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import os
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")
llm_model_name: str = "HuggingFaceH4/zephyr-7b-beta"
context_window_size: int = 5
retrieval_top_k: int = 3
temperature: float = 0.2
max_length: int = 2048
hf_token: str = os.getenv("HF_TOKEN")
if not hf_token:
raise ValueError(
"ERREUR : Le token Hugging Face (HF_TOKEN) n'est pas défini ! Ajoute-le dans les variables d'environnement Hugging Face Spaces."
)
embedding_model_name: str = "sentence-transformers/sentence-t5-xxl"
# qdrant_url: str = "http://qdrant:6333"
qdrant_url: str = "http://localhost:6333"
parser: str = "openparse"
history_store: dict = {}
session_id: str = "user012025"
user_collection_name: str = "User_Ademe_collection"
doc_collection_name: str = "Doc_Ademe_collection"
provider: str = "hf_api"
settings = Settings()
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