SelfQueryRetriever.from_llm(    llm, vectorstore, document_content_description, metadata_field_info, verbose=True)Testing it out‚ÄãAnd now we can try actually using our retriever!# This example only specifies a relevant queryretriever.get_relevant_documents("What are some movies about dinosaurs")    /home/ubuntu/langchain_activeloop/langchain/libs/langchain/langchain/chains/llm.py:279: UserWarning: The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain.      warnings.warn(    query='dinosaur' filter=None limit=None    [Document(page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose', metadata={'year': 1993, 'rating': 7.7, 'genre': 'science fiction'}),     Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'}),     Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'}),     Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6})]# This example only specifies a filterretriever.get_relevant_documents("I want to watch a movie rated higher than 8.5")# in case if this example errored out, consider installing libdeeplake manually: `pip install libdeeplake`, and then restart notebook.    query=' ' filter=Comparison(comparator=<Comparator.GT: 'gt'>, attribute='rating', value=8.5) limit=None    [Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6}),     Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre':
Deep Lake is a multimodal database for building AI applications
Deep Lake is a multimodal database for building AI applications ->: SelfQueryRetriever.from_llm(    llm, vectorstore, document_content_description, metadata_field_info, verbose=True)Testing it out‚ÄãAnd now we can try actually using our retriever!# This example only specifies a relevant queryretriever.get_relevant_documents("What are some movies about dinosaurs")    /home/ubuntu/langchain_activeloop/langchain/libs/langchain/langchain/chains/llm.py:279: UserWarning: The predict_and_parse method is deprecated, instead pass an output parser directly to LLMChain.      warnings.warn(    query='dinosaur' filter=None limit=None    [Document(page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose', metadata={'year': 1993, 'rating': 7.7, 'genre': 'science fiction'}),     Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'}),     Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'}),     Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6})]# This example only specifies a filterretriever.get_relevant_documents("I want to watch a movie rated higher than 8.5")# in case if this example errored out, consider installing libdeeplake manually: `pip install libdeeplake`, and then restart notebook.    query=' ' filter=Comparison(comparator=<Comparator.GT: 'gt'>, attribute='rating', value=8.5) limit=None    [Document(page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea', metadata={'year': 2006, 'director': 'Satoshi Kon', 'rating': 8.6}),     Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre':