Makar / __init__.py
TimurZav's picture
Create __init__.py
acbdc6c
raw
history blame
2.54 kB
import os
from langchain.document_loaders import (
CSVLoader,
EverNoteLoader,
PDFMinerLoader,
TextLoader,
UnstructuredEPubLoader,
UnstructuredHTMLLoader,
UnstructuredMarkdownLoader,
UnstructuredODTLoader,
UnstructuredPowerPointLoader,
UnstructuredWordDocumentLoader,
)
FAVICON_PATH: str = 'https://github.com/agladsoft/LocalChatGPT/blob/main/sclogo1.png?raw=true'
SYSTEM_PROMPT: str = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
SYSTEM_TOKEN: int = 1788
USER_TOKEN: int = 1404
BOT_TOKEN: int = 9225
LINEBREAK_TOKEN: int = 13
ROLE_TOKENS: dict = {
"user": USER_TOKEN,
"bot": BOT_TOKEN,
"system": SYSTEM_TOKEN
}
LOADER_MAPPING: dict = {
".csv": (CSVLoader, {}),
".doc": (UnstructuredWordDocumentLoader, {}),
".docx": (UnstructuredWordDocumentLoader, {}),
".enex": (EverNoteLoader, {}),
".epub": (UnstructuredEPubLoader, {}),
".html": (UnstructuredHTMLLoader, {}),
".md": (UnstructuredMarkdownLoader, {}),
".odt": (UnstructuredODTLoader, {}),
".pdf": (PDFMinerLoader, {}),
".ppt": (UnstructuredPowerPointLoader, {}),
".pptx": (UnstructuredPowerPointLoader, {}),
".txt": (TextLoader, {"encoding": "utf8"}),
}
DICT_REPO_AND_MODELS: dict = {
"https://huggingface.co/IlyaGusev/saiga2_7b_gguf/resolve/main/model-q2_K.gguf":
"saiga2_7b_gguf/model-q2_K.gguf",
"https://huggingface.co/IlyaGusev/saiga2_7b_gguf/resolve/main/model-q4_K.gguf":
"saiga2_7b_gguf/model-q4_K.gguf",
"https://huggingface.co/IlyaGusev/saiga2_7b_gguf/resolve/main/model-q8_0.gguf":
"saiga2_7b_gguf/model-q8_0.gguf",
"https://huggingface.co/IlyaGusev/saiga2_13b_gguf/resolve/main/model-q4_K.gguf":
"saiga2_13b_gguf/model-q4_K.gguf",
# "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/resolve/main/llama-2-7b-chat.Q2_K.gguf":
# "llama-2-7b-chat.Q2_K.gguf",
# "https://huggingface.co/TheBloke/OpenBuddy-Llama2-13B-v11.1-GGUF/resolve/main/openbuddy-llama2-13b-v11.1.Q2_K.gguf":
# "openbuddy-llama2-13b-v11.1.Q2_K.gguf",
}
EMBEDDER_NAME: str = "sentence-transformers/paraphrase-multilingual-mpnet-base-v2"
MAX_NEW_TOKENS: int = 1500
ABS_PATH = os.path.dirname(os.path.abspath(__file__))
MODELS_DIR = os.path.join(ABS_PATH, "../models")
AUTH_FILE = os.path.join(ABS_PATH, "auth.csv")
BLOCK_CSS = """
#buttons button {
min-width: min(120px,100%);
}
"""