ValidationError: document_store.update_embeddings

[willmsMwx]

Hello,

I wanted to implement the following example with Qdrant: https://haystack.deepset.ai/tutorials/15_tableqa

Initialisation of the DocumentStore:
document_store = QdrantDocumentStore(
":memory:",
index="document",
embedding_dim=768
)

A list with Document(content=current_df, content_type="table", id=key) is created (read_tables()):

tables = read_tables(f"{doc_dir}/tables.json")
document_store.write_documents(tables, index=document_index)

An error is thrown when updating the embeddings in the DocumentStore:
retriever = TableTextRetriever(
document_store=document_store
)
document_store.update_embeddings(retriever=retriever)

---

File /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/qdrant_haystack/document_stores/qdrant.py:372, in QdrantDocumentStore.update_embeddings(self, retriever, index, update_existing_embeddings, filters, batch_size, headers)
362 doc_generator = self.get_all_documents_generator(
363 index=index,
364 filters=filters,
365 batch_size=batch_size,
366 headers=headers,
367 )
369 with tqdm(
370 total=document_count, position=0, unit=" Docs", desc="Updating embeddings"
371 ) as progress_bar:
--> 372 for document_batch in get_batches_from_generator(doc_generator, batch_size):
...
ValidationError: 2 validation errors for Document
content
str type expected (type=type_error.str)
content
instance of DataFrame expected (type=type_error.arbitrary_type; expected_arbitrary_type=DataFrame)