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https://github.com/hwchase17/langchain
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# Description To support [langchain indexing](https://python.langchain.com/docs/modules/data_connection/indexing) as requested by users, vectorstore Milvus needs to support: - document addition by id (`add_documents` method with `ids` argument) - delete by id (`delete` method with `ids` argument) Example usage: ```python from langchain.indexes import SQLRecordManager, index from langchain.schema import Document from langchain_community.vectorstores import Milvus from langchain_openai import OpenAIEmbeddings collection_name = "test_index" embedding = OpenAIEmbeddings() vectorstore = Milvus(embedding_function=embedding, collection_name=collection_name) namespace = f"milvus/{collection_name}" record_manager = SQLRecordManager( namespace, db_url="sqlite:///record_manager_cache.sql" ) record_manager.create_schema() doc1 = Document(page_content="kitty", metadata={"source": "kitty.txt"}) doc2 = Document(page_content="doggy", metadata={"source": "doggy.txt"}) index( [doc1, doc1, doc2], record_manager, vectorstore, cleanup="incremental", # None, "incremental", or "full" source_id_key="source", ) ``` # Fix issues Fix https://github.com/milvus-io/milvus/issues/30112 --------- Signed-off-by: Jael Gu <mengjia.gu@zilliz.com> Co-authored-by: Bagatur <baskaryan@gmail.com> |
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| .. | ||
| agent_toolkits | ||
| callbacks | ||
| chat_loaders | ||
| chat_message_histories | ||
| chat_models | ||
| docstore | ||
| document_loaders | ||
| document_transformers | ||
| embeddings | ||
| examples | ||
| graphs | ||
| indexes | ||
| llms | ||
| retrievers | ||
| storage | ||
| tools | ||
| utilities | ||
| utils | ||
| vectorstores | ||
| __init__.py | ||
| conftest.py | ||
| test_dependencies.py | ||
| test_imports.py | ||
| test_sqlalchemy.py | ||