2024-01-23 10:54:18 +07:00
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from pathlib import Path
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from decouple import config
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from platformdirs import user_cache_dir
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from theflow.settings.default import * # noqa
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user_cache_dir = Path(
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user_cache_dir(str(config("KH_APP_NAME", default="ktem")), "Cinnamon")
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)
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user_cache_dir.mkdir(parents=True, exist_ok=True)
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COHERE_API_KEY = config("COHERE_API_KEY", default="")
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2024-01-25 19:07:53 +07:00
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KH_MODE = "dev"
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2024-03-15 16:17:33 +07:00
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KH_FEATURE_USER_MANAGEMENT = False
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2024-03-07 14:19:37 +07:00
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KH_FEATURE_USER_MANAGEMENT_ADMIN = str(
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config("KH_FEATURE_USER_MANAGEMENT_ADMIN", default="admin")
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)
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KH_FEATURE_USER_MANAGEMENT_PASSWORD = str(
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config("KH_FEATURE_USER_MANAGEMENT_PASSWORD", default="XsdMbe8zKP8KdeE@")
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)
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2024-01-28 19:54:15 +07:00
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KH_ENABLE_ALEMBIC = False
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2024-01-23 10:54:18 +07:00
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KH_DATABASE = f"sqlite:///{user_cache_dir / 'sql.db'}"
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2024-03-15 16:17:33 +07:00
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KH_FILESTORAGE_PATH = str(user_cache_dir / "files")
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2024-01-23 10:54:18 +07:00
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KH_DOCSTORE = {
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"__type__": "kotaemon.storages.SimpleFileDocumentStore",
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"path": str(user_cache_dir / "docstore"),
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}
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KH_VECTORSTORE = {
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"__type__": "kotaemon.storages.ChromaVectorStore",
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"path": str(user_cache_dir / "vectorstore"),
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}
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KH_LLMS = {
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2024-03-15 16:17:33 +07:00
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# example for using Azure OpenAI, the config variables can set as environment
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# variables or in the .env file
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# "gpt4": {
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# "def": {
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# "__type__": "kotaemon.llms.AzureChatOpenAI",
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# "temperature": 0,
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# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
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# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
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# "openai_api_version": config("OPENAI_API_VERSION", default=""),
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# "deployment_name": "<your deployment name>",
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# "stream": True,
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# },
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# "accuracy": 10,
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# "cost": 10,
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# "default": False,
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# },
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# "gpt35": {
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# "def": {
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# "__type__": "kotaemon.llms.AzureChatOpenAI",
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# "temperature": 0,
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# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
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# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
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# "openai_api_version": config("OPENAI_API_VERSION", default=""),
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# "deployment_name": "<your deployment name>",
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# "request_timeout": 10,
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# "stream": False,
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# },
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# "accuracy": 5,
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# "cost": 5,
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# "default": False,
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# },
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"local": {
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2024-01-23 10:54:18 +07:00
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"def": {
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2024-03-15 16:17:33 +07:00
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"__type__": "kotaemon.llms.EndpointChatLLM",
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"endpoint_url": "http://localhost:31415/v1/chat/completions",
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2024-01-23 10:54:18 +07:00
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},
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"default": False,
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},
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}
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KH_EMBEDDINGS = {
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2024-03-15 16:17:33 +07:00
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# example for using Azure OpenAI, the config variables can set as environment
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# variables or in the .env file
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# "ada": {
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# "def": {
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# "__type__": "kotaemon.embeddings.AzureOpenAIEmbeddings",
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# "model": "text-embedding-ada-002",
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# "azure_endpoint": config("AZURE_OPENAI_ENDPOINT", default=""),
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# "openai_api_key": config("AZURE_OPENAI_API_KEY", default=""),
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# "deployment": "<your deployment name>",
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# "chunk_size": 16,
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# },
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# "accuracy": 5,
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# "cost": 5,
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# "default": True,
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# },
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"local": {
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2024-01-23 10:54:18 +07:00
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"def": {
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2024-03-15 16:17:33 +07:00
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"__type__": "kotaemon.embeddings.EndpointEmbeddings",
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"endpoint_url": "http://localhost:31415/v1/embeddings",
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2024-01-23 10:54:18 +07:00
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},
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2024-03-15 16:17:33 +07:00
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"default": False,
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2024-01-23 10:54:18 +07:00
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},
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}
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2024-01-26 22:31:52 +07:00
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KH_REASONINGS = ["ktem.reasoning.simple.FullQAPipeline"]
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2024-01-23 10:54:18 +07:00
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SETTINGS_APP = {
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"lang": {
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"name": "Language",
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"value": "en",
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"choices": [("English", "en"), ("Japanese", "ja")],
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"component": "dropdown",
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}
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}
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SETTINGS_REASONING = {
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"use": {
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"name": "Reasoning options",
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"value": None,
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"choices": [],
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"component": "radio",
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},
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"lang": {
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"name": "Language",
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"value": "en",
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"choices": [("English", "en"), ("Japanese", "ja")],
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"component": "dropdown",
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},
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}
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2024-03-07 01:50:47 +07:00
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KH_INDEX_TYPES = ["ktem.index.file.FileIndex"]
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KH_INDICES = [
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{
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"id": 1,
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"name": "File",
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"config": {},
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"index_type": "ktem.index.file.FileIndex",
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}
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]
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