ReMe/memory_scope/handler/init_handler.py
2024-06-19 15:39:37 +08:00

119 lines
4.7 KiB
Python

import json
import os
import re
from typing import Dict, Any
from memory_scope.db.base_db_client import BaseDBClient
from memory_scope.models.base_model import BaseModel
from memory_scope.monitor.base_monitor import BaseMonitor
from memory_scope.utils.tool_functions import init_instance_by_config_v2
from memory_scope.worker.base_worker import BaseWorker
class InitHandler(object):
def __init__(self, path: str):
self.path: str = path
self.config_name: str = os.path.basename(path)
self.config_base_dir: str = os.path.dirname(path)
self.config: dict = {}
self.global_configs: Dict[str, Any] = {}
self.worker_dict: Dict[str, BaseWorker] = {}
self.model_dict: Dict[str, BaseModel] = {}
self.db_client: BaseDBClient | None = None
self.monitor: BaseMonitor | None = None
self.worker_base_dir: str = ""
self.model_base_dir: str = ""
self.db_base_dir: str = ""
self.minitor_base_dir: str = ""
self.retrieve_pipeline: list = []
self.summary_short_pipeline: list = []
self.summary_long_pipeline: list = []
def init(self):
with open(self.path) as f:
self.config = json.load(f)
self.init_global_config(self.config["global"])
self.init_workers(self.config["workers"])
self.init_db(self.config["db"])
self.init_chat_model(self.config["chat_model"])
self.init_monitor(self.config["monitor"])
self.retrieve_pipeline = self.parse_pipeline(self.config["pipelines"]["retrieve"])
self.summary_short_pipeline = self.parse_pipeline(self.config["pipelines"]["summary_short"])
self.summary_long_pipeline = self.parse_pipeline(self.config["pipelines"]["summary_long"])
def init_global_config(self, global_configs: Dict[str, str]):
"""set global_configs & set apikey into env
"""
self.worker_base_dir = global_configs["worker_base_dir"]
self.model_base_dir = global_configs["model_base_dir"]
self.db_base_dir = global_configs["db_base_dir"]
self.minitor_base_dir = global_configs["minitor_base_dir"]
# TODO sen
def init_workers(self, worker_config_name: str):
""" load worker config & init workers
"""
with open(os.path.join(self.config_base_dir, worker_config_name)) as f:
worker_config_dict = json.load(f)
for worker_name, worker_config in worker_config_dict.items():
if worker_name in self.worker_dict:
continue
self.worker_dict[worker_name] = init_instance_by_config_v2(worker_config,
default_clazz_path=self.worker_base_dir,
suffix_name="worker",
**self.global_configs)
self.init_model(worker_config.get("embedding_model"))
self.init_model(worker_config.get("generation_model"))
self.init_model(worker_config.get("rank_model"))
def init_model(self, model_name: str):
if not model_name or model_name in self.model_dict:
return
with open(os.path.join(self.config_base_dir, "model", model_name)) as f:
model_config = json.load(f)
self.model_dict[model_name] = init_instance_by_config_v2(model_config,
default_clazz_path=self.model_base_dir)
def init_db(self, db_config: dict):
self.db_client = init_instance_by_config_v2(db_config, default_clazz_path=self.db_base_dir)
def init_chat_model(self, chat_model_config: dict):
chat_model_name = chat_model_config["name"]
self.init_model(chat_model_name)
def init_monitor(self, monitor_config: dict):
self.monitor = init_instance_by_config_v2(monitor_config, default_clazz_path=self.db_base_dir)
@staticmethod
def parse_pipeline(pipeline_str: str) -> list:
# re-match e.g., [a|b],c,[d,e,f|g,h],j
pattern = r'(\[[^\]]*\]|[^,]+)'
pipeline_split = re.findall(pattern, pipeline_str)
pipeline_list = []
for pipeline_part in pipeline_split:
# e.g., [d,e,f|g,h]
pipeline_part = pipeline_part.strip()
if '[' in pipeline_part or ']' in pipeline_part:
pipeline_part = pipeline_part.replace('[', '').replace(']', '')
# e.g., ["d,e,f", "g,h"]
line_split = [x.strip() for x in pipeline_part.split("|") if x]
if len(line_split) <= 0:
continue
# e.g., ["d","e","f"]
pipeline_list.append([x.split(",") for x in line_split])
return pipeline_list