import os from importlib.metadata import version from inspect import currentframe, getframeinfo from pathlib import Path from decouple import config from theflow.settings.default import * # noqa cur_frame = currentframe() if cur_frame is None: raise ValueError("Cannot get the current frame.") this_file = getframeinfo(cur_frame).filename this_dir = Path(this_file).parent # change this if your app use a different name KH_PACKAGE_NAME = "kotaemon_app" KH_APP_VERSION = None try: # Caution: This might produce the wrong version # https://stackoverflow.com/a/59533071 KH_APP_VERSION = version(KH_PACKAGE_NAME) except Exception as e: print(f"Failed to get app version: {e}") # App can be ran from anywhere and it's not trivial to decide where to store app data. # So let's use the same directory as the flowsetting.py file. KH_APP_DATA_DIR = this_dir / "ktem_app_data" KH_APP_DATA_DIR.mkdir(parents=True, exist_ok=True) # User data directory KH_USER_DATA_DIR = KH_APP_DATA_DIR / "user_data" KH_USER_DATA_DIR.mkdir(parents=True, exist_ok=True) # doc directory KH_DOC_DIR = this_dir / "docs" # HF models can be big, let's store them in the app data directory so that it's easier # for users to manage their storage. # ref: https://huggingface.co/docs/huggingface_hub/en/guides/manage-cache os.environ["HF_HOME"] = str(KH_APP_DATA_DIR / "huggingface") os.environ["HF_HUB_CACHE"] = str(KH_APP_DATA_DIR / "huggingface") COHERE_API_KEY = config("COHERE_API_KEY", default="") KH_MODE = "dev" KH_FEATURE_USER_MANAGEMENT = False KH_FEATURE_USER_MANAGEMENT_ADMIN = str( config("KH_FEATURE_USER_MANAGEMENT_ADMIN", default="admin") ) KH_FEATURE_USER_MANAGEMENT_PASSWORD = str( config("KH_FEATURE_USER_MANAGEMENT_PASSWORD", default="XsdMbe8zKP8KdeE@") ) KH_ENABLE_ALEMBIC = False KH_DATABASE = f"sqlite:///{KH_USER_DATA_DIR / 'sql.db'}" KH_FILESTORAGE_PATH = str(KH_USER_DATA_DIR / "files") KH_DOCSTORE = { "__type__": "kotaemon.storages.SimpleFileDocumentStore", "path": str(KH_USER_DATA_DIR / "docstore"), } KH_VECTORSTORE = { "__type__": "kotaemon.storages.ChromaVectorStore", "path": str(KH_USER_DATA_DIR / "vectorstore"), } KH_LLMS = {} KH_EMBEDDINGS = {} # populate options from config if config("AZURE_OPENAI_API_KEY", default="") and config( "AZURE_OPENAI_ENDPOINT", default="" ): if config("AZURE_OPENAI_CHAT_DEPLOYMENT", default=""): KH_LLMS["azure"] = { "spec": { "__type__": "kotaemon.llms.AzureChatOpenAI", "temperature": 0, "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""), "api_key": config("AZURE_OPENAI_API_KEY", default=""), "api_version": config("OPENAI_API_VERSION", default="") or "2024-02-15-preview", "azure_deployment": config("AZURE_OPENAI_CHAT_DEPLOYMENT", default=""), "timeout": 20, }, "default": False, "accuracy": 5, "cost": 5, } if config("AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT", default=""): KH_EMBEDDINGS["azure"] = { "spec": { "__type__": "kotaemon.embeddings.AzureOpenAIEmbeddings", "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""), "api_key": config("AZURE_OPENAI_API_KEY", default=""), "api_version": config("OPENAI_API_VERSION", default="") or "2024-02-15-preview", "azure_deployment": config( "AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT", default="" ), "timeout": 10, }, "default": False, } if config("OPENAI_API_KEY", default=""): KH_LLMS["openai"] = { "spec": { "__type__": "kotaemon.llms.ChatOpenAI", "temperature": 0, "base_url": config("OPENAI_API_BASE", default="") or "https://api.openai.com/v1", "api_key": config("OPENAI_API_KEY", default=""), "model": config("OPENAI_CHAT_MODEL", default="") or "gpt-3.5-turbo", "timeout": 10, }, "default": False, } if len(KH_EMBEDDINGS) < 1: KH_EMBEDDINGS["openai"] = { "spec": { "__type__": "kotaemon.embeddings.OpenAIEmbeddings", "base_url": config("OPENAI_API_BASE", default="") or "https://api.openai.com/v1", "api_key": config("OPENAI_API_KEY", default=""), "model": config( "OPENAI_EMBEDDINGS_MODEL", default="text-embedding-ada-002" ) or "text-embedding-ada-002", "timeout": 10, }, "default": False, } if config("LOCAL_MODEL", default=""): KH_LLMS["local"] = { "spec": { "__type__": "kotaemon.llms.EndpointChatLLM", "endpoint_url": "http://localhost:31415/v1/chat/completions", }, "default": False, "cost": 0, } if len(KH_EMBEDDINGS) < 1: KH_EMBEDDINGS["local"] = { "spec": { "__type__": "kotaemon.embeddings.EndpointEmbeddings", "endpoint_url": "http://localhost:31415/v1/embeddings", }, "default": False, "cost": 0, } OPENROUTER_API_KEY = config("OPENROUTER_API_KEY", default="") openrouter_models = { "Mistral 7B Instruct (free)": "mistralai/mistral-7b-instruct:free", "Toppy M 7B (free)": "undi95/toppy-m-7b:free", "Meta: LLama 3 8B Instruct (free)": "meta-llama/llama-3-8b-instruct:free", "OpenChat 3.5 (free)": "openchat/openchat-7b:free", "MythoMist 7B (free)": "gryphe/mythomist-7b:free", "Nous: Capybara 7B (free)": "nousresearch/nous-capybara-7b:free", "Google: Gemma 7B (free)": "google/gemma-7b-it:free", "Cinematika 7B (alpha) (free)": "openrouter/cinematika-7b:free", "Hugging Face: Zephyr 7B (free)": "huggingfaceh4/zephyr-7b-beta:free", "RWKV v5: Eagle 7B": "recursal/eagle-7b", } for name, model in openrouter_models.items(): KH_LLMS[f"OpenRouter - {name}"] = { "spec": { "__type__": "kotaemon.llms.ChatOpenAI", "base_url": "https://openrouter.ai/api/v1/", "api_key": OPENROUTER_API_KEY, "model": model, }, "cost": 0, "default": model == "mistralai/mistral-7b-instruct:free", } if len(KH_EMBEDDINGS) < 1: KH_EMBEDDINGS["local-bge-base-en-v1.5"] = { "spec": { "__type__": "kotaemon.embeddings.FastEmbedEmbeddings", "model_name": "BAAI/bge-base-en-v1.5", }, "default": True, } KH_REASONINGS = [ "ktem.reasoning.simple.FullQAPipeline", "ktem.reasoning.react.ReactAgentPipeline", "ktem.reasoning.rewoo.RewooAgentPipeline", ] KH_VLM_ENDPOINT = "{0}/openai/deployments/{1}/chat/completions?api-version={2}".format( config("AZURE_OPENAI_ENDPOINT", default=""), config("OPENAI_VISION_DEPLOYMENT_NAME", default="gpt-4-vision"), config("OPENAI_API_VERSION", default=""), ) SETTINGS_APP = { "lang": { "name": "Language", "value": "en", "choices": [("English", "en"), ("Japanese", "ja")], "component": "dropdown", } } SETTINGS_REASONING = { "use": { "name": "Reasoning options", "value": None, "choices": [], "component": "radio", }, "lang": { "name": "Language", "value": "en", "choices": [("English", "en"), ("Japanese", "ja")], "component": "dropdown", }, } KH_INDEX_TYPES = ["ktem.index.file.FileIndex"] KH_INDICES = [ { "name": "File", "config": {}, "index_type": "ktem.index.file.FileIndex", }, ]