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Merge pull request #998 from vespa-engine/kkraune-patch-1
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kkraune authored Dec 20, 2024
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14 changes: 7 additions & 7 deletions docs/sphinx/source/examples/feed_performance_cloud.ipynb
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"# Feeding to Vespa Cloud\n",
"\n",
"Our [previous notebook](https://pyvespa.readthedocs.io/en/latest/examples/feed_performance.html), we demonstrated one way of benchmarking feed performance to a local Vespa instance running in Docker.\n",
"In this notebook, we will llok at the same methods, but how feeding to [Vespa Cloud](https://cloud.vespa.ai) affects performance of the different methods.\n",
"In this notebook, we will look at the same methods but how feeding to [Vespa Cloud](https://cloud.vespa.ai) affects the performance of the different methods.\n",
"\n",
"The key difference between feeding to a local Vespa instance and a Vespa Cloud instance is the network latency.\n",
"Additionally, we will introduce embedding in Vespa at feed time, which is a realistic scenario for many use-cases.\n",
"Additionally, we will introduce embedding in Vespa at feed time, which is a realistic scenario for many use cases.\n",
"\n",
"We will look at these 3 different methods:\n",
"\n",
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"id": "6f74324a",
"metadata": {},
"source": [
"Follow the instrauctions from the output above and add the control-plane key in the console at `https://console.vespa-cloud.com/tenant/TENANT_NAME/account/keys`\n",
"Follow the instructions from the output above and add the control-plane key in the console at `https://console.vespa-cloud.com/tenant/TENANT_NAME/account/keys`\n",
"(replace TENANT_NAME with your tenant name).\n"
]
},
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"In this example we use [HF Datasets](https://huggingface.co/docs/datasets/index) library to stream the\n",
"[\"Cohere/wikipedia-2023-11-embed-multilingual-v3\"](https://huggingface.co/datasets/Cohere/wikipedia-2023-11-embed-multilingual-v3) dataset and index in our newly deployed Vespa instance.\n",
"\n",
"The dataset contains wikipedia-pages, and their corresponding embeddings.\n",
"The dataset contains Wikipedia-pages, and their corresponding embeddings.\n",
"\n",
"> For this exploration we will use the `id` , `text` and `embedding`-fields\n",
"> For this exploration, we will use the `id`, `text` and `embedding`-fields\n",
"\n",
"The following uses the [stream](https://huggingface.co/docs/datasets/stream) option of datasets to stream the data without\n",
"downloading all the contents locally.\n",
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"id": "e2b68592",
"metadata": {},
"source": [
"## Utility function to create dataset with different number of documents\n"
"## Utility function to create a dataset with different number of documents\n"
]
},
{
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},
"nbformat": 4,
"nbformat_minor": 5
}
}

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