from environs import Env

env = Env()
env.read_env()

DEBUG = env.bool("DEBUG", default=True)

TIDB_DATABASE = env.str("TIDB_DATABASE", default="test")
TIDB_HOST = env.str("TIDB_HOST", default="localhost")
TIDB_USER = env.str("TIDB_USER", default="root")
TIDB_PASSWORD = env.str("TIDB_PASSWORD", default="")
TIDB_PORT = env.int("TIDB_PORT", default=4000)


OPENAI_API_KEY = env.str("OPENAI_API_KEY", default="")
OPENAI_EMBEDDING_MODEL = env.str(
    "OPENAI_EMBEDDING_MODEL", default="text-embedding-3-small"
)


SENTRY_DSN = env.str("SENTRY_DSN", default="")

CELERY_BROKER_URL = env.str("CELERY_BROKER_URL", default="redis://127.0.0.1:6379/1")
CELERY_RESULT_BACKEND = env.str(
    "CELERY_RESULT_BACKEND", default="redis://127.0.0.1:6379/1"
)

ENABLE_API_KEY = env.bool("ENABLE_API_KEY", default=False)


TIDB_AI_CHAT_ENDPOINT = env.str(
    "TIDB_AI_CHAT_ENDPOINT", default="https://tidb.ai/api/v1/chats"
)
TIDB_AI_API_KEY = env.str("TIDB_AI_API_KEY", default="")


# Since we are using post-filter when searching relationships to enable vector index,
# we need to specify a top-k factor to adjust the top-k for post-filtering.
RELATIONSHIP_POST_FILTER_TOP_K_FACTOR = env.int(
    "RELATIONSHIP_SEARCH_POST_FILTER_TOP_K_FACTOR", default=10
)

GOOGLE_API_KEY = env.str("GOOGLE_API_KEY", default="")


GRAPH_EXTRACT_LLM_PROVIDER = env.str(
    "GRAPH_EXTRACT_LLM_PROVIDER", default="openai"
).lower()