To retrieve all nodes from your PGVectorDB for use with a BM25 Retriever, ensure your document store (docstore) is correctly initialized with documents from PGVectorDB. The BM25Retriever can be initialized with this document store using the from_defaults method, which will automatically handle the retrieval of nodes if the docstore parameter is provided.

Here's how you can initialize the BM25Retriever with a document store from PGVectorDB:

from llama_index.retrievers.bm25.base import BM25Retriever
from llama_index.vector_stores.postgres import PGVectorStore

# Assuming you have a PGVectorStore instance
vector_store = PGVectorStore.from_params(
    database="vector_db",
    host="localhost",
    password="password",
    port=5432,
    user="postgres",
    table_name="your_table_name",
    embed_dim=1536  # Dimension of your embeddings
)

# Initialize BM25Retriever with the document store
bm25_retriever = BM25Retriever.from_defaults(docstore=vector_store, tokenizer=None, verbose=True)

Make sure your PGVectorDB instance or wrapper correctly implements the BaseDocumentStore interface, especially the .docs attribute or method that returns documents in a format compatible with BaseNode. This will allow the BM25Retriever to access and use the documents stored in PGVectorDB for retrieval tasks efficiently.

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@doganaktarr 请问您这个问题解决了吗 ，我在使用ES数据库的时候也遇到这个问题，nodes: dict_values([]) ，