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"""
This file consolidates parameters for logging, database connections, model paths, API settings, and security.
"""
import torch
import logging # kind of advanced logger
import os
base_path = os.path.dirname(os.path.realpath(__file__))
# Logging setup for console output.
logging.basicConfig(
level=logging.INFO,
format="%(levelname)s: %(message)s",
handlers=[logging.StreamHandler()]
)
# Qdrant vector database connection.
qdrant_client_config = {
"host": "localhost",
"port": 6333,
}
# Automatically detects CUDA or uses CPU.
device = "cuda" if torch.cuda.is_available() else 'cpu'
embedder_model = "all-MiniLM-L6-v2"
reranker_model = "cross-encoder/ms-marco-MiniLM-L6-v2"
local_llm_config = {
"model_path_or_repo_id": "TheBloke/Mistral-7B-v0.1-GGUF",
"model_file": "mistral-7b-v0.1.Q5_K_S.gguf",
"model_type": "mistral",
"gpu_layers": 20 if torch.cuda.is_available() else 0,
"threads": 8,
"context_length": 4096, # The maximum context window is 4096 tokens
"mlock": True, # Locks the model into RAM to prevent swapping
}
local_generation_config = {
"last_n_tokens": 128, # The most recent of tokens that will be penalized (if it was repeated)
"temperature": 0.3, # Controls the randomness of output. Higher value - higher randomness
"repetition_penalty": 1.2,
}
text_splitter_config = {
"chunk_size": 1000, # The maximum size of chunk
"chunk_overlap": 100,
"length_function": len, # Function to measure chunk length
"is_separator_regex": False,
"add_start_index": True,
}
# "127.0.0.1"
api_config = {
"app": "app.api:api",
"host": "0.0.0.0",
"port": 5050,
"reload": True, # The server will reload on system changes
}
gemini_generation_config = {
"temperature": 0, # deterministic, predictable output
"top_p": 0.95,
"top_k": 20,
"candidate_count": 1,
"seed": 5,
"max_output_tokens": 1000,
"stop_sequences": ['STOP!'],
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
}
use_gemini: bool = True
max_delta = 0.15 # defines what is the minimum boundary for vectors to be considered similar
# for postgres client
# Note: you should run postgres server with similar host, post, and do not forget to create a user with similar settings
host = "localhost"
port = 5432
user = "postgres"
password = "lol"
dbname = "exp"
postgres_client_config = {
"url": os.environ['DATABASE_URL'],
"echo": False,
}
very_secret_pepper = "goida" # +1 point, имба
jwt_algorithm = "HS256"
max_cookie_lifetime = 300 # in seconds
url_user_not_required = ["login", "", "viewer", "message_with_docs", "new_user"] |