mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Added changes (#1909)
This commit is contained in:
Dmytro Struk
@@ -3,6 +3,7 @@
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import importlib.metadata
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from ._chat_client import AzureAIAgentClient, AzureAISettings
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from ._chat_client_v2 import AzureAIAgentClientV2
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try:
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__version__ = importlib.metadata.version(__name__)
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@@ -11,6 +12,7 @@ except importlib.metadata.PackageNotFoundError:
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__all__ = [
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"AzureAIAgentClient",
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"AzureAIAgentClientV2",
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"AzureAISettings",
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"__version__",
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]
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@@ -40,9 +40,9 @@ from agent_framework import (
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use_chat_middleware,
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use_function_invocation,
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)
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from agent_framework._pydantic import AFBaseSettings
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from agent_framework.exceptions import ServiceInitializationError, ServiceResponseException
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from agent_framework.observability import use_observability
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from azure.ai.agents.aio import AgentsClient
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from azure.ai.agents.models import (
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Agent,
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AgentsNamedToolChoice,
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@@ -85,11 +85,11 @@ from azure.ai.agents.models import (
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ToolDefinition,
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ToolOutput,
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)
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from azure.ai.projects.aio import AIProjectClient
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from azure.core.credentials_async import AsyncTokenCredential
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from azure.core.exceptions import HttpResponseError, ResourceNotFoundError
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from pydantic import ValidationError
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from ._shared import AzureAISettings
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if sys.version_info >= (3, 11):
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from typing import Self # pragma: no cover
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else:
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@@ -99,47 +99,6 @@ else:
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logger = get_logger("agent_framework.azure")
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class AzureAISettings(AFBaseSettings):
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"""Azure AI Project settings.
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The settings are first loaded from environment variables with the prefix 'AZURE_AI_'.
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If the environment variables are not found, the settings can be loaded from a .env file
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with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
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are ignored; however, validation will fail alerting that the settings are missing.
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Keyword Args:
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project_endpoint: The Azure AI Project endpoint URL.
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Can be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
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model_deployment_name: The name of the model deployment to use.
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Can be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
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env_file_path: If provided, the .env settings are read from this file path location.
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env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
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Examples:
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.. code-block:: python
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from agent_framework_azure_ai import AzureAISettings
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# Using environment variables
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# Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
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# Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
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settings = AzureAISettings()
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# Or passing parameters directly
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settings = AzureAISettings(
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project_endpoint="https://your-project.cognitiveservices.azure.com", model_deployment_name="gpt-4"
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)
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# Or loading from a .env file
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settings = AzureAISettings(env_file_path="path/to/.env")
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"""
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env_prefix: ClassVar[str] = "AZURE_AI_"
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project_endpoint: str | None = None
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model_deployment_name: str | None = None
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TAzureAIAgentClient = TypeVar("TAzureAIAgentClient", bound="AzureAIAgentClient")
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@@ -154,7 +113,7 @@ class AzureAIAgentClient(BaseChatClient):
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def __init__(
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self,
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*,
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project_client: AIProjectClient | None = None,
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agents_client: AgentsClient | None = None,
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agent_id: str | None = None,
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agent_name: str | None = None,
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thread_id: str | None = None,
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@@ -168,16 +127,16 @@ class AzureAIAgentClient(BaseChatClient):
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"""Initialize an Azure AI Agent client.
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Keyword Args:
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project_client: An existing AIProjectClient to use. If not provided, one will be created.
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agent_id: The ID of an existing agent to use. If not provided and project_client is provided,
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a new agent will be created (and deleted after the request). If neither project_client
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agents_client: An existing AgentsClient to use. If not provided, one will be created.
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agent_id: The ID of an existing agent to use. If not provided and agents_client is provided,
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a new agent will be created (and deleted after the request). If neither agents_client
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nor agent_id is provided, both will be created and managed automatically.
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agent_name: The name to use when creating new agents.
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thread_id: Default thread ID to use for conversations. Can be overridden by
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conversation_id property when making a request.
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project_endpoint: The Azure AI Project endpoint URL.
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Can also be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
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Ignored when a project_client is passed.
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Ignored when a agents_client is passed.
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model_deployment_name: The model deployment name to use for agent creation.
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Can also be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
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async_credential: Azure async credential to use for authentication.
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@@ -217,9 +176,9 @@ class AzureAIAgentClient(BaseChatClient):
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except ValidationError as ex:
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raise ServiceInitializationError("Failed to create Azure AI settings.", ex) from ex
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# If no project_client is provided, create one
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# If no agents_client is provided, create one
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should_close_client = False
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if project_client is None:
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if agents_client is None:
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if not azure_ai_settings.project_endpoint:
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raise ServiceInitializationError(
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"Azure AI project endpoint is required. Set via 'project_endpoint' parameter "
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@@ -234,10 +193,11 @@ class AzureAIAgentClient(BaseChatClient):
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# Use provided credential
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if not async_credential:
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raise ServiceInitializationError("Azure credential is required when project_client is not provided.")
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project_client = AIProjectClient(
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raise ServiceInitializationError("Azure credential is required when agents_client is not provided.")
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agents_client = AgentsClient(
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endpoint=azure_ai_settings.project_endpoint,
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credential=async_credential,
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# TODO (dmytrostruk): Verify if user_agent works with AgentsClient
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user_agent=AGENT_FRAMEWORK_USER_AGENT,
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)
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should_close_client = True
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@@ -246,7 +206,7 @@ class AzureAIAgentClient(BaseChatClient):
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super().__init__(**kwargs)
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# Initialize instance variables
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self.project_client = project_client
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self.agents_client = agents_client
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self.credential = async_credential
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self.agent_id = agent_id
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self.agent_name = agent_name
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@@ -256,27 +216,6 @@ class AzureAIAgentClient(BaseChatClient):
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self._should_close_client = should_close_client # Track whether we should close client connection
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self._agent_definition: Agent | None = None # Cached definition for existing agent
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async def setup_azure_ai_observability(self, enable_sensitive_data: bool | None = None) -> None:
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"""Use this method to setup tracing in your Azure AI Project.
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This will take the connection string from the project project_client.
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It will override any connection string that is set in the environment variables.
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It will disable any OTLP endpoint that might have been set.
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"""
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try:
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conn_string = await self.project_client.telemetry.get_application_insights_connection_string()
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except ResourceNotFoundError:
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logger.warning(
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"No Application Insights connection string found for the Azure AI Project, "
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"please call setup_observability() manually."
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)
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return
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from agent_framework.observability import setup_observability
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setup_observability(
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applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data
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)
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async def __aenter__(self) -> "Self":
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"""Async context manager entry."""
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return self
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@@ -286,7 +225,7 @@ class AzureAIAgentClient(BaseChatClient):
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await self.close()
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async def close(self) -> None:
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"""Close the project_client and clean up any agents we created."""
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"""Close the agents_client and clean up any agents we created."""
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await self._cleanup_agent_if_needed()
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await self._close_client_if_needed()
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@@ -298,7 +237,7 @@ class AzureAIAgentClient(BaseChatClient):
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settings: A dictionary of settings for the service.
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"""
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return cls(
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project_client=settings.get("project_client"),
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agents_client=settings.get("agents_client"),
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agent_id=settings.get("agent_id"),
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thread_id=settings.get("thread_id"),
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project_endpoint=settings.get("project_endpoint"),
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@@ -374,11 +313,14 @@ class AzureAIAgentClient(BaseChatClient):
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args["instructions"] = run_options["instructions"]
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if "response_format" in run_options:
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args["response_format"] = run_options["response_format"]
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if "temperature" in run_options:
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args["temperature"] = run_options["temperature"]
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if "top_p" in run_options:
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args["top_p"] = run_options["top_p"]
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created_agent = await self.project_client.agents.create_agent(**args)
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created_agent = await self.agents_client.create_agent(**args)
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self.agent_id = str(created_agent.id)
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self._agent_definition = created_agent
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self._should_delete_agent = True
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@@ -422,7 +364,7 @@ class AzureAIAgentClient(BaseChatClient):
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args["tool_outputs"] = tool_outputs
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if tool_approvals:
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args["tool_approvals"] = tool_approvals
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await self.project_client.agents.runs.submit_tool_outputs_stream(**args) # type: ignore[reportUnknownMemberType]
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await self.agents_client.runs.submit_tool_outputs_stream(**args) # type: ignore[reportUnknownMemberType]
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# Pass the handler to the stream to continue processing
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stream = handler # type: ignore
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final_thread_id = thread_run.thread_id
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@@ -432,7 +374,7 @@ class AzureAIAgentClient(BaseChatClient):
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# Now create a new run and stream the results.
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run_options.pop("conversation_id", None)
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stream = await self.project_client.agents.runs.stream( # type: ignore[reportUnknownMemberType]
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stream = await self.agents_client.runs.stream( # type: ignore[reportUnknownMemberType]
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final_thread_id, agent_id=agent_id, **run_options
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)
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@@ -443,9 +385,7 @@ class AzureAIAgentClient(BaseChatClient):
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if thread_id is None:
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return None
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async for run in self.project_client.agents.runs.list(
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thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING
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): # type: ignore[reportUnknownMemberType]
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async for run in self.agents_client.runs.list(thread_id=thread_id, limit=1, order=ListSortOrder.DESCENDING): # type: ignore[reportUnknownMemberType]
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if run.status not in [
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RunStatus.COMPLETED,
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RunStatus.CANCELLED,
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@@ -462,12 +402,12 @@ class AzureAIAgentClient(BaseChatClient):
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if thread_id is not None:
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if thread_run is not None:
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# There was an active run; we need to cancel it before starting a new run.
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await self.project_client.agents.runs.cancel(thread_id, thread_run.id)
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await self.agents_client.runs.cancel(thread_id, thread_run.id)
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return thread_id
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# No thread ID was provided, so create a new thread.
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thread = await self.project_client.agents.threads.create(
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thread = await self.agents_client.threads.create(
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tool_resources=run_options.get("tool_resources"), metadata=run_options.get("metadata")
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)
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thread_id = thread.id
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@@ -476,7 +416,7 @@ class AzureAIAgentClient(BaseChatClient):
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# once fixed, in the function above, readd:
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# `messages=run_options.pop("additional_messages")`
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for msg in run_options.pop("additional_messages", []):
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await self.project_client.agents.messages.create(
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await self.agents_client.messages.create(
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thread_id=thread_id, role=msg.role, content=msg.content, metadata=msg.metadata
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)
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# and remove until here.
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@@ -709,21 +649,21 @@ class AzureAIAgentClient(BaseChatClient):
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return []
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async def _close_client_if_needed(self) -> None:
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"""Close project_client session if we created it."""
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"""Close agents_client session if we created it."""
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if self._should_close_client:
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await self.project_client.close()
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await self.agents_client.close()
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async def _cleanup_agent_if_needed(self) -> None:
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"""Clean up the agent if we created it."""
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if self._should_delete_agent and self.agent_id is not None:
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await self.project_client.agents.delete_agent(self.agent_id)
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await self.agents_client.delete_agent(self.agent_id)
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self.agent_id = None
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self._should_delete_agent = False
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async def _load_agent_definition_if_needed(self) -> Agent | None:
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"""Load and cache agent details if not already loaded."""
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if self._agent_definition is None and self.agent_id is not None:
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self._agent_definition = await self.project_client.agents.get_agent(self.agent_id)
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self._agent_definition = await self.agents_client.get_agent(self.agent_id)
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return self._agent_definition
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def _prepare_tool_choice(self, chat_options: ChatOptions) -> None:
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@@ -915,57 +855,32 @@ class AzureAIAgentClient(BaseChatClient):
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config_args["set_lang"] = set_lang
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# Bing Grounding (support both connection_id and connection_name)
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connection_id = additional_props.get("connection_id") or os.getenv("BING_CONNECTION_ID")
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connection_name = additional_props.get("connection_name") or os.getenv("BING_CONNECTION_NAME")
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# Custom Bing Search
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custom_connection_name = additional_props.get("custom_connection_name") or os.getenv(
|
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"BING_CUSTOM_CONNECTION_NAME"
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custom_connection_id = additional_props.get("custom_connection_id") or os.getenv(
|
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"BING_CUSTOM_CONNECTION_ID"
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)
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custom_configuration_name = additional_props.get("custom_instance_name") or os.getenv(
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custom_instance_name = additional_props.get("custom_instance_name") or os.getenv(
|
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"BING_CUSTOM_INSTANCE_NAME"
|
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)
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bing_search: BingGroundingTool | BingCustomSearchTool | None = None
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if (
|
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(connection_id or connection_name)
|
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and not custom_connection_name
|
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and not custom_configuration_name
|
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):
|
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if (connection_id) and not custom_connection_id and not custom_instance_name:
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if connection_id:
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conn_id = connection_id
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elif connection_name:
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try:
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bing_connection = await self.project_client.connections.get(name=connection_name)
|
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except HttpResponseError as err:
|
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raise ServiceInitializationError(
|
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f"Bing connection '{connection_name}' not found in the Azure AI Project.",
|
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err,
|
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) from err
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else:
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conn_id = bing_connection.id
|
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else:
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raise ServiceInitializationError("Neither connection_id nor connection_name provided.")
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bing_search = BingGroundingTool(connection_id=conn_id, **config_args)
|
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if custom_connection_name and custom_configuration_name:
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try:
|
||||
bing_custom_connection = await self.project_client.connections.get(
|
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name=custom_connection_name
|
||||
)
|
||||
except HttpResponseError as err:
|
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raise ServiceInitializationError(
|
||||
f"Bing custom connection '{custom_connection_name}' not found in the Azure AI Project.",
|
||||
err,
|
||||
) from err
|
||||
else:
|
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bing_search = BingCustomSearchTool(
|
||||
connection_id=bing_custom_connection.id,
|
||||
instance_name=custom_configuration_name,
|
||||
**config_args,
|
||||
)
|
||||
if custom_connection_id and custom_instance_name:
|
||||
bing_search = BingCustomSearchTool(
|
||||
connection_id=custom_connection_id,
|
||||
instance_name=custom_instance_name,
|
||||
**config_args,
|
||||
)
|
||||
if not bing_search:
|
||||
raise ServiceInitializationError(
|
||||
"Bing search tool requires either 'connection_id' or 'connection_name' for Bing Grounding "
|
||||
"or both 'custom_connection_name' and 'custom_instance_name' for Custom Bing Search. "
|
||||
"Bing search tool requires either 'connection_id' for Bing Grounding "
|
||||
"or both 'custom_connection_id' and 'custom_instance_name' for Custom Bing Search. "
|
||||
"These can be provided via additional_properties or environment variables: "
|
||||
"'BING_CONNECTION_ID', 'BING_CONNECTION_NAME', 'BING_CUSTOM_CONNECTION_NAME', "
|
||||
"'BING_CONNECTION_ID', 'BING_CUSTOM_CONNECTION_ID', "
|
||||
"'BING_CUSTOM_INSTANCE_NAME'"
|
||||
)
|
||||
tool_definitions.extend(bing_search.definitions)
|
||||
@@ -1056,4 +971,4 @@ class AzureAIAgentClient(BaseChatClient):
|
||||
Returns:
|
||||
The service URL for the chat client, or None if not set.
|
||||
"""
|
||||
return self.project_client._config.endpoint
|
||||
return self.agents_client._config.endpoint # type: ignore
|
||||
|
||||
@@ -0,0 +1,310 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import sys
|
||||
from collections.abc import MutableSequence
|
||||
from typing import Any, ClassVar, TypeVar
|
||||
|
||||
from agent_framework import (
|
||||
AGENT_FRAMEWORK_USER_AGENT,
|
||||
ChatMessage,
|
||||
ChatOptions,
|
||||
TextContent,
|
||||
get_logger,
|
||||
use_chat_middleware,
|
||||
use_function_invocation,
|
||||
)
|
||||
from agent_framework.exceptions import ServiceInitializationError
|
||||
from agent_framework.observability import use_observability
|
||||
from agent_framework.openai._responses_client import OpenAIBaseResponsesClient
|
||||
from azure.ai.projects.aio import AIProjectClient
|
||||
from azure.ai.projects.models import PromptAgentDefinition
|
||||
from azure.core.credentials_async import AsyncTokenCredential
|
||||
from azure.core.exceptions import ResourceNotFoundError
|
||||
from openai.types.responses.parsed_response import (
|
||||
ParsedResponse,
|
||||
)
|
||||
from openai.types.responses.response import Response as OpenAIResponse
|
||||
from pydantic import BaseModel, ValidationError
|
||||
|
||||
from ._shared import AzureAISettings
|
||||
|
||||
if sys.version_info >= (3, 11):
|
||||
from typing import Self # pragma: no cover
|
||||
else:
|
||||
from typing_extensions import Self # pragma: no cover
|
||||
|
||||
|
||||
logger = get_logger("agent_framework.azure")
|
||||
|
||||
|
||||
TAzureAIAgentClient = TypeVar("TAzureAIAgentClient", bound="AzureAIAgentClientV2")
|
||||
|
||||
|
||||
@use_function_invocation
|
||||
@use_observability
|
||||
@use_chat_middleware
|
||||
class AzureAIAgentClientV2(OpenAIBaseResponsesClient):
|
||||
"""Azure AI Agent Chat client."""
|
||||
|
||||
OTEL_PROVIDER_NAME: ClassVar[str] = "azure.ai" # type: ignore[reportIncompatibleVariableOverride, misc]
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
project_client: AIProjectClient | None = None,
|
||||
agent_name: str | None = None,
|
||||
agent_version: str | None = None,
|
||||
conversation_id: str | None = None,
|
||||
project_endpoint: str | None = None,
|
||||
model_deployment_name: str | None = None,
|
||||
async_credential: AsyncTokenCredential | None = None,
|
||||
env_file_path: str | None = None,
|
||||
env_file_encoding: str | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize an Azure AI Agent client.
|
||||
|
||||
Keyword Args:
|
||||
project_client: An existing AIProjectClient to use. If not provided, one will be created.
|
||||
agent_name: The name to use when creating new agents.
|
||||
agent_version: The version of the agent to use.
|
||||
conversation_id: Default conversation ID to use for conversations. Can be overridden by
|
||||
conversation_id property when making a request.
|
||||
project_endpoint: The Azure AI Project endpoint URL.
|
||||
Can also be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
|
||||
Ignored when a project_client is passed.
|
||||
model_deployment_name: The model deployment name to use for agent creation.
|
||||
Can also be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
|
||||
async_credential: Azure async credential to use for authentication.
|
||||
env_file_path: Path to environment file for loading settings.
|
||||
env_file_encoding: Encoding of the environment file.
|
||||
kwargs: Additional keyword arguments passed to the parent class.
|
||||
|
||||
Examples:
|
||||
.. code-block:: python
|
||||
|
||||
from agent_framework.azure import AzureAIAgentClient
|
||||
from azure.identity.aio import DefaultAzureCredential
|
||||
|
||||
# Using environment variables
|
||||
# Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
|
||||
# Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
|
||||
credential = DefaultAzureCredential()
|
||||
client = AzureAIAgentClient(async_credential=credential)
|
||||
|
||||
# Or passing parameters directly
|
||||
client = AzureAIAgentClient(
|
||||
project_endpoint="https://your-project.cognitiveservices.azure.com",
|
||||
model_deployment_name="gpt-4",
|
||||
async_credential=credential,
|
||||
)
|
||||
|
||||
# Or loading from a .env file
|
||||
client = AzureAIAgentClient(async_credential=credential, env_file_path="path/to/.env")
|
||||
"""
|
||||
try:
|
||||
azure_ai_settings = AzureAISettings(
|
||||
project_endpoint=project_endpoint,
|
||||
model_deployment_name=model_deployment_name,
|
||||
env_file_path=env_file_path,
|
||||
env_file_encoding=env_file_encoding,
|
||||
)
|
||||
except ValidationError as ex:
|
||||
raise ServiceInitializationError("Failed to create Azure AI settings.", ex) from ex
|
||||
|
||||
# If no project_client is provided, create one
|
||||
should_close_client = False
|
||||
if project_client is None:
|
||||
if not azure_ai_settings.project_endpoint:
|
||||
raise ServiceInitializationError(
|
||||
"Azure AI project endpoint is required. Set via 'project_endpoint' parameter "
|
||||
"or 'AZURE_AI_PROJECT_ENDPOINT' environment variable."
|
||||
)
|
||||
|
||||
if not azure_ai_settings.model_deployment_name:
|
||||
raise ServiceInitializationError(
|
||||
"Azure AI model deployment name is required. Set via 'model_deployment_name' parameter "
|
||||
"or 'AZURE_AI_MODEL_DEPLOYMENT_NAME' environment variable."
|
||||
)
|
||||
|
||||
# Use provided credential
|
||||
if not async_credential:
|
||||
raise ServiceInitializationError("Azure credential is required when project_client is not provided.")
|
||||
project_client = AIProjectClient(
|
||||
endpoint=azure_ai_settings.project_endpoint,
|
||||
credential=async_credential,
|
||||
user_agent=AGENT_FRAMEWORK_USER_AGENT,
|
||||
)
|
||||
should_close_client = True
|
||||
|
||||
# Initialize parent
|
||||
super().__init__(
|
||||
model_id=azure_ai_settings.model_deployment_name, # type: ignore
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
# Initialize instance variables
|
||||
self.agent_name = agent_name
|
||||
self.agent_version = agent_version
|
||||
self.project_client = project_client
|
||||
self.credential = async_credential
|
||||
self.model_id = azure_ai_settings.model_deployment_name
|
||||
self.conversation_id = conversation_id
|
||||
self._should_close_client = should_close_client # Track whether we should close client connection
|
||||
|
||||
async def setup_azure_ai_observability(self, enable_sensitive_data: bool | None = None) -> None:
|
||||
"""Use this method to setup tracing in your Azure AI Project.
|
||||
|
||||
This will take the connection string from the project project_client.
|
||||
It will override any connection string that is set in the environment variables.
|
||||
It will disable any OTLP endpoint that might have been set.
|
||||
"""
|
||||
try:
|
||||
conn_string = await self.project_client.telemetry.get_application_insights_connection_string()
|
||||
except ResourceNotFoundError:
|
||||
logger.warning(
|
||||
"No Application Insights connection string found for the Azure AI Project, "
|
||||
"please call setup_observability() manually."
|
||||
)
|
||||
return
|
||||
from agent_framework.observability import setup_observability
|
||||
|
||||
setup_observability(
|
||||
applicationinsights_connection_string=conn_string, enable_sensitive_data=enable_sensitive_data
|
||||
)
|
||||
|
||||
async def __aenter__(self) -> "Self":
|
||||
"""Async context manager entry."""
|
||||
return self
|
||||
|
||||
async def __aexit__(self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: Any) -> None:
|
||||
"""Async context manager exit."""
|
||||
await self.close()
|
||||
|
||||
async def close(self) -> None:
|
||||
"""Close the project_client."""
|
||||
await self._close_client_if_needed()
|
||||
|
||||
async def _get_agent_reference_or_create(
|
||||
self, run_options: dict[str, Any], messages_instructions: str | None
|
||||
) -> dict[str, str]:
|
||||
"""Determine which agent to use and create if needed.
|
||||
|
||||
Returns:
|
||||
str: The agent_name to use
|
||||
"""
|
||||
agent_name = self.agent_name or "UnnamedAgent"
|
||||
|
||||
# If no agent_version is provided, create a new agent
|
||||
if self.agent_version is None:
|
||||
if "model" not in run_options or not run_options["model"]:
|
||||
raise ServiceInitializationError(
|
||||
"Model deployment name is required for agent creation, "
|
||||
"can also be passed to the get_response methods."
|
||||
)
|
||||
|
||||
args: dict[str, Any] = {
|
||||
"model": run_options["model"],
|
||||
}
|
||||
if "tools" in run_options:
|
||||
args["tools"] = run_options["tools"]
|
||||
|
||||
# Combine instructions from messages and options
|
||||
combined_instructions = [
|
||||
instructions
|
||||
for instructions in [messages_instructions, run_options.get("instructions")]
|
||||
if instructions
|
||||
]
|
||||
if combined_instructions:
|
||||
args["instructions"] = "".join(combined_instructions)
|
||||
|
||||
# TODO (dmytrostruk): Add response format
|
||||
|
||||
created_agent = await self.project_client.agents.create_version(
|
||||
agent_name=agent_name, definition=PromptAgentDefinition(**args)
|
||||
)
|
||||
|
||||
self.agent_name = created_agent.name
|
||||
self.agent_version = created_agent.version
|
||||
|
||||
return {"name": agent_name, "version": self.agent_version, "type": "agent_reference"}
|
||||
|
||||
async def _get_conversation_id_or_create(self, run_options: dict[str, Any]) -> str:
|
||||
# Since "conversation" property is used, remove "previous_response_id" from options
|
||||
# Use global conversation_id as fallback
|
||||
conversation_id = run_options.pop("previous_response_id", self.conversation_id)
|
||||
|
||||
if conversation_id:
|
||||
return conversation_id
|
||||
|
||||
# Create a new conversation with messages
|
||||
created_conversation = await self.client.conversations.create()
|
||||
return created_conversation.id
|
||||
|
||||
async def _close_client_if_needed(self) -> None:
|
||||
"""Close project_client session if we created it."""
|
||||
if self._should_close_client:
|
||||
await self.project_client.close()
|
||||
|
||||
def _prepare_input(self, messages: MutableSequence[ChatMessage]) -> tuple[list[ChatMessage], str | None]:
|
||||
"""Prepare input from messages and convert system/developer messages to instructions."""
|
||||
result: list[ChatMessage] = []
|
||||
instructions_list: list[str] = []
|
||||
instructions: str | None = None
|
||||
|
||||
# System/developer messages are turned into instructions, since there is no such message roles in Azure AI.
|
||||
for message in messages:
|
||||
if message.role.value in ["system", "developer"]:
|
||||
for text_content in [content for content in message.contents if isinstance(content, TextContent)]:
|
||||
instructions_list.append(text_content.text)
|
||||
else:
|
||||
result.append(message)
|
||||
|
||||
if len(instructions_list) > 0:
|
||||
instructions = "".join(instructions_list)
|
||||
|
||||
return result, instructions
|
||||
|
||||
async def prepare_options(
|
||||
self, messages: MutableSequence[ChatMessage], chat_options: ChatOptions
|
||||
) -> dict[str, Any]:
|
||||
prepared_messages, instructions = self._prepare_input(messages)
|
||||
run_options = await super().prepare_options(prepared_messages, chat_options)
|
||||
agent_reference = await self._get_agent_reference_or_create(run_options, instructions)
|
||||
|
||||
store = run_options.get("store", False)
|
||||
|
||||
if store:
|
||||
conversation_id = await self._get_conversation_id_or_create(run_options)
|
||||
run_options["conversation"] = conversation_id
|
||||
|
||||
run_options["extra_body"] = {"agent": agent_reference}
|
||||
|
||||
# Remove properties that are not supported
|
||||
# Model and tools captured in the agent setup
|
||||
if "model" in run_options:
|
||||
run_options.pop("model", None)
|
||||
|
||||
if "tools" in run_options:
|
||||
run_options.pop("tools", None)
|
||||
|
||||
return run_options
|
||||
|
||||
async def initialize_client(self):
|
||||
"""Initialize OpenAI client asynchronously."""
|
||||
self.client = await self.project_client.get_openai_client() # type: ignore
|
||||
|
||||
def get_conversation_id(self, response: OpenAIResponse | ParsedResponse[BaseModel], store: bool) -> str | None:
|
||||
"""Get the conversation ID from the response if store is True."""
|
||||
return response.conversation.id if response.conversation and store else None
|
||||
|
||||
def _update_agent_name(self, agent_name: str | None) -> None:
|
||||
"""Update the agent name in the chat client.
|
||||
|
||||
Args:
|
||||
agent_name: The new name for the agent.
|
||||
"""
|
||||
# This is a no-op in the base class, but can be overridden by subclasses
|
||||
# to update the agent name in the client.
|
||||
if agent_name and not self.agent_name:
|
||||
self.agent_name = agent_name
|
||||
@@ -0,0 +1,46 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
from typing import ClassVar
|
||||
|
||||
from agent_framework._pydantic import AFBaseSettings
|
||||
|
||||
|
||||
class AzureAISettings(AFBaseSettings):
|
||||
"""Azure AI Project settings.
|
||||
|
||||
The settings are first loaded from environment variables with the prefix 'AZURE_AI_'.
|
||||
If the environment variables are not found, the settings can be loaded from a .env file
|
||||
with the encoding 'utf-8'. If the settings are not found in the .env file, the settings
|
||||
are ignored; however, validation will fail alerting that the settings are missing.
|
||||
|
||||
Keyword Args:
|
||||
project_endpoint: The Azure AI Project endpoint URL.
|
||||
Can be set via environment variable AZURE_AI_PROJECT_ENDPOINT.
|
||||
model_deployment_name: The name of the model deployment to use.
|
||||
Can be set via environment variable AZURE_AI_MODEL_DEPLOYMENT_NAME.
|
||||
env_file_path: If provided, the .env settings are read from this file path location.
|
||||
env_file_encoding: The encoding of the .env file, defaults to 'utf-8'.
|
||||
|
||||
Examples:
|
||||
.. code-block:: python
|
||||
|
||||
from agent_framework.azure import AzureAISettings
|
||||
|
||||
# Using environment variables
|
||||
# Set AZURE_AI_PROJECT_ENDPOINT=https://your-project.cognitiveservices.azure.com
|
||||
# Set AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4
|
||||
settings = AzureAISettings()
|
||||
|
||||
# Or passing parameters directly
|
||||
settings = AzureAISettings(
|
||||
project_endpoint="https://your-project.cognitiveservices.azure.com", model_deployment_name="gpt-4"
|
||||
)
|
||||
|
||||
# Or loading from a .env file
|
||||
settings = AzureAISettings(env_file_path="path/to/.env")
|
||||
"""
|
||||
|
||||
env_prefix: ClassVar[str] = "AZURE_AI_"
|
||||
|
||||
project_endpoint: str | None = None
|
||||
model_deployment_name: str | None = None
|
||||
Reference in New Issue
Block a user