sickn33/antigravity-awesome-skills/hosted-agents-v2-py

Name: hosted-agents-v2-py
Author: sickn33

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Build hosted agents using Azure AI Projects SDK with HostedAgentDefinition. Use when creating container-based agents in Azure AI Foundry.

Install

npx vskill@latest install sickn33/antigravity-awesome-skills/hosted-agents-v2-py

SKILL.md

Compatibility and maintenance

Primary editorial path for this compatibility group. The instruction-only procedure remains local; no executable support files are bundled so existing installations continue to work offline. This is one shared procedure, not an additional capability. 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

bash

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

bash

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

Prerequisites

Before creating hosted agents:

Container Image - Build and push to Azure Container Registry (ACR)
ACR Pull Permissions - Grant the project identity the registry role supported by its permission mode; current hosted-agent guidance uses Container Registry Repository Reader
Capability Host - Confirm current project/region hosted-agent availability and the application's network policy; do not enable public hosting automatically
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:

python

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

python

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

python

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

python

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

python

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

HostedAgentDefinition Parameters

Parameter	Type	Required	Description
`protocol_versions`	`list[ProtocolVersionRecord]`	Yes	Protocol versions the agent supports
`container_configuration`	`ContainerConfiguration`	Yes for an image deployment	Reviewed registry image reference
`cpu`	`str`	No	CPU allocation (e.g., "1", "2")
`memory`	`str`	No	Memory allocation (e.g., "2Gi", "4Gi")
`environment_variables`	`dict[str, str]`	No	Environment variables for the container

Protocol Versions

The protocol_versions parameter specifies which protocols your agent supports:

python

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:

Protocol	Description
`AgentEndpointProtocol.RESPONSES`	Standard response protocol for agent interactions

Resource Allocation

Specify CPU and memory for your container:

python

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:

Resource	Min	Max	Default
CPU	0.5	4	1
Memory	1Gi	8Gi	2Gi

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

python

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

MCP Tools

python

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

Multiple Tools

python

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:

python

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

python

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

python

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

Error	Cause	Solution
`ImagePullBackOff`	ACR pull permission denied	Verify registry permission mode and scoped reader role for the project identity
`InvalidContainerImage`	Image not found	Verify image path and tag exist in ACR
`CapabilityHostNotFound`	No capability host configured	Create account-level capability host
`ProtocolVersionNotSupported`	Invalid protocol version	Use `AgentEndpointProtocol.RESPONSES` with version `"2.0.0"`

Best Practices

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

Reference Links

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.

Security

Security scanPassed, 93 of 100Pattern checks on the skill's files.
Model reviewNot runA model review is scheduled for the next rescan.

See the full security report

Quality evaluation

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Source

SKILL.md in the repositoryCheckingskills/hosted-agents-v2-py/SKILL.md

Popularity

Repository stars: 27,223
Repository forks: 4,596
Repository npm downloads, 7 days: 9,651
7-day trend score: 73

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 25 Mar 2026, 7 months ago.

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