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| from pathlib import Path | |
| from typing import Any, Dict, List, Type | |
| from pydantic import BaseModel, BaseSettings, Extra | |
| import os | |
| def json_config_settings_source(settings: BaseSettings) -> Dict[str, Any]: | |
| from util import load_json | |
| # Load settings from JSON config file | |
| config_dir = Path(os.getcwd(), ".suspicionagent") | |
| config_file = Path(config_dir, "config.json") | |
| if not config_dir.exists() or not config_file.exists(): | |
| print("[Error] Please config suspicionagent") | |
| import sys | |
| sys.exit(-1) | |
| return load_json(config_file) | |
| class LLMSettings(BaseModel): | |
| """ | |
| LLM/ChatModel related settings | |
| """ | |
| type: str = "chatopenai" | |
| class Config: | |
| extra = Extra.allow | |
| class EmbeddingSettings(BaseModel): | |
| """ | |
| Embedding related settings | |
| """ | |
| type: str = "openaiembeddings" | |
| class Config: | |
| extra = Extra.allow | |
| class ModelSettings(BaseModel): | |
| """ | |
| Model related settings | |
| """ | |
| type: str = "" | |
| llm: LLMSettings = LLMSettings() | |
| embedding: EmbeddingSettings = EmbeddingSettings() | |
| class Config: | |
| extra = Extra.allow | |
| class Settings(BaseSettings): | |
| """ | |
| Root settings | |
| """ | |
| name: str = "default" | |
| model: ModelSettings = ModelSettings() | |
| class Config: | |
| env_prefix = "skyagi_" | |
| env_file_encoding = "utf-8" | |
| extra = Extra.allow | |
| def customise_sources( | |
| cls, | |
| init_settings, | |
| env_settings, | |
| file_secret_settings, | |
| ): | |
| return ( | |
| init_settings, | |
| #json_config_settings_source, | |
| env_settings, | |
| file_secret_settings, | |
| ) | |
| # ---------------------------------------------------------------------------- # | |
| # Preset configurations # | |
| # ---------------------------------------------------------------------------- # | |
| class OpenAIGPT4Settings(ModelSettings): | |
| # NOTE: GPT4 is in waitlist | |
| type = "openai-gpt-4-0613" | |
| llm = LLMSettings(type="chatopenai", model="gpt-4-0613", max_tokens=3000,temperature=0.1, request_timeout=120) | |
| embedding = EmbeddingSettings(type="openaiembeddings") | |
| class OpenAIGPT432kSettings(ModelSettings): | |
| # NOTE: GPT4 is in waitlist | |
| type = "openai-gpt-4-32k-0613" | |
| llm = LLMSettings(type="chatopenai", model="gpt-4-32k-0613", max_tokens=2500) | |
| embedding = EmbeddingSettings(type="openaiembeddings") | |
| class OpenAIGPT3_5TurboSettings(ModelSettings): | |
| type = "openai-gpt-3.5-turbo" | |
| llm = LLMSettings(type="chatopenai", model="gpt-3.5-turbo-16k-0613", max_tokens=2500) | |
| embedding = EmbeddingSettings(type="openaiembeddings") | |
| class OpenAIGPT3_5TextDavinci003Settings(ModelSettings): | |
| type = "openai-gpt-3.5-text-davinci-003" | |
| llm = LLMSettings(type="openai", model_name="text-davinci-003", max_tokens=2500) | |
| embedding = EmbeddingSettings(type="openaiembeddings") | |
| # class Llama2_70b_Settings(ModelSettings): | |
| # from transformers import LlamaForCausalLM, LlamaTokenizer | |
| # type = "llama2-70b" | |
| # tokenizer = LlamaTokenizer.from_pretrained("/groups/gcb50389/pretrained/llama2-HF/Llama-2-70b-hf") | |
| # llm = LlamaForCausalLM.from_pretrained("/groups/gcb50389/pretrained/llama2-HF/Llama-2-70b-hf") | |
| # embedding = EmbeddingSettings(type="openaiembeddings") | |
| # ------------------------- Model settings registry ------------------------ # | |
| model_setting_type_to_cls_dict: Dict[str, Type[ModelSettings]] = { | |
| "openai-gpt-4-0613": OpenAIGPT4Settings, | |
| "openai-gpt-4-32k-0613": OpenAIGPT432kSettings, | |
| "openai-gpt-3.5-turbo": OpenAIGPT3_5TurboSettings, | |
| "openai-gpt-3.5-text-davinci-003": OpenAIGPT3_5TextDavinci003Settings, | |
| # "llama2-70b":Llama2_70b_Settings | |
| } | |
| def load_model_setting(type: str) -> ModelSettings: | |
| if type not in model_setting_type_to_cls_dict: | |
| raise ValueError(f"Loading {type} setting not supported") | |
| cls = model_setting_type_to_cls_dict[type] | |
| return cls() | |
| def get_all_model_settings() -> List[str]: | |
| """Get all supported Embeddings""" | |
| return list(model_setting_type_to_cls_dict.keys()) | |