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Python: Create/Get Agent API for Azure V1 (#3192)
* Added provider implementation for Azure AI V1 * Small fixes * Fixed OpenAPI example * Fixed local MCP example * Fixed hosted MCP example * Fixed file search sample * Small fixes * Resolved comments * Doc updates
This commit is contained in:
Dmytro Struk
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GitHub
parent
6e9420f614
commit
48d124efbe
@@ -2,9 +2,10 @@
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import importlib.metadata
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from ._agent_provider import AzureAIAgentsProvider
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from ._chat_client import AzureAIAgentClient, AzureAIAgentOptions
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from ._client import AzureAIClient
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from ._provider import AzureAIProjectAgentProvider
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from ._project_provider import AzureAIProjectAgentProvider
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from ._shared import AzureAISettings
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try:
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@@ -15,6 +16,7 @@ except importlib.metadata.PackageNotFoundError:
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__all__ = [
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"AzureAIAgentClient",
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"AzureAIAgentOptions",
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"AzureAIAgentsProvider",
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"AzureAIClient",
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"AzureAIProjectAgentProvider",
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"AzureAISettings",
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@@ -0,0 +1,519 @@
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# Copyright (c) Microsoft. All rights reserved.
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import sys
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from collections.abc import Callable, MutableMapping, Sequence
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from typing import TYPE_CHECKING, Any, Generic, TypedDict, cast
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from agent_framework import (
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AGENT_FRAMEWORK_USER_AGENT,
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AIFunction,
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ChatAgent,
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ContextProvider,
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Middleware,
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ToolProtocol,
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normalize_tools,
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)
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from agent_framework._mcp import MCPTool
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from agent_framework.exceptions import ServiceInitializationError
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from azure.ai.agents.aio import AgentsClient
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from azure.ai.agents.models import Agent, ResponseFormatJsonSchema, ResponseFormatJsonSchemaType
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from azure.core.credentials_async import AsyncTokenCredential
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from pydantic import BaseModel, ValidationError
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from ._chat_client import AzureAIAgentClient
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from ._shared import AzureAISettings, from_azure_ai_agent_tools, to_azure_ai_agent_tools
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if TYPE_CHECKING:
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from ._chat_client import AzureAIAgentOptions
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if sys.version_info >= (3, 13):
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from typing import Self, TypeVar # pragma: no cover
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else:
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from typing_extensions import Self, TypeVar # pragma: no cover
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# Type variable for options - allows typed ChatAgent[TOptions] returns
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# Default matches AzureAIAgentClient's default options type
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TOptions_co = TypeVar(
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"TOptions_co",
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bound=TypedDict, # type: ignore[valid-type]
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default="AzureAIAgentOptions",
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covariant=True,
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)
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class AzureAIAgentsProvider(Generic[TOptions_co]):
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"""Provider for Azure AI Agent Service V1 (Persistent Agents API).
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This provider enables creating, retrieving, and wrapping Azure AI agents as ChatAgent
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instances. It manages the underlying AgentsClient lifecycle and provides a high-level
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interface for agent operations.
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The provider can be initialized with either:
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- An existing AgentsClient instance
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- Azure credentials and endpoint for automatic client creation
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Examples:
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Using credentials (auto-creates client):
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.. code-block:: python
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from agent_framework.azure import AzureAIAgentsProvider
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from azure.identity.aio import AzureCliCredential
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async with (
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AzureCliCredential() as credential,
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AzureAIAgentsProvider(credential=credential) as provider,
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):
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agent = await provider.create_agent(
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name="MyAgent",
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instructions="You are a helpful assistant.",
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)
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result = await agent.run("Hello!")
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Using existing AgentsClient:
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.. code-block:: python
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from agent_framework.azure import AzureAIAgentsProvider
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from azure.ai.agents.aio import AgentsClient
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async with AgentsClient(endpoint=endpoint, credential=credential) as client:
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provider = AzureAIAgentsProvider(agents_client=client)
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agent = await provider.create_agent(name="MyAgent", instructions="...")
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"""
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def __init__(
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self,
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agents_client: AgentsClient | None = None,
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*,
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project_endpoint: str | None = None,
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credential: AsyncTokenCredential | None = None,
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env_file_path: str | None = None,
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env_file_encoding: str | None = None,
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) -> None:
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"""Initialize the Azure AI Agents Provider.
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Args:
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agents_client: An existing AgentsClient to use. If provided, the provider
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will not manage its lifecycle.
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Keyword Args:
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project_endpoint: The Azure AI Project endpoint URL.
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Can also be set via AZURE_AI_PROJECT_ENDPOINT environment variable.
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credential: Azure async credential for authentication.
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Required if agents_client is not provided.
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env_file_path: Path to .env file for loading settings.
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env_file_encoding: Encoding of the .env file.
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Raises:
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ServiceInitializationError: If required parameters are missing or invalid.
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"""
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try:
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self._settings = AzureAISettings(
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project_endpoint=project_endpoint,
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env_file_path=env_file_path,
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env_file_encoding=env_file_encoding,
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)
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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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self._should_close_client = False
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if agents_client is not None:
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self._agents_client = agents_client
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else:
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if not self._settings.project_endpoint:
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raise ServiceInitializationError(
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"Azure AI project endpoint is required. Provide 'project_endpoint' parameter "
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"or set 'AZURE_AI_PROJECT_ENDPOINT' environment variable."
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)
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if not credential:
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raise ServiceInitializationError("Azure credential is required when agents_client is not provided.")
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self._agents_client = AgentsClient(
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endpoint=self._settings.project_endpoint,
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credential=credential,
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user_agent=AGENT_FRAMEWORK_USER_AGENT,
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)
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self._should_close_client = True
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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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async def __aexit__(
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self,
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exc_type: type[BaseException] | None,
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exc_val: BaseException | None,
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exc_tb: Any,
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) -> None:
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"""Async context manager exit."""
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await self.close()
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async def close(self) -> None:
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"""Close the provider and release resources.
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Only closes the AgentsClient if it was created by this provider.
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"""
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if self._should_close_client:
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await self._agents_client.close()
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async def create_agent(
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self,
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name: str,
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*,
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model: str | None = None,
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instructions: str | None = None,
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description: str | None = None,
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tools: ToolProtocol
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| Callable[..., Any]
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| MutableMapping[str, Any]
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| Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
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| None = None,
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default_options: TOptions_co | None = None,
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middleware: Sequence[Middleware] | None = None,
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context_provider: ContextProvider | None = None,
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) -> "ChatAgent[TOptions_co]":
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"""Create a new agent on the Azure AI service and return a ChatAgent.
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This method creates a persistent agent on the Azure AI service with the specified
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configuration and returns a local ChatAgent instance for interaction.
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Args:
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name: The name for the agent.
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Keyword Args:
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model: The model deployment name to use. Falls back to
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AZURE_AI_MODEL_DEPLOYMENT_NAME environment variable if not provided.
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instructions: Instructions for the agent's behavior.
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description: A description of the agent's purpose.
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tools: Tools to make available to the agent.
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default_options: A TypedDict containing default chat options for the agent.
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These options are applied to every run unless overridden.
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middleware: List of middleware to intercept agent and function invocations.
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context_provider: Context provider to include during agent invocation.
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Returns:
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ChatAgent: A ChatAgent instance configured with the created agent.
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Raises:
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ServiceInitializationError: If model deployment name is not available.
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Examples:
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.. code-block:: python
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agent = await provider.create_agent(
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name="WeatherAgent",
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instructions="You are a helpful weather assistant.",
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tools=get_weather,
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)
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"""
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resolved_model = model or self._settings.model_deployment_name
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if not resolved_model:
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raise ServiceInitializationError(
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"Model deployment name is required. Provide 'model' parameter "
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"or set 'AZURE_AI_MODEL_DEPLOYMENT_NAME' environment variable."
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)
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# Extract response_format from default_options if present
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opts = dict(default_options) if default_options else {}
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response_format = opts.get("response_format")
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args: dict[str, Any] = {
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"model": resolved_model,
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"name": name,
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}
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if description:
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args["description"] = description
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if instructions:
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args["instructions"] = instructions
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# Handle response format
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if response_format and isinstance(response_format, type) and issubclass(response_format, BaseModel):
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args["response_format"] = self._create_response_format_config(response_format)
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# Normalize and convert tools
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# Local MCP tools (MCPTool) are handled by ChatAgent at runtime, not stored on the Azure agent
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normalized_tools = normalize_tools(tools)
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if normalized_tools:
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# Only convert non-MCP tools to Azure AI format
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non_mcp_tools = [t for t in normalized_tools if not isinstance(t, MCPTool)]
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if non_mcp_tools:
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# Pass run_options to capture tool_resources (e.g., for file search vector stores)
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run_options: dict[str, Any] = {}
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args["tools"] = to_azure_ai_agent_tools(non_mcp_tools, run_options)
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if "tool_resources" in run_options:
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args["tool_resources"] = run_options["tool_resources"]
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# Create the agent on the service
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created_agent = await self._agents_client.create_agent(**args)
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# Create ChatAgent wrapper
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return self._to_chat_agent_from_agent(
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created_agent,
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normalized_tools,
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default_options=default_options,
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middleware=middleware,
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context_provider=context_provider,
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)
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async def get_agent(
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self,
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id: str,
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*,
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tools: ToolProtocol
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| Callable[..., Any]
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| MutableMapping[str, Any]
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| Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
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| None = None,
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default_options: TOptions_co | None = None,
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middleware: Sequence[Middleware] | None = None,
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context_provider: ContextProvider | None = None,
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) -> "ChatAgent[TOptions_co]":
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"""Retrieve an existing agent from the service and return a ChatAgent.
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This method fetches an agent by ID from the Azure AI service
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and returns a local ChatAgent instance for interaction.
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Args:
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id: The ID of the agent to retrieve from the service.
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Keyword Args:
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tools: Tools to make available to the agent. Required if the agent
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has function tools that need implementations.
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default_options: A TypedDict containing default chat options for the agent.
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These options are applied to every run unless overridden.
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middleware: List of middleware to intercept agent and function invocations.
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context_provider: Context provider to include during agent invocation.
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Returns:
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ChatAgent: A ChatAgent instance configured with the retrieved agent.
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Raises:
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ServiceInitializationError: If required function tools are not provided.
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Examples:
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.. code-block:: python
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agent = await provider.get_agent("agent-123")
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# With function tools
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agent = await provider.get_agent("agent-123", tools=my_function)
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"""
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agent = await self._agents_client.get_agent(id)
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# Validate function tools
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normalized_tools = normalize_tools(tools)
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self._validate_function_tools(agent.tools, normalized_tools)
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return self._to_chat_agent_from_agent(
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agent,
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normalized_tools,
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default_options=default_options,
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middleware=middleware,
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context_provider=context_provider,
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)
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def as_agent(
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self,
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agent: Agent,
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tools: ToolProtocol
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| Callable[..., Any]
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| MutableMapping[str, Any]
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| Sequence[ToolProtocol | Callable[..., Any] | MutableMapping[str, Any]]
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| None = None,
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default_options: TOptions_co | None = None,
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middleware: Sequence[Middleware] | None = None,
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context_provider: ContextProvider | None = None,
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) -> "ChatAgent[TOptions_co]":
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"""Wrap an existing Agent SDK object as a ChatAgent without making HTTP calls.
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Use this method when you already have an Agent object from a previous
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SDK operation and want to use it with the Agent Framework.
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Args:
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agent: The Agent object to wrap.
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tools: Tools to make available to the agent. Required if the agent
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has function tools that need implementations.
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default_options: A TypedDict containing default chat options for the agent.
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These options are applied to every run unless overridden.
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middleware: List of middleware to intercept agent and function invocations.
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context_provider: Context provider to include during agent invocation.
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Returns:
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ChatAgent: A ChatAgent instance configured with the agent.
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Raises:
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ServiceInitializationError: If required function tools are not provided.
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Examples:
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.. code-block:: python
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# Create agent directly with SDK
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sdk_agent = await agents_client.create_agent(
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model="gpt-4",
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name="MyAgent",
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instructions="...",
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)
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# Wrap as ChatAgent
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chat_agent = provider.as_agent(sdk_agent)
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"""
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# Validate function tools
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normalized_tools = normalize_tools(tools)
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self._validate_function_tools(agent.tools, normalized_tools)
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return self._to_chat_agent_from_agent(
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agent,
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normalized_tools,
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default_options=default_options,
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middleware=middleware,
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context_provider=context_provider,
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)
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def _to_chat_agent_from_agent(
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self,
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agent: Agent,
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provided_tools: Sequence[ToolProtocol | MutableMapping[str, Any]] | None = None,
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default_options: TOptions_co | None = None,
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middleware: Sequence[Middleware] | None = None,
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context_provider: ContextProvider | None = None,
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) -> "ChatAgent[TOptions_co]":
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"""Create a ChatAgent from an Agent SDK object.
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Args:
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agent: The Agent SDK object.
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provided_tools: User-provided tools (including function implementations).
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default_options: A TypedDict containing default chat options for the agent.
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These options are applied to every run unless overridden.
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middleware: List of middleware to intercept agent and function invocations.
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context_provider: Context provider to include during agent invocation.
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"""
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# Create the underlying client
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client = AzureAIAgentClient(
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agents_client=self._agents_client,
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agent_id=agent.id,
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agent_name=agent.name,
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agent_description=agent.description,
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should_cleanup_agent=False, # Provider manages agent lifecycle
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)
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# Merge tools: convert agent's hosted tools + user-provided function tools
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merged_tools = self._merge_tools(agent.tools, provided_tools)
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return ChatAgent( # type: ignore[return-value]
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chat_client=client,
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id=agent.id,
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name=agent.name,
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description=agent.description,
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instructions=agent.instructions,
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model_id=agent.model,
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tools=merged_tools,
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default_options=default_options, # type: ignore[arg-type]
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middleware=middleware,
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context_provider=context_provider,
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)
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def _merge_tools(
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self,
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agent_tools: Sequence[Any] | None,
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provided_tools: Sequence[ToolProtocol | MutableMapping[str, Any]] | None,
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) -> list[ToolProtocol | dict[str, Any]]:
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"""Merge hosted tools from agent with user-provided function tools.
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Args:
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agent_tools: Tools from the agent definition (Azure AI format).
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provided_tools: User-provided tools (Agent Framework format).
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Returns:
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Combined list of tools for the ChatAgent.
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"""
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merged: list[ToolProtocol | dict[str, Any]] = []
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# Convert hosted tools from agent definition
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hosted_tools = from_azure_ai_agent_tools(agent_tools)
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for hosted_tool in hosted_tools:
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# Skip function tool dicts - they don't have implementations
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# Skip OpenAPI tool dicts - they're defined on the agent, not needed at runtime
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if isinstance(hosted_tool, dict):
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tool_type = hosted_tool.get("type")
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if tool_type == "function" or tool_type == "openapi":
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continue
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merged.append(hosted_tool)
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# Add user-provided function tools and MCP tools
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if provided_tools:
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for provided_tool in provided_tools:
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# AIFunction - has implementation for function calling
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# MCPTool - ChatAgent handles MCP connection and tool discovery at runtime
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if isinstance(provided_tool, (AIFunction, MCPTool)):
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merged.append(provided_tool) # type: ignore[reportUnknownArgumentType]
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return merged
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def _validate_function_tools(
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self,
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agent_tools: Sequence[Any] | None,
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provided_tools: Sequence[ToolProtocol | MutableMapping[str, Any]] | None,
|
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) -> None:
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"""Validate that required function tools are provided.
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|
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Raises:
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ServiceInitializationError: If agent has function tools but user
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didn't provide implementations.
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"""
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if not agent_tools:
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return
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# Get function tool names from agent definition
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function_tool_names: set[str] = set()
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for tool in agent_tools:
|
||||
if isinstance(tool, dict):
|
||||
tool_dict = cast(dict[str, Any], tool)
|
||||
if tool_dict.get("type") == "function":
|
||||
func_def = cast(dict[str, Any], tool_dict.get("function", {}))
|
||||
name = func_def.get("name")
|
||||
if isinstance(name, str):
|
||||
function_tool_names.add(name)
|
||||
elif hasattr(tool, "type") and tool.type == "function":
|
||||
func_attr = getattr(tool, "function", None)
|
||||
if func_attr and hasattr(func_attr, "name"):
|
||||
function_tool_names.add(str(func_attr.name))
|
||||
|
||||
if not function_tool_names:
|
||||
return
|
||||
|
||||
# Get provided function names
|
||||
provided_names: set[str] = set()
|
||||
if provided_tools:
|
||||
for tool in provided_tools:
|
||||
if isinstance(tool, AIFunction):
|
||||
provided_names.add(tool.name)
|
||||
|
||||
# Check for missing implementations
|
||||
missing = function_tool_names - provided_names
|
||||
if missing:
|
||||
raise ServiceInitializationError(
|
||||
f"Agent has function tools that require implementations: {missing}. "
|
||||
"Provide these functions via the 'tools' parameter."
|
||||
)
|
||||
|
||||
def _create_response_format_config(
|
||||
self,
|
||||
response_format: type[BaseModel],
|
||||
) -> ResponseFormatJsonSchemaType:
|
||||
"""Create response format configuration for Azure AI.
|
||||
|
||||
Args:
|
||||
response_format: Pydantic model for structured output.
|
||||
|
||||
Returns:
|
||||
Azure AI response format configuration.
|
||||
"""
|
||||
return ResponseFormatJsonSchemaType(
|
||||
json_schema=ResponseFormatJsonSchema(
|
||||
name=response_format.__name__,
|
||||
schema=response_format.model_json_schema(),
|
||||
)
|
||||
)
|
||||
@@ -2,7 +2,6 @@
|
||||
|
||||
import ast
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
from collections.abc import AsyncIterable, Mapping, MutableMapping, MutableSequence, Sequence
|
||||
@@ -10,7 +9,6 @@ from typing import Any, ClassVar, Generic, TypedDict
|
||||
|
||||
from agent_framework import (
|
||||
AGENT_FRAMEWORK_USER_AGENT,
|
||||
AIFunction,
|
||||
BaseChatClient,
|
||||
ChatMessage,
|
||||
ChatOptions,
|
||||
@@ -23,12 +21,8 @@ from agent_framework import (
|
||||
FunctionApprovalResponseContent,
|
||||
FunctionCallContent,
|
||||
FunctionResultContent,
|
||||
HostedCodeInterpreterTool,
|
||||
HostedFileContent,
|
||||
HostedFileSearchTool,
|
||||
HostedMCPTool,
|
||||
HostedVectorStoreContent,
|
||||
HostedWebSearchTool,
|
||||
Role,
|
||||
TextContent,
|
||||
TextSpanRegion,
|
||||
@@ -52,14 +46,9 @@ from azure.ai.agents.models import (
|
||||
AgentStreamEvent,
|
||||
AsyncAgentEventHandler,
|
||||
AsyncAgentRunStream,
|
||||
BingCustomSearchTool,
|
||||
BingGroundingTool,
|
||||
CodeInterpreterToolDefinition,
|
||||
FileSearchTool,
|
||||
FunctionName,
|
||||
FunctionToolDefinition,
|
||||
ListSortOrder,
|
||||
McpTool,
|
||||
MessageDeltaChunk,
|
||||
MessageDeltaTextContent,
|
||||
MessageDeltaTextFileCitationAnnotation,
|
||||
@@ -91,7 +80,7 @@ from azure.ai.agents.models import (
|
||||
from azure.core.credentials_async import AsyncTokenCredential
|
||||
from pydantic import BaseModel, ValidationError
|
||||
|
||||
from ._shared import AzureAISettings
|
||||
from ._shared import AzureAISettings, to_azure_ai_agent_tools
|
||||
|
||||
if sys.version_info >= (3, 13):
|
||||
from typing import TypeVar # type: ignore # pragma: no cover
|
||||
@@ -1007,7 +996,7 @@ class AzureAIAgentClient(BaseChatClient[TAzureAIAgentOptions], Generic[TAzureAIA
|
||||
tool_choice = options.get("tool_choice")
|
||||
tools = options.get("tools")
|
||||
if tool_choice is not None and tool_choice != "none" and tools:
|
||||
tool_definitions.extend(await self._prepare_tools_for_azure_ai(tools, run_options))
|
||||
tool_definitions.extend(to_azure_ai_agent_tools(tools, run_options))
|
||||
|
||||
# Handle MCP tool resources
|
||||
mcp_resources = self._prepare_mcp_resources(tools)
|
||||
@@ -1106,82 +1095,6 @@ class AzureAIAgentClient(BaseChatClient[TAzureAIAgentOptions], Generic[TAzureAIA
|
||||
|
||||
return additional_messages, instructions, required_action_results
|
||||
|
||||
async def _prepare_tools_for_azure_ai(
|
||||
self, tools: Sequence["ToolProtocol | MutableMapping[str, Any]"], run_options: dict[str, Any] | None = None
|
||||
) -> list[ToolDefinition | dict[str, Any]]:
|
||||
"""Prepare tool definitions for the Azure AI Agents API."""
|
||||
tool_definitions: list[ToolDefinition | dict[str, Any]] = []
|
||||
for tool in tools:
|
||||
match tool:
|
||||
case AIFunction():
|
||||
tool_definitions.append(tool.to_json_schema_spec()) # type: ignore[reportUnknownArgumentType]
|
||||
case HostedWebSearchTool():
|
||||
additional_props = tool.additional_properties or {}
|
||||
config_args: dict[str, Any] = {}
|
||||
if count := additional_props.get("count"):
|
||||
config_args["count"] = count
|
||||
if freshness := additional_props.get("freshness"):
|
||||
config_args["freshness"] = freshness
|
||||
if market := additional_props.get("market"):
|
||||
config_args["market"] = market
|
||||
if set_lang := additional_props.get("set_lang"):
|
||||
config_args["set_lang"] = set_lang
|
||||
# Bing Grounding
|
||||
connection_id = additional_props.get("connection_id") or os.getenv("BING_CONNECTION_ID")
|
||||
# Custom Bing Search
|
||||
custom_connection_id = additional_props.get("custom_connection_id") or os.getenv(
|
||||
"BING_CUSTOM_CONNECTION_ID"
|
||||
)
|
||||
custom_instance_name = additional_props.get("custom_instance_name") or os.getenv(
|
||||
"BING_CUSTOM_INSTANCE_NAME"
|
||||
)
|
||||
bing_search: BingGroundingTool | BingCustomSearchTool | None = None
|
||||
if (connection_id) and not custom_connection_id and not custom_instance_name:
|
||||
if connection_id:
|
||||
conn_id = connection_id
|
||||
else:
|
||||
raise ServiceInitializationError("Parameter connection_id is not provided.")
|
||||
bing_search = BingGroundingTool(connection_id=conn_id, **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' 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_CUSTOM_CONNECTION_ID', "
|
||||
"'BING_CUSTOM_INSTANCE_NAME'"
|
||||
)
|
||||
tool_definitions.extend(bing_search.definitions)
|
||||
case HostedCodeInterpreterTool():
|
||||
tool_definitions.append(CodeInterpreterToolDefinition())
|
||||
case HostedMCPTool():
|
||||
mcp_tool = McpTool(
|
||||
server_label=tool.name.replace(" ", "_"),
|
||||
server_url=str(tool.url),
|
||||
allowed_tools=list(tool.allowed_tools) if tool.allowed_tools else [],
|
||||
)
|
||||
tool_definitions.extend(mcp_tool.definitions)
|
||||
case HostedFileSearchTool():
|
||||
vector_stores = [inp for inp in tool.inputs or [] if isinstance(inp, HostedVectorStoreContent)]
|
||||
if vector_stores:
|
||||
file_search = FileSearchTool(vector_store_ids=[vs.vector_store_id for vs in vector_stores])
|
||||
tool_definitions.extend(file_search.definitions)
|
||||
# Set tool_resources for file search to work properly with Azure AI
|
||||
if run_options is not None and "tool_resources" not in run_options:
|
||||
run_options["tool_resources"] = file_search.resources
|
||||
case ToolDefinition():
|
||||
tool_definitions.append(tool)
|
||||
case dict():
|
||||
tool_definitions.append(tool)
|
||||
case _:
|
||||
raise ServiceInitializationError(f"Unsupported tool type: {type(tool)}")
|
||||
return tool_definitions
|
||||
|
||||
def _prepare_tool_outputs_for_azure_ai(
|
||||
self,
|
||||
required_action_results: list[FunctionResultContent | FunctionApprovalResponseContent] | None,
|
||||
|
||||
+9
-11
@@ -24,7 +24,7 @@ from azure.ai.projects.models import (
|
||||
PromptAgentDefinitionText,
|
||||
)
|
||||
from azure.core.credentials_async import AsyncTokenCredential
|
||||
from pydantic import BaseModel, ValidationError
|
||||
from pydantic import ValidationError
|
||||
|
||||
from ._client import AzureAIClient
|
||||
from ._shared import AzureAISettings, create_text_format_config, from_azure_ai_tools, to_azure_ai_tools
|
||||
@@ -156,7 +156,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
model: str | None = None,
|
||||
instructions: str | None = None,
|
||||
description: str | None = None,
|
||||
response_format: type[BaseModel] | MutableMapping[str, Any] | None = None,
|
||||
tools: ToolProtocol
|
||||
| Callable[..., Any]
|
||||
| MutableMapping[str, Any]
|
||||
@@ -174,8 +173,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
environment variable if not provided.
|
||||
instructions: Instructions for the agent.
|
||||
description: A description of the agent.
|
||||
response_format: The format of the response. Can be a Pydantic model for structured
|
||||
output, or a dict with JSON schema configuration.
|
||||
tools: Tools to make available to the agent.
|
||||
default_options: A TypedDict containing default chat options for the agent.
|
||||
These options are applied to every run unless overridden.
|
||||
@@ -196,12 +193,18 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
"or set 'AZURE_AI_MODEL_DEPLOYMENT_NAME' environment variable."
|
||||
)
|
||||
|
||||
# Extract response_format from default_options if present
|
||||
opts = dict(default_options) if default_options else {}
|
||||
response_format = opts.get("response_format")
|
||||
|
||||
args: dict[str, Any] = {"model": resolved_model}
|
||||
|
||||
if instructions:
|
||||
args["instructions"] = instructions
|
||||
if response_format:
|
||||
args["text"] = PromptAgentDefinitionText(format=create_text_format_config(response_format))
|
||||
if response_format and isinstance(response_format, (type, dict)):
|
||||
args["text"] = PromptAgentDefinitionText(
|
||||
format=create_text_format_config(response_format) # type: ignore[arg-type]
|
||||
)
|
||||
|
||||
# Normalize tools once and reuse for both Azure AI API and ChatAgent
|
||||
normalized_tools = normalize_tools(tools)
|
||||
@@ -217,7 +220,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
return self._to_chat_agent_from_details(
|
||||
created_agent,
|
||||
normalized_tools,
|
||||
response_format=response_format,
|
||||
default_options=default_options,
|
||||
middleware=middleware,
|
||||
context_provider=context_provider,
|
||||
@@ -333,7 +335,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
self,
|
||||
details: AgentVersionDetails,
|
||||
provided_tools: Sequence[ToolProtocol | MutableMapping[str, Any]] | None = None,
|
||||
response_format: type[BaseModel] | MutableMapping[str, Any] | None = None,
|
||||
default_options: TOptions_co | None = None,
|
||||
middleware: Sequence[Middleware] | None = None,
|
||||
context_provider: ContextProvider | None = None,
|
||||
@@ -344,8 +345,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
details: The AgentVersionDetails containing the agent definition.
|
||||
provided_tools: User-provided tools (including function implementations).
|
||||
These are merged with hosted tools from the definition.
|
||||
response_format: The response format. Can be a Pydantic model for structured
|
||||
output parsing, or a dict with JSON schema for service-side formatting.
|
||||
default_options: A TypedDict containing default chat options for the agent.
|
||||
These options are applied to every run unless overridden.
|
||||
middleware: List of middleware to intercept agent and function invocations.
|
||||
@@ -374,7 +373,6 @@ class AzureAIProjectAgentProvider(Generic[TOptions_co]):
|
||||
instructions=details.definition.instructions,
|
||||
model_id=details.definition.model,
|
||||
tools=merged_tools,
|
||||
response_format=response_format,
|
||||
default_options=default_options, # type: ignore[arg-type]
|
||||
middleware=middleware,
|
||||
context_provider=context_provider,
|
||||
@@ -1,5 +1,6 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import os
|
||||
from collections.abc import Mapping, MutableMapping, Sequence
|
||||
from typing import Any, ClassVar, Literal, cast
|
||||
|
||||
@@ -16,12 +17,19 @@ from agent_framework import (
|
||||
get_logger,
|
||||
)
|
||||
from agent_framework._pydantic import AFBaseSettings
|
||||
from agent_framework.exceptions import ServiceInvalidRequestError
|
||||
from agent_framework.exceptions import ServiceInitializationError, ServiceInvalidRequestError
|
||||
from azure.ai.agents.models import (
|
||||
BingCustomSearchTool,
|
||||
BingGroundingTool,
|
||||
CodeInterpreterToolDefinition,
|
||||
McpTool,
|
||||
ToolDefinition,
|
||||
)
|
||||
from azure.ai.agents.models import FileSearchTool as AgentsFileSearchTool
|
||||
from azure.ai.projects.models import (
|
||||
ApproximateLocation,
|
||||
CodeInterpreterTool,
|
||||
CodeInterpreterToolAuto,
|
||||
FileSearchTool,
|
||||
FunctionTool,
|
||||
MCPTool,
|
||||
ResponseTextFormatConfigurationJsonObject,
|
||||
@@ -30,6 +38,9 @@ from azure.ai.projects.models import (
|
||||
Tool,
|
||||
WebSearchPreviewTool,
|
||||
)
|
||||
from azure.ai.projects.models import (
|
||||
FileSearchTool as ProjectsFileSearchTool,
|
||||
)
|
||||
from pydantic import BaseModel
|
||||
|
||||
logger = get_logger("agent_framework.azure")
|
||||
@@ -76,6 +87,207 @@ class AzureAISettings(AFBaseSettings):
|
||||
model_deployment_name: str | None = None
|
||||
|
||||
|
||||
def to_azure_ai_agent_tools(
|
||||
tools: Sequence[ToolProtocol | MutableMapping[str, Any]] | None,
|
||||
run_options: dict[str, Any] | None = None,
|
||||
) -> list[ToolDefinition | dict[str, Any]]:
|
||||
"""Convert Agent Framework tools to Azure AI V1 SDK tool definitions.
|
||||
|
||||
Args:
|
||||
tools: Sequence of Agent Framework tools to convert.
|
||||
run_options: Optional dict with run options.
|
||||
|
||||
Returns:
|
||||
List of Azure AI V1 SDK tool definitions.
|
||||
|
||||
Raises:
|
||||
ServiceInitializationError: If tool configuration is invalid.
|
||||
"""
|
||||
if not tools:
|
||||
return []
|
||||
|
||||
tool_definitions: list[ToolDefinition | dict[str, Any]] = []
|
||||
for tool in tools:
|
||||
match tool:
|
||||
case AIFunction():
|
||||
tool_definitions.append(tool.to_json_schema_spec()) # type: ignore[reportUnknownArgumentType]
|
||||
case HostedWebSearchTool():
|
||||
additional_props = tool.additional_properties or {}
|
||||
config_args: dict[str, Any] = {}
|
||||
if count := additional_props.get("count"):
|
||||
config_args["count"] = count
|
||||
if freshness := additional_props.get("freshness"):
|
||||
config_args["freshness"] = freshness
|
||||
if market := additional_props.get("market"):
|
||||
config_args["market"] = market
|
||||
if set_lang := additional_props.get("set_lang"):
|
||||
config_args["set_lang"] = set_lang
|
||||
# Bing Grounding
|
||||
connection_id = additional_props.get("connection_id") or os.getenv("BING_CONNECTION_ID")
|
||||
# Custom Bing Search
|
||||
custom_connection_id = additional_props.get("custom_connection_id") or os.getenv(
|
||||
"BING_CUSTOM_CONNECTION_ID"
|
||||
)
|
||||
custom_instance_name = additional_props.get("custom_instance_name") or os.getenv(
|
||||
"BING_CUSTOM_INSTANCE_NAME"
|
||||
)
|
||||
bing_search: BingGroundingTool | BingCustomSearchTool | None = None
|
||||
if connection_id and not custom_connection_id and not custom_instance_name:
|
||||
bing_search = BingGroundingTool(connection_id=connection_id, **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' 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_CUSTOM_CONNECTION_ID', 'BING_CUSTOM_INSTANCE_NAME'"
|
||||
)
|
||||
tool_definitions.extend(bing_search.definitions)
|
||||
case HostedCodeInterpreterTool():
|
||||
tool_definitions.append(CodeInterpreterToolDefinition())
|
||||
case HostedMCPTool():
|
||||
mcp_tool = McpTool(
|
||||
server_label=tool.name.replace(" ", "_"),
|
||||
server_url=str(tool.url),
|
||||
allowed_tools=list(tool.allowed_tools) if tool.allowed_tools else [],
|
||||
)
|
||||
tool_definitions.extend(mcp_tool.definitions)
|
||||
case HostedFileSearchTool():
|
||||
vector_stores = [inp for inp in tool.inputs or [] if isinstance(inp, HostedVectorStoreContent)]
|
||||
if vector_stores:
|
||||
file_search = AgentsFileSearchTool(vector_store_ids=[vs.vector_store_id for vs in vector_stores])
|
||||
tool_definitions.extend(file_search.definitions)
|
||||
# Set tool_resources for file search to work properly with Azure AI
|
||||
if run_options is not None and "tool_resources" not in run_options:
|
||||
run_options["tool_resources"] = file_search.resources
|
||||
case ToolDefinition():
|
||||
tool_definitions.append(tool)
|
||||
case dict():
|
||||
tool_definitions.append(tool)
|
||||
case _:
|
||||
raise ServiceInitializationError(f"Unsupported tool type: {type(tool)}")
|
||||
return tool_definitions
|
||||
|
||||
|
||||
def from_azure_ai_agent_tools(
|
||||
tools: Sequence[ToolDefinition | dict[str, Any]] | None,
|
||||
) -> list[ToolProtocol | dict[str, Any]]:
|
||||
"""Convert Azure AI V1 SDK tool definitions to Agent Framework tools.
|
||||
|
||||
Args:
|
||||
tools: Sequence of Azure AI V1 SDK tool definitions.
|
||||
|
||||
Returns:
|
||||
List of Agent Framework tools.
|
||||
"""
|
||||
if not tools:
|
||||
return []
|
||||
|
||||
result: list[ToolProtocol | dict[str, Any]] = []
|
||||
for tool in tools:
|
||||
# Handle SDK objects
|
||||
if isinstance(tool, CodeInterpreterToolDefinition):
|
||||
result.append(HostedCodeInterpreterTool())
|
||||
elif isinstance(tool, dict):
|
||||
# Handle dict format
|
||||
converted = _convert_dict_tool(tool)
|
||||
if converted is not None:
|
||||
result.append(converted)
|
||||
elif hasattr(tool, "type"):
|
||||
# Handle other SDK objects by type
|
||||
converted = _convert_sdk_tool(tool)
|
||||
if converted is not None:
|
||||
result.append(converted)
|
||||
return result
|
||||
|
||||
|
||||
def _convert_dict_tool(tool: dict[str, Any]) -> ToolProtocol | dict[str, Any] | None:
|
||||
"""Convert a dict-format Azure AI tool to Agent Framework tool."""
|
||||
tool_type = tool.get("type")
|
||||
|
||||
if tool_type == "code_interpreter":
|
||||
return HostedCodeInterpreterTool()
|
||||
|
||||
if tool_type == "file_search":
|
||||
file_search_config = tool.get("file_search", {})
|
||||
vector_store_ids = file_search_config.get("vector_store_ids", [])
|
||||
inputs = [HostedVectorStoreContent(vector_store_id=vs_id) for vs_id in vector_store_ids]
|
||||
return HostedFileSearchTool(inputs=inputs if inputs else None) # type: ignore
|
||||
|
||||
if tool_type == "bing_grounding":
|
||||
bing_config = tool.get("bing_grounding", {})
|
||||
connection_id = bing_config.get("connection_id")
|
||||
return HostedWebSearchTool(additional_properties={"connection_id": connection_id} if connection_id else None)
|
||||
|
||||
if tool_type == "bing_custom_search":
|
||||
bing_config = tool.get("bing_custom_search", {})
|
||||
return HostedWebSearchTool(
|
||||
additional_properties={
|
||||
"custom_connection_id": bing_config.get("connection_id"),
|
||||
"custom_instance_name": bing_config.get("instance_name"),
|
||||
}
|
||||
)
|
||||
|
||||
if tool_type == "mcp":
|
||||
# Hosted MCP tools are defined on the Azure agent, no local handling needed
|
||||
# Azure may not return full server_url, so skip conversion
|
||||
return None
|
||||
|
||||
if tool_type == "function":
|
||||
# Function tools are returned as dicts - users must provide implementations
|
||||
return tool
|
||||
|
||||
# Unknown tool type - pass through
|
||||
return tool
|
||||
|
||||
|
||||
def _convert_sdk_tool(tool: ToolDefinition) -> ToolProtocol | dict[str, Any] | None:
|
||||
"""Convert an SDK-object Azure AI tool to Agent Framework tool."""
|
||||
tool_type = getattr(tool, "type", None)
|
||||
|
||||
if tool_type == "code_interpreter":
|
||||
return HostedCodeInterpreterTool()
|
||||
|
||||
if tool_type == "file_search":
|
||||
file_search_config = getattr(tool, "file_search", None)
|
||||
vector_store_ids = getattr(file_search_config, "vector_store_ids", []) if file_search_config else []
|
||||
inputs = [HostedVectorStoreContent(vector_store_id=vs_id) for vs_id in vector_store_ids]
|
||||
return HostedFileSearchTool(inputs=inputs if inputs else None) # type: ignore
|
||||
|
||||
if tool_type == "bing_grounding":
|
||||
bing_config = getattr(tool, "bing_grounding", None)
|
||||
connection_id = getattr(bing_config, "connection_id", None) if bing_config else None
|
||||
return HostedWebSearchTool(additional_properties={"connection_id": connection_id} if connection_id else None)
|
||||
|
||||
if tool_type == "bing_custom_search":
|
||||
bing_config = getattr(tool, "bing_custom_search", None)
|
||||
return HostedWebSearchTool(
|
||||
additional_properties={
|
||||
"custom_connection_id": getattr(bing_config, "connection_id", None) if bing_config else None,
|
||||
"custom_instance_name": getattr(bing_config, "instance_name", None) if bing_config else None,
|
||||
}
|
||||
)
|
||||
|
||||
if tool_type == "mcp":
|
||||
# Hosted MCP tools are defined on the Azure agent, no local handling needed
|
||||
# Azure may not return full server_url, so skip conversion
|
||||
return None
|
||||
|
||||
if tool_type == "function":
|
||||
# Function tools from SDK don't have implementations - skip
|
||||
return None
|
||||
|
||||
# Unknown tool type - convert to dict if possible
|
||||
if hasattr(tool, "as_dict"):
|
||||
return tool.as_dict() # type: ignore[union-attr]
|
||||
return {"type": tool_type} if tool_type else {}
|
||||
|
||||
|
||||
def from_azure_ai_tools(tools: Sequence[Tool | dict[str, Any]] | None) -> list[ToolProtocol | dict[str, Any]]:
|
||||
"""Parses and converts a sequence of Azure AI tools into Agent Framework compatible tools.
|
||||
|
||||
@@ -130,7 +342,7 @@ def from_azure_ai_tools(tools: Sequence[Tool | dict[str, Any]] | None) -> list[T
|
||||
|
||||
agent_tools.append(HostedCodeInterpreterTool(inputs=ci_inputs if ci_inputs else None)) # type: ignore
|
||||
elif tool_type == "file_search":
|
||||
fs_tool = cast(FileSearchTool, tool_dict)
|
||||
fs_tool = cast(ProjectsFileSearchTool, tool_dict)
|
||||
fs_inputs: list[Contents] = []
|
||||
if "vector_store_ids" in fs_tool:
|
||||
for vs_id in fs_tool["vector_store_ids"]:
|
||||
@@ -210,7 +422,7 @@ def to_azure_ai_tools(
|
||||
raise ValueError(
|
||||
"HostedFileSearchTool requires inputs to be of type `HostedVectorStoreContent`."
|
||||
)
|
||||
fs_tool: FileSearchTool = FileSearchTool(vector_store_ids=vector_store_ids)
|
||||
fs_tool: ProjectsFileSearchTool = ProjectsFileSearchTool(vector_store_ids=vector_store_ids)
|
||||
if tool.max_results:
|
||||
fs_tool["max_num_results"] = tool.max_results
|
||||
azure_tools.append(fs_tool)
|
||||
|
||||
@@ -0,0 +1,803 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import os
|
||||
from typing import Any
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
import pytest
|
||||
from agent_framework import (
|
||||
ChatAgent,
|
||||
HostedCodeInterpreterTool,
|
||||
HostedFileSearchTool,
|
||||
HostedMCPTool,
|
||||
HostedVectorStoreContent,
|
||||
HostedWebSearchTool,
|
||||
ai_function,
|
||||
)
|
||||
from agent_framework.exceptions import ServiceInitializationError
|
||||
from azure.ai.agents.models import (
|
||||
Agent,
|
||||
CodeInterpreterToolDefinition,
|
||||
)
|
||||
from pydantic import BaseModel
|
||||
|
||||
from agent_framework_azure_ai import (
|
||||
AzureAIAgentsProvider,
|
||||
AzureAISettings,
|
||||
)
|
||||
from agent_framework_azure_ai._shared import (
|
||||
from_azure_ai_agent_tools,
|
||||
to_azure_ai_agent_tools,
|
||||
)
|
||||
|
||||
skip_if_azure_ai_integration_tests_disabled = pytest.mark.skipif(
|
||||
os.getenv("RUN_INTEGRATION_TESTS", "false").lower() != "true"
|
||||
or os.getenv("AZURE_AI_PROJECT_ENDPOINT", "") in ("", "https://test-project.cognitiveservices.azure.com/"),
|
||||
reason="No real AZURE_AI_PROJECT_ENDPOINT provided; skipping integration tests."
|
||||
if os.getenv("RUN_INTEGRATION_TESTS", "false").lower() == "true"
|
||||
else "Integration tests are disabled.",
|
||||
)
|
||||
|
||||
|
||||
# region Provider Initialization Tests
|
||||
|
||||
|
||||
def test_provider_init_with_agents_client(mock_agents_client: MagicMock) -> None:
|
||||
"""Test AzureAIAgentsProvider initialization with existing AgentsClient."""
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
assert provider._agents_client is mock_agents_client # type: ignore
|
||||
assert provider._should_close_client is False # type: ignore
|
||||
|
||||
|
||||
def test_provider_init_with_credential(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_azure_credential: MagicMock,
|
||||
) -> None:
|
||||
"""Test AzureAIAgentsProvider initialization with credential."""
|
||||
with patch("agent_framework_azure_ai._agent_provider.AgentsClient") as mock_client_class:
|
||||
mock_client_instance = MagicMock()
|
||||
mock_client_class.return_value = mock_client_instance
|
||||
|
||||
provider = AzureAIAgentsProvider(credential=mock_azure_credential)
|
||||
|
||||
mock_client_class.assert_called_once()
|
||||
assert provider._agents_client is mock_client_instance # type: ignore
|
||||
assert provider._should_close_client is True # type: ignore
|
||||
|
||||
|
||||
def test_provider_init_with_explicit_endpoint(mock_azure_credential: MagicMock) -> None:
|
||||
"""Test AzureAIAgentsProvider initialization with explicit endpoint."""
|
||||
with patch("agent_framework_azure_ai._agent_provider.AgentsClient") as mock_client_class:
|
||||
mock_client_instance = MagicMock()
|
||||
mock_client_class.return_value = mock_client_instance
|
||||
|
||||
provider = AzureAIAgentsProvider(
|
||||
project_endpoint="https://custom-endpoint.com/",
|
||||
credential=mock_azure_credential,
|
||||
)
|
||||
|
||||
mock_client_class.assert_called_once()
|
||||
call_kwargs = mock_client_class.call_args.kwargs
|
||||
assert call_kwargs["endpoint"] == "https://custom-endpoint.com/"
|
||||
assert provider._should_close_client is True # type: ignore
|
||||
|
||||
|
||||
def test_provider_init_missing_endpoint_raises(
|
||||
mock_azure_credential: MagicMock,
|
||||
) -> None:
|
||||
"""Test AzureAIAgentsProvider raises error when endpoint is missing."""
|
||||
# Mock AzureAISettings to return None for project_endpoint
|
||||
with patch("agent_framework_azure_ai._agent_provider.AzureAISettings") as mock_settings_class:
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.project_endpoint = None
|
||||
mock_settings.model_deployment_name = "test-model"
|
||||
mock_settings_class.return_value = mock_settings
|
||||
|
||||
with pytest.raises(ServiceInitializationError) as exc_info:
|
||||
AzureAIAgentsProvider(credential=mock_azure_credential)
|
||||
|
||||
assert "project endpoint is required" in str(exc_info.value).lower()
|
||||
|
||||
|
||||
def test_provider_init_missing_credential_raises(azure_ai_unit_test_env: dict[str, str]) -> None:
|
||||
"""Test AzureAIAgentsProvider raises error when credential is missing."""
|
||||
with pytest.raises(ServiceInitializationError) as exc_info:
|
||||
AzureAIAgentsProvider()
|
||||
|
||||
assert "credential is required" in str(exc_info.value).lower()
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region Context Manager Tests
|
||||
|
||||
|
||||
async def test_provider_context_manager_closes_client(mock_agents_client: MagicMock) -> None:
|
||||
"""Test that context manager closes client when it was created by provider."""
|
||||
with patch("agent_framework_azure_ai._agent_provider.AgentsClient") as mock_client_class:
|
||||
mock_client_instance = AsyncMock()
|
||||
mock_client_class.return_value = mock_client_instance
|
||||
|
||||
with patch.object(AzureAIAgentsProvider, "__init__", lambda self: None): # type: ignore
|
||||
provider = AzureAIAgentsProvider.__new__(AzureAIAgentsProvider)
|
||||
provider._agents_client = mock_client_instance # type: ignore
|
||||
provider._should_close_client = True # type: ignore
|
||||
provider._settings = AzureAISettings(project_endpoint="https://test.com") # type: ignore
|
||||
|
||||
async with provider:
|
||||
pass
|
||||
|
||||
mock_client_instance.close.assert_called_once()
|
||||
|
||||
|
||||
async def test_provider_context_manager_does_not_close_external_client(mock_agents_client: MagicMock) -> None:
|
||||
"""Test that context manager does not close externally provided client."""
|
||||
mock_agents_client.close = AsyncMock()
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
async with provider:
|
||||
pass
|
||||
|
||||
mock_agents_client.close.assert_not_called()
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region create_agent Tests
|
||||
|
||||
|
||||
async def test_create_agent_basic(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test creating a basic agent."""
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "test-agent-id"
|
||||
mock_agent.name = "TestAgent"
|
||||
mock_agent.description = "A test agent"
|
||||
mock_agent.instructions = "Be helpful"
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = 0.7
|
||||
mock_agent.top_p = 0.9
|
||||
mock_agent.tools = []
|
||||
mock_agents_client.create_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
agent = await provider.create_agent(
|
||||
name="TestAgent",
|
||||
instructions="Be helpful",
|
||||
description="A test agent",
|
||||
)
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.name == "TestAgent"
|
||||
assert agent.id == "test-agent-id"
|
||||
mock_agents_client.create_agent.assert_called_once()
|
||||
|
||||
|
||||
async def test_create_agent_with_model(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test creating an agent with explicit model."""
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "test-agent-id"
|
||||
mock_agent.name = "TestAgent"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "custom-model"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = []
|
||||
mock_agents_client.create_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
await provider.create_agent(name="TestAgent", model="custom-model")
|
||||
|
||||
call_kwargs = mock_agents_client.create_agent.call_args.kwargs
|
||||
assert call_kwargs["model"] == "custom-model"
|
||||
|
||||
|
||||
async def test_create_agent_with_tools(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test creating an agent with tools."""
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "test-agent-id"
|
||||
mock_agent.name = "TestAgent"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = []
|
||||
mock_agents_client.create_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
@ai_function
|
||||
def get_weather(city: str) -> str:
|
||||
"""Get weather for a city."""
|
||||
return f"Weather in {city}"
|
||||
|
||||
await provider.create_agent(name="TestAgent", tools=get_weather)
|
||||
|
||||
call_kwargs = mock_agents_client.create_agent.call_args.kwargs
|
||||
assert "tools" in call_kwargs
|
||||
assert len(call_kwargs["tools"]) > 0
|
||||
|
||||
|
||||
async def test_create_agent_with_response_format(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test creating an agent with structured response format via default_options."""
|
||||
|
||||
class WeatherResponse(BaseModel):
|
||||
temperature: float
|
||||
description: str
|
||||
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "test-agent-id"
|
||||
mock_agent.name = "TestAgent"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = []
|
||||
mock_agents_client.create_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
await provider.create_agent(
|
||||
name="TestAgent",
|
||||
default_options={"response_format": WeatherResponse},
|
||||
)
|
||||
|
||||
call_kwargs = mock_agents_client.create_agent.call_args.kwargs
|
||||
assert "response_format" in call_kwargs
|
||||
|
||||
|
||||
async def test_create_agent_missing_model_raises(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test that create_agent raises error when model is not specified."""
|
||||
# Create provider with mocked settings that has no model
|
||||
with patch("agent_framework_azure_ai._agent_provider.AzureAISettings") as mock_settings_class:
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.project_endpoint = "https://test.com"
|
||||
mock_settings.model_deployment_name = None # No model configured
|
||||
mock_settings_class.return_value = mock_settings
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
with pytest.raises(ServiceInitializationError) as exc_info:
|
||||
await provider.create_agent(name="TestAgent")
|
||||
|
||||
assert "model deployment name is required" in str(exc_info.value).lower()
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region get_agent Tests
|
||||
|
||||
|
||||
async def test_get_agent_by_id(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test getting an agent by ID."""
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "existing-agent-id"
|
||||
mock_agent.name = "ExistingAgent"
|
||||
mock_agent.description = "An existing agent"
|
||||
mock_agent.instructions = "Be helpful"
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = 0.7
|
||||
mock_agent.top_p = 0.9
|
||||
mock_agent.tools = []
|
||||
mock_agents_client.get_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
agent = await provider.get_agent("existing-agent-id")
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.id == "existing-agent-id"
|
||||
mock_agents_client.get_agent.assert_called_once_with("existing-agent-id")
|
||||
|
||||
|
||||
async def test_get_agent_with_function_tools(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test getting an agent that has function tools requires tool implementations."""
|
||||
mock_function_tool = MagicMock()
|
||||
mock_function_tool.type = "function"
|
||||
mock_function_tool.function = MagicMock()
|
||||
mock_function_tool.function.name = "get_weather"
|
||||
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "agent-with-tools"
|
||||
mock_agent.name = "AgentWithTools"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = [mock_function_tool]
|
||||
mock_agents_client.get_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
with pytest.raises(ServiceInitializationError) as exc_info:
|
||||
await provider.get_agent("agent-with-tools")
|
||||
|
||||
assert "get_weather" in str(exc_info.value)
|
||||
|
||||
|
||||
async def test_get_agent_with_provided_function_tools(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test getting an agent with function tools when implementations are provided."""
|
||||
mock_function_tool = MagicMock()
|
||||
mock_function_tool.type = "function"
|
||||
mock_function_tool.function = MagicMock()
|
||||
mock_function_tool.function.name = "get_weather"
|
||||
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "agent-with-tools"
|
||||
mock_agent.name = "AgentWithTools"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = [mock_function_tool]
|
||||
mock_agents_client.get_agent = AsyncMock(return_value=mock_agent)
|
||||
|
||||
@ai_function
|
||||
def get_weather(city: str) -> str:
|
||||
"""Get weather for a city."""
|
||||
return f"Weather in {city}"
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
agent = await provider.get_agent("agent-with-tools", tools=get_weather)
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.id == "agent-with-tools"
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region as_agent Tests
|
||||
|
||||
|
||||
def test_as_agent_wraps_without_http(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test as_agent wraps Agent object without making HTTP calls."""
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "wrap-agent-id"
|
||||
mock_agent.name = "WrapAgent"
|
||||
mock_agent.description = "Wrapped agent"
|
||||
mock_agent.instructions = "Be helpful"
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = 0.5
|
||||
mock_agent.top_p = 0.8
|
||||
mock_agent.tools = []
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
agent = provider.as_agent(mock_agent)
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.id == "wrap-agent-id"
|
||||
assert agent.name == "WrapAgent"
|
||||
# Ensure no HTTP calls were made
|
||||
mock_agents_client.get_agent.assert_not_called()
|
||||
mock_agents_client.create_agent.assert_not_called()
|
||||
|
||||
|
||||
def test_as_agent_with_function_tools_validates(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test as_agent validates that function tool implementations are provided."""
|
||||
mock_function_tool = MagicMock()
|
||||
mock_function_tool.type = "function"
|
||||
mock_function_tool.function = MagicMock()
|
||||
mock_function_tool.function.name = "my_function"
|
||||
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "agent-id"
|
||||
mock_agent.name = "Agent"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = [mock_function_tool]
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
with pytest.raises(ServiceInitializationError) as exc_info:
|
||||
provider.as_agent(mock_agent)
|
||||
|
||||
assert "my_function" in str(exc_info.value)
|
||||
|
||||
|
||||
def test_as_agent_with_hosted_tools(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test as_agent handles hosted tools correctly."""
|
||||
mock_code_interpreter = MagicMock()
|
||||
mock_code_interpreter.type = "code_interpreter"
|
||||
|
||||
mock_agent = MagicMock(spec=Agent)
|
||||
mock_agent.id = "agent-id"
|
||||
mock_agent.name = "Agent"
|
||||
mock_agent.description = None
|
||||
mock_agent.instructions = None
|
||||
mock_agent.model = "gpt-4"
|
||||
mock_agent.temperature = None
|
||||
mock_agent.top_p = None
|
||||
mock_agent.tools = [mock_code_interpreter]
|
||||
|
||||
provider = AzureAIAgentsProvider(agents_client=mock_agents_client)
|
||||
|
||||
agent = provider.as_agent(mock_agent)
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
# Should have HostedCodeInterpreterTool in the default_options tools
|
||||
assert any(isinstance(t, HostedCodeInterpreterTool) for t in (agent.default_options.get("tools") or []))
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region Tool Conversion Tests - to_azure_ai_agent_tools
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_empty() -> None:
|
||||
"""Test converting empty tools list."""
|
||||
result = to_azure_ai_agent_tools(None)
|
||||
assert result == []
|
||||
|
||||
result = to_azure_ai_agent_tools([])
|
||||
assert result == []
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_function() -> None:
|
||||
"""Test converting AIFunction to Azure tool definition."""
|
||||
|
||||
@ai_function
|
||||
def get_weather(city: str) -> str:
|
||||
"""Get weather for a city."""
|
||||
return f"Weather in {city}"
|
||||
|
||||
result = to_azure_ai_agent_tools([get_weather])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0]["type"] == "function"
|
||||
assert result[0]["function"]["name"] == "get_weather"
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_code_interpreter() -> None:
|
||||
"""Test converting HostedCodeInterpreterTool."""
|
||||
tool = HostedCodeInterpreterTool()
|
||||
|
||||
result = to_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], CodeInterpreterToolDefinition)
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_file_search() -> None:
|
||||
"""Test converting HostedFileSearchTool with vector stores."""
|
||||
tool = HostedFileSearchTool(inputs=[HostedVectorStoreContent(vector_store_id="vs-123")])
|
||||
run_options: dict[str, Any] = {}
|
||||
|
||||
result = to_azure_ai_agent_tools([tool], run_options)
|
||||
|
||||
assert len(result) == 1
|
||||
assert "tool_resources" in run_options
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_web_search_bing_grounding(monkeypatch: Any) -> None:
|
||||
"""Test converting HostedWebSearchTool for Bing Grounding."""
|
||||
# Use a properly formatted connection ID as required by Azure SDK
|
||||
valid_conn_id = (
|
||||
"/subscriptions/test-sub/resourceGroups/test-rg/"
|
||||
"providers/Microsoft.CognitiveServices/accounts/test-account/"
|
||||
"projects/test-project/connections/test-connection"
|
||||
)
|
||||
monkeypatch.setenv("BING_CONNECTION_ID", valid_conn_id)
|
||||
tool = HostedWebSearchTool()
|
||||
|
||||
result = to_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) > 0
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_web_search_custom(monkeypatch: Any) -> None:
|
||||
"""Test converting HostedWebSearchTool for Custom Bing Search."""
|
||||
monkeypatch.setenv("BING_CUSTOM_CONNECTION_ID", "custom-conn-id")
|
||||
monkeypatch.setenv("BING_CUSTOM_INSTANCE_NAME", "my-instance")
|
||||
tool = HostedWebSearchTool()
|
||||
|
||||
result = to_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) > 0
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_web_search_missing_config(monkeypatch: Any) -> None:
|
||||
"""Test converting HostedWebSearchTool raises error when config is missing."""
|
||||
monkeypatch.delenv("BING_CONNECTION_ID", raising=False)
|
||||
monkeypatch.delenv("BING_CUSTOM_CONNECTION_ID", raising=False)
|
||||
monkeypatch.delenv("BING_CUSTOM_INSTANCE_NAME", raising=False)
|
||||
tool = HostedWebSearchTool()
|
||||
|
||||
with pytest.raises(ServiceInitializationError):
|
||||
to_azure_ai_agent_tools([tool])
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_mcp() -> None:
|
||||
"""Test converting HostedMCPTool."""
|
||||
tool = HostedMCPTool(
|
||||
name="my mcp server",
|
||||
url="https://mcp.example.com",
|
||||
allowed_tools=["tool1", "tool2"],
|
||||
)
|
||||
|
||||
result = to_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) > 0
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_dict_passthrough() -> None:
|
||||
"""Test that dict tools are passed through."""
|
||||
tool = {"type": "custom_tool", "config": {"key": "value"}}
|
||||
|
||||
result = to_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == tool
|
||||
|
||||
|
||||
def test_to_azure_ai_agent_tools_unsupported_type() -> None:
|
||||
"""Test that unsupported tool types raise error."""
|
||||
|
||||
class UnsupportedTool:
|
||||
pass
|
||||
|
||||
with pytest.raises(ServiceInitializationError):
|
||||
to_azure_ai_agent_tools([UnsupportedTool()]) # type: ignore
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region Tool Conversion Tests - from_azure_ai_agent_tools
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_empty() -> None:
|
||||
"""Test converting empty tools list."""
|
||||
result = from_azure_ai_agent_tools(None)
|
||||
assert result == []
|
||||
|
||||
result = from_azure_ai_agent_tools([])
|
||||
assert result == []
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_code_interpreter() -> None:
|
||||
"""Test converting CodeInterpreterToolDefinition."""
|
||||
tool = CodeInterpreterToolDefinition()
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], HostedCodeInterpreterTool)
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_code_interpreter_dict() -> None:
|
||||
"""Test converting code_interpreter dict."""
|
||||
tool = {"type": "code_interpreter"}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], HostedCodeInterpreterTool)
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_file_search_dict() -> None:
|
||||
"""Test converting file_search dict with vector store IDs."""
|
||||
tool = {
|
||||
"type": "file_search",
|
||||
"file_search": {"vector_store_ids": ["vs-123", "vs-456"]},
|
||||
}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], HostedFileSearchTool)
|
||||
assert len(result[0].inputs or []) == 2
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_bing_grounding_dict() -> None:
|
||||
"""Test converting bing_grounding dict."""
|
||||
tool = {
|
||||
"type": "bing_grounding",
|
||||
"bing_grounding": {"connection_id": "conn-123"},
|
||||
}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], HostedWebSearchTool)
|
||||
|
||||
additional_properties = result[0].additional_properties
|
||||
|
||||
assert additional_properties
|
||||
assert additional_properties.get("connection_id") == "conn-123"
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_bing_custom_search_dict() -> None:
|
||||
"""Test converting bing_custom_search dict."""
|
||||
tool = {
|
||||
"type": "bing_custom_search",
|
||||
"bing_custom_search": {
|
||||
"connection_id": "custom-conn",
|
||||
"instance_name": "my-instance",
|
||||
},
|
||||
}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], HostedWebSearchTool)
|
||||
additional_properties = result[0].additional_properties
|
||||
|
||||
assert additional_properties
|
||||
assert additional_properties.get("custom_connection_id") == "custom-conn"
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_mcp_dict() -> None:
|
||||
"""Test that mcp dict is skipped (hosted on Azure, no local handling needed)."""
|
||||
tool = {
|
||||
"type": "mcp",
|
||||
"mcp": {
|
||||
"server_label": "my_server",
|
||||
"server_url": "https://mcp.example.com",
|
||||
"allowed_tools": ["tool1"],
|
||||
},
|
||||
}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
# MCP tools are hosted on Azure agent, skipped in conversion
|
||||
assert len(result) == 0
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_function_dict() -> None:
|
||||
"""Test converting function tool dict (returned as-is)."""
|
||||
tool: dict[str, Any] = {
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": "get_weather",
|
||||
"description": "Get weather",
|
||||
"parameters": {},
|
||||
},
|
||||
}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == tool
|
||||
|
||||
|
||||
def test_from_azure_ai_agent_tools_unknown_dict() -> None:
|
||||
"""Test converting unknown tool type dict."""
|
||||
tool = {"type": "unknown_tool", "config": "value"}
|
||||
|
||||
result = from_azure_ai_agent_tools([tool])
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == tool
|
||||
|
||||
|
||||
# endregion
|
||||
|
||||
|
||||
# region Integration Tests
|
||||
|
||||
|
||||
@skip_if_azure_ai_integration_tests_disabled
|
||||
async def test_integration_create_agent() -> None:
|
||||
"""Integration test: Create an agent using the provider."""
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentsProvider(credential=credential) as provider,
|
||||
):
|
||||
agent = await provider.create_agent(
|
||||
name="IntegrationTestAgent",
|
||||
instructions="You are a helpful assistant for testing.",
|
||||
)
|
||||
|
||||
try:
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.name == "IntegrationTestAgent"
|
||||
assert agent.id is not None
|
||||
finally:
|
||||
# Cleanup: delete the agent
|
||||
if agent.id:
|
||||
await provider._agents_client.delete_agent(agent.id) # type: ignore
|
||||
|
||||
|
||||
@skip_if_azure_ai_integration_tests_disabled
|
||||
async def test_integration_get_agent() -> None:
|
||||
"""Integration test: Get an existing agent using the provider."""
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentsProvider(credential=credential) as provider,
|
||||
):
|
||||
# First create an agent
|
||||
created = await provider._agents_client.create_agent( # type: ignore
|
||||
model=os.getenv("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o"),
|
||||
name="GetAgentTest",
|
||||
instructions="Test agent",
|
||||
)
|
||||
|
||||
try:
|
||||
# Then get it using the provider
|
||||
agent = await provider.get_agent(created.id)
|
||||
|
||||
assert isinstance(agent, ChatAgent)
|
||||
assert agent.id == created.id
|
||||
finally:
|
||||
await provider._agents_client.delete_agent(created.id) # type: ignore
|
||||
|
||||
|
||||
@skip_if_azure_ai_integration_tests_disabled
|
||||
async def test_integration_create_and_run() -> None:
|
||||
"""Integration test: Create an agent and run a conversation."""
|
||||
from azure.identity.aio import AzureCliCredential
|
||||
|
||||
async with (
|
||||
AzureCliCredential() as credential,
|
||||
AzureAIAgentsProvider(credential=credential) as provider,
|
||||
):
|
||||
agent = await provider.create_agent(
|
||||
name="RunTestAgent",
|
||||
instructions="You are a helpful assistant. Always respond with 'Hello!' to any greeting.",
|
||||
)
|
||||
|
||||
try:
|
||||
result = await agent.run("Hi there!")
|
||||
|
||||
assert result is not None
|
||||
assert len(result.messages) > 0
|
||||
finally:
|
||||
if agent.id:
|
||||
await provider._agents_client.delete_agent(agent.id) # type: ignore
|
||||
|
||||
|
||||
# endregion
|
||||
@@ -11,7 +11,6 @@ from agent_framework import (
|
||||
AgentResponse,
|
||||
AgentResponseUpdate,
|
||||
AgentThread,
|
||||
AIFunction,
|
||||
ChatAgent,
|
||||
ChatClientProtocol,
|
||||
ChatMessage,
|
||||
@@ -28,7 +27,6 @@ from agent_framework import (
|
||||
HostedFileSearchTool,
|
||||
HostedMCPTool,
|
||||
HostedVectorStoreContent,
|
||||
HostedWebSearchTool,
|
||||
Role,
|
||||
TextContent,
|
||||
UriContent,
|
||||
@@ -38,7 +36,6 @@ from agent_framework.exceptions import ServiceInitializationError
|
||||
from azure.ai.agents.models import (
|
||||
AgentsNamedToolChoice,
|
||||
AgentsNamedToolChoiceType,
|
||||
CodeInterpreterToolDefinition,
|
||||
FileInfo,
|
||||
MessageDeltaChunk,
|
||||
MessageDeltaTextContent,
|
||||
@@ -672,60 +669,6 @@ def test_azure_ai_chat_client_service_url_method(mock_agents_client: MagicMock)
|
||||
assert url == "https://test-endpoint.com/"
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_ai_function(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with AIFunction tool."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
# Create a mock AIFunction
|
||||
mock_ai_function = MagicMock(spec=AIFunction)
|
||||
mock_ai_function.to_json_schema_spec.return_value = {"type": "function", "function": {"name": "test_function"}}
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([mock_ai_function]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "function", "function": {"name": "test_function"}}
|
||||
mock_ai_function.to_json_schema_spec.assert_called_once()
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_code_interpreter(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with HostedCodeInterpreterTool."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
code_interpreter_tool = HostedCodeInterpreterTool()
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([code_interpreter_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], CodeInterpreterToolDefinition)
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_mcp_tool(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with HostedMCPTool."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
mcp_tool = HostedMCPTool(name="Test MCP Tool", url="https://example.com/mcp", allowed_tools=["tool1", "tool2"])
|
||||
|
||||
# Mock McpTool to have a definitions attribute
|
||||
with patch("agent_framework_azure_ai._chat_client.McpTool") as mock_mcp_tool_class:
|
||||
mock_mcp_tool = MagicMock()
|
||||
mock_mcp_tool.definitions = [{"type": "mcp", "name": "test_mcp"}]
|
||||
mock_mcp_tool_class.return_value = mock_mcp_tool
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([mcp_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "mcp", "name": "test_mcp"}
|
||||
# Check that the call was made (order of allowed_tools may vary)
|
||||
mock_mcp_tool_class.assert_called_once()
|
||||
call_args = mock_mcp_tool_class.call_args[1]
|
||||
assert call_args["server_label"] == "Test_MCP_Tool"
|
||||
assert call_args["server_url"] == "https://example.com/mcp"
|
||||
assert set(call_args["allowed_tools"]) == {"tool1", "tool2"}
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_options_mcp_never_require(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_options with HostedMCPTool having never_require approval mode."""
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
|
||||
@@ -735,8 +678,7 @@ async def test_azure_ai_chat_client_prepare_options_mcp_never_require(mock_agent
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
chat_options: ChatOptions = {"tools": [mcp_tool], "tool_choice": "auto"}
|
||||
|
||||
with patch("agent_framework_azure_ai._chat_client.McpTool") as mock_mcp_tool_class:
|
||||
# Mock _prepare_tools_for_azure_ai to avoid actual tool preparation
|
||||
with patch("agent_framework_azure_ai._shared.McpTool") as mock_mcp_tool_class:
|
||||
mock_mcp_tool_instance = MagicMock()
|
||||
mock_mcp_tool_instance.definitions = [{"type": "mcp", "name": "test_mcp"}]
|
||||
mock_mcp_tool_class.return_value = mock_mcp_tool_instance
|
||||
@@ -768,8 +710,7 @@ async def test_azure_ai_chat_client_prepare_options_mcp_with_headers(mock_agents
|
||||
messages = [ChatMessage(role=Role.USER, text="Hello")]
|
||||
chat_options: ChatOptions = {"tools": [mcp_tool], "tool_choice": "auto"}
|
||||
|
||||
with patch("agent_framework_azure_ai._chat_client.McpTool") as mock_mcp_tool_class:
|
||||
# Mock _prepare_tools_for_azure_ai to avoid actual tool preparation
|
||||
with patch("agent_framework_azure_ai._shared.McpTool") as mock_mcp_tool_class:
|
||||
mock_mcp_tool_instance = MagicMock()
|
||||
mock_mcp_tool_instance.definitions = [{"type": "mcp", "name": "test_mcp"}]
|
||||
mock_mcp_tool_class.return_value = mock_mcp_tool_instance
|
||||
@@ -787,121 +728,6 @@ async def test_azure_ai_chat_client_prepare_options_mcp_with_headers(mock_agents
|
||||
assert mcp_resource["headers"] == headers
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_bing_grounding(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with HostedWebSearchTool using Bing Grounding."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
web_search_tool = HostedWebSearchTool(
|
||||
additional_properties={
|
||||
"connection_id": "test-connection-id",
|
||||
"count": 5,
|
||||
"freshness": "Day",
|
||||
"market": "en-US",
|
||||
"set_lang": "en",
|
||||
}
|
||||
)
|
||||
|
||||
# Mock BingGroundingTool
|
||||
with patch("agent_framework_azure_ai._chat_client.BingGroundingTool") as mock_bing_grounding:
|
||||
mock_bing_tool = MagicMock()
|
||||
mock_bing_tool.definitions = [{"type": "bing_grounding"}]
|
||||
mock_bing_grounding.return_value = mock_bing_tool
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "bing_grounding"}
|
||||
call_args = mock_bing_grounding.call_args[1]
|
||||
assert call_args["count"] == 5
|
||||
assert call_args["freshness"] == "Day"
|
||||
assert call_args["market"] == "en-US"
|
||||
assert call_args["set_lang"] == "en"
|
||||
assert "connection_id" in call_args
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_bing_grounding_with_connection_id(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test _prepare_tools_... with HostedWebSearchTool using Bing Grounding with connection_id (no HTTP call)."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
web_search_tool = HostedWebSearchTool(
|
||||
additional_properties={
|
||||
"connection_id": "direct-connection-id",
|
||||
"count": 3,
|
||||
}
|
||||
)
|
||||
|
||||
# Mock BingGroundingTool
|
||||
with patch("agent_framework_azure_ai._chat_client.BingGroundingTool") as mock_bing_grounding:
|
||||
mock_bing_tool = MagicMock()
|
||||
mock_bing_tool.definitions = [{"type": "bing_grounding"}]
|
||||
mock_bing_grounding.return_value = mock_bing_tool
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "bing_grounding"}
|
||||
mock_bing_grounding.assert_called_once_with(connection_id="direct-connection-id", count=3)
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_custom_bing(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with HostedWebSearchTool using Custom Bing Search."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
web_search_tool = HostedWebSearchTool(
|
||||
additional_properties={
|
||||
"custom_connection_id": "custom-connection-id",
|
||||
"custom_instance_name": "custom-instance",
|
||||
"count": 10,
|
||||
}
|
||||
)
|
||||
|
||||
# Mock BingCustomSearchTool
|
||||
with patch("agent_framework_azure_ai._chat_client.BingCustomSearchTool") as mock_custom_bing:
|
||||
mock_custom_tool = MagicMock()
|
||||
mock_custom_tool.definitions = [{"type": "bing_custom_search"}]
|
||||
mock_custom_bing.return_value = mock_custom_tool
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "bing_custom_search"}
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_file_search_with_vector_stores(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with HostedFileSearchTool using vector stores."""
|
||||
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
vector_store_input = HostedVectorStoreContent(vector_store_id="vs-123")
|
||||
file_search_tool = HostedFileSearchTool(inputs=[vector_store_input])
|
||||
|
||||
# Mock FileSearchTool
|
||||
with patch("agent_framework_azure_ai._chat_client.FileSearchTool") as mock_file_search:
|
||||
mock_file_tool = MagicMock()
|
||||
mock_file_tool.definitions = [{"type": "file_search"}]
|
||||
mock_file_tool.resources = {"vector_store_ids": ["vs-123"]}
|
||||
mock_file_search.return_value = mock_file_tool
|
||||
|
||||
run_options = {}
|
||||
result = await chat_client._prepare_tools_for_azure_ai([file_search_tool], run_options) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == {"type": "file_search"}
|
||||
assert run_options["tool_resources"] == {"vector_store_ids": ["vs-123"]}
|
||||
mock_file_search.assert_called_once_with(vector_store_ids=["vs-123"])
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_create_agent_stream_submit_tool_approvals(
|
||||
mock_agents_client: MagicMock,
|
||||
) -> None:
|
||||
@@ -943,28 +769,6 @@ async def test_azure_ai_chat_client_create_agent_stream_submit_tool_approvals(
|
||||
assert call_args["tool_approvals"][0].approve is True
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_dict_tool(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with dictionary tool definition."""
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
dict_tool = {"type": "custom_tool", "config": {"param": "value"}}
|
||||
|
||||
result = await chat_client._prepare_tools_for_azure_ai([dict_tool]) # type: ignore
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0] == dict_tool
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_unsupported_tool(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _prepare_tools_for_azure_ai with unsupported tool type."""
|
||||
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
|
||||
|
||||
unsupported_tool = "not_a_tool"
|
||||
|
||||
with pytest.raises(ServiceInitializationError, match="Unsupported tool type: <class 'str'>"):
|
||||
await chat_client._prepare_tools_for_azure_ai([unsupported_tool]) # type: ignore
|
||||
|
||||
|
||||
async def test_azure_ai_chat_client_get_active_thread_run_with_active_run(mock_agents_client: MagicMock) -> None:
|
||||
"""Test _get_active_thread_run when there's an active run."""
|
||||
|
||||
|
||||
@@ -86,7 +86,7 @@ def test_provider_init_with_credential_and_endpoint(
|
||||
mock_azure_credential: MagicMock,
|
||||
) -> None:
|
||||
"""Test AzureAIProjectAgentProvider initialization with credential and endpoint."""
|
||||
with patch("agent_framework_azure_ai._provider.AIProjectClient") as mock_ai_project_client:
|
||||
with patch("agent_framework_azure_ai._project_provider.AIProjectClient") as mock_ai_project_client:
|
||||
mock_client = MagicMock()
|
||||
mock_ai_project_client.return_value = mock_client
|
||||
|
||||
@@ -104,7 +104,7 @@ def test_provider_init_with_credential_and_endpoint(
|
||||
|
||||
def test_provider_init_missing_endpoint() -> None:
|
||||
"""Test AzureAIProjectAgentProvider initialization when endpoint is missing."""
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = None
|
||||
mock_settings.return_value.model_deployment_name = "test-model"
|
||||
|
||||
@@ -127,7 +127,7 @@ async def test_provider_create_agent(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
) -> None:
|
||||
"""Test AzureAIProjectAgentProvider.create_agent method."""
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = azure_ai_unit_test_env["AZURE_AI_PROJECT_ENDPOINT"]
|
||||
mock_settings.return_value.model_deployment_name = azure_ai_unit_test_env["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
|
||||
|
||||
@@ -165,7 +165,7 @@ async def test_provider_create_agent_with_env_model(
|
||||
azure_ai_unit_test_env: dict[str, str],
|
||||
) -> None:
|
||||
"""Test AzureAIProjectAgentProvider.create_agent uses model from env var."""
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = azure_ai_unit_test_env["AZURE_AI_PROJECT_ENDPOINT"]
|
||||
mock_settings.return_value.model_deployment_name = azure_ai_unit_test_env["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
|
||||
|
||||
@@ -197,7 +197,7 @@ async def test_provider_create_agent_with_env_model(
|
||||
|
||||
async def test_provider_create_agent_missing_model(mock_project_client: MagicMock) -> None:
|
||||
"""Test AzureAIProjectAgentProvider.create_agent raises when model is missing."""
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = "https://test.com"
|
||||
mock_settings.return_value.model_deployment_name = None
|
||||
|
||||
@@ -326,12 +326,12 @@ def test_provider_as_agent(mock_project_client: MagicMock) -> None:
|
||||
|
||||
async def test_provider_context_manager(mock_project_client: MagicMock) -> None:
|
||||
"""Test AzureAIProjectAgentProvider async context manager."""
|
||||
with patch("agent_framework_azure_ai._provider.AIProjectClient") as mock_ai_project_client:
|
||||
with patch("agent_framework_azure_ai._project_provider.AIProjectClient") as mock_ai_project_client:
|
||||
mock_client = MagicMock()
|
||||
mock_client.close = AsyncMock()
|
||||
mock_ai_project_client.return_value = mock_client
|
||||
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = "https://test.com"
|
||||
mock_settings.return_value.model_deployment_name = "test-model"
|
||||
|
||||
@@ -355,12 +355,12 @@ async def test_provider_context_manager_with_provided_client(mock_project_client
|
||||
|
||||
async def test_provider_close_method(mock_project_client: MagicMock) -> None:
|
||||
"""Test AzureAIProjectAgentProvider.close method."""
|
||||
with patch("agent_framework_azure_ai._provider.AIProjectClient") as mock_ai_project_client:
|
||||
with patch("agent_framework_azure_ai._project_provider.AIProjectClient") as mock_ai_project_client:
|
||||
mock_client = MagicMock()
|
||||
mock_client.close = AsyncMock()
|
||||
mock_ai_project_client.return_value = mock_client
|
||||
|
||||
with patch("agent_framework_azure_ai._provider.AzureAISettings") as mock_settings:
|
||||
with patch("agent_framework_azure_ai._project_provider.AzureAISettings") as mock_settings:
|
||||
mock_settings.return_value.project_endpoint = "https://test.com"
|
||||
mock_settings.return_value.model_deployment_name = "test-model"
|
||||
|
||||
|
||||
@@ -14,6 +14,7 @@ _IMPORTS: dict[str, tuple[str, str]] = {
|
||||
"AzureAISearchContextProvider": ("agent_framework_azure_ai_search", "agent-framework-azure-ai-search"),
|
||||
"AzureAISearchSettings": ("agent_framework_azure_ai_search", "agent-framework-azure-ai-search"),
|
||||
"AzureAISettings": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
|
||||
"AzureAIAgentsProvider": ("agent_framework_azure_ai", "agent-framework-azure-ai"),
|
||||
"AzureOpenAIAssistantsClient": ("agent_framework.azure._assistants_client", "agent-framework-core"),
|
||||
"AzureOpenAIAssistantsOptions": ("agent_framework.azure._assistants_client", "agent-framework-core"),
|
||||
"AzureOpenAIChatClient": ("agent_framework.azure._chat_client", "agent-framework-core"),
|
||||
|
||||
@@ -1,6 +1,12 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
from agent_framework_azure_ai import AzureAIAgentClient, AzureAIClient, AzureAIProjectAgentProvider, AzureAISettings
|
||||
from agent_framework_azure_ai import (
|
||||
AzureAIAgentClient,
|
||||
AzureAIAgentsProvider,
|
||||
AzureAIClient,
|
||||
AzureAIProjectAgentProvider,
|
||||
AzureAISettings,
|
||||
)
|
||||
from agent_framework_azure_ai_search import AzureAISearchContextProvider, AzureAISearchSettings
|
||||
from agent_framework_azurefunctions import (
|
||||
AgentCallbackContext,
|
||||
@@ -20,6 +26,7 @@ __all__ = [
|
||||
"AgentFunctionApp",
|
||||
"AgentResponseCallbackProtocol",
|
||||
"AzureAIAgentClient",
|
||||
"AzureAIAgentsProvider",
|
||||
"AzureAIClient",
|
||||
"AzureAIProjectAgentProvider",
|
||||
"AzureAISearchContextProvider",
|
||||
|
||||
Reference in New Issue
Block a user