Level 200: Practitioner

This code snippet demonstrates how to use agent operations with the Sharepoint tool from the Azure Agents service using a synchronous client. It creates an agent, initializes a Sharepoint tool with a connection ID, and interacts with agents and threads for communication. The code provides a practical implementation of agent orchestration and tool integration within an AI project environment.

This code snippet demonstrates how to use agent operations with a toolset from the Azure Agents service using a synchronous client. It showcases creating an agent with a toolset, enabling auto function calls, creating threads for communication, and sending messages within an agent system.

This code snippet demonstrates how to use agent operations with the OpenAPI tool from the Azure Agents service using custom key authentication against the TripAdvisor API. It showcases setting up connections, loading OpenAPI specs, and initializing an Agent OpenAPI tool. This code provides practical implementation examples for integrating Azure AI services with external APIs.

This code snippet demonstrates how to use the Azure Agents service with OpenAPI tools for agent operations using a synchronous client. It showcases setting up authentication, initializing agent tools with OpenAPI specs, and creating an agent to retrieve weather information and a list of countries. The code provides hands-on experience in integrating Azure AI services and working with OpenAPI specifications.

This code snippet demonstrates how to use agent operations with multiple Model Context Protocol (MCP) servers from the Azure Agents service using a synchronous client. It showcases how to interact with AI models deployed on different MCP servers and manage tools dynamically within the agents.

This code snippet demonstrates how to use Azure Agents service with the Connected Agent tool in Python. It shows how to create multiple agents, such as 'stock_price_bot' and 'weather_bot', and provides instructions for setting up the environment variables and dependencies before running the sample.

This code snippet demonstrates how to use agent operations with custom functions from the Azure Agents service using a synchronous client. It showcases creating an agent, running user requests with function calls, creating threads, messages, and runs, and monitoring the status of the run.

This code snippet demonstrates how to use Agent operations with the Microsoft Fabric grounding tool from the Azure Agents service using a synchronous client. It showcases creating an agent, initializing a Fabric tool, creating threads for communication, and processing an Agent run with tools.

This code snippet demonstrates how to use agent operations with a code interpreter from the Azure Agents service using a synchronous client. It showcases creating an agent, creating a thread, and uploading a local file to Azure for vector store creation.

This code snippet demonstrates how to use agent operations with a code interpreter from the Azure Agents service using a synchronous client. It showcases uploading a file, creating an agent with a code interpreter tool, and creating a message thread within an AI project environment.

This code snippet demonstrates how to create an agent using the Bing grounding tool from the Azure Agents service. It showcases the integration of the Azure AI Project client, agent creation with specific tools, and message handling within a thread, providing insights into building AI agents with specialized functionalities.

This code snippet demonstrates how to use the Azure Agents service with the Bing Custom Search tool to create an agent for performing search operations. It showcases the integration of Azure AI tools for agent orchestration and communication.

The video provides a concise overview of Google Agentspace, explaining its functionality and purpose. It offers a quick insight into building AI agents on Google Cloud, making it a valuable resource for AI developers interested in multi-agent systems and cloud-based AI development.