mirror of https://github.com/hwchase17/langchain
Fix bug in `index` api (#10614)
<!-- Thank you for contributing to LangChain! Replace this entire comment with: - **Description:** a description of the change, - **Issue:** the issue # it fixes (if applicable), - **Dependencies:** any dependencies required for this change, - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> - **Description:** a fix for `index`. - **Issue:** Not applicable. - **Dependencies:** None - **Tag maintainer:** - **Twitter handle:** richarddwang # Problem Replication code ```python from pprint import pprint from langchain.embeddings import OpenAIEmbeddings from langchain.indexes import SQLRecordManager, index from langchain.schema import Document from langchain.vectorstores import Qdrant from langchain_setup.qdrant import pprint_qdrant_documents, create_inmemory_empty_qdrant # Documents metadata1 = {"source": "fullhell.alchemist"} doc1_1 = Document(page_content="1-1 I have a dog~", metadata=metadata1) doc1_2 = Document(page_content="1-2 I have a daugter~", metadata=metadata1) doc1_3 = Document(page_content="1-3 Ahh! O..Oniichan", metadata=metadata1) doc2 = Document(page_content="2 Lancer died again.", metadata={"source": "fate.docx"}) # Create empty vectorstore collection_name = "secret_of_D_disk" vectorstore: Qdrant = create_inmemory_empty_qdrant() # Create record Manager import tempfile from pathlib import Path record_manager = SQLRecordManager( namespace="qdrant/{collection_name}", db_url=f"sqlite:///{Path(tempfile.gettempdir())/collection_name}.sql", ) record_manager.create_schema() # 必須 sync_result = index( [doc1_1, doc1_2, doc1_2, doc2], record_manager, vectorstore, cleanup="full", source_id_key="source", ) print(sync_result, end="\n\n") pprint_qdrant_documents(vectorstore) ``` <details> <summary>Code of helper functions `pprint_qdrant_documents` and `create_inmemory_empty_qdrant`</summary> ```python def create_inmemory_empty_qdrant(**from_texts_kwargs): # Qdrant requires vector size, which can be only know after applying embedder vectorstore = Qdrant.from_texts(["dummy"], location=":memory:", embedding=OpenAIEmbeddings(), **from_texts_kwargs) dummy_document_id = vectorstore.client.scroll(vectorstore.collection_name)[0][0].id vectorstore.delete([dummy_document_id]) return vectorstore def pprint_qdrant_documents(vectorstore, limit: int = 100, **scroll_kwargs): document_ids, documents = [], [] for record in vectorstore.client.scroll( vectorstore.collection_name, limit=100, **scroll_kwargs )[0]: document_ids.append(record.id) documents.append( Document( page_content=record.payload["page_content"], metadata=record.payload["metadata"] or {}, ) ) pprint_documents(documents, document_ids=document_ids) def pprint_document(document: Document = None, document_id=None, return_string=False): displayed_text = "" if document_id: displayed_text += f"Document {document_id}:\n\n" displayed_text += f"{document.page_content}\n\n" metadata_text = pformat(document.metadata, indent=1) if "\n" in metadata_text: displayed_text += f"Metadata:\n{metadata_text}" else: displayed_text += f"Metadata:{metadata_text}" if return_string: return displayed_text else: print(displayed_text) def pprint_documents(documents, document_ids=None): if not document_ids: document_ids = [i + 1 for i in range(len(documents))] displayed_texts = [] for document_id, document in zip(document_ids, documents): displayed_text = pprint_document( document_id=document_id, document=document, return_string=True ) displayed_texts.append(displayed_text) print(f"\n{'-' * 100}\n".join(displayed_texts)) ``` </details> You will get ``` {'num_added': 3, 'num_updated': 0, 'num_skipped': 0, 'num_deleted': 0} Document 1b19816e-b802-53c0-ad60-5ff9d9b9b911: 1-2 I have a daugter~ Metadata:{'source': 'fullhell.alchemist'} ---------------------------------------------------------------------------------------------------- Document 3362f9bc-991a-5dd5-b465-c564786ce19c: 1-1 I have a dog~ Metadata:{'source': 'fullhell.alchemist'} ---------------------------------------------------------------------------------------------------- Document a4d50169-2fda-5339-a196-249b5f54a0de: 1-2 I have a daugter~ Metadata:{'source': 'fullhell.alchemist'} ``` This is not correct. We should be able to expect that the vectorsotre now includes doc1_1, doc1_2, and doc2, but not doc1_1, doc1_2, and doc1_2. # Reason In `index`, the original code is ```python uids = [] docs_to_index = [] for doc, hashed_doc, doc_exists in zip(doc_batch, hashed_docs, exists_batch): if doc_exists: # Must be updated to refresh timestamp. record_manager.update([hashed_doc.uid], time_at_least=index_start_dt) num_skipped += 1 continue uids.append(hashed_doc.uid) docs_to_index.append(doc) ``` In the aforementioned example, `len(doc_batch) == 4`, but `len(hashed_docs) == len(exists_batch) == 3`. This is because the deduplication of input documents [doc1_1, doc1_2, doc1_2, doc2] is [doc1_1, doc1_2, doc2]. So `index` insert doc1_1, doc1_2, doc1_2 with the uid of doc1_1, doc1_2, doc2. --------- Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>pull/10971/head
parent
d67b120a41
commit
b809c243af
Loading…
Reference in New Issue