hosted-agents-v2-py

仓库: sickn33/antigravity-awesome-skills
安装量: 44
排名: #16739

安装

npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill hosted-agents-v2-py

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 azure-identity Minimum SDK Version: 2.0.0b3 or later required for hosted agent support. 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 AcrPull role on the ACR Capability Host - Account-level capability host with enablePublicHostingEnvironment=true SDK Version - Ensure azure-ai-projects>=2.0.0b3 Authentication Always use DefaultAzureCredential : from azure . identity import DefaultAzureCredential from azure . ai . projects import AIProjectClient 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

) Resource Limits: 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 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 Azure AI Projects SDK Hosted Agents Documentation Azure Container Registry When to Use This skill is applicable to execute the workflow or actions described in the overview.

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