mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-28 16:07:46 +00:00
WinstonLiyt
c8e8989edc
* fix some bugs in llm calling * fix a CI error * fix a small bug in kmeans group number choosing * fix a ci bug
111 lines
3.5 KiB
Python
111 lines
3.5 KiB
Python
from __future__ import annotations
|
|
|
|
from pathlib import Path
|
|
|
|
from dotenv import load_dotenv
|
|
from pydantic_settings import BaseSettings
|
|
|
|
# TODO: use pydantic for other modules in Qlib
|
|
# from pydantic_settings import BaseSettings
|
|
|
|
# make sure that env variable is loaded while calling Config()
|
|
load_dotenv(verbose=True, override=True)
|
|
|
|
|
|
class RDAgentSettings(BaseSettings):
|
|
# TODO: (xiao) I think LLMSetting may be a better name.
|
|
# TODO: (xiao) I think most of the config should be in oai.config
|
|
# Log configs
|
|
# TODO: (xiao) think it can be a separate config.
|
|
log_trace_path: str | None = None
|
|
log_llm_chat_content: bool = True
|
|
|
|
use_azure: bool = False
|
|
use_azure_token_provider: bool = False
|
|
managed_identity_client_id: str | None = None
|
|
max_retry: int = 10
|
|
retry_wait_seconds: int = 1
|
|
dump_chat_cache: bool = False
|
|
use_chat_cache: bool = False
|
|
dump_embedding_cache: bool = False
|
|
use_embedding_cache: bool = False
|
|
prompt_cache_path: str = str(Path.cwd() / "prompt_cache.db")
|
|
session_cache_folder_location: str = str(Path.cwd() / "session_cache_folder/")
|
|
max_past_message_include: int = 10
|
|
|
|
# Chat configs
|
|
openai_api_key: str = "" # TODO: simplify the key design.
|
|
chat_openai_api_key: str = ""
|
|
chat_azure_api_base: str = ""
|
|
chat_azure_api_version: str = ""
|
|
chat_model: str = ""
|
|
chat_max_tokens: int = 3000
|
|
chat_temperature: float = 0.5
|
|
chat_stream: bool = True
|
|
chat_seed: int | None = None
|
|
chat_frequency_penalty: float = 0.0
|
|
chat_presence_penalty: float = 0.0
|
|
chat_token_limit: int = (
|
|
100000 # 100000 is the maximum limit of gpt4, which might increase in the future version of gpt
|
|
)
|
|
default_system_prompt: str = "You are an AI assistant who helps to answer user's questions."
|
|
|
|
# Embedding configs
|
|
embedding_openai_api_key: str = ""
|
|
embedding_azure_api_base: str = ""
|
|
embedding_azure_api_version: str = ""
|
|
embedding_model: str = ""
|
|
|
|
# offline llama2 related config
|
|
use_llama2: bool = False
|
|
llama2_ckpt_dir: str = "Llama-2-7b-chat"
|
|
llama2_tokenizer_path: str = "Llama-2-7b-chat/tokenizer.model"
|
|
llams2_max_batch_size: int = 8
|
|
|
|
# azure document intelligence configs
|
|
azure_document_intelligence_key: str = ""
|
|
azure_document_intelligence_endpoint: str = ""
|
|
|
|
# server served endpoints
|
|
use_gcr_endpoint: bool = False
|
|
gcr_endpoint_type: str = "llama2_70b" # or "llama3_70b", "phi2", "phi3_4k", "phi3_128k"
|
|
|
|
llama2_70b_endpoint: str = ""
|
|
llama2_70b_endpoint_key: str = ""
|
|
llama2_70b_endpoint_deployment: str = ""
|
|
|
|
llama3_70b_endpoint: str = ""
|
|
llama3_70b_endpoint_key: str = ""
|
|
llama3_70b_endpoint_deployment: str = ""
|
|
|
|
phi2_endpoint: str = ""
|
|
phi2_endpoint_key: str = ""
|
|
phi2_endpoint_deployment: str = ""
|
|
|
|
phi3_4k_endpoint: str = ""
|
|
phi3_4k_endpoint_key: str = ""
|
|
phi3_4k_endpoint_deployment: str = ""
|
|
|
|
phi3_128k_endpoint: str = ""
|
|
phi3_128k_endpoint_key: str = ""
|
|
phi3_128k_endpoint_deployment: str = ""
|
|
|
|
gcr_endpoint_temperature: float = 0.7
|
|
gcr_endpoint_top_p: float = 0.9
|
|
gcr_endpoint_do_sample: bool = False
|
|
gcr_endpoint_max_token: int = 100
|
|
|
|
# factor extraction conf
|
|
max_input_duplicate_factor_group: int = 300
|
|
max_output_duplicate_factor_group: int = 20
|
|
max_kmeans_group_number: int = 40
|
|
|
|
# workspace conf
|
|
workspace_path: Path = Path.cwd() / "git_ignore_folder" / "RD-Agent_workspace"
|
|
|
|
# multi processing conf
|
|
multi_proc_n: int = 1
|
|
|
|
|
|
RD_AGENT_SETTINGS = RDAgentSettings()
|