docs/docs/examples/vector_stores/WeaviateIndex_metadata_filter.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "23cf319b",
   "metadata": {},
   "source": [
    "<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>"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "307804a3-c02b-4a57-ac0d-172c30ddc851",
   "metadata": {},
   "source": [
    "# Weaviate Vector Store Metadata Filter"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "5508d8ac",
   "metadata": {},
   "source": [
    "If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0beb6603",
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install llama-index-vector-stores-weaviate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b05d5956",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install llama-index weaviate-client"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "f7010b1d-d1bb-4f08-9309-a328bb4ea396",
   "metadata": {},
   "source": [
    "#### Creating a Weaviate Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "08ad68ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "\n",
    "os.environ[\"OPENAI_API_KEY\"] = \"\"\n",
    "openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eccceb71",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "import sys\n",
    "\n",
    "logging.basicConfig(stream=sys.stdout, level=logging.INFO)\n",
    "logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df8b27e5-5ad5-4dfe-90c7-0cf1f1d1b37f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/meta \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/meta \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://pypi.org/pypi/weaviate-client/json \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://pypi.org/pypi/weaviate-client/json \"HTTP/1.1 200 OK\"\n"
     ]
    }
   ],
   "source": [
    "import weaviate\n",
    "\n",
    "# cloud\n",
    "cluster_url = \"\"\n",
    "api_key = \"\"\n",
    "\n",
    "client = weaviate.connect_to_wcs(\n",
    "    cluster_url=cluster_url,\n",
    "    auth_credentials=weaviate.auth.AuthApiKey(api_key),\n",
    ")\n",
    "\n",
    "# local\n",
    "# client = weaviate.connect_to_local()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8ee4473a-094f-4d0a-a825-e1213db07240",
   "metadata": {},
   "source": [
    "#### Load documents, build the VectorStoreIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a2bcc07",
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import VectorStoreIndex\n",
    "from llama_index.vector_stores.weaviate import WeaviateVectorStore\n",
    "from IPython.display import Markdown, display"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "3a41a70d",
   "metadata": {},
   "source": [
    "## Metadata Filtering\n",
    "\n",
    "Let's insert a dummy document, and try to filter so that only that document is returned."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df6b6d46",
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core.schema import TextNode\n",
    "\n",
    "nodes = [\n",
    "    TextNode(\n",
    "        text=\"The Shawshank Redemption\",\n",
    "        metadata={\n",
    "            \"author\": \"Stephen King\",\n",
    "            \"theme\": \"Friendship\",\n",
    "            \"year\": 1994,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"The Godfather\",\n",
    "        metadata={\n",
    "            \"director\": \"Francis Ford Coppola\",\n",
    "            \"theme\": \"Mafia\",\n",
    "            \"year\": 1972,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"Inception\",\n",
    "        metadata={\n",
    "            \"director\": \"Christopher Nolan\",\n",
    "            \"theme\": \"Fiction\",\n",
    "            \"year\": 2010,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"To Kill a Mockingbird\",\n",
    "        metadata={\n",
    "            \"author\": \"Harper Lee\",\n",
    "            \"theme\": \"Mafia\",\n",
    "            \"year\": 1960,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"1984\",\n",
    "        metadata={\n",
    "            \"author\": \"George Orwell\",\n",
    "            \"theme\": \"Totalitarianism\",\n",
    "            \"year\": 1949,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"The Great Gatsby\",\n",
    "        metadata={\n",
    "            \"author\": \"F. Scott Fitzgerald\",\n",
    "            \"theme\": \"The American Dream\",\n",
    "            \"year\": 1925,\n",
    "        },\n",
    "    ),\n",
    "    TextNode(\n",
    "        text=\"Harry Potter and the Sorcerer's Stone\",\n",
    "        metadata={\n",
    "            \"author\": \"J.K. Rowling\",\n",
    "            \"theme\": \"Fiction\",\n",
    "            \"year\": 1997,\n",
    "        },\n",
    "    ),\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "30b0b2e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 404 Not Found\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 404 Not Found\"\n",
      "INFO:httpx:HTTP Request: POST https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/nodes \"HTTP/1.1 200 OK\"\n"
     ]
    }
   ],
   "source": [
    "from llama_index.core import StorageContext\n",
    "\n",
    "vector_store = WeaviateVectorStore(\n",
    "    weaviate_client=client, index_name=\"LlamaIndex_filter\"\n",
    ")\n",
    "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n",
    "index = VectorStoreIndex(nodes, storage_context=storage_context)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfe83ebf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n"
     ]
    },
    {
     "data": {
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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)]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retriever = index.as_retriever()\n",
    "retriever.retrieve(\"What is inception?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1bd18f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
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0.012822728604078293, -0.03806121647357941, -0.027570480480790138, 0.010477815754711628, -0.014818809926509857, 0.004857779014855623, -0.0012104073539376259, -0.00779699394479394, 0.01996082067489624, 0.020981471985578537, 0.001960553228855133, -0.0066794464364647865, 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)]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from llama_index.core.vector_stores import (\n",
    "    MetadataFilter,\n",
    "    MetadataFilters,\n",
    "    FilterOperator,\n",
    ")\n",
    "\n",
    "\n",
    "filters = MetadataFilters(\n",
    "    filters=[\n",
    "        MetadataFilter(key=\"theme\", operator=FilterOperator.EQ, value=\"Mafia\"),\n",
    "    ]\n",
    ")\n",
    "\n",
    "retriever = index.as_retriever(filters=filters)\n",
    "retriever.retrieve(\"What is inception about?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "642bef1e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
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-0.0281443502753973, -0.02501300722360611, 0.023780591785907745, 0.012437338009476662, 0.03065948374569416, -0.011726812459528446, -0.010337200947105885, 0.006595938932150602, -0.003624937031418085, 0.0007325327605940402, 0.012034916318953037, -0.01555610354989767, 0.010683031752705574, 0.015669284388422966, 0.023441048339009285, -0.006709120236337185, 0.022573327645659447, -2.9474227858372615e-07, 0.026987388730049133, 0.011544465087354183, -0.012978091835975647, -0.05613779276609421, -0.0036343687679618597, -0.018134117126464844, -0.01981925591826439, -0.0035652024671435356, 0.013594299554824829, -0.00691033061593771, 0.011431284248828888, 0.008890998549759388, 0.007796915713697672, 0.027087993919849396, -0.04341121390461922, 0.022749386727809906, -0.027440112084150314, -0.007205858826637268, 0.03843124955892563, 0.013355361297726631, -0.005350947845727205, -0.01622261479496956, -0.025541186332702637], metadata={'director': 'Francis Ford Coppola', 'theme': 'Mafia', 'year': 1972}, excluded_embed_metadata_keys=[], excluded_llm_metadata_keys=[], 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)]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from llama_index.core.vector_stores import ExactMatchFilter, MetadataFilters\n",
    "\n",
    "\n",
    "filters = MetadataFilters(\n",
    "    filters=[\n",
    "        MetadataFilter(key=\"theme\", value=\"Mafia\"),\n",
    "        MetadataFilter(key=\"year\", value=1972),\n",
    "    ]\n",
    ")\n",
    "\n",
    "retriever = index.as_retriever(filters=filters)\n",
    "retriever.retrieve(\"What is inception?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "63ca00ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:httpx:HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "INFO:httpx:HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n",
      "HTTP Request: GET https://llamaindex-pythonv4-dhqgeqxq.weaviate.network/v1/schema/LlamaIndex_filter \"HTTP/1.1 200 OK\"\n"
     ]
    },
    {
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0.01086384803056717, -0.046513836830854416, -0.013661050237715244, 0.03234304487705231, 0.01424725167453289, 0.01671949401497841, -0.01081287395209074, -0.04197714477777481, 0.010730041190981865, 0.0007630180916748941, 0.0035267684143036604, -0.007792660500854254, 0.004756517708301544, 0.01548337284475565, 0.007894609123468399, 0.0035267684143036604, -0.008257798850536346, 0.008684706874191761, -0.009837995283305645, 0.035579897463321686, 0.014196277596056461, -0.025474289432168007, -0.05265621095895767, -0.01712728664278984, -0.020083783194422722, -0.016821442171931267, 0.003737036371603608, 0.024913575500249863, 0.004383769817650318, 0.011067744344472885, -0.014897171407938004, -0.01043056882917881, 0.03343898802995682, -0.023613736033439636, 0.03216463699936867, -0.01985439844429493, -0.02595854364335537, 0.005157938692718744, 0.020822906866669655, -0.0013332904782146215, -0.004982715006917715, -0.03565635904669762], metadata={'director': 'Christopher Nolan', 'theme': 'Fiction', 'year': 2010}, excluded_embed_metadata_keys=[], excluded_llm_metadata_keys=[], relationships={}, text='Inception', 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)]"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from llama_index.core.vector_stores import FilterOperator, FilterCondition\n",
    "\n",
    "\n",
    "filters = MetadataFilters(\n",
    "    filters=[\n",
    "        MetadataFilter(key=\"theme\", value=\"Fiction\"),\n",
    "        MetadataFilter(key=\"year\", value=1997, operator=FilterOperator.GT),\n",
    "    ],\n",
    "    condition=FilterCondition.OR,\n",
    ")\n",
    "\n",
    "retriever = index.as_retriever(filters=filters)\n",
    "retriever.retrieve(\"Harry Potter?\")"
   ]
  }
 ],
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