import os
from dotenv import load_dotenv

load_dotenv()


class Config:
    LLM_MODEL = os.getenv("LLM_MODEL", "models/gemini-2.5-flash")
    EMBED_MODEL = os.getenv("EMBED_MODEL", "models/gemini-embedding-001")
    GEMINI_API_KEY = os.getenv("GEMINI_API_KEY", "")
    MAX_HISTORY = int(os.getenv("MAX_HISTORY", "15"))
    MILVUS_URI = os.getenv("MILVUS_URI", "http://localhost:19530")
    MILVUS_COLLECTION = os.getenv("MILVUS_COLLECTION", "gemini_sentence_index")
    STORE_MILVUS_COLLECTION = os.getenv(
        "STORE_MILVUS_COLLECTION", "store_gemini_sentence_index"
    )
    MONGO_URI: str = os.environ.get("MONGO_URI", "mongodb://localhost:27017")
    MONGO_DB: str = os.environ.get("MONGO_DB", "dial_ai-dev")
    MONGO_COLLECTION: str = os.environ.get("MONGO_COLLECTION", "documents")
    EMBED_DIM: str = int(os.getenv("DIMENSION", "768"))
    LOG_LEVEL: str = os.environ.get("LOG_LEVEL", "INFO")
    QDRANT_URI: str = os.environ.get("QDRANT_URI", "http://146.190.9.173:6333")
    QDRANT_API_KEY: str = os.environ.get("QDRANT_API_KEY", "")
    QDRANT_COLLECTION: str = os.environ.get("QDRANT_COLLECTION", "knowledge_collection")
    PRODUCT_QDRANT_COLLECTION: str = os.environ.get("PRODUCT_QDRANT_COLLECTION", "products_hybrid")
    RAG_QDRANT_COLLECTION: str = os.environ.get("RAG_QDRANT_COLLECTION", "Agent-QA")
    JWT_SECRET: str = os.environ.get("JWT_SECRET", "")