Agents V2 Py

Compatibility and maintenance

Compatibility alias of hosted-agents-v2-py; use that ID for new references when no existing contract requires this one. The instruction-only procedure remains local; no executable support files are bundled so existing installations continue to work offline. This compatibility guide documents the hosted-agent procedure, not an additional capability; older copies may use retired preview names. Preserve the callable ID when an existing manifest or client configuration uses it. Modified in AAS on 2026-09-05; original metadata and license notices are retained.

Azure AI Hosted Agents (Python)

Build container-based hosted agents using HostedAgentDefinition from the Azure AI Projects SDK.

Installation

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pip install 'azure-ai-projects==2.3.0' azure-identity

These are SDK 2.3.0 instruction fragments aligned with the current Microsoft hosted-agent guide. Validate the installed schema and service support before provisioning; documentation inspection is not a cloud integration test.

Environment Variables

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export AZURE_AI_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"

Prerequisites

Before creating hosted agents:

1. Container Image - Build and push to Azure Container Registry (ACR)
2. ACR Pull Permissions - Grant the project identity the registry role supported by its permission mode; current hosted-agent guidance uses Container Registry Repository Reader
3. Capability Host - Confirm current project/region hosted-agent availability and the application's network policy; do not enable public hosting automatically
4. SDK Version - Ensure azure-ai-projects==2.3.0

Authentication

Use the approved Azure credential flow for the intended tenant/subscription; this sketch uses DefaultAzureCredential:

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from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient

import os

credential = DefaultAzureCredential()
client = AIProjectClient(
    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
    credential=credential
)

Core Workflow

1. Imports

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import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
    HostedAgentDefinition,
    ContainerConfiguration,
    ProtocolVersionRecord,
    AgentEndpointProtocol,
)

2. Create Hosted Agent

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client = AIProjectClient(
    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
    credential=DefaultAzureCredential()
)

agent = client.agents.create_version(
    agent_name="my-hosted-agent",
    definition=HostedAgentDefinition(
        protocol_versions=[
            ProtocolVersionRecord(protocol=AgentEndpointProtocol.RESPONSES, version="2.0.0")
        ],
        cpu="1",
        memory="2Gi",
        container_configuration=ContainerConfiguration(image=os.environ["REVIEWED_CONTAINER_IMAGE"]),
        environment_variables={
            "AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
            "MODEL_NAME": os.environ["MODEL_DEPLOYMENT_NAME"]
        }
    )
)

print(f"Created agent: {agent.name} (version: {agent.version})")

3. List Agent Versions

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versions = client.agents.list_versions(agent_name="my-hosted-agent")
for version in versions:
    print(f"Version: {version.version}")  # Inspect supported status fields via get_version

Inspect the exact returned model for supported fields; a created version is not proof a running container is healthy. Close synchronous client/credential resources through their supported context managers or close() methods.

4. Delete Agent Version

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client.agents.delete_version(
    agent_name="my-hosted-agent",
    agent_version=agent.version
)

HostedAgentDefinition Parameters

Protocol Versions

The protocol_versions parameter specifies which protocols your agent supports:

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from azure.ai.projects.models import ProtocolVersionRecord, AgentEndpointProtocol

# RESPONSES protocol - standard agent responses
protocol_versions=[
    ProtocolVersionRecord(protocol=AgentEndpointProtocol.RESPONSES, version="2.0.0")
]

Available Protocols:

Resource Allocation

Specify CPU and memory for your container:

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definition=HostedAgentDefinition(
    protocol_versions=[...],
    container_configuration=ContainerConfiguration(image=os.environ["REVIEWED_CONTAINER_IMAGE"]),
    cpu="2",      # 2 CPU cores
    memory="4Gi"  # 4 GiB memory
)

Illustrative resource sizes; verify regional/SKU limits before provisioning:

Tools Configuration

Configure tool support inside the selected container runtime/framework. The following tool dictionaries describe application-specific intent; do not assume a tools field exists on HostedAgentDefinition or that defining it provisions a tool or grants permission:

Code Interpreter

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tools=[{"type": "code_interpreter"}]

MCP Tools

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tools=[
    {"type": "code_interpreter"},
    {
        "type": "mcp",
        "server_label": "my-mcp-server",
        "server_url": "https://my-mcp-server.example.com"
    }
]

Multiple Tools

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tools=[
    {"type": "code_interpreter"},
    {"type": "file_search"},
    {
        "type": "mcp",
        "server_label": "custom-tool",
        "server_url": "https://custom-tool.example.com"
    }
]

Environment Variables

Pass configuration to your container:

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environment_variables={
    "AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
    "MODEL_NAME": os.environ["MODEL_DEPLOYMENT_NAME"],
    "LOG_LEVEL": "INFO",
    "CUSTOM_CONFIG": "value"
}

Best Practice: Keep non-secret deployment names and a reviewed immutable image reference in configuration; secrets need the platform's actual protected injection mechanism. Arbitrary environment dictionaries do not establish Key Vault integration.

Complete Example

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import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
    HostedAgentDefinition,
    ContainerConfiguration,
    ProtocolVersionRecord,
    AgentEndpointProtocol,
)

def create_hosted_agent():
    """Create a hosted agent with custom container image."""
    
    client = AIProjectClient(
        endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
        credential=DefaultAzureCredential()
    )
    
    agent = client.agents.create_version(
        agent_name="data-processor-agent",
        definition=HostedAgentDefinition(
            protocol_versions=[
                ProtocolVersionRecord(
                    protocol=AgentEndpointProtocol.RESPONSES,
                    version="2.0.0"
                )
            ],
            container_configuration=ContainerConfiguration(image=os.environ["REVIEWED_CONTAINER_IMAGE"]),
            cpu="2",
            memory="4Gi",
            environment_variables={
                "AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
                "MODEL_NAME": os.environ["MODEL_DEPLOYMENT_NAME"],
                "MAX_RETRIES": "3"
            }
        )
    )
    
    print(f"Created hosted agent: {agent.name}")
    print(f"Version: {agent.version}")
    # Poll get_version status with a deadline before treating deployment as active.
    
    return agent

if __name__ == "__main__":
    create_hosted_agent()

Async Pattern

pythonCopy code
import os
from azure.identity.aio import DefaultAzureCredential
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
    HostedAgentDefinition,
    ContainerConfiguration,
    ProtocolVersionRecord,
    AgentEndpointProtocol,
)

async def create_hosted_agent_async():
    """Create a hosted agent asynchronously."""
    
    async with DefaultAzureCredential() as credential:
        async with AIProjectClient(
            endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
            credential=credential
        ) as client:
            agent = await client.agents.create_version(
                agent_name="async-agent",
                definition=HostedAgentDefinition(
                    protocol_versions=[
                        ProtocolVersionRecord(
                            protocol=AgentEndpointProtocol.RESPONSES,
                            version="2.0.0"
                        )
                    ],
                    container_configuration=ContainerConfiguration(image=os.environ["REVIEWED_CONTAINER_IMAGE"]),
                    cpu="1",
                    memory="2Gi"
                )
            )
            return agent

Common Errors

Best Practices

1. Version Your Images - Use specific tags, not latest in production
2. Minimal Resources - Start with minimum CPU/memory, scale up as needed
3. Environment Variables - Use for all configuration, never hardcode
4. Error Handling - Wrap agent creation in try/except blocks
5. Cleanup - Delete unused agent versions to free resources

Reference Links

• Azure AI Projects SDK
• Hosted Agents Documentation
• Azure Container Registry

When to Use

Use for reviewing or creating an explicitly requested container-based Foundry hosted agent. First confirm image digest, subscription/tenant, region, service availability, permissions and cost scope. Creating agents, granting roles and deleting versions are cloud writes; do them only within the user's authorization.

Review example

Given a pinned container image and test project, check SDK model fields and registry pull access, then prepare the create request. Provision only if authorized and record the exact returned version and observed health. Do not delete unrelated versions as routine cleanup. Expected result is a version-specific receipt, not an assumed deploy.

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.