Set up a ChromaDB vector database with LangChain integration.

Args:
    texts: List of text strings to be embedded and stored in the vector database.
    metadatas: Optional list of metadata dictionaries corresponding to each text.
    persist_directory: Optional directory path to persist the vector database.
                      If None, an in-memory database will be created.

Returns:
    Dict containing retriever info and success status.

Query a ChromaDB vector database using LangChain integration.

Args:
    query: The query string to search for in the vector database.
    persist_directory: Directory path where the vector database is persisted.
    top_k: Number of top results to return (default: 3).

Returns:
    List of retrieved documents with their content and metadata.

Demonstrate the ChromaDB vector database with LangChain integration.

Args:
    sample_texts: Optional list of sample texts to use for demonstration.
                 If not provided, default sample texts will be used.

Returns:
    Results of setting up and querying the ChromaDB vector database.