openai

Azure AI chat model using the OpenAI-compatible API.

This class wraps :class:langchain_openai.ChatOpenAI and adds support for the project-endpoint pattern available in Azure AI Foundry, in addition to the classic endpoint + API-key style used by OpenAI-compatible services.

Use AzureAIOpenAIApiChatModel with any Foundry model compatible with OpenAI APIs (e.g. gpt-5, Mistral, Cohere.) to get the benefits of unified authentication, single configuration, and seamless integration with other Azure services.

By default, this class uses Responses API. Set use_responses_api=False to disable it and use the standard chat completions API instead.

Project-endpoint pattern (recommended for Azure AI Foundry):

from langchain_azure_ai.chat_models import AzureAIOpenAIApiChatModel
from azure.identity import DefaultAzureCredential

model = AzureAIOpenAIApiChatModel(
    project_endpoint=(
        "https://resource.services.ai.azure.com/api/projects/my-project"
    ),
    credential=DefaultAzureCredential(),
    model="gpt-4o",
)

Parameter model refers to the model deployment name in Azure AI Foundry, which may differ from the base model name (e.g. "gpt-4o") depending on how the deployment was configured.

If project_endpoint is omitted the value of the AZURE_AI_PROJECT_ENDPOINT environment variable is used.

Direct endpoint + API-key pattern:

from langchain_azure_ai.chat_models import AzureAIOpenAIApiChatModel

model = AzureAIOpenAIApiChatModel(
    endpoint="https://resource.services.ai.azure.com/openai/v1",
    credential="your-api-key",
    model="gpt-4o",
)

Use api_version parameter to specify the API version when using a direct endpoint, or rely on the automatic API version detection when using a project endpoint.

from langchain_azure_ai.chat_models import AzureAIOpenAIApiChatModel

model = AzureAIOpenAIApiChatModel(
    endpoint="https://resource.services.ai.azure.com/openai/v1",
    credential="your-api-key",
    model="gpt-4o",
    api_version="2025-05-12"
)

Environment variables:

The following environment variables are recognised as fallbacks when the corresponding constructor parameters are not provided:

• AZURE_AI_PROJECT_ENDPOINT – used as project_endpoint.
• AZURE_AI_OPENAI_ENDPOINT – direct OpenAI-compatible endpoint (e.g. https://<resource>.services.ai.azure.com/openai/v1). Used as endpoint verbatim (no path is appended).
• AZURE_OPENAI_ENDPOINT – root Azure OpenAI endpoint (e.g. https://<resource>.services.ai.azure.com). /openai/v1 is appended automatically and the result is treated as endpoint.
• AZURE_OPENAI_DEPLOYMENT_NAME – model deployment name (model).
• AZURE_OPENAI_API_VERSION – API version passed as the api-version query parameter on every request.

Resolution priority (highest → lowest):

1. Constructor parameters.
2. AZURE_AI_PROJECT_ENDPOINT environment variable.
3. AZURE_AI_OPENAI_ENDPOINT environment variable.
4. AZURE_OPENAI_ENDPOINT / AZURE_OPENAI_API_VERSION / AZURE_OPENAI_DEPLOYMENT_NAME environment variables.

AZURE_AI_PROJECT_ENDPOINT, AZURE_AI_OPENAI_ENDPOINT, and AZURE_OPENAI_ENDPOINT may all be set at the same time; the project endpoint takes precedence, then AZURE_AI_OPENAI_ENDPOINT, then AZURE_OPENAI_ENDPOINT. However, passing both project_endpoint and endpoint as constructor parameters raises :class:ValueError.

All other keyword arguments accepted by :class:langchain_openai.ChatOpenAI are forwarded as-is, so you retain full control over temperature, max_tokens, streaming, etc.