For quickstart, you can rely on the default embedding utils. By default we use "HuggingFaceEmbedding" This eliminates the need to configure embeddings, making the process effortless.

To utilize the vectordb configuration with the default embedding:

=> Vectordb Usage

from langchain.docstore.document import Document as LangDocument

from genai_stack.vectordb.chromadb import ChromaDB
from genai_stack.vectordb.weaviate_db import Weaviate
from genai_stack.embedding.utils import get_default_embedding
from genai_stack.stack.stack import Stack

embedding = get_default_embedding()
chromadb = ChromaDB.from_kwargs()
chroma_stack = Stack(model=None, embedding=embedding, vectordb=chromadb)

# Add your documents
                    page_content="Some page content explaining something", metadata={"some_metadata": "some_metadata"}

# Output 
# Your search results 

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