k=2, fetch_k=10)for i, doc in enumerate(found_docs):    print(f"{i + 1}.", doc.page_content, "\n")PreviousDashVectorNextDocArray HnswSearchAdding More Text to an Existing IndexMaximal Marginal Relevance SearchesCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.
Dingo is a distributed multi-mode vector database, which combines the characteristics of data lakes and vector databases, and can store data of any type and size (Key-Value, PDF, audio, video, etc.). It has real-time low-latency processing capabilities to achieve rapid insight and response, and can efficiently conduct instant analysis and process multi-modal data.
Dingo is a distributed multi-mode vector database, which combines the characteristics of data lakes and vector databases, and can store data of any type and size (Key-Value, PDF, audio, video, etc.). It has real-time low-latency processing capabilities to achieve rapid insight and response, and can efficiently conduct instant analysis and process multi-modal data. ->: k=2, fetch_k=10)for i, doc in enumerate(found_docs):    print(f"{i + 1}.", doc.page_content, "\n")PreviousDashVectorNextDocArray HnswSearchAdding More Text to an Existing IndexMaximal Marginal Relevance SearchesCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright ¬© 2023 LangChain, Inc.