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Adding finetuning samples and tests #43749

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ec4bcd2
Adding ft samples and tests
Oct 31, 2025
fe53830
formating the operations
Nov 4, 2025
21ff72c
Adding oss files and test cases
Nov 4, 2025
daa1e16
applying black
Nov 4, 2025
546c270
Merge branch 'feature/azure-ai-projects/2.0.0b1' into jatanna/ft_v1
Nov 5, 2025
ee2f384
correcting comments
Nov 6, 2025
55d5ebe
adding end to end scenarios
Nov 6, 2025
2a9c272
Adding comments
Nov 6, 2025
ec53357
Adding deployment and inferecing test cases
Nov 7, 2025
8e1e744
resolving review comments
Nov 7, 2025
738848e
applying black and updating readme.md file
Nov 7, 2025
239d968
resolving mypy errors
Nov 7, 2025
b1a929c
merging with base branch
Nov 7, 2025
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11 changes: 7 additions & 4 deletions sdk/ai/azure-ai-projects/.env.template
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Expand Up @@ -37,10 +37,13 @@ AZURE_AI_PROJECTS_TESTS_CONTAINER_PROJECT_ENDPOINT=
AZURE_AI_PROJECTS_TESTS_CONTAINER_APP_RESOURCE_ID=
AZURE_AI_PROJECTS_TESTS_CONTAINER_INGRESS_SUBDOMAIN_SUFFIX=

# Used in fine-tuning deployment and inferencing tests
AZURE_AI_PROJECTS_TESTS_AZURE_SUBSCRIPTION_ID=
AZURE_AI_PROJECTS_TESTS_AZURE_RESOURCE_GROUP=
AZURE_AI_PROJECTS_TESTS_AZURE_AOAI_ACCOUNT=
# Used in fine-tuning job submission, deployment and inferencing
AZURE_AI_PROJECTS_AZURE_SUBSCRIPTION_ID=
AZURE_AI_PROJECTS_AZURE_RESOURCE_GROUP=
AZURE_AI_PROJECTS_AZURE_AOAI_ACCOUNT=
VALIDATION_FILE_PATH=
TRAINING_FILE_PATH=
MODEL_NAME=



4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/samples/files/sample_files.py
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Expand Up @@ -14,10 +14,10 @@
Before running the sample:
pip install azure-ai-projects azure-identity openai python-dotenv
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv
Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) FILE_PATH - Optional. Path to the file to upload. Defaults to the `data` folder.
"""
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4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/samples/files/sample_files_async.py
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Expand Up @@ -14,10 +14,10 @@
Before running the sample:
pip install azure-ai-projects azure-identity openai python-dotenv aiohttp
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv aiohttp
Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) FILE_PATH - Optional. Path to the file to upload. Defaults to the `data` folder.
"""
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8 changes: 4 additions & 4 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_dpo_job.py
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Expand Up @@ -8,17 +8,17 @@
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the synchronous
`.fine_tuning_jobs` methods to create DPO (Direct Preference Optimization) fine-tuning jobs.
Supported OAI Models: GPT 4o, 4.1, 4.1-mini, 4.1-nano, gpt-4o-mini
Supported OpenAI models: GPT-4o, GPT-4.1, GPT-4.1-mini, GPT-4.1-nano, and GPT-4o-mini.

USAGE:
python sample_finetuning_dpo_job.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `gpt-4o` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -33,7 +33,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "gpt-4o-mini")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "dpo_training_set.jsonl"))
Expand Down
8 changes: 4 additions & 4 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_dpo_job_async.py
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Expand Up @@ -8,17 +8,17 @@
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the asynchronous
`.fine_tuning_jobs` methods to create DPO (Direct Preference Optimization) fine-tuning jobs.
Supported OAI Models: GPT 4o, 4.1, 4.1-mini, 4.1-nano, gpt-4o-mini
Supported OpenAI models: GPT-4o, GPT-4.1, GPT-4.1-mini, GPT-4.1-nano, and GPT-4o-mini.

USAGE:
python sample_finetuning_dpo_job_async.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv aiohttp
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv aiohttp

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `gpt-4o` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -34,7 +34,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "gpt-4o-mini")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "dpo_training_set.jsonl"))
Expand Down
12 changes: 6 additions & 6 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_oss_models_supervised_job.py
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Expand Up @@ -7,18 +7,18 @@
"""
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the synchronous
`.fine_tuning.jobs` methods to create supervised fine-tuning jobs using OSS model.
Supported OSS models with SFT technique: Ministral-3b , Llama-3.3-70b , Qwen3-32b , Gpt-oss-20b
`.fine_tuning.jobs` methods to create supervised fine-tuning jobs using open-source model.
Supported open-source models with SFT: Ministral-3b , Llama-3.3-70b , Qwen3-32b , Gpt-oss-20b

USAGE:
python sample_finetuning_supervised_job.py
python sample_finetuning_oss_models_supervised_job.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `gpt-4.1` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -33,7 +33,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "Ministral-3B")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "sft_training_set.jsonl"))
Expand Down
10 changes: 5 additions & 5 deletions ...azure-ai-projects/samples/finetuning/sample_finetuning_oss_models_supervised_job_async.py
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Expand Up @@ -7,18 +7,18 @@
"""
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the asynchronous
`.fine_tuning.jobs` methods to create supervised fine-tuning jobs using OSS model.
Supported OSS models with SFT technique: Ministral-3b , Llama-3.3-70b , Qwen3-32b , Gpt-oss-20b
`.fine_tuning.jobs` methods to create supervised fine-tuning jobs using open-source model.
Supported open-source models with SFT: Ministral-3b , Llama-3.3-70b , Qwen3-32b , Gpt-oss-20b

USAGE:
python sample_finetuning_oss_models_supervised_job_async.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv aiohttp
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv aiohttp

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `Ministral-3B` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -34,7 +34,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "Ministral-3B")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "sft_training_set.jsonl"))
Expand Down
8 changes: 4 additions & 4 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_reinforcement_job.py
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Expand Up @@ -8,17 +8,17 @@
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the synchronous
`.fine_tuning.jobs` methods to create reinforcement fine-tuning jobs.
Supported OAI Models: o4-mini
Supported OpenAI models: o4-mini

USAGE:
python sample_finetuning_reinforcement_job.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `o4-mini` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -33,7 +33,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "o4-mini")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "rft_training_set.jsonl"))
Expand Down
8 changes: 4 additions & 4 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_reinforcement_job_async.py
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Expand Up @@ -8,17 +8,17 @@
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the asynchronous
`.fine_tuning.jobs` methods to create reinforcement fine-tuning jobs.
Supported OAI Models: o4-mini
Supported OpenAI models: o4-mini

USAGE:
python sample_finetuning_reinforcement_job_async.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv aiohttp
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv aiohttp

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `o4-mini` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
Expand All @@ -34,7 +34,7 @@

load_dotenv()

endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "o4-mini")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "rft_training_set.jsonl"))
Expand Down
26 changes: 14 additions & 12 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_supervised_job.py
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Expand Up @@ -7,26 +7,28 @@
"""
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the synchronous
`.fine_tuning.jobs` methods to create, get, list, cancel, pause, resume, list events and list checkpoints supervised fine-tuning jobs.
It also shows how to deploy the fine-tuned model using Azure Cognitive Services Management Client and perform inference on the deployed model.
Supported OAI Models: GPT 4o, 4o-mini, 4.1, 4.1-mini
`.fine_tuning.jobs` methods to create, get, list, cancel, pause, resume, list events
and list checkpoints supervised fine-tuning jobs.
It also shows how to deploy the fine-tuned model using Azure Cognitive Services Management
Client and perform inference on the deployed model.
Supported OpenAI models: GPT 4o, 4o-mini, 4.1, 4.1-mini

USAGE:
python sample_finetuning_supervised_job.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv azure-mgmt-cognitiveservices
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv azure-mgmt-cognitiveservices

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `gpt-4.1` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
4) VALIDATION_FILE_PATH - Optional. Path to the validation data file. Default to the `data` folder.
5) AZURE_SUBSCRIPTION_ID - Required. Your Azure subscription ID for fine-tuned model deployment and inferencing.
6) AZURE_RESOURCE_GROUP - Required. The resource group name containing your Azure OpenAI resource.
7) AZURE_AOAI_ACCOUNT - Required. The name of your Azure OpenAI account for fine-tuned model deployment and inferencing.
5) AZURE_AI_PROJECTS_AZURE_SUBSCRIPTION_ID - Required. Your Azure subscription ID for fine-tuned model deployment and inferencing.
6) AZURE_AI_PROJECTS_AZURE_RESOURCE_GROUP - Required. The resource group name containing your Azure OpenAI resource.
7) AZURE_AI_PROJECTS_AZURE_AOAI_ACCOUNT - Required. The name of your Azure OpenAI account for fine-tuned model deployment and inferencing.
"""

import os
Expand All @@ -41,7 +43,7 @@
load_dotenv()

# For fine-tuning
endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "gpt-4.1")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "sft_training_set.jsonl"))
Expand All @@ -50,9 +52,9 @@
)

# For Deployment and inferencing on model
subscription_id = os.environ.get("AZURE_SUBSCRIPTION_ID")
resource_group = os.environ.get("AZURE_RESOURCE_GROUP")
account_name = os.environ.get("AZURE_AOAI_ACCOUNT")
subscription_id = os.environ.get("AZURE_AI_PROJECTS_AZURE_SUBSCRIPTION_ID")
resource_group = os.environ.get("AZURE_AI_PROJECTS_AZURE_RESOURCE_GROUP")
account_name = os.environ.get("AZURE_AI_PROJECTS_AZURE_AOAI_ACCOUNT")

with DefaultAzureCredential(exclude_interactive_browser_credential=False) as credential:

Expand Down
26 changes: 14 additions & 12 deletions sdk/ai/azure-ai-projects/samples/finetuning/sample_finetuning_supervised_job_async.py
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Expand Up @@ -7,26 +7,28 @@
"""
DESCRIPTION:
Given an AIProjectClient, this sample demonstrates how to use the asynchronous
.fine_tuning.jobs methods to create, get, list, cancel, pause, resume, list events and list checkpoints supervised fine-tuning jobs.
It also shows how to deploy the fine-tuned model using Azure Cognitive Services Management Client and perform inference on the deployed model.
Supported OAI Models: GPT 4o, 4o-mini, 4.1, 4.1-mini
.fine_tuning.jobs methods to create, get, list, cancel, pause, resume, list events
and list checkpoints supervised fine-tuning jobs.
It also shows how to deploy the fine-tuned model using Azure Cognitive Services Management
Client and perform inference on the deployed model.
Supported OpenAI models: GPT 4o, 4o-mini, 4.1, 4.1-mini

USAGE:
python sample_finetuning_supervised_job_async.py

Before running the sample:

pip install azure-ai-projects azure-identity openai python-dotenv aiohttp azure-mgmt-cognitiveservices
pip install azure-ai-projects>=2.0.0b1 azure-identity openai python-dotenv aiohttp azure-mgmt-cognitiveservices

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
Azure AI Foundry project.
2) MODEL_NAME - Optional. The base model name to use for fine-tuning. Default to the `gpt-4.1` model.
3) TRAINING_FILE_PATH - Optional. Path to the training data file. Default to the `data` folder.
4) VALIDATION_FILE_PATH - Optional. Path to the validation data file. Default to the `data` folder.
5) AZURE_SUBSCRIPTION_ID - Required. Your Azure subscription ID for fine-tuned model deployment and inferencing.
6) AZURE_RESOURCE_GROUP - Required. The resource group name containing your Azure OpenAI resource.
7) AZURE_AOAI_ACCOUNT - Required. The name of your Azure OpenAI account for fine-tuned model deployment and inferencing.
5) AZURE_AI_PROJECTS_AZURE_SUBSCRIPTION_ID - Required. Your Azure subscription ID for fine-tuned model deployment and inferencing.
6) AZURE_AI_PROJECTS_AZURE_RESOURCE_GROUP - Required. The resource group name containing your Azure OpenAI resource.
7) AZURE_AI_PROJECTS_AZURE_AOAI_ACCOUNT - Required. The name of your Azure OpenAI account for fine-tuned model deployment and inferencing.
"""

import asyncio
Expand All @@ -42,7 +44,7 @@
load_dotenv()

# For fine-tuning
endpoint = os.environ["PROJECT_ENDPOINT"]
endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
model_name = os.environ.get("MODEL_NAME", "gpt-4.1")
script_dir = Path(__file__).parent
training_file_path = os.environ.get("TRAINING_FILE_PATH", os.path.join(script_dir, "data", "sft_training_set.jsonl"))
Expand All @@ -51,9 +53,9 @@
)

# For Deployment and inferencing on model
subscription_id = os.environ.get("AZURE_SUBSCRIPTION_ID")
resource_group = os.environ.get("AZURE_RESOURCE_GROUP")
account_name = os.environ.get("AZURE_AOAI_ACCOUNT")
subscription_id = os.environ.get("AZURE_AI_PROJECTS_AZURE_SUBSCRIPTION_ID")
resource_group = os.environ.get("AZURE_AI_PROJECTS_AZURE_RESOURCE_GROUP")
account_name = os.environ.get("AZURE_AI_PROJECTS_AZURE_AOAI_ACCOUNT")


async def main():
Expand Down
4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/tests/finetuning/test_finetuning.py
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Expand Up @@ -406,8 +406,8 @@ def test_sft_pre_finetuning_job_deploy_infer(self, **kwargs):
pre_finetuned_model = self.test_finetuning_params["sft"]["openai"]["deployment"]["pre_finetuned_model"]
deployment_name = f"{self.test_finetuning_params['sft']['openai']['deployment']['deployment_name']}-{int(time.time())}"

resource_group = kwargs.get("azure_ai_projects_tests_azure_resource_group", "")
account_name = kwargs.get("azure_ai_projects_tests_azure_aoai_account", "")
resource_group = kwargs.get("azure_ai_projects_azure_resource_group", "")
account_name = kwargs.get("azure_ai_projects_azure_aoai_account", "")

assert resource_group, "Azure resource group is required for deployment test"
assert account_name, "Azure OpenAI account name is required for deployment test"
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4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/tests/finetuning/test_finetuning_async.py
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Expand Up @@ -436,8 +436,8 @@ async def test_sft_pre_finetuning_job_deploy_infer_async(self, **kwargs):
pre_finetuned_model = self.test_finetuning_params["sft"]["openai"]["deployment"]["pre_finetuned_model"]
deployment_name = f"{self.test_finetuning_params['sft']['openai']['deployment']['deployment_name']}-async-{int(time.time())}"

resource_group = kwargs.get("azure_ai_projects_tests_azure_resource_group", "")
account_name = kwargs.get("azure_ai_projects_tests_azure_aoai_account", "")
resource_group = kwargs.get("azure_ai_projects_azure_resource_group", "")
account_name = kwargs.get("azure_ai_projects_azure_aoai_account", "")

assert resource_group, "Azure resource group is required for deployment test"
assert account_name, "Azure OpenAI account name is required for deployment test"
Expand Down
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