mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-26 19:06:11 +01:00
24ac9f3e5a
* swap sqlite_vec for chroma in requirements * load sqlite_vec in embeddings manager * remove chroma and revamp Embeddings class for sqlite_vec * manual minilm onnx inference * remove chroma in clip model * migrate api from chroma to sqlite_vec * migrate event cleanup from chroma to sqlite_vec * migrate embedding maintainer from chroma to sqlite_vec * genai description for sqlite_vec * load sqlite_vec in main thread db * extend the SqliteQueueDatabase class and use peewee db.execute_sql * search with Event type for similarity * fix similarity search * install and add comment about transformers * fix normalization * add id filter * clean up * clean up * fully remove chroma and add transformers env var * readd uvicorn for fastapi * readd tokenizer parallelism env var * remove chroma from docs * remove chroma from UI * try removing custom pysqlite3 build * hard code limit * optimize queries * revert explore query * fix query * keep building pysqlite3 * single pass fetch and process * remove unnecessary re-embed * update deps * move SqliteVecQueueDatabase to db directory * make search thumbnail take up full size of results box * improve typing * improve model downloading and add status screen * daemon downloading thread * catch case when semantic search is disabled * fix typing * build sqlite_vec from source * resolve conflict * file permissions * try build deps * remove sources * sources * fix thread start * include git in build * reorder embeddings after detectors are started * build with sqlite amalgamation * non-platform specific * use wget instead of curl * remove unzip -d * remove sqlite_vec from requirements and load the compiled version * fix build * avoid race in db connection * add scale_factor and bias to description zscore normalization
67 lines
1.8 KiB
Python
67 lines
1.8 KiB
Python
"""Generative AI module for Frigate."""
|
|
|
|
import importlib
|
|
import os
|
|
from typing import Optional
|
|
|
|
from frigate.config import CameraConfig, GenAIConfig, GenAIProviderEnum
|
|
|
|
PROVIDERS = {}
|
|
|
|
|
|
def register_genai_provider(key: GenAIProviderEnum):
|
|
"""Register a GenAI provider."""
|
|
|
|
def decorator(cls):
|
|
PROVIDERS[key] = cls
|
|
return cls
|
|
|
|
return decorator
|
|
|
|
|
|
class GenAIClient:
|
|
"""Generative AI client for Frigate."""
|
|
|
|
def __init__(self, genai_config: GenAIConfig, timeout: int = 60) -> None:
|
|
self.genai_config: GenAIConfig = genai_config
|
|
self.timeout = timeout
|
|
self.provider = self._init_provider()
|
|
|
|
def generate_description(
|
|
self,
|
|
camera_config: CameraConfig,
|
|
thumbnails: list[bytes],
|
|
label: str,
|
|
) -> Optional[str]:
|
|
"""Generate a description for the frame."""
|
|
prompt = camera_config.genai.object_prompts.get(
|
|
label, camera_config.genai.prompt
|
|
)
|
|
return self._send(prompt, thumbnails)
|
|
|
|
def _init_provider(self):
|
|
"""Initialize the client."""
|
|
return None
|
|
|
|
def _send(self, prompt: str, images: list[bytes]) -> Optional[str]:
|
|
"""Submit a request to the provider."""
|
|
return None
|
|
|
|
|
|
def get_genai_client(genai_config: GenAIConfig) -> Optional[GenAIClient]:
|
|
"""Get the GenAI client."""
|
|
if genai_config.enabled:
|
|
load_providers()
|
|
provider = PROVIDERS.get(genai_config.provider)
|
|
if provider:
|
|
return provider(genai_config)
|
|
return None
|
|
|
|
|
|
def load_providers():
|
|
package_dir = os.path.dirname(__file__)
|
|
for filename in os.listdir(package_dir):
|
|
if filename.endswith(".py") and filename != "__init__.py":
|
|
module_name = f"frigate.genai.{filename[:-3]}"
|
|
importlib.import_module(module_name)
|