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update for redisvl 0.4.0
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-3614
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‎python-recipes/RAG/01_redisvl.ipynb‎

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‎python-recipes/RAG/02_langchain.ipynb‎

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‎python-recipes/RAG/03_llamaindex.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"%pip install -q llama-index llama-index-vector-stores-redis llama-index-embeddings-cohere llama-index-embeddings-openai"
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"%pip install -q llama-index \"llama-index-vector-stores-redis>=0.4.0\" llama-index-embeddings-cohere llama-index-embeddings-openai"
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]
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"cell_type": "code",
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@@ -171,7 +163,7 @@
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {
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"colab": {
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"base_uri": "https://localhost:8080/"
@@ -184,13 +176,8 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Sample doc Doc ID: c013353e-dae7-4d17-befd-9e784c8acf79\n",
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"Text: UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington,\n",
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"D.C. 20549 FORM 10-K (Mark One) ☒ ANNUAL REPORT PURSUANT T O SECTION\n",
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"13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year\n",
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"ended September 24, 2022 or ☐ TRANSITION REPORT PURSUANT T O SECTION\n",
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"13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition\n",
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"period...\n"
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"Sample doc Doc ID: b90e8ae9-7204-4e86-87ff-16cc68f9fff4\n",
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"Text: 2022 COLORADO\n"
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]
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}
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],
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},
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"cell_type": "code",
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"execution_count": 5,
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},
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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},
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"text": [
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"Node ID: d2e6cd9c-0716-49d8-8563-407a00d05445\n",
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"Text: Table of Contents FISCAL 2023 NIKE BRAND REVENUE HIGHLIGHTS The\n",
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"Node ID: 023a5d47-4560-4591-ab20-37e4522863aa\n",
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"Text: Table of Contents FISCAL 2023 NIKE BRAND REVENUE HIGHLIGHTSThe\n",
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"following tables present NIKE Brand revenues disaggregated by\n",
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"reportable operating segment, distribution channel and major product\n",
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"line: FISCAL 2023 COMPARED TO FISCAL 2022 •NIKE, Inc. Revenues were\n",
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"line: FISCAL 2023 COMPARED TO FISCAL 2022 • NIKE, Inc. Revenues were\n",
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"$51.2 billion in fiscal 2023, which increased 10% and 16% compared to\n",
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"fiscal 2022 on...\n",
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"Score: 0.900\n",
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"Score: 0.899\n",
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"\n",
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"Node ID: 28542d3b-b345-4e9e-b675-f62361ec85d9\n",
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"Text: Table of Contents NORTH AMERICA (Dollars in millions) FISCAL\n",
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"2023FISCAL 2022 % CHANGE% CHANGE EXCLUDING CURRENCY CHANGESFISCAL 2021\n",
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"% CHANGE% CHANGE EXCLUDING CURRENCY CHANGES Revenues by: Footwear $\n",
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"14,897 $ 12,228 22 % 22 %$ 11,644 5 % 5 % Apparel 5,947 5,492 8 % 9 %\n",
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"5,028 9 % 9 % Equipment 764 633 21 % 21 % 507 25 % 25 % TOTAL REVENUES\n",
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"$ 21,6...\n",
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"Score: 0.885\n",
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"Node ID: 10b3b6b1-112c-4279-a75a-d4d866c07f6b\n",
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"Text: Sales through NIKE Direct Global Brand Divisions in FISCAL 2023\n",
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"amounted to $21,308 million. Total NIKE Brand Wholesale Equivalent\n",
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"Revenues for FISCAL 2023 were $48,763 million, with a 10% rise from\n",
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"FISCAL 2022. NIKE Brand Wholesale Equivalent Revenues included sales\n",
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"from Men's, Women's, and NIKE Kids' categories. Jordan Brand revenues\n",
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"increased...\n",
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"Score: 0.883\n",
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"\n"
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]
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}
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},
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"cell_type": "code",
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"\"NIKE's revenue in fiscal 23 was $51.2 billion.\""
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]
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{
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"IndexInfo(name='custom_index', prefix='docs', key_separator=':', storage_type=<StorageType.HASH: 'hash'>)"
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]
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{
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" 'vector': HNSWVectorField(name='vector', type='vector', path=None, attrs=HNSWVectorFieldAttributes(dims=1536, algorithm=<VectorIndexAlgorithm.HNSW: 'HNSW'>, datatype=<VectorDataType.FLOAT32: 'FLOAT32'>, distance_metric=<VectorDistanceMetric.COSINE: 'COSINE'>, initial_cap=None, m=16, ef_construction=200, ef_runtime=10, epsilon=0.01))}"
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"cell_type": "code",
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"metadata": {},
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"source": [
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"# from datetime import datetime\n",
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"\n",
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"\n",
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"# def date_to_timestamp(date_string: str) -> int:\n",
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"# date_format: str = \"%Y-%m-%d\"\n",
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"# return int(datetime.strptime(date_string, date_format).timestamp())\n",
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"\n",
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"\n",
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"# # iterate through documents and add new field\n",
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"# for document in docs:\n",
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"# document.metadata[\"updated_at\"] = date_to_timestamp(\n",
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"# document.metadata[\"last_modified_date\"]\n",
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"# )"
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]
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},
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"metadata": {},
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"text": [
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"Node ID: cd0c5d8f-e3b1-4cbb-aa6a-5960003cdb2d\n",
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"Node ID: 013f339e-7fda-4fc7-baf0-afbb3dadf47d\n",
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"Text: Table of Contents valuation. In the ordinary course of our\n",
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"business, there are many transactions and calculations for which the\n",
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"ultimate tax determination is uncertain. Significant judgment is\n",
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"required in evaluating and estimating our tax expense, assets, and\n",
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"liabilities. We are also subject to tax controversies in various\n",
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"jurisdictions that can...\n",
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"Score: 0.746\n",
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"Score: 0.747\n",
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"\n",
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"Node ID: 6745f668-4c7a-43bf-a9c3-9b04e1a497f8\n",
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"Node ID: ac3f2b03-0520-4a50-ba3e-a97ad0a6f643\n",
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"Text: Table of Contents Included in other income (expense), net in\n",
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"2021 and 2022 is a marketable equity securities valuation gain (loss)\n",
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"of $11.8 billion and $(12.7) billion from our equity investment in\n",
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"observable changes in ...\n",
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"Score: 0.740\n",
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"\n",
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"Node ID: 717666fe-fea5-488b-999c-84e6d8b9a0db\n",
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"Node ID: 62ef1673-dcfe-4ba0-a437-7b142cda4114\n",
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"Text: Exhibit 31.1 CERTIFICATIONS I, Andrew R. Jassy, certify that: 1.\n",
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"I have reviewed this Form 10-K of Amazon.com, Inc.; 2. Based on my\n",
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"knowledge, this report does not contain any untrue statement of a\n",

‎python-recipes/RAG/04_advanced_redisvl.ipynb‎

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}
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],
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"source": [
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"%pip install -q redis redisvl pandas \"unstructured[pdf]\" sentence-transformers langchain langchain-community \"openai>=1.57.0\" tqdm"
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"%pip install -q \"redisvl>=0.4.1\" pandas \"unstructured[pdf]\" sentence-transformers langchain langchain-community \"openai>=1.57.0\" tqdm"
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"source": [
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"from redis import Redis\n",
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"source": [
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"# connect to redis\n",
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"client = Redis.from_url(REDIS_URL)\n",
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"\n",
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"# create an index from schema and the client\n",
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"index = SearchIndex.from_dict(schema)\n",
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"index.set_client(client)\n",
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"index = SearchIndex.from_dict(schema, redis_url=REDIS_URL)\n",
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'schema' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mredisvl\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mindex\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m AsyncSearchIndex\n\u001b[0;32m----> 3\u001b[0m index \u001b[38;5;241m=\u001b[39m AsyncSearchIndex\u001b[38;5;241m.\u001b[39mfrom_dict(\u001b[43mschema\u001b[49m, redis_url\u001b[38;5;241m=\u001b[39mREDIS_URL)\n",
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"\u001b[0;31mNameError\u001b[0m: name 'schema' is not defined"
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]
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}
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],
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"source": [
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"from redis.asyncio import Redis as AsyncRedis\n",
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"from redisvl.index import AsyncSearchIndex\n",
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"\n",
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"client = AsyncRedis.from_url(REDIS_URL)\n",
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"index = AsyncSearchIndex.from_dict(schema)\n",
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"_ = await index.set_client(client)"
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"index = AsyncSearchIndex.from_dict(schema, redis_url=REDIS_URL)"
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]
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},
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{

‎python-recipes/RAG/05_nvidia_ai_rag_redis.ipynb‎

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"source": [
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"%pip install --upgrade -q langchain-core langchain-community langchain-nvidia-ai-endpoints\n",
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"%pip install -q \"unstructured[pdf]\" sentence-transformers\n",
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"%pip install -q redisvl>=0.3.0"
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"%pip install -q \"redisvl>=0.4.1\""
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{
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"name": "python3"
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"language_info": {
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"name": "python"
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"name": "python",
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"version": "3.11.9"
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}
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},
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"nbformat": 4,

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