +55,7 @@ class GeminiClient(GenAIClient):
         ] + [prompt]
         try:
             # Merge runtime_options into generation_config if provided
-            generation_config_dict = {"candidate_count": 1}
+            generation_config_dict: dict[str, Any] = {"candidate_count": 1}
             generation_config_dict.update(self.genai_config.runtime_options)
 
             if response_format and response_format.get("type") == "json_schema":
@@ -65,7 +66,7 @@ class GeminiClient(GenAIClient):
 
             response = self.provider.models.generate_content(
                 model=self.genai_config.model,
-                contents=contents,
+                contents=contents,  # type: ignore[arg-type]
                 config=types.GenerateContentConfig(
                     **generation_config_dict,
                 ),
@@ -78,6 +79,8 @@ class GeminiClient(GenAIClient):
             return None
 
         try:
+            if response.text is None:
+                return None
             description = response.text.strip()
         except (ValueError, AttributeError):
             # No description was generated
@@ -102,7 +105,7 @@ class GeminiClient(GenAIClient):
         """
         try:
             # Convert messages to Gemini format
-            gemini_messages = []
+            gemini_messages: list[types.Content] = []
             for msg in messages:
                 role = msg.get("role", "user")
                 content = msg.get("content", "")
@@ -110,7 +113,11 @@ class GeminiClient(GenAIClient):
                 # Map roles to Gemini format
                 if role == "system":
                     # Gemini doesn't have system role, prepend to first user message
-                    if gemini_messages and gemini_messages[0].role == "user":
+                    if (
+                        gemini_messages
+                        and gemini_messages[0].role == "user"
+                        and gemini_messages[0].parts
+                    ):
                         gemini_messages[0].parts[
                             0
                         ].text = f"{content}\n\n{gemini_messages[0].parts[0].text}"
@@ -136,7 +143,7 @@ class GeminiClient(GenAIClient):
                         types.Content(
                             role="function",
                             parts=[
-                                types.Part.from_function_response(function_response)
+                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
                             ],
                         )
                     )
@@ -171,19 +178,25 @@ class GeminiClient(GenAIClient):
             if tool_choice:
                 if tool_choice == "none":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="NONE")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.NONE
+                        )
                     )
                 elif tool_choice == "auto":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="AUTO")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.AUTO
+                        )
                     )
                 elif tool_choice == "required":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="ANY")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.ANY
+                        )
                     )
 
             # Build request config
-            config_params = {"candidate_count": 1}
+            config_params: dict[str, Any] = {"candidate_count": 1}
 
             if gemini_tools:
                 config_params["tools"] = gemini_tools
@@ -197,7 +210,7 @@ class GeminiClient(GenAIClient):
 
             response = self.provider.models.generate_content(
                 model=self.genai_config.model,
-                contents=gemini_messages,
+                contents=gemini_messages,  # type: ignore[arg-type]
                 config=types.GenerateContentConfig(**config_params),
             )
 
@@ -291,7 +304,7 @@ class GeminiClient(GenAIClient):
         messages: list[dict[str, Any]],
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
-    ):
+    ) -> AsyncGenerator[tuple[str, Any], None]:
         """
         Stream chat with tools; yields content deltas then final message.
 
@@ -299,7 +312,7 @@ class GeminiClient(GenAIClient):
         """
         try:
             # Convert messages to Gemini format
-            gemini_messages = []
+            gemini_messages: list[types.Content] = []
             for msg in messages:
                 role = msg.get("role", "user")
                 content = msg.get("content", "")
@@ -307,7 +320,11 @@ class GeminiClient(GenAIClient):
                 # Map roles to Gemini format
                 if role == "system":
                     # Gemini doesn't have system role, prepend to first user message
-                    if gemini_messages and gemini_messages[0].role == "user":
+                    if (
+                        gemini_messages
+                        and gemini_messages[0].role == "user"
+                        and gemini_messages[0].parts
+                    ):
                         gemini_messages[0].parts[
                             0
                         ].text = f"{content}\n\n{gemini_messages[0].parts[0].text}"
@@ -333,7 +350,7 @@ class GeminiClient(GenAIClient):
                         types.Content(
                             role="function",
                             parts=[
-                                types.Part.from_function_response(function_response)
+                                types.Part.from_function_response(function_response)  # type: ignore[misc,call-arg,arg-type]
                             ],
                         )
                     )
@@ -368,19 +385,25 @@ class GeminiClient(GenAIClient):
             if tool_choice:
                 if tool_choice == "none":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="NONE")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.NONE
+                        )
                     )
                 elif tool_choice == "auto":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="AUTO")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.AUTO
+                        )
                     )
                 elif tool_choice == "required":
                     tool_config = types.ToolConfig(
-                        function_calling_config=types.FunctionCallingConfig(mode="ANY")
+                        function_calling_config=types.FunctionCallingConfig(
+                            mode=FunctionCallingConfigMode.ANY
+                        )
                     )
 
             # Build request config
-            config_params = {"candidate_count": 1}
+            config_params: dict[str, Any] = {"candidate_count": 1}
 
             if gemini_tools:
                 config_params["tools"] = gemini_tools
@@ -399,7 +422,7 @@ class GeminiClient(GenAIClient):
 
             stream = await self.provider.aio.models.generate_content_stream(
                 model=self.genai_config.model,
-                contents=gemini_messages,
+                contents=gemini_messages,  # type: ignore[arg-type]
                 config=types.GenerateContentConfig(**config_params),
             )
 

frigate/genai/llama_cpp.py

@@ -4,7 +4,7 @@ import base64
 import io
 import json
 import logging
-from typing import Any, Optional
+from typing import Any, AsyncGenerator, Optional
 
 import httpx
 import numpy as np
@@ -23,7 +23,7 @@ def _to_jpeg(img_bytes: bytes) -> bytes | None:
     try:
         img = Image.open(io.BytesIO(img_bytes))
         if img.mode != "RGB":
-            img = img.convert("RGB")
+            img = img.convert("RGB")  # type: ignore[assignment]
         buf = io.BytesIO()
         img.save(buf, format="JPEG", quality=85)
         return buf.getvalue()
@@ -36,10 +36,10 @@ def _to_jpeg(img_bytes: bytes) -> bytes | None:
 class LlamaCppClient(GenAIClient):
     """Generative AI client for Frigate using llama.cpp server."""
 
-    provider: str  # base_url
+    provider: str | None  # base_url
     provider_options: dict[str, Any]
 
-    def _init_provider(self):
+    def _init_provider(self) -> str | None:
         """Initialize the client."""
         self.provider_options = {
             **self.genai_config.provider_options,
@@ -75,7 +75,7 @@ class LlamaCppClient(GenAIClient):
                 content.append(
                     {
                         "type": "image_url",
-                        "image_url": {
+                        "image_url": {  # type: ignore[dict-item]
                             "url": f"data:image/jpeg;base64,{encoded_image}",
                         },
                     }
@@ -111,7 +111,7 @@ class LlamaCppClient(GenAIClient):
             ):
                 choice = result["choices"][0]
                 if "message" in choice and "content" in choice["message"]:
-                    return choice["message"]["content"].strip()
+                    return str(choice["message"]["content"].strip())
             return None
         except Exception as e:
             logger.warning("llama.cpp returned an error: %s", str(e))
@@ -229,7 +229,7 @@ class LlamaCppClient(GenAIClient):
             content.append(
                 {
                     "prompt_string": "<__media__>\n",
-                    "multimodal_data": [encoded],
+                    "multimodal_data": [encoded],  # type: ignore[dict-item]
                 }
             )
 
@@ -367,7 +367,7 @@ class LlamaCppClient(GenAIClient):
         messages: list[dict[str, Any]],
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
-    ):
+    ) -> AsyncGenerator[tuple[str, Any], None]:
         """Stream chat with tools via OpenAI-compatible streaming API."""
         if self.provider is None:
             logger.warning(

frigate/genai/ollama.py

@@ -2,7 +2,7 @@
 
 import json
 import logging
-from typing import Any, Optional
+from typing import Any, AsyncGenerator, Optional
 
 from httpx import RemoteProtocolError, TimeoutException
 from ollama import AsyncClient as OllamaAsyncClient
@@ -28,10 +28,10 @@ class OllamaClient(GenAIClient):
         },
     }
 
-    provider: ApiClient
+    provider: ApiClient | None
     provider_options: dict[str, Any]
 
-    def _init_provider(self):
+    def _init_provider(self) -> ApiClient | None:
         """Initialize the client."""
         self.provider_options = {
             **self.LOCAL_OPTIMIZED_OPTIONS,
@@ -73,7 +73,7 @@ class OllamaClient(GenAIClient):
             "exclusiveMinimum",
             "exclusiveMaximum",
         }
-        result = {}
+        result: dict[str, Any] = {}
         for key, value in schema.items():
             if not _is_properties and key in STRIP_KEYS:
                 continue
@@ -122,7 +122,7 @@ class OllamaClient(GenAIClient):
             logger.debug(
                 f"Ollama tokens used: eval_count={result.get('eval_count')}, prompt_eval_count={result.get('prompt_eval_count')}"
             )
-            return result["response"].strip()
+            return str(result["response"]).strip()
         except (
             TimeoutException,
             ResponseError,
@@ -263,7 +263,7 @@ class OllamaClient(GenAIClient):
         messages: list[dict[str, Any]],
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
-    ):
+    ) -> AsyncGenerator[tuple[str, Any], None]:
         """Stream chat with tools; yields content deltas then final message.
 
         When tools are provided, Ollama streaming does not include tool_calls

frigate/genai/openai.py

@@ -3,7 +3,7 @@
 import base64
 import json
 import logging
-from typing import Any, Optional
+from typing import Any, AsyncGenerator, Optional
 
 from httpx import TimeoutException
 from openai import OpenAI
@@ -21,7 +21,7 @@ class OpenAIClient(GenAIClient):
     provider: OpenAI
     context_size: Optional[int] = None
 
-    def _init_provider(self):
+    def _init_provider(self) -> OpenAI:
         """Initialize the client."""
         # Extract context_size from provider_options as it's not a valid OpenAI client parameter
         # It will be used in get_context_size() instead
@@ -81,7 +81,7 @@ class OpenAIClient(GenAIClient):
                 and hasattr(result, "choices")
                 and len(result.choices) > 0
             ):
-                return result.choices[0].message.content.strip()
+                return str(result.choices[0].message.content.strip())
             return None
         except (TimeoutException, Exception) as e:
             logger.warning("OpenAI returned an error: %s", str(e))
@@ -171,7 +171,7 @@ class OpenAIClient(GenAIClient):
                 }
                 request_params.update(provider_opts)
 
-            result = self.provider.chat.completions.create(**request_params)
+            result = self.provider.chat.completions.create(**request_params)  # type: ignore[call-overload]
 
             if (
                 result is None
@@ -245,7 +245,7 @@ class OpenAIClient(GenAIClient):
         messages: list[dict[str, Any]],
         tools: Optional[list[dict[str, Any]]] = None,
         tool_choice: Optional[str] = "auto",
-    ):
+    ) -> AsyncGenerator[tuple[str, Any], None]:
         """
         Stream chat with tools; yields content deltas then final message.
 
@@ -287,7 +287,7 @@ class OpenAIClient(GenAIClient):
             tool_calls_by_index: dict[int, dict[str, Any]] = {}
             finish_reason = "stop"
 
-            stream = self.provider.chat.completions.create(**request_params)
+            stream = self.provider.chat.completions.create(**request_params)  # type: ignore[call-overload]
 
             for chunk in stream:
                 if not chunk or not chunk.choices:

frigate/jobs/media_sync.py

@@ -5,7 +5,7 @@ import os
 import threading
 from dataclasses import dataclass, field
 from datetime import datetime
-from typing import Optional
+from typing import Optional, cast
 
 from frigate.comms.inter_process import InterProcessRequestor
 from frigate.const import CONFIG_DIR, UPDATE_JOB_STATE
@@ -122,7 +122,7 @@ def start_media_sync_job(
     if job_is_running("media_sync"):
         current = get_current_job("media_sync")
         logger.warning(
-            f"Media sync job {current.id} is already running. Rejecting new request."
+            f"Media sync job {current.id if current else 'unknown'} is already running. Rejecting new request."
         )
         return None
 
@@ -146,9 +146,9 @@ def start_media_sync_job(
 
 def get_current_media_sync_job() -> Optional[MediaSyncJob]:
     """Get the current running/queued media sync job, if any."""
-    return get_current_job("media_sync")
+    return cast(Optional[MediaSyncJob], get_current_job("media_sync"))
 
 
 def get_media_sync_job_by_id(job_id: str) -> Optional[MediaSyncJob]:
     """Get media sync job by ID. Currently only tracks the current job."""
-    return get_job_by_id("media_sync", job_id)
+    return cast(Optional[MediaSyncJob], get_job_by_id("media_sync", job_id))

frigate/jobs/motion_search.py

@@ -6,7 +6,7 @@ import threading
 from concurrent.futures import Future, ThreadPoolExecutor, as_completed
 from dataclasses import asdict, dataclass, field
 from datetime import datetime
-from typing import Any, Optional
+from typing import Any, Optional, cast
 
 import cv2
 import numpy as np
@@ -96,7 +96,7 @@ def create_polygon_mask(
         dtype=np.int32,
     )
     mask = np.zeros((frame_height, frame_width), dtype=np.uint8)
-    cv2.fillPoly(mask, [motion_points], 255)
+    cv2.fillPoly(mask, [motion_points], (255,))
     return mask
 
 
@@ -116,7 +116,7 @@ def compute_roi_bbox_normalized(
 
 
 def heatmap_overlaps_roi(
-    heatmap: dict[str, int], roi_bbox: tuple[float, float, float, float]
+    heatmap: object, roi_bbox: tuple[float, float, float, float]
 ) -> bool:
     """Check if a sparse motion heatmap has any overlap with the ROI bounding box.
 
@@ -155,9 +155,9 @@ def segment_passes_activity_gate(recording: Recordings) -> bool:
     Returns True if any of motion, objects, or regions is non-zero/non-null.
     Returns True if all are null (old segments without data).
     """
-    motion = recording.motion
+    motion: Any = recording.motion
-    objects = recording.objects
+    objects: Any = recording.objects
-    regions = recording.regions
+    regions: Any = recording.regions
 
     # Old segments without metadata - pass through (conservative)
     if motion is None and objects is None and regions is None:
@@ -278,6 +278,9 @@ class MotionSearchRunner(threading.Thread):
         frame_width = camera_config.detect.width
         frame_height = camera_config.detect.height
 
+        if frame_width is None or frame_height is None:
+            raise ValueError(f"Camera {camera_name} detect dimensions not configured")
+
         # Create polygon mask
         polygon_mask = create_polygon_mask(
             self.job.polygon_points, frame_width, frame_height
@@ -415,11 +418,13 @@ class MotionSearchRunner(threading.Thread):
                 if self._should_stop():
                     break
 
+                rec_start: float = recording.start_time  # type: ignore[assignment]
+                rec_end: float = recording.end_time  # type: ignore[assignment]
                 future = executor.submit(
                     self._process_recording_for_motion,
-                    recording.path,
+                    str(recording.path),
-                    recording.start_time,
+                    rec_start,
-                    recording.end_time,
+                    rec_end,
                     self.job.start_time_range,
                     self.job.end_time_range,
                     polygon_mask,
@@ -524,10 +529,12 @@ class MotionSearchRunner(threading.Thread):
                 break
 
             try:
+                rec_start: float = recording.start_time  # type: ignore[assignment]
+                rec_end: float = recording.end_time  # type: ignore[assignment]
                 results, frames = self._process_recording_for_motion(
-                    recording.path,
+                    str(recording.path),
-                    recording.start_time,
+                    rec_start,
-                    recording.end_time,
+                    rec_end,
                     self.job.start_time_range,
                     self.job.end_time_range,
                     polygon_mask,
@@ -672,7 +679,9 @@ class MotionSearchRunner(threading.Thread):
                 # Handle frame dimension changes
                 if gray.shape != polygon_mask.shape:
                     resized_mask = cv2.resize(
-                        polygon_mask, (gray.shape[1], gray.shape[0]), cv2.INTER_NEAREST
+                        polygon_mask,
+                        (gray.shape[1], gray.shape[0]),
+                        interpolation=cv2.INTER_NEAREST,
                     )
                     current_bbox = cv2.boundingRect(resized_mask)
                 else:
@@ -698,7 +707,7 @@ class MotionSearchRunner(threading.Thread):
                 )
 
                 if prev_frame_gray is not None:
-                    diff = cv2.absdiff(prev_frame_gray, masked_gray)
+                    diff = cv2.absdiff(prev_frame_gray, masked_gray)  # type: ignore[unreachable]
                     diff_blurred = cv2.GaussianBlur(diff, (3, 3), 0)
                     _, thresh = cv2.threshold(
                         diff_blurred, threshold, 255, cv2.THRESH_BINARY
@@ -825,7 +834,7 @@ def get_motion_search_job(job_id: str) -> Optional[MotionSearchJob]:
         if job_entry:
             return job_entry[0]
     # Check completed jobs via manager
-    return get_job_by_id("motion_search", job_id)
+    return cast(Optional[MotionSearchJob], get_job_by_id("motion_search", job_id))
 
 
 def cancel_motion_search_job(job_id: str) -> bool:

frigate/jobs/vlm_watch.py

@@ -54,9 +54,9 @@ class VLMWatchRunner(threading.Thread):
         job: VLMWatchJob,
         config: FrigateConfig,
         cancel_event: threading.Event,
-        frame_processor,
+        frame_processor: Any,
-        genai_manager,
+        genai_manager: Any,
-        dispatcher,
+        dispatcher: Any,
     ) -> None:
         super().__init__(daemon=True, name=f"vlm_watch_{job.id}")
         self.job = job
@@ -226,9 +226,12 @@ class VLMWatchRunner(threading.Thread):
             remaining = deadline - time.time()
             if remaining <= 0:
                 break
-            topic, payload = self.detection_subscriber.check_for_update(
+            result = self.detection_subscriber.check_for_update(
                 timeout=min(1.0, remaining)
             )
+            if result is None:
+                continue
+            topic, payload = result
             if topic is None or payload is None:
                 continue
             # payload = (camera, frame_name, frame_time, tracked_objects, motion_boxes, regions)
@@ -328,9 +331,9 @@ def start_vlm_watch_job(
     condition: str,
     max_duration_minutes: int,
     config: FrigateConfig,
-    frame_processor,
+    frame_processor: Any,
-    genai_manager,
+    genai_manager: Any,
-    dispatcher,
+    dispatcher: Any,
     labels: list[str] | None = None,
     zones: list[str] | None = None,
 ) -> str:

frigate/motion/__init__.py

@@ -13,10 +13,10 @@ class MotionDetector(ABC):
         frame_shape: Tuple[int, int, int],
         config: MotionConfig,
         fps: int,
-        improve_contrast,
+        improve_contrast: bool,
-        threshold,
+        threshold: int,
-        contour_area,
+        contour_area: int | None,
-    ):
+    ) -> None:
         pass
 
     @abstractmethod
@@ -25,7 +25,7 @@ class MotionDetector(ABC):
         pass
 
     @abstractmethod
-    def is_calibrating(self):
+    def is_calibrating(self) -> bool:
         """Return if motion is recalibrating."""
         pass
 
@@ -35,6 +35,6 @@ class MotionDetector(ABC):
         pass
 
     @abstractmethod
-    def stop(self):
+    def stop(self) -> None:
         """Stop any ongoing work and processes."""
         pass

frigate/mypy.ini

@@ -41,6 +41,24 @@ ignore_errors = false
 [mypy-frigate.events]
 ignore_errors = false
 
+[mypy-frigate.genai.*]
+ignore_errors = false
+
+[mypy-frigate.jobs.*]
+ignore_errors = false
+
+[mypy-frigate.motion]
+ignore_errors = false
+
+[mypy-frigate.object_detection]
+ignore_errors = false
+
+[mypy-frigate.output]
+ignore_errors = false
+
+[mypy-frigate.ptz]
+ignore_errors = false
+
 [mypy-frigate.log]
 ignore_errors = false