8a90fcfc99
1. Introduce the concept of "collection_name" to docstore and vector store. Each collection can be viewed similarly to a table in a SQL database. It allows better organizing information within this data source. 2. Move the `Index` and `Source` tables from the application scope into the index scope. For each new index created by user, these tables should increase accordingly. So it depends on the index, rather than the app. 3. Make each index responsible for the UI components in the app. 4. Construct the File UI page.
110 lines
3.0 KiB
Python
110 lines
3.0 KiB
Python
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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KH_MODE = "dev"
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KH_ENABLE_ALEMBIC = False
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KH_DATABASE = f"sqlite:///{user_cache_dir / 'sql.db'}"
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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_FILESTORAGE_PATH = str(user_cache_dir / "files")
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KH_LLMS = {
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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": "dummy-q2",
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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": "dummy-q2",
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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": True,
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},
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}
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KH_EMBEDDINGS = {
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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": "dummy-q2-text-embedding",
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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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}
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KH_REASONINGS = ["ktem.reasoning.simple.FullQAPipeline"]
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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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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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