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Merge pull request #270654 from mrbullwinkle/mrb_03_29_2024_API_updates
[Azure OpenAI] [Bulk update] Increment API versions
2 parents a2946e8 + b6fec93 commit 117e241

18 files changed

+61
-57
lines changed

‎articles/ai-services/openai/concepts/content-filter.md

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@@ -640,7 +640,7 @@ main().catch((err) => {
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$openai = @{
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api_key = $Env:AZURE_OPENAI_API_KEY
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api_base = $Env:AZURE_OPENAI_ENDPOINT # your endpoint should look like the following https://YOUR_RESOURCE_NAME.openai.azure.com/
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api_version = '2023-10-01-preview' # this may change in the future
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api_version = '2024-03-01-preview' # this may change in the future
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name = 'YOUR-DEPLOYMENT-NAME-HERE' #This will correspond to the custom name you chose for your deployment when you deployed a model.
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}
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‎articles/ai-services/openai/how-to/embeddings.md

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@@ -23,7 +23,7 @@ To obtain an embedding vector for a piece of text, we make a request to the embe
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# [console](#tab/console)
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```console
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curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings?api-version=2023-05-15\
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curl https://YOUR_RESOURCE_NAME.openai.azure.com/openai/deployments/YOUR_DEPLOYMENT_NAME/embeddings?api-version=2024-02-01\
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-H 'Content-Type: application/json' \
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-H 'api-key: YOUR_API_KEY' \
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-d '{"input": "Sample Document goes here"}'
@@ -37,7 +37,7 @@ from openai import AzureOpenAI
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client = AzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-05-15",
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api_version = "2024-02-01",
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azure_endpoint =os.getenv("AZURE_OPENAI_ENDPOINT")
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)
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@@ -59,7 +59,7 @@ import openai
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openai.api_type = "azure"
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openai.api_key = YOUR_API_KEY
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openai.api_base = "https://YOUR_RESOURCE_NAME.openai.azure.com"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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response = openai.Embedding.create(
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input="Your text string goes here",
@@ -101,7 +101,7 @@ foreach (float item in returnValue.Value.Data[0].Embedding.ToArray())
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$openai = @{
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api_key = $Env:AZURE_OPENAI_API_KEY
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api_base = $Env:AZURE_OPENAI_ENDPOINT # your endpoint should look like the following https://YOUR_RESOURCE_NAME.openai.azure.com/
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api_version = '2023-05-15' # this may change in the future
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api_version = '2024-02-01' # this may change in the future
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name = 'YOUR-DEPLOYMENT-NAME-HERE' #This will correspond to the custom name you chose for your deployment when you deployed a model.
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}
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‎articles/ai-services/openai/how-to/function-calling.md

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@@ -31,11 +31,13 @@ Parallel function calls are supported with:
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### Supported models
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* `gpt-35-turbo` (1106)
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* `gpt-4` (1106-preview)
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* `gpt-35-turbo` (0125)
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* `gpt-4` (1106-Preview)
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* `gpt-4` (0125-Preview)
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### Supported API versions
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### API support
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* [`2023-12-01-preview`](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview/inference.json)
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Support for parallel function was first added in API version [`2023-12-01-preview`](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview/inference.json)
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Parallel function calls allow you to perform multiple function calls together, allowing for parallel execution and retrieval of results. This reduces the number of calls to the API that need to be made and can improve overall performance.
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@@ -58,7 +60,7 @@ import json
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client = AzureOpenAI(
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-12-01-preview"
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api_version="2024-03-01-preview"
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)
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‎articles/ai-services/openai/how-to/json-mode.md

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@@ -23,12 +23,14 @@ JSON mode is only currently supported with the following models:
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### Supported models
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- `gpt-4-1106-preview` ([region availability](../concepts/models.md#gpt-4-and-gpt-4-turbo-preview-model-availability))
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- `gpt-35-turbo-1106` ([region availability)](../concepts/models.md#gpt-35-turbo-model-availability))
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* `gpt-35-turbo` (1106)
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* `gpt-35-turbo` (0125)
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* `gpt-4` (1106-Preview)
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* `gpt-4` (0125-Preview)
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### API version
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### API support
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- `2023-12-01-preview`
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Support for JSON mode was first added in API version [`2023-12-01-preview`](https://github.com/Azure/azure-rest-api-specs/blob/main/specification/cognitiveservices/data-plane/AzureOpenAI/inference/preview/2023-12-01-preview/inference.json)
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## Example
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client = AzureOpenAI(
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-12-01-preview"
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api_version="2024-03-01-preview"
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)
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response = client.chat.completions.create(
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model="gpt-4-1106-preview", # Model = should match the deployment name you chose for your 1106-preview model deployment
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model="gpt-4-0125-Preview", # Model = should match the deployment name you chose for your 0125-Preview model deployment
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response_format={ "type": "json_object" },
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messages=[
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{"role": "system", "content": "You are a helpful assistant designed to output JSON."},
@@ -74,7 +76,7 @@ because they plan to use the output for further scripting.
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$openai = @{
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api_key = $Env:AZURE_OPENAI_API_KEY
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api_base = $Env:AZURE_OPENAI_ENDPOINT # like the following https://YOUR_RESOURCE_NAME.openai.azure.com/
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api_version = '2023-12-01-preview' # may change in the future
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api_version = '2024-03-01-preview' # may change in the future
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name = 'YOUR-DEPLOYMENT-NAME-HERE' # name you chose for your deployment
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}
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‎articles/ai-services/openai/how-to/migration.md

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@@ -70,7 +70,7 @@ from openai import AzureOpenAI
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client = AzureOpenAI(
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-05-15"
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api_version="2024-02-01"
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)
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response = client.chat.completions.create(
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openai.api_type = "azure"
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT")
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openai.api_key = os.getenv("AZURE_OPENAI_API_KEY")
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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response = openai.ChatCompletion.create(
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engine="gpt-35-turbo", # engine = "deployment_name".
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client = AzureOpenAI(
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-12-01-preview",
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api_version="2024-02-01",
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
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)
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openai.api_key = os.getenv("AZURE_OPENAI_API_KEY")
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") # your endpoint should look like the following https://YOUR_RESOURCE_NAME.openai.azure.com/
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openai.api_type = 'azure'
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openai.api_version = '2023-05-15' # this might change in the future
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openai.api_version = '2024-02-01' # this might change in the future
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deployment_name='REPLACE_WITH_YOUR_DEPLOYMENT_NAME' #This will correspond to the custom name you chose for your deployment when you deployed a model.
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client = AzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-05-15",
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api_version = "2024-02-01",
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azure_endpoint =os.getenv("AZURE_OPENAI_ENDPOINT")
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)
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openai.api_type = "azure"
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openai.api_key = YOUR_API_KEY
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openai.api_base = "https://YOUR_RESOURCE_NAME.openai.azure.com"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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response = openai.Embedding.create(
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input="Your text string goes here",
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async def main():
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client = AsyncAzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-12-01-preview",
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api_version = "2024-02-01",
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
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)
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response = await client.chat.completions.create(model="gpt-35-turbo", messages=[{"role": "user", "content": "Hello world"}])
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token_provider = get_bearer_token_provider(DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default")
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api_version = "2023-12-01-preview"
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api_version = "2024-02-01"
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endpoint = "https://my-resource.openai.azure.com"
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client = AzureOpenAI(

‎articles/ai-services/openai/how-to/provisioned-get-started.md

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@@ -79,7 +79,7 @@ The inferencing code for provisioned deployments is the same a standard deployme
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client = AzureOpenAI(
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-05-15"
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api_version="2024-02-01"
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response = client.chat.completions.create(
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client = AzureOpenAI(
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
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api_key=os.getenv("AZURE_OPENAI_API_KEY"),
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api_version="2023-05-15",
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api_version="2024-02-01",
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max_retries=5,# default is 2
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)
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‎articles/ai-services/openai/how-to/use-blocklists.md

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@@ -47,7 +47,7 @@ Copy the cURL command below to a text editor and make the following changes:
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1. Optionally replace the value of the "description" field with a custom description.
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```bash
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curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiBlocklists/{raiBlocklistName}?api-version=2023-10-01-preview' \
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curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiBlocklists/{raiBlocklistName}?api-version=2024-03-01-preview' \
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--header 'Authorization: Bearer {token}' \
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--header 'Content-Type: application/json' \
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--data-raw '{
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1. Replace "raiBlocklistName" in the body with a custom name for your list. Allowed characters: `0-9, A-Z, a-z, - . _ ~`.
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```bash
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curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiPolicies/{raiPolicyName}?api-version=2023-10-01-preview' \
76+
curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiPolicies/{raiPolicyName}?api-version=2024-03-01-preview' \
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--header 'Authorization: Bearer {token}' \
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--header 'Content-Type: application/json' \
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--data-raw '{
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1. Replace the value of the `"blocking pattern"` field with the item you'd like to add to your blocklist. The maximum length of a blockItem is 1000 characters. Also specify whether the pattern is regex or exact match.
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```bash
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curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiBlocklists/{raiBlocklistName}/raiBlocklistItems/{raiBlocklistItemName}?api-version=2023-10-01-preview' \
106+
curl --location --request PUT 'https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/raiBlocklists/{raiBlocklistName}/raiBlocklistItems/{raiBlocklistItemName}?api-version=2024-03-01-preview' \
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--header 'Authorization: Bearer {token}' \
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--header 'Content-Type: application/json' \
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--data-raw '{

‎articles/ai-services/openai/includes/chat-completion.md

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client = AzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-05-15",
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api_version = "2024-02-01",
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
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)
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import os
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import openai
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openai.api_type = "azure"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") # Your Azure OpenAI resource's endpoint value.
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openai.api_key = os.getenv("AZURE_OPENAI_API_KEY")
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client = AzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-05-15",
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api_version = "2024-02-01",
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") # Your Azure OpenAI resource's endpoint value.
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)
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340340
import os
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import openai
342342
openai.api_type = "azure"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") # Your Azure OpenAI resource's endpoint value.
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openai.api_key = os.getenv("AZURE_OPENAI_API_KEY")
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client = AzureOpenAI(
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api_key = os.getenv("AZURE_OPENAI_API_KEY"),
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api_version = "2023-05-15",
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api_version = "2024-02-01",
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azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") # Your Azure OpenAI resource's endpoint value.
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)
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import os
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openai.api_type = "azure"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") # Your Azure OpenAI resource's endpoint value.
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openai.api_key = os.getenv("AZURE_OPENAI_API_KEY")
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‎articles/ai-services/openai/includes/chat-markup-language.md

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import openai
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openai.api_type = "azure"
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openai.api_base = "https://{your-resource-name}.openai.azure.com/"
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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openai.api_key = os.getenv("OPENAI_API_KEY")
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response = openai.Completion.create(
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import openai
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openai.api_type = "azure"
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openai.api_base = "https://{your-resource-name}.openai.azure.com/" #This corresponds to your Azure OpenAI resource's endpoint value
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openai.api_version = "2023-05-15"
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openai.api_version = "2024-02-01"
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openai.api_key = os.getenv("OPENAI_API_KEY")
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# defining a function to create the prompt from the system message and the conversation messages

‎articles/ai-services/openai/includes/chatgpt-powershell.md

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$openai = @{
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api_key = $Env:AZURE_OPENAI_API_KEY
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api_base = $Env:AZURE_OPENAI_ENDPOINT # your endpoint should look like the following https://YOUR_RESOURCE_NAME.openai.azure.com/
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api_version = '2023-05-15' # this may change in the future
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api_version = '2024-02-01' # this may change in the future
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name = 'YOUR-DEPLOYMENT-NAME-HERE' #This will correspond to the custom name you chose for your deployment when you deployed a model.
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}
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