Weaviate Vector Store Metadata Filter
Source: llama_index

<a href="https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/docs/examples/vector_stores/WeaviateIndex_metadata_filter.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a># Weaviate Vector Store Metadata FilterIf you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.```python%pip install llama-index-vector-stores-weaviate``````python!pip install llama-index weaviate-client```#### Creating a Weaviate Client```pythonimport osimport openaios.environ["OPENAI_API_KEY"] = ""openai.api_key = os.environ["OPENAI_API_KEY"]``````pythonimport loggingimport syslogging.basicConfig(stream=sys.stdout, level=logging.INFO)logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))``````pythonimport weaviate# cloudcluster_url = ""api_key = ""client = weaviate.connect_to_wcs(    cluster_url=cluster_url,    auth_credentials=weaviate.auth.AuthApiKey(api_key),)# local# client = weaviate.connect_to_local()```    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/meta "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/meta "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://pypi.org/pypi/weaviate-client/json "HTTP/1.1 200 OK"    HTTP Request: GET https://pypi.org/pypi/weaviate-client/json "HTTP/1.1 200 OK"#### Load documents, build the VectorStoreIndex```pythonfrom llama_index.core import VectorStoreIndexfrom llama_index.vector_stores.weaviate import WeaviateVectorStorefrom IPython.display import Markdown, display```## Metadata FilteringLet's insert a dummy document, and try to filter so that only that document is returned.```pythonfrom llama_index.core.schema import TextNodenodes = [    TextNode(        text="The Shawshank Redemption",        metadata={            "author": "Stephen King",            "theme": "Friendship",            "year": 1994,        },    ),    TextNode(        text="The Godfather",        metadata={            "director": "Francis Ford Coppola",            "theme": "Mafia",            "year": 1972,        },    ),    TextNode(        text="Inception",        metadata={            "director": "Christopher Nolan",            "theme": "Fiction",            "year": 2010,        },    ),    TextNode(        text="To Kill a Mockingbird",        metadata={            "author": "Harper Lee",            "theme": "Mafia",            "year": 1960,        },    ),    TextNode(        text="1984",        metadata={            "author": "George Orwell",            "theme": "Totalitarianism",            "year": 1949,        },    ),    TextNode(        text="The Great Gatsby",        metadata={            "author": "F. Scott Fitzgerald",            "theme": "The American Dream",            "year": 1925,        },    ),    TextNode(        text="Harry Potter and the Sorcerer's Stone",        metadata={            "author": "J.K. Rowling",            "theme": "Fiction",            "year": 1997,        },    ),]``````pythonfrom llama_index.core import StorageContextvector_store = WeaviateVectorStore(    weaviate_client=client, index_name="LlamaIndex_filter")storage_context = StorageContext.from_defaults(vector_store=vector_store)index = VectorStoreIndex(nodes, storage_context=storage_context)```    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 404 Not Found"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 404 Not Found"    INFO:httpx:HTTP Request: POST https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema "HTTP/1.1 200 OK"    HTTP Request: POST https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes "HTTP/1.1 200 OK"```pythonretriever = index.as_retriever()retriever.retrieve("What is inception?")```    INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    [NodeWithScore(node=TextNode(id_='df310070-1480-46c1-8ec0-1052c172905e', embedding=[0.0031030464451760054, -0.024837113916873932, -0.022581512108445168, -0.03652292117476463, -0.007072651758790016, 0.011845098808407784, -0.04032048583030701, -0.027602458372712135, -0.01594213955104351, 0.007690712343901396, 0.02783184126019478, 0.02994726411998272, 0.018847661092877388, -0.0044156285002827644, 0.004122527781873941, 0.004409256856888533, 0.027449535205960274, -0.007537790108472109, -0.0030807452276349068, -0.012775375507771969, -0.005791928619146347, -0.019370146095752716, 0.001938607543706894, 0.008990551345050335, 0.0020947156008332968, -0.012953785248100758, 0.013661050237715244, -0.029386550188064575, 0.015011862851679325, 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-0.014768587425351143, -0.005285531748086214, 0.011144038289785385, -0.003544074483215809, -0.004902475513517857, -0.0016561547527089715, 0.011485247872769833, 0.010693384334445, -0.019043365493416786, 0.03821548819541931, -0.02224944904446602, 0.005678244866430759, -0.0005492349737323821, 0.006125680170953274, -0.020433956757187843, -0.00033275995519943535, -0.02667873725295067], metadata={'author': 'J.K. Rowling', 'theme': 'Fiction', 'year': 1997}, excluded_embed_metadata_keys=[], excluded_llm_metadata_keys=[], relationships={}, text="Harry Potter and the Sorcerer's Stone", start_char_idx=None, end_char_idx=None, text_template='{metadata_str}\n\n{content}', metadata_template='{key}: {value}', metadata_seperator='\n'), score=1.0)]```pythonfrom llama_index.core.vector_stores import (    MetadataFilter,    MetadataFilters,    FilterOperator,)filters = MetadataFilters(    filters=[        MetadataFilter(key="theme", operator=FilterOperator.EQ, value="Mafia"),    ])retriever = index.as_retriever(filters=filters)retriever.retrieve("What is inception about?")```    INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    [NodeWithScore(node=TextNode(id_='34d778a1-b6bf-4a24-a1bf-ac659a9959ea', embedding=[-0.0017794573213905096, -0.023969227448105812, -0.01290263794362545, -0.035538844764232635, -0.00970841757953167, 0.02575497329235077, -0.0005831966991536319, 0.0009125220822170377, -0.02186909131705761, -0.0278173815459013, 0.023969227448105812, 0.018712596967816353, 0.028471317142248154, -0.0018627711106091738, 0.006259539630264044, 0.015468074008822441, 0.029024647548794746, -0.007985550910234451, 0.010418943129479885, -0.00027961216983385384, 0.010318337008357048, 0.006847452372312546, -0.029955245554447174, -0.0007384276250377297, 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0.005510220304131508, -0.011692261323332787, 0.03152388706803322, 0.0046284557320177555, 0.002291618613526225, -0.05700138583779335, 0.002971513895317912, -0.006873240694403648, -0.004034153185784817, -0.014392462559044361, 0.011201315559446812, -0.004018003586679697, 0.00875304639339447, 0.0023546016309410334, 0.022945255041122437, 0.022131318226456642, -0.026485232636332512, 0.018862653523683548, -0.02326824516057968, -0.01074912864714861, 0.021511176601052284, 0.010290482081472874, -0.016963468864560127, -0.015774862840771675, -0.009334429167211056], metadata={'author': 'Harper Lee', 'theme': 'Mafia', 'year': 1960}, excluded_embed_metadata_keys=[], excluded_llm_metadata_keys=[], relationships={}, text='To Kill a Mockingbird', start_char_idx=None, end_char_idx=None, text_template='{metadata_str}\n\n{content}', metadata_template='{key}: {value}', metadata_seperator='\n'), score=1.0)]```pythonfrom llama_index.core.vector_stores import ExactMatchFilter, MetadataFiltersfilters = MetadataFilters(    filters=[        MetadataFilter(key="theme", value="Mafia"),        MetadataFilter(key="year", value=1972),    ])retriever = index.as_retriever(filters=filters)retriever.retrieve("What is inception?")```    INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    [NodeWithScore(node=TextNode(id_='34d778a1-b6bf-4a24-a1bf-ac659a9959ea', 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relationships={}, text='The Godfather', start_char_idx=None, end_char_idx=None, text_template='{metadata_str}\n\n{content}', metadata_template='{key}: {value}', metadata_seperator='\n'), score=1.0)]```pythonfrom llama_index.core.vector_stores import FilterOperator, FilterConditionfilters = MetadataFilters(    filters=[        MetadataFilter(key="theme", value="Fiction"),        MetadataFilter(key="year", value=1997, operator=FilterOperator.GT),    ],    condition=FilterCondition.OR,)retriever = index.as_retriever(filters=filters)retriever.retrieve("Harry Potter?")```    INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    HTTP Request: POST https://api.openai.com/v1/embeddings "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter "HTTP/1.1 200 OK"    [NodeWithScore(node=TextNode(id_='b9a4dffd-b9f1-4d83-9c13-f4402d1036b8', embedding=[0.012515314854681492, -0.014948848634958267, -0.04071340337395668, -0.006991580594331026, -0.010674070566892624, 0.016596956178545952, -0.029305409640073776, -0.050885315984487534, -0.021270886063575745, -0.01666133478283882, 0.024966251105070114, 0.013841526582837105, 0.017202120274305344, 0.0007604792481288314, -0.010571063496172428, -0.000707366387359798, 0.022494090721011162, -0.01047449465841055, 0.01530937198549509, -0.014923096634447575, -0.016712838783860207, -0.009611813351511955, -0.008382171392440796, 0.010004526935517788, -0.010493808425962925, -0.0017655993578955531, 0.02235245518386364, -0.04220699891448021, 0.019970426335930824, 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