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| import os | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| class Config: | |
| # API Keys | |
| LLAMA_API_KEY = os.getenv("LLAMA_API_KEY") | |
| SECRET_KEY = os.getenv("SECRET_KEY", "your-secret-key-change-this") | |
| # Model settings | |
| MODEL_NAME = "LLaMA 3 70B" | |
| EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2" | |
| # Vector database settings | |
| VECTOR_DB_PATH = os.getenv("VECTOR_DB_PATH", "data/vector_store") | |
| # RAG settings | |
| MAX_DOCUMENTS = 5 # Maximum number of documents to retrieve | |
| SIMILARITY_THRESHOLD = 1.5 # Modified threshold to be more lenient | |
| # Flask settings | |
| DEBUG = os.getenv("DEBUG", "False").lower() == "true" | |
| # File upload settings | |
| MAX_CONTENT_LENGTH = 16 * 1024 * 1024 # 16MB max file size |