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Colin Jarvis 2023-01-16 07:47:58 -08:00
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6
examples/vector_databases/Using_vector_databases_for_embeddings_search.ipynb
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@ -374,7 +374,7 @@
"source": [
"## Pinecone\n",
"\n",
"Now we'll look to index these embedded documents in a vector database and search them. The first option we'll look at is **Pinecone**, a managed vector database which offers a cloud-native option.\n",
"We'll index these embedded documents in a vector database and search them. The first option we'll look at is **Pinecone**, a managed vector database which offers a cloud-native option.\n",
"\n",
"Before you proceed with this step you'll need to navigate to [Pinecone](pinecone.io), sign up and then save your API key as an environment variable titled ```PINECONE_API_KEY```.\n",
"\n",
@ -686,7 +686,7 @@
"source": [
"### Setup\n",
"\n",
"To get Weaviate running locally we used Docker and followed the instructions contained in this article: https://weaviate.io/developers/weaviate/current/installation/docker-compose.html\n",
"To get Weaviate running locally we used Docker and followed the instructions contained the Weaviate documentation here: https://weaviate.io/developers/weaviate/current/installation/docker-compose.html\n",
"\n",
"For an example docker-compose.yaml file please refer to `./weaviate/docker-compose.yaml` in this repo\n",
"\n",
@ -757,7 +757,7 @@
"\n",
"In this case we'll create a schema called **Article** with the **title** vector from above included for us to search by.\n",
"\n",
"The next few steps closely follow the documents Weaviate provides [here](https://weaviate.io/developers/weaviate/current/tutorials/how-to-use-weaviate-without-modules.htm)"
"The next few steps closely follow the documentation Weaviate provides [here](https://weaviate.io/developers/weaviate/current/tutorials/how-to-use-weaviate-without-modules.htm)"
]
},
{