SuiAgentic

import os from dotenv import load_dotenv # Load environment variables load_dotenv() # Qdrant configuration QDRANT_URL = os.getenv("QDRANT_URL", "localhost") QDRANT_PORT = int(os.getenv("QDRANT_PORT", "6333")) QDRANT_COLLECTION_NAME = os.getenv("QDRANT_COLLECTION_NAME", "contextmore") # Vector dimensions # Note: Most sentence transformer models don't output 3072 dimensions by default # The actual output dimensions might be smaller (usually 768 or 1024) # To achieve 3072 dimensions, you can use a larger model or potentially # use techniques like concatenation or dimensionality expansion VECTOR_SIZE = 3072 # Model configuration # Using one of the largest sentence-transformer models available MODEL_NAME = 'sentence-transformers/all-mpnet-base-v2' # 768 dimensions # Set this to True to recreate the collection with new vector dimensions RECREATE_COLLECTION = True