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Update embeddings notebook

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* Update api_version to 2022-12-01
* Fix some texts
This commit is contained in:
Christian Muertz 2022-12-16 11:48:32 +01:00
parent 838f000935
commit 7165609030
1 changed files with 15 additions and 9 deletions
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24
examples/azure/embeddings.ipynb
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@ -6,7 +6,7 @@
"source": [
"# Azure embeddings example\n",
"In this example we'll try to go over all operations for embeddings that can be done using the Azure endpoints. \\\n",
"This example focuses on finetuning but touches on the majority of operations that are also available using the API. This example is meant to be a quick way of showing simple operations and is not meant as a tutorial."
"This example focuses on embeddings but also touches on the some other operations that are also available using the API. This example is meant to be a quick way of showing simple operations and is not meant as a tutorial."
]
},
{
@ -38,7 +38,7 @@
"openai.api_base = '' # Please add your endpoint here\n",
"\n",
"openai.api_type = 'azure'\n",
"openai.api_version = '2022-03-01-preview' # this may change in the future"
"openai.api_version = '2022-12-01' # this may change in the future"
]
},
{
@ -46,7 +46,7 @@
"metadata": {},
"source": [
"## Deployments\n",
"In this section we are going to create a deployment using the finetune model that we just adapted and then used the deployment to create a simple completion operation."
"In this section we are going to create a deployment that we can use to create embeddings."
]
},
{
@ -54,7 +54,7 @@
"metadata": {},
"source": [
"### Deployments: Create Manually\n",
"Let's create a deployment using the text-similarity-curie-001 engine. You can create a new deployment by going to your Resource in your portal under \"Resource Management\" -> \"Deployments\"."
"Let's create a deployment using the `text-similarity-curie-001` engine. Create a new deployment by going to your Resource in your portal under \"Resource Management\" -> \"Deployments\"."
]
},
{
@ -113,18 +113,24 @@
"metadata": {},
"outputs": [],
"source": [
"print('While deployment running, selecting a completed one.')\n",
"print('While deployment running, selecting a completed one that supports embeddings.')\n",
"deployment_id = None\n",
"result = openai.Deployment.list()\n",
"for deployment in result.data:\n",
" if deployment[\"status\"] == \"succeeded\":\n",
" deployment_id = deployment[\"id\"]\n",
" break\n",
" if deployment[\"status\"] != \"succeeded\":\n",
" continue\n",
" \n",
" model = openai.Model.retrieve(deployment[\"model\"])\n",
" if model[\"capabilities\"][\"embeddings\"] != True:\n",
" continue\n",
" \n",
" deployment_id = deployment[\"id\"]\n",
" break\n",
"\n",
"if not deployment_id:\n",
" print('No deployment with status: succeeded found.')\n",
"else:\n",
" print(f'Found a successful deployment with id: {deployment_id}.')"
" print(f'Found a succeeded deployment that supports embeddings with id: {deployment_id}.')"
]
},
{