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‎articles/ai-services/openai/how-to/migration.md

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ms.service: azure-ai-openai
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ms.custom:
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ms.topic: how-to
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ms.date: 11/09/2023
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ms.date: 11/10/2023
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manager: nitinme
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---
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# Migrating to the OpenAI Python API library 1.x
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OpenAI has just released a new version of the [OpenAI Python API library](https://github.com/openai/openai-python/). This guide is supplemental to [OpenAI's migration guide](https://github.com/openai/openai-python/discussions/631) and will help bring you up to speed on the changes specific to Azure OpenAI.
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OpenAI has just released a new version of the [OpenAI Python API library](https://github.com/openai/openai-python/). This guide is supplemental to [OpenAI's migration guide](https://github.com/openai/openai-python/discussions/742) and will help bring you up to speed on the changes specific to Azure OpenAI.
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## Updates
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‎articles/ai-services/openai/includes/use-your-data-python.md

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1. Create a new folder named *openai-python* for your project and a new Python code file named *main.py*. Change into that directory:
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```cmd
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mkdir openai-python
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cd openai-python
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```
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1. Install the following Python Libraries:
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# [OpenAI Python 0.28.1](#tab/python)
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```console
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pip install openai==0.28.1
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pip install python-dotenv
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```
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# [OpenAI Python 1.x](#tab/python-new)
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```console
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pip install openai
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pip install python-dotenv
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```
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```cmd
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mkdir openai-python
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cd openai-python
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```
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2. Install the following Python Libraries:
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---
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# [OpenAI Python 0.28.1](#tab/python)
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```console
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pip install openai==0.28.1
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pip install python-dotenv
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```
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# [OpenAI Python 1.x](#tab/python-new)
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```console
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pip install openai
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pip install python-dotenv
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```
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---
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## Create the Python app
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1. From the project directory, open the *main.py* file and add the following code:
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# [OpenAI Python 0.28.1](#tab/python)
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```python
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import os
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import openai
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import dotenv
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import requests
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dotenv.load_dotenv()
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openai.api_base = os.environ.get("AOAIEndpoint")
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# Azure OpenAI on your own data is only supported by the 2023-08-01-preview API version
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openai.api_version = "2023-08-01-preview"
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openai.api_type = 'azure'
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openai.api_key = os.environ.get("AOAIKey")
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def setup_byod(deployment_id: str) -> None:
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"""Sets up the OpenAI Python SDK to use your own data for the chat endpoint.
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# [OpenAI Python 0.28.1](#tab/python)
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:param deployment_id: The deployment ID for the model to use with your own data.
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To remove this configuration, simply set openai.requestssession to None.
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"""
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class BringYourOwnDataAdapter(requests.adapters.HTTPAdapter):
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def send(self, request, **kwargs):
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request.url = f"{openai.api_base}/openai/deployments/{deployment_id}/extensions/chat/completions?api-version={openai.api_version}"
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return super().send(request, **kwargs)
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session = requests.Session()
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# Mount a custom adapter which will use the extensions endpoint for any call using the given `deployment_id`
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session.mount(
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prefix=f"{openai.api_base}/openai/deployments/{deployment_id}",
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adapter=BringYourOwnDataAdapter()
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)
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openai.requestssession = session
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aoai_deployment_id = os.environ.get("AOAIDeploymentId")
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setup_byod(aoai_deployment_id)
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completion = openai.ChatCompletion.create(
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messages=[{"role": "user", "content": "What are the differences between Azure Machine Learning and Azure AI services?"}],
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deployment_id=os.environ.get("AOAIDeploymentId"),
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dataSources=[ # camelCase is intentional, as this is the format the API expects
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{
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"type": "AzureCognitiveSearch",
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"parameters": {
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"endpoint": os.environ.get("SearchEndpoint"),
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"key": os.environ.get("SearchKey"),
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"indexName": os.environ.get("SearchIndex"),
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```python
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import os
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import openai
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import dotenv
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import requests
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dotenv.load_dotenv()
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openai.api_base = os.environ.get("AOAIEndpoint")
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# Azure OpenAI on your own data is only supported by the 2023-08-01-preview API version
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openai.api_version = "2023-08-01-preview"
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openai.api_type = 'azure'
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openai.api_key = os.environ.get("AOAIKey")
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def setup_byod(deployment_id: str) -> None:
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"""Sets up the OpenAI Python SDK to use your own data for the chat endpoint.
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:param deployment_id: The deployment ID for the model to use with your own data.
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To remove this configuration, simply set openai.requestssession to None.
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"""
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class BringYourOwnDataAdapter(requests.adapters.HTTPAdapter):
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def send(self, request, **kwargs):
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request.url = f"{openai.api_base}/openai/deployments/{deployment_id}/extensions/chat/completions?api-version={openai.api_version}"
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return super().send(request, **kwargs)
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session = requests.Session()
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# Mount a custom adapter which will use the extensions endpoint for any call using the given `deployment_id`
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session.mount(
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prefix=f"{openai.api_base}/openai/deployments/{deployment_id}",
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adapter=BringYourOwnDataAdapter()
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)
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openai.requestssession = session
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aoai_deployment_id = os.environ.get("AOAIDeploymentId")
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setup_byod(aoai_deployment_id)
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completion = openai.ChatCompletion.create(
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messages=[{"role": "user", "content": "What are the differences between Azure Machine Learning and Azure AI services?"}],
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deployment_id=os.environ.get("AOAIDeploymentId"),
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dataSources=[ # camelCase is intentional, as this is the format the API expects
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{
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"type": "AzureCognitiveSearch",
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"parameters": {
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"endpoint": os.environ.get("SearchEndpoint"),
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"key": os.environ.get("SearchKey"),
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"indexName": os.environ.get("SearchIndex"),
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}
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}
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}
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]
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)
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print(completion)
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```
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]
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)
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print(completion)
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```
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# [OpenAI Python 1.x](#tab/python-new)
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```python
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import os
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import openai
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import dotenv
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dotenv.load_dotenv()
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endpoint = os.environ.get("AOAIEndpoint")
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api_key = os.environ.get("AOAIKey")
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deployment = os.environ.get("AOAIDeploymentId")
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client = openai.AzureOpenAI(
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base_url=f"{endpoint}/openai/deployments/{deployment}/extensions",
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api_key=api_key,
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api_version="2023-08-01-preview",
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)
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completion = client.chat.completions.create(
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model=deployment,
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messages=[
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{
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"role": "user",
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"content": "How is Azure machine learning different than Azure OpenAI?",
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},
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],
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extra_body={
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"dataSources": [
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```python
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import os
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import openai
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import dotenv
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dotenv.load_dotenv()
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endpoint = os.environ.get("AOAIEndpoint")
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api_key = os.environ.get("AOAIKey")
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deployment = os.environ.get("AOAIDeploymentId")
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client = openai.AzureOpenAI(
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base_url=f"{endpoint}/openai/deployments/{deployment}/extensions",
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api_key=api_key,
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api_version="2023-08-01-preview",
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)
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completion = client.chat.completions.create(
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model=deployment,
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messages=[
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{
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"type": "AzureCognitiveSearch",
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"parameters": {
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"endpoint": os.environ["SearchEndpoint"],
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"key": os.environ["SearchKey"],
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"indexName": os.environ["SearchIndex"]
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"role": "user",
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"content": "How is Azure machine learning different than Azure OpenAI?",
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},
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],
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extra_body={
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"dataSources": [
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{
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"type": "AzureCognitiveSearch",
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"parameters": {
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"endpoint": os.environ["SearchEndpoint"],
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"key": os.environ["SearchKey"],
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"indexName": os.environ["SearchIndex"]
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}
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}
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}
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]
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}
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)
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print(completion.model_dump_json(indent=2))
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```
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---
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]
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}
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)
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print(completion.model_dump_json(indent=2))
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```
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---
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> [!IMPORTANT]
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> For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](../../../key-vault/general/overview.md). For more information about credential security, see the Azure AI services [security](../../security-features.md) article.
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1. Execute the following command:
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2. Execute the following command:
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```cmd
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python main.py

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