agents-v2-py
SkillCloud & infraLets your agent build and deploy hosted AI agents that run in custom container images on Azure AI Foundry.
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About this capability
Build container-based Foundry Agents with Azure AI Projects SDK (ImageBasedHostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.
What this skill tells your AI
The instructions your AI receives, as published by sickn33/agentic-awesome-skills in skills/agents-v2-py/SKILL.md and read by ahel’s review.
Compatibility and maintenance
Compatibility alias of hosted-agents-v2-py; use that ID for new references when no existing contract requires this one. The full instructions and support files remain local 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 ImageBasedHostedAgentDefinition from the Azure AI Projects SDK.
Installation
pip install 'azure-ai-projects>=2.0.0b3,<3' azure-identity
These are preview-era SDK v2 sketches. Check the exact installed version and current Azure hosted-agent documentation before provisioning; a broad version range is not an integration test.
Environment Variables
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 your project's managed identity
AcrPullrole on the ACR - Capability Host - Account-level capability host with
enablePublicHostingEnvironment=true - SDK Version - Ensure
azure-ai-projects>=2.0.0b3
Authentication
Use the approved Azure credential flow for the intended tenant/subscription; this sketch uses DefaultAzureCredential:
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
import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
ImageBasedHostedAgentDefinition,
ProtocolVersionRecord,
AgentProtocol,
)
2. Create Hosted Agent
client = AIProjectClient(
endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
credential=DefaultAzureCredential()
)
agent = client.agents.create_version(
agent_name="my-hosted-agent",
definition=ImageBasedHostedAgentDefinition(
container_protocol_versions=[
ProtocolVersionRecord(protocol=AgentProtocol.RESPONSES, version="v1")
],
cpu="1",
memory="2Gi",
image="myregistry.azurecr.io/my-agent:latest",
tools=[{"type": "code_interpreter"}],
environment_variables={
"AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
"MODEL_NAME": "gpt-4o-mini"
}
)
)
print(f"Created agent: {agent.name} (version: {agent.version})")
3. List Agent Versions
versions = client.agents.list_versions(agent_name="my-hosted-agent")
for version in versions:
print(f"Version: {version.version}, State: {version.state}")
4. Delete Agent Version
client.agents.delete_version(
agent_name="my-hosted-agent",
version=agent.version
)
ImageBasedHostedAgentDefinition Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
container_protocol_versions | list[ProtocolVersionRecord] | Yes | Protocol versions the agent supports |
image | str | Yes | Full container image path (registry/image:tag) |
cpu | str | No | CPU allocation (e.g., "1", "2") |
memory | str | No | Memory allocation (e.g., "2Gi", "4Gi") |
tools | list[dict] | No | Tools available to the agent |
environment_variables | dict[str, str] | No | Environment variables for the container |
Protocol Versions
The container_protocol_versions parameter specifies which protocols your agent supports:
from azure.ai.projects.models import ProtocolVersionRecord, AgentProtocol
# RESPONSES protocol - standard agent responses
container_protocol_versions=[
ProtocolVersionRecord(protocol=AgentProtocol.RESPONSES, version="v1")
]
Available Protocols:
| Protocol | Description |
|---|---|
AgentProtocol.RESPONSES | Standard response protocol for agent interactions |
Resource Allocation
Specify CPU and memory for your container:
definition=ImageBasedHostedAgentDefinition(
container_protocol_versions=[...],
image="myregistry.azurecr.io/my-agent:latest",
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
Add tools to your hosted agent:
Code Interpreter
tools=[{"type": "code_interpreter"}]
MCP Tools
tools=[
{"type": "code_interpreter"},
{
"type": "mcp",
"server_label": "my-mcp-server",
"server_url": "https://my-mcp-server.example.com"
}
]
Multiple Tools
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:
environment_variables={
"AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
"MODEL_NAME": "gpt-4o-mini",
"LOG_LEVEL": "INFO",
"CUSTOM_CONFIG": "value"
}
Best Practice: Never hardcode secrets. Use environment variables or Azure Key Vault.
Complete Example
import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import (
ImageBasedHostedAgentDefinition,
ProtocolVersionRecord,
AgentProtocol,
)
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=ImageBasedHostedAgentDefinition(
container_protocol_versions=[
ProtocolVersionRecord(
protocol=AgentProtocol.RESPONSES,
version="v1"
)
],
image="myregistry.azurecr.io/data-processor:v1.0",
cpu="2",
memory="4Gi",
tools=[
{"type": "code_interpreter"},
{"type": "file_search"}
],
environment_variables={
"AZURE_AI_PROJECT_ENDPOINT": os.environ["AZURE_AI_PROJECT_ENDPOINT"],
"MODEL_NAME": "gpt-4o-mini",
"MAX_RETRIES": "3"
}
)
)
print(f"Created hosted agent: {agent.name}")
print(f"Version: {agent.version}")
print(f"State: {agent.state}")
return agent
if __name__ == "__main__":
create_hosted_agent()
Async Pattern
import os
from azure.identity.aio import DefaultAzureCredential
from azure.ai.projects.aio import AIProjectClient
from azure.ai.projects.models import (
ImageBasedHostedAgentDefinition,
ProtocolVersionRecord,
AgentProtocol,
)
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=ImageBasedHostedAgentDefinition(
container_protocol_versions=[
ProtocolVersionRecord(
protocol=AgentProtocol.RESPONSES,
version="v1"
)
],
image="myregistry.azurecr.io/async-agent:latest",
cpu="1",
memory="2Gi"
)
)
return agent
Common Errors
| Error | Cause | Solution |
|---|---|---|
ImagePullBackOff | ACR pull permission denied | Grant AcrPull role to project's managed 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 AgentProtocol.RESPONSES with version "v1" |
Best Practices
- Version Your Images - Use specific tags, not
latestin 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.
Signals
- GitHub stars
- 46k
- Forks
- 7k
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
agents-v2-py-sickn33- Source
- github.com/sickn33/agentic-awesome-skills