azure-ai-agents-py
Build AI agents using the Azure AI Agents Python SDK (azure-ai-agents). Use when creating agents hosted on Azure AI Foundry with tools (File Search, Code Interpreter, Bing Grounding, Azure AI Search, Function Calling, OpenAPI, MCP), managing threads and messages, implementing streaming responses, or working with vector stores. This is the low-level SDK - for higher-level abstractions, use the agent-framework skill instead.
Why use this skill?
Build and manage AI agents on Azure AI Foundry using the azure-ai-agents-py SDK. Leverage code execution, file search, and function calling tools.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/thegovind/azure-ai-agents-pyWhat This Skill Does
The azure-ai-agents-py skill provides a robust interface for interacting with the Azure AI Agents service via the official Python SDK (azure-ai-agents). It enables OpenClaw users to programmatically manage the full lifecycle of AI agents hosted on Azure AI Foundry. This includes creating agents, defining their behavior through instructions, attaching advanced tools like Code Interpreter and Azure AI Search, managing stateful threads, and executing runs to generate intelligent, context-aware responses. By using this skill, developers can build agents capable of performing complex reasoning, RAG (Retrieval-Augmented Generation) over private data, and real-time internet research via Bing Grounding.
Installation
To use this skill within OpenClaw, ensure you have the necessary environment configured with your Azure credentials and project endpoints. Install the skill by running the following command in your terminal:
clawhub install openclaw/skills/skills/thegovind/azure-ai-agents-py
Make sure to set your PROJECT_ENDPOINT and MODEL_DEPLOYMENT_NAME environment variables before initializing the client, as these are critical for the SDK to authenticate and connect to your specific Azure AI Foundry project.
Use Cases
This skill is ideal for enterprise-grade AI automation. Use it for building customer support bots that access internal documentation via File Search, creating autonomous research agents that use Bing Grounding to pull current data, or developing data analysis pipelines that leverage the Code Interpreter tool to perform calculations and generate visualizations. It is particularly effective for workflows requiring long-term memory via threads and message history management.
Example Prompts
- "Initialize a new Azure agent named 'DataAnalyst' using the gpt-4o-mini model, enable Code Interpreter, and attach the file with ID 'file-12345' for analysis."
- "List all active threads in my Azure AI project and retrieve the latest message from the assistant in the thread with ID 'thread-abc-987'."
- "Create a function tool named 'get_weather' and assign it to the 'SupportAgent' so it can provide live weather updates to users."
Tips & Limitations
The azure-ai-agents-py skill is a low-level SDK wrapper. While this provides maximum control over agent configuration, it requires manual handling of runs, polling for status, and thread management. For simpler implementations or higher-level abstractions, consider the agent-framework skill. Always ensure that your AzureIdentity credentials have sufficient permissions for the target project. Monitor your Azure token usage, as active agents can incur costs based on the model deployment and processing volume.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-thegovind-azure-ai-agents-py": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, file-read, file-write, external-api, code-execution
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