From 80c4ce2b5d225e0ffbbc0e60c418a581ad3577fa Mon Sep 17 00:00:00 2001 From: Nicolas Mowen Date: Wed, 25 Mar 2026 09:28:48 -0600 Subject: [PATCH] Increase mypy coverage and fixes (#22632) --- frigate/genai/__init__.py | 12 +++---- frigate/genai/azure-openai.py | 14 ++++---- frigate/genai/gemini.py | 67 +++++++++++++++++++++++------------ frigate/genai/llama_cpp.py | 16 ++++----- frigate/genai/ollama.py | 12 +++---- frigate/genai/openai.py | 12 +++---- frigate/jobs/media_sync.py | 8 ++--- frigate/jobs/motion_search.py | 39 ++++++++++++-------- frigate/jobs/vlm_watch.py | 17 +++++---- frigate/motion/__init__.py | 12 +++---- frigate/mypy.ini | 18 ++++++++++ 11 files changed, 140 insertions(+), 87 deletions(-) diff --git a/frigate/genai/__init__.py b/frigate/genai/__init__.py index f799931ec..96e956242 100644 --- a/frigate/genai/__init__.py +++ b/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": diff --git a/frigate/genai/azure-openai.py b/frigate/genai/azure-openai.py index f424f7610..7cd8894a4 100644 --- a/frigate/genai/azure-openai.py +++ b/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: diff --git a/frigate/genai/gemini.py b/frigate/genai/gemini.py index f32d37e80..e0c0c7698 100644 --- a/frigate/genai/gemini.py +++ b/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), ) diff --git a/frigate/genai/llama_cpp.py b/frigate/genai/llama_cpp.py index 48ea9747c..fbb1b45df 100644 --- a/frigate/genai/llama_cpp.py +++ b/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( diff --git a/frigate/genai/ollama.py b/frigate/genai/ollama.py index 0bfb95000..2af1a6350 100644 --- a/frigate/genai/ollama.py +++ b/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 diff --git a/frigate/genai/openai.py b/frigate/genai/openai.py index 7d8700579..02ad301fa 100644 --- a/frigate/genai/openai.py +++ b/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: diff --git a/frigate/jobs/media_sync.py b/frigate/jobs/media_sync.py index 803a80a9d..4a3fdc355 100644 --- a/frigate/jobs/media_sync.py +++ b/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)) diff --git a/frigate/jobs/motion_search.py b/frigate/jobs/motion_search.py index d7c8f8fbc..1a90f0bb9 100644 --- a/frigate/jobs/motion_search.py +++ b/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 - objects = recording.objects - regions = recording.regions + motion: Any = recording.motion + objects: Any = recording.objects + 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, - recording.start_time, - recording.end_time, + str(recording.path), + rec_start, + 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, - recording.start_time, - recording.end_time, + str(recording.path), + rec_start, + 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: diff --git a/frigate/jobs/vlm_watch.py b/frigate/jobs/vlm_watch.py index dae5e5f41..a66f60dfc 100644 --- a/frigate/jobs/vlm_watch.py +++ b/frigate/jobs/vlm_watch.py @@ -54,9 +54,9 @@ class VLMWatchRunner(threading.Thread): job: VLMWatchJob, config: FrigateConfig, cancel_event: threading.Event, - frame_processor, - genai_manager, - dispatcher, + frame_processor: Any, + genai_manager: Any, + 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, - genai_manager, - dispatcher, + frame_processor: Any, + genai_manager: Any, + dispatcher: Any, labels: list[str] | None = None, zones: list[str] | None = None, ) -> str: diff --git a/frigate/motion/__init__.py b/frigate/motion/__init__.py index 1f6785d5d..58f781f46 100644 --- a/frigate/motion/__init__.py +++ b/frigate/motion/__init__.py @@ -13,10 +13,10 @@ class MotionDetector(ABC): frame_shape: Tuple[int, int, int], config: MotionConfig, fps: int, - improve_contrast, - threshold, - contour_area, - ): + improve_contrast: bool, + threshold: int, + 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 diff --git a/frigate/mypy.ini b/frigate/mypy.ini index 5bad10f49..e1da675be 100644 --- a/frigate/mypy.ini +++ b/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