Restructure embeddings

frigate/api/event.py

@@ -472,7 +472,7 @@ def events_search(request: Request, params: EventsSearchQueryParams = Depends())
                 status_code=404,
             )
 
-        thumb_result = context.embeddings.search_thumbnail(search_event)
+        thumb_result = context.search_thumbnail(search_event)
         thumb_ids = dict(
             zip(
                 [result[0] for result in thumb_result],
@@ -487,7 +487,7 @@ def events_search(request: Request, params: EventsSearchQueryParams = Depends())
         search_types = search_type.split(",")
 
         if "thumbnail" in search_types:
-            thumb_result = context.embeddings.search_thumbnail(query)
+            thumb_result = context.search_thumbnail(query)
             thumb_ids = dict(
                 zip(
                     [result[0] for result in thumb_result],
@@ -504,7 +504,7 @@ def events_search(request: Request, params: EventsSearchQueryParams = Depends())
             )
 
         if "description" in search_types:
-            desc_result = context.embeddings.search_description(query)
+            desc_result = context.search_description(query)
             desc_ids = dict(
                 zip(
                     [result[0] for result in desc_result],
@@ -944,9 +944,9 @@ def set_description(
     # If semantic search is enabled, update the index
     if request.app.frigate_config.semantic_search.enabled:
         context: EmbeddingsContext = request.app.embeddings
-        context.embeddings.upsert_description(
-            event_id=event_id,
-            description=new_description,
+        context.update_description(
+            event_id,
+            new_description,
         )
 
     response_message = (
@@ -1033,8 +1033,8 @@ def delete_event(request: Request, event_id: str):
     # If semantic search is enabled, update the index
     if request.app.frigate_config.semantic_search.enabled:
         context: EmbeddingsContext = request.app.embeddings
-        context.embeddings.delete_thumbnail(id=[event_id])
-        context.embeddings.delete_description(id=[event_id])
+        context.db.delete_embeddings_thumbnail(id=[event_id])
+        context.db.delete_embeddings_description(id=[event_id])
     return JSONResponse(
         content=({"success": True, "message": "Event " + event_id + " deleted"}),
         status_code=200,

frigate/app.py

@@ -276,7 +276,7 @@ def check_db_data_migrations(self) -> None:
     def init_embeddings_client(self) -> None:
         if self.config.semantic_search.enabled:
             # Create a client for other processes to use
-            self.embeddings = EmbeddingsContext(self.config, self.db)
+            self.embeddings = EmbeddingsContext(self.db)
 
     def init_external_event_processor(self) -> None:
         self.external_event_processor = ExternalEventProcessor(self.config)
@@ -699,7 +699,7 @@ def stop(self) -> None:
 
         # Save embeddings stats to disk
         if self.embeddings:
-            self.embeddings.save_stats()
+            self.embeddings.stop()
 
         # Stop Communicators
         self.inter_process_communicator.stop()

frigate/comms/embeddings_updater.py

@@ -0,0 +1,62 @@
+"""Facilitates communication between processes."""
+
+from enum import Enum
+from typing import Callable
+
+import zmq
+
+SOCKET_REP_REQ = "ipc:///tmp/cache/embeddings"
+
+
+class EmbeddingsRequestEnum(Enum):
+    embed_description = "embed_description"
+    embed_thumbnail = "embed_thumbnail"
+    generate_search = "generate_search"
+
+
+class EmbeddingsResponder:
+    def __init__(self) -> None:
+        self.context = zmq.Context()
+        self.socket = self.context.socket(zmq.REP)
+        self.socket.bind(SOCKET_REP_REQ)
+
+    def check_for_request(self, process: Callable) -> None:
+        while True:  # load all messages that are queued
+            has_message, _, _ = zmq.select([self.socket], [], [], 1)
+
+            if not has_message:
+                break
+
+            try:
+                (topic, value) = self.socket.recv_json(flags=zmq.NOBLOCK)
+
+                response = process(topic, value)
+
+                if response is not None:
+                    self.socket.send_json(response)
+                else:
+                    self.socket.send_json([])
+            except zmq.ZMQError:
+                break
+
+    def stop(self) -> None:
+        self.socket.close()
+        self.context.destroy()
+
+
+class EmbeddingsRequestor:
+    """Simplifies sending data to EmbeddingsResponder and getting a reply."""
+
+    def __init__(self) -> None:
+        self.context = zmq.Context()
+        self.socket = self.context.socket(zmq.REQ)
+        self.socket.connect(SOCKET_REP_REQ)
+
+    def send_data(self, topic: str, data: any) -> str:
+        """Sends data and then waits for reply."""
+        self.socket.send_json((topic, data))
+        return self.socket.recv_json()
+
+    def stop(self) -> None:
+        self.socket.close()
+        self.context.destroy()

frigate/db/sqlitevecq.py

@@ -20,3 +20,11 @@ def _load_vec_extension(self, conn: sqlite3.Connection) -> None:
         conn.enable_load_extension(True)
         conn.load_extension(self.sqlite_vec_path)
         conn.enable_load_extension(False)
+
+    def delete_embeddings_thumbnail(self, event_ids: list[str]) -> None:
+        ids = ",".join(["?" for _ in event_ids])
+        self.execute_sql(f"DELETE FROM vec_thumbnails WHERE id IN ({ids})", event_ids)
+
+    def delete_embeddings_description(self, event_ids: list[str]) -> None:
+        ids = ",".join(["?" for _ in event_ids])
+        self.execute_sql(f"DELETE FROM vec_descriptions WHERE id IN ({ids})", event_ids)

frigate/embeddings/__init__.py

@@ -7,14 +7,16 @@
 import signal
 import threading
 from types import FrameType
-from typing import Optional
+from typing import Optional, Union
 
 from setproctitle import setproctitle
 
+from frigate.comms.embeddings_updater import EmbeddingsRequestEnum, EmbeddingsRequestor
 from frigate.config import FrigateConfig
 from frigate.const import CONFIG_DIR
 from frigate.db.sqlitevecq import SqliteVecQueueDatabase
 from frigate.models import Event
+from frigate.util.builtin import serialize
 from frigate.util.services import listen
 
 from .embeddings import Embeddings
@@ -70,10 +72,11 @@ def receiveSignal(signalNumber: int, frame: Optional[FrameType]) -> None:
 
 
 class EmbeddingsContext:
-    def __init__(self, config: FrigateConfig, db: SqliteVecQueueDatabase):
-        self.embeddings = Embeddings(config.semantic_search, db)
+    def __init__(self, db: SqliteVecQueueDatabase):
+        self.db = db
         self.thumb_stats = ZScoreNormalization()
         self.desc_stats = ZScoreNormalization()
+        self.requestor = EmbeddingsRequestor()
 
         # load stats from disk
         try:
@@ -84,11 +87,108 @@ def __init__(self, config: FrigateConfig, db: SqliteVecQueueDatabase):
         except FileNotFoundError:
             pass
 
-    def save_stats(self):
+    def stop(self):
         """Write the stats to disk as JSON on exit."""
         contents = {
             "thumb_stats": self.thumb_stats.to_dict(),
             "desc_stats": self.desc_stats.to_dict(),
         }
         with open(os.path.join(CONFIG_DIR, ".search_stats.json"), "w") as f:
             json.dump(contents, f)
+        self.requestor.stop()
+
+    def search_thumbnail(
+        self, query: Union[Event, str], event_ids: list[str] = None
+    ) -> list[tuple[str, float]]:
+        if query.__class__ == Event:
+            cursor = self.db.execute_sql(
+                """
+                SELECT thumbnail_embedding FROM vec_thumbnails WHERE id = ?
+                """,
+                [query.id],
+            )
+
+            row = cursor.fetchone() if cursor else None
+
+            if row:
+                query_embedding = row[0]
+            else:
+                # If no embedding found, generate it and return it
+                query_embedding = serialize(
+                    self.requestor.send_data(
+                        EmbeddingsRequestEnum.embed_thumbnail.value,
+                        {"id": query.id, "thumbnail": query.thumbnail},
+                    )
+                )
+        else:
+            query_embedding = serialize(
+                self.requestor.send_data(
+                    EmbeddingsRequestEnum.generate_search.value, query
+                )
+            )
+
+        sql_query = """
+            SELECT
+                id,
+                distance
+            FROM vec_thumbnails
+            WHERE thumbnail_embedding MATCH ?
+                AND k = 100
+        """
+
+        # Add the IN clause if event_ids is provided and not empty
+        # this is the only filter supported by sqlite-vec as of 0.1.3
+        # but it seems to be broken in this version
+        if event_ids:
+            sql_query += " AND id IN ({})".format(",".join("?" * len(event_ids)))
+
+        # order by distance DESC is not implemented in this version of sqlite-vec
+        # when it's implemented, we can use cosine similarity
+        sql_query += " ORDER BY distance"
+
+        parameters = [query_embedding] + event_ids if event_ids else [query_embedding]
+
+        results = self.db.execute_sql(sql_query, parameters).fetchall()
+
+        return results
+
+    def search_description(
+        self, query_text: str, event_ids: list[str] = None
+    ) -> list[tuple[str, float]]:
+        query_embedding = serialize(
+            self.requestor.send_data(
+                EmbeddingsRequestEnum.generate_search.value, query_text
+            )
+        )
+
+        # Prepare the base SQL query
+        sql_query = """
+            SELECT
+                id,
+                distance
+            FROM vec_descriptions
+            WHERE description_embedding MATCH ?
+                AND k = 100
+        """
+
+        # Add the IN clause if event_ids is provided and not empty
+        # this is the only filter supported by sqlite-vec as of 0.1.3
+        # but it seems to be broken in this version
+        if event_ids:
+            sql_query += " AND id IN ({})".format(",".join("?" * len(event_ids)))
+
+        # order by distance DESC is not implemented in this version of sqlite-vec
+        # when it's implemented, we can use cosine similarity
+        sql_query += " ORDER BY distance"
+
+        parameters = [query_embedding] + event_ids if event_ids else [query_embedding]
+
+        results = self.db.execute_sql(sql_query, parameters).fetchall()
+
+        return results
+
+    def update_description(self, event_id: str, description: str) -> None:
+        self.requestor.send_data(
+            EmbeddingsRequestEnum.embed_description.value,
+            {"id": event_id, "description": description},
+        )