# Agent Framework Azure Ai Py

> Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code int...

- **Type:** Skill
- **Install:** `agentstack add skill-christophacham-agent-skills-library-agent-framework-azure-ai-py`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [christophacham](https://agentstack.voostack.com/s/christophacham)
- **Installs:** 0
- **Category:** [Cloud & Infrastructure](https://agentstack.voostack.com/c/cloud-infrastructure)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [christophacham](https://github.com/christophacham)
- **Source:** https://github.com/christophacham/agent-skills-library/tree/main/skills/ai-ml/agent-framework-azure-ai-py

## Install

```sh
agentstack add skill-christophacham-agent-skills-library-agent-framework-azure-ai-py
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Agent Framework Azure Hosted Agents

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

## Architecture

```
User Query → AzureAIAgentsProvider → Azure AI Agent Service (Persistent)
                    ↓
              Agent.run() / Agent.run_stream()
                    ↓
              Tools: Functions | Hosted (Code/Search/Web) | MCP
                    ↓
              AgentThread (conversation persistence)
```

## Installation

```bash
# Full framework (recommended)
pip install agent-framework --pre

# Or Azure-specific package only
pip install agent-framework-azure-ai --pre
```

## Environment Variables

```bash
export AZURE_AI_PROJECT_ENDPOINT="https://.services.ai.azure.com/api/projects/"
export AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
export BING_CONNECTION_ID="your-bing-connection-id"  # For web search
```

## Authentication

```python
from azure.identity.aio import AzureCliCredential, DefaultAzureCredential

# Development
credential = AzureCliCredential()

# Production
credential = DefaultAzureCredential()
```

## Core Workflow

### Basic Agent

```python
import asyncio
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="MyAgent",
            instructions="You are a helpful assistant.",
        )
        
        result = await agent.run("Hello!")
        print(result.text)

asyncio.run(main())
```

### Agent with Function Tools

```python
from typing import Annotated
from pydantic import Field
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

def get_weather(
    location: Annotated[str, Field(description="City name to get weather for")],
) -> str:
    """Get the current weather for a location."""
    return f"Weather in {location}: 72°F, sunny"

def get_current_time() -> str:
    """Get the current UTC time."""
    from datetime import datetime, timezone
    return datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")

async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="WeatherAgent",
            instructions="You help with weather and time queries.",
            tools=[get_weather, get_current_time],  # Pass functions directly
        )
        
        result = await agent.run("What's the weather in Seattle?")
        print(result.text)
```

### Agent with Hosted Tools

```python
from agent_framework import (
    HostedCodeInterpreterTool,
    HostedFileSearchTool,
    HostedWebSearchTool,
)
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="MultiToolAgent",
            instructions="You can execute code, search files, and search the web.",
            tools=[
                HostedCodeInterpreterTool(),
                HostedWebSearchTool(name="Bing"),
            ],
        )
        
        result = await agent.run("Calculate the factorial of 20 in Python")
        print(result.text)
```

### Streaming Responses

```python
async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="StreamingAgent",
            instructions="You are a helpful assistant.",
        )
        
        print("Agent: ", end="", flush=True)
        async for chunk in agent.run_stream("Tell me a short story"):
            if chunk.text:
                print(chunk.text, end="", flush=True)
        print()
```

### Conversation Threads

```python
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="ChatAgent",
            instructions="You are a helpful assistant.",
            tools=[get_weather],
        )
        
        # Create thread for conversation persistence
        thread = agent.get_new_thread()
        
        # First turn
        result1 = await agent.run("What's the weather in Seattle?", thread=thread)
        print(f"Agent: {result1.text}")
        
        # Second turn - context is maintained
        result2 = await agent.run("What about Portland?", thread=thread)
        print(f"Agent: {result2.text}")
        
        # Save thread ID for later resumption
        print(f"Conversation ID: {thread.conversation_id}")
```

### Structured Outputs

```python
from pydantic import BaseModel, ConfigDict
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

class WeatherResponse(BaseModel):
    model_config = ConfigDict(extra="forbid")
    
    location: str
    temperature: float
    unit: str
    conditions: str

async def main():
    async with (
        AzureCliCredential() as credential,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="StructuredAgent",
            instructions="Provide weather information in structured format.",
            response_format=WeatherResponse,
        )
        
        result = await agent.run("Weather in Seattle?")
        weather = WeatherResponse.model_validate_json(result.text)
        print(f"{weather.location}: {weather.temperature}°{weather.unit}")
```

## Provider Methods

| Method | Description |
|--------|-------------|
| `create_agent()` | Create new agent on Azure AI service |
| `get_agent(agent_id)` | Retrieve existing agent by ID |
| `as_agent(sdk_agent)` | Wrap SDK Agent object (no HTTP call) |

## Hosted Tools Quick Reference

| Tool | Import | Purpose |
|------|--------|---------|
| `HostedCodeInterpreterTool` | `from agent_framework import HostedCodeInterpreterTool` | Execute Python code |
| `HostedFileSearchTool` | `from agent_framework import HostedFileSearchTool` | Search vector stores |
| `HostedWebSearchTool` | `from agent_framework import HostedWebSearchTool` | Bing web search |
| `HostedMCPTool` | `from agent_framework import HostedMCPTool` | Service-managed MCP |
| `MCPStreamableHTTPTool` | `from agent_framework import MCPStreamableHTTPTool` | Client-managed MCP |

## Complete Example

```python
import asyncio
from typing import Annotated
from pydantic import BaseModel, Field
from agent_framework import (
    HostedCodeInterpreterTool,
    HostedWebSearchTool,
    MCPStreamableHTTPTool,
)
from agent_framework.azure import AzureAIAgentsProvider
from azure.identity.aio import AzureCliCredential

def get_weather(
    location: Annotated[str, Field(description="City name")],
) -> str:
    """Get weather for a location."""
    return f"Weather in {location}: 72°F, sunny"

class AnalysisResult(BaseModel):
    summary: str
    key_findings: list[str]
    confidence: float

async def main():
    async with (
        AzureCliCredential() as credential,
        MCPStreamableHTTPTool(
            name="Docs MCP",
            url="https://learn.microsoft.com/api/mcp",
        ) as mcp_tool,
        AzureAIAgentsProvider(credential=credential) as provider,
    ):
        agent = await provider.create_agent(
            name="ResearchAssistant",
            instructions="You are a research assistant with multiple capabilities.",
            tools=[
                get_weather,
                HostedCodeInterpreterTool(),
                HostedWebSearchTool(name="Bing"),
                mcp_tool,
            ],
        )
        
        thread = agent.get_new_thread()
        
        # Non-streaming
        result = await agent.run(
            "Search for Python best practices and summarize",
            thread=thread,
        )
        print(f"Response: {result.text}")
        
        # Streaming
        print("\nStreaming: ", end="")
        async for chunk in agent.run_stream("Continue with examples", thread=thread):
            if chunk.text:
                print(chunk.text, end="", flush=True)
        print()
        
        # Structured output
        result = await agent.run(
            "Analyze findings",
            thread=thread,
            response_format=AnalysisResult,
        )
        analysis = AnalysisResult.model_validate_json(result.text)
        print(f"\nConfidence: {analysis.confidence}")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conventions

- Always use async context managers: `async with provider:`
- Pass functions directly to `tools=` parameter (auto-converted to AIFunction)
- Use `Annotated[type, Field(description=...)]` for function parameters
- Use `get_new_thread()` for multi-turn conversations
- Prefer `HostedMCPTool` for service-managed MCP, `MCPStreamableHTTPTool` for client-managed

## Reference Files

- references/tools.md: Detailed hosted tool patterns
- references/mcp.md: MCP integration (hosted + local)
- references/threads.md: Thread and conversation management
- references/advanced.md: OpenAPI, citations, structured outputs

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [christophacham](https://github.com/christophacham)
- **Source:** [christophacham/agent-skills-library](https://github.com/christophacham/agent-skills-library)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-christophacham-agent-skills-library-agent-framework-azure-ai-py
- Seller: https://agentstack.voostack.com/s/christophacham
- Browse the marketplace: https://agentstack.voostack.com/browse

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