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import logging
from llama_index import MockEmbedding
from llama_index.embeddings.base import BaseEmbedding
from app._config import settings
from app.enums import EmbeddingMode
from app.paths import models_cache_path
logger = logging.getLogger(__name__)
MOCK_EMBEDDING_DIM = 1536
class EmbeddingComponent:
embedding_model: BaseEmbedding
def __init__(self) -> None:
embedding_mode = settings.EMBEDDING_MODE
logger.info("Initializing the embedding model in mode=%s", embedding_mode)
match embedding_mode:
case EmbeddingMode.OPENAI:
from llama_index import OpenAIEmbedding
self.embedding_model = OpenAIEmbedding(api_key=settings.OPENAI_API_KEY)
case EmbeddingMode.MOCK:
# Not a random number, is the dimensionality used by
# the default embedding model
self.embedding_model = MockEmbedding(MOCK_EMBEDDING_DIM)
case EmbeddingMode.LOCAL:
from llama_index.embeddings import HuggingFaceEmbedding
self.embedding_model = HuggingFaceEmbedding(
model_name=settings.LOCAL_HF_EMBEDDING_MODEL_NAME,
cache_folder=str(models_cache_path),
)
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