Dataset_Recommender / config.py
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Update config.py
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import os
try:
from dotenv import load_dotenv
load_dotenv()
except ImportError:
pass
KAGGLE_USERNAME: str = os.environ.get("KAGGLE_USERNAME", "")
KAGGLE_KEY: str = os.environ.get("KAGGLE_KEY", "")
RESULTS_PER_SOURCE: int = 20
RETRIEVER_TIMEOUT_SECONDS: int = 15
EMBEDDING_MODEL: str = "sentence-transformers/all-MiniLM-L6-v2"
FAISS_TOP_K: int = 10
LLM_MODEL_ID: str = "Qwen/Qwen2.5-7B-Instruct"
LLM_MAX_NEW_TOKENS: int = 900
LLM_INPUT_COUNT: int = 5
DISPLAY_TOP_N: int = 5
LLM_MAX_RETRIES: int = 3
LLM_RETRY_BACKOFF_SECONDS: int = 5
def check_secrets() -> dict[str, bool]:
"""
Returns a dict showing which optional secrets are configured.
Used at startup to warn the user if a retrieval lane will be skipped.
"""
return {
"kaggle": bool(KAGGLE_USERNAME and KAGGLE_KEY),
"huggingface": True,
"datagov": True,
}