Miscellaneous Fixes (#20848)

* Fix filtering for classification

* Adjust prompt to account for response tokens

* Correctly return response for reprocess

* Use API response to update data instead of trying to re-parse all of the values

* Implement rename class api

* Fix model deletion / rename dialog

* Remove camera spatial context

* Catch error

frigate/api/classification.py

@@ -112,9 +112,18 @@ def reclassify_face(request: Request, body: dict = None):
     context: EmbeddingsContext = request.app.embeddings
     response = context.reprocess_face(training_file)
 
+    if not isinstance(response, dict):
+        return JSONResponse(
+            status_code=500,
+            content={
+                "success": False,
+                "message": "Could not process request.",
+            },
+        )
+
     return JSONResponse(
+        status_code=200 if response.get("success", True) else 400,
         content=response,
-        status_code=200,
     )
 
 
@@ -671,6 +680,97 @@ def delete_classification_dataset_images(
     )
 
 
+@router.put(
+    "/classification/{name}/dataset/{old_category}/rename",
+    response_model=GenericResponse,
+    dependencies=[Depends(require_role(["admin"]))],
+    summary="Rename a classification category",
+    description="""Renames a classification category for a given classification model.
+    The old category must exist and the new name must be valid. Returns a success message or an error if the name is invalid.""",
+)
+def rename_classification_category(
+    request: Request, name: str, old_category: str, body: dict = None
+):
+    config: FrigateConfig = request.app.frigate_config
+
+    if name not in config.classification.custom:
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"{name} is not a known classification model.",
+                }
+            ),
+            status_code=404,
+        )
+
+    json: dict[str, Any] = body or {}
+    new_category = sanitize_filename(json.get("new_category", ""))
+
+    if not new_category:
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": "New category name is required.",
+                }
+            ),
+            status_code=400,
+        )
+
+    old_folder = os.path.join(
+        CLIPS_DIR, sanitize_filename(name), "dataset", sanitize_filename(old_category)
+    )
+    new_folder = os.path.join(
+        CLIPS_DIR, sanitize_filename(name), "dataset", new_category
+    )
+
+    if not os.path.exists(old_folder):
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"Category {old_category} does not exist.",
+                }
+            ),
+            status_code=404,
+        )
+
+    if os.path.exists(new_folder):
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": f"Category {new_category} already exists.",
+                }
+            ),
+            status_code=400,
+        )
+
+    try:
+        os.rename(old_folder, new_folder)
+        return JSONResponse(
+            content=(
+                {
+                    "success": True,
+                    "message": f"Successfully renamed category to {new_category}.",
+                }
+            ),
+            status_code=200,
+        )
+    except Exception as e:
+        logger.error(f"Error renaming category: {e}")
+        return JSONResponse(
+            content=(
+                {
+                    "success": False,
+                    "message": "Failed to rename category",
+                }
+            ),
+            status_code=500,
+        )
+
+
 @router.post(
     "/classification/{name}/dataset/categorize",
     response_model=GenericResponse,

frigate/config/camera/review.py

@@ -140,10 +140,6 @@ Evaluate in this order:
 The mere presence of an unidentified person in private areas during late night hours is inherently suspicious and warrants human review, regardless of what activity they appear to be doing or how brief the sequence is.""",
         title="Custom activity context prompt defining normal and suspicious activity patterns for this property.",
     )
-    camera_context: str = Field(
-        default="",
-        title="Spatial context about the camera's field of view to help with descriptive accuracy. Should describe physical features and locations outside the frame.",
-    )
 
 
 class ReviewConfig(FrigateBaseModel):

frigate/data_processing/post/review_descriptions.py

@@ -90,7 +90,8 @@ class ReviewDescriptionProcessor(PostProcessorApi):
         pixels_per_image = width * height
         tokens_per_image = pixels_per_image / 1250
         prompt_tokens = 3500
-        available_tokens = context_size * 0.98 - prompt_tokens
+        response_tokens = 300
+        available_tokens = context_size - prompt_tokens - response_tokens
         max_frames = int(available_tokens / tokens_per_image)
 
         return min(max(max_frames, 3), 20)
@@ -458,7 +459,6 @@ def run_analysis(
         genai_config.preferred_language,
         genai_config.debug_save_thumbnails,
         genai_config.activity_context_prompt,
-        genai_config.camera_context,
     )
     review_inference_speed.update(datetime.datetime.now().timestamp() - start)
 

frigate/data_processing/real_time/face.py

@@ -423,7 +423,10 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             res = self.recognizer.classify(img)
 
             if not res:
-                return
+                return {
+                    "message": "No face was recognized.",
+                    "success": False,
+                }
 
             sub_label, score = res
 
@@ -442,6 +445,13 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
                 )
                 shutil.move(current_file, new_file)
 
+            return {
+                "message": f"Successfully reprocessed face. Result: {sub_label} (score: {score:.2f})",
+                "success": True,
+                "face_name": sub_label,
+                "score": score,
+            }
+
     def expire_object(self, object_id: str, camera: str):
         if object_id in self.person_face_history:
             self.person_face_history.pop(object_id)

frigate/genai/__init__.py

@@ -45,7 +45,6 @@ class GenAIClient:
         preferred_language: str | None,
         debug_save: bool,
         activity_context_prompt: str,
-        camera_context: str = "",
     ) -> ReviewMetadata | None:
         """Generate a description for the review item activity."""
 
@@ -70,16 +69,6 @@ class GenAIClient:
             else:
                 return "\n- (No objects detected)"
 
-        def get_camera_context_section() -> str:
-            if camera_context:
-                return f"""## Camera Spatial Context
-
-Use this spatial information when writing the title and scene description to provide more accurate context about where activity is occurring or where people/objects are moving to/from.
-
-{camera_context}"""
-            return ""
-
-        camera_context_section = get_camera_context_section()
         context_prompt = f"""
 Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"].replace("_", " ")} security camera.
 
@@ -87,8 +76,6 @@ Your task is to analyze the sequence of images ({len(thumbnails)} total) taken i
 
 {activity_context_prompt}
 
-{camera_context_section}
-
 ## Task Instructions
 
 Your task is to provide a clear, accurate description of the scene that:
@@ -113,7 +100,7 @@ When forming your description:
 ## Response Format
 
 Your response MUST be a flat JSON object with:
-- `title` (string): A concise, direct title that describes the primary action or event in the sequence, not just what you literally see. {"Use spatial context when available to make titles more meaningful." if camera_context_section else ""} When multiple objects/actions are present, prioritize whichever is most prominent or occurs first. Use names from "Objects in Scene" based on what you visually observe. If you see both a name and an unidentified object of the same type but visually observe only one person/object, use ONLY the name. Examples: "Joe walking dog", "Person taking out trash", "Vehicle arriving in driveway", "Joe accessing vehicle", "Person leaving porch for driveway".
+- `title` (string): A concise, direct title that describes the primary action or event in the sequence, not just what you literally see. Use spatial context when available to make titles more meaningful. When multiple objects/actions are present, prioritize whichever is most prominent or occurs first. Use names from "Objects in Scene" based on what you visually observe. If you see both a name and an unidentified object of the same type but visually observe only one person/object, use ONLY the name. Examples: "Joe walking dog", "Person taking out trash", "Vehicle arriving in driveway", "Joe accessing vehicle", "Person leaving porch for driveway".
 - `scene` (string): A narrative description of what happens across the sequence from start to finish, in chronological order. Start by describing how the sequence begins, then describe the progression of events. **Describe all significant movements and actions in the order they occur.** For example, if a vehicle arrives and then a person exits, describe both actions sequentially. **Only describe actions you can actually observe happening in the frames provided.** Do not infer or assume actions that aren't visible (e.g., if you see someone walking but never see them sit, don't say they sat down). Include setting, detected objects, and their observable actions. Avoid speculation or filling in assumed behaviors. Your description should align with and support the threat level you assign.
 - `confidence` (float): 0-1 confidence in your analysis. Higher confidence when objects/actions are clearly visible and context is unambiguous. Lower confidence when the sequence is unclear, objects are partially obscured, or context is ambiguous.
 - `potential_threat_level` (integer): 0, 1, or 2 as defined in "Normal Activity Patterns for This Property" above. Your threat level must be consistent with your scene description and the guidance above.