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* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse Simplify the public API by removing redundant 'Chat' prefix from core types: - ChatAgent -> Agent - RawChatAgent -> RawAgent - ChatMessage -> Message - ChatClientProtocol -> SupportsChatGetResponse Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision. No backward compatibility aliases - this is a clean breaking change. * [BREAKING] Rename Agent chat_client parameter to client * Fix rebase issues: WorkflowMessage references and broken markdown links * Fix formatting and lint issues from code quality checks * Fix import ordering in workflow sample files * fixed rebase * Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename - Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests - Fix isinstance check in A2A agent to use A2AMessage instead of Message - Fix import in test_workflow_observability.py (Message→WorkflowMessage) * Fix lint, fmt, and sample errors after ChatMessage→Message rename - Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs) - Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample - Fix _normalize_messages→normalize_messages in custom agent sample - Fix context.terminate→raise MiddlewareTermination in middleware samples - Fix with_update_hook→with_transform_hook in override middleware sample - Add TOptions_co import back to custom_chat_client sample - Add noqa for FastAPI File() default in chatkit sample - Fix B023 loop variable capture in weather agent sample * fix: update Agent constructor calls from chat_client to client in declaration-only tool tests * fix: add register_cleanup to devui lazy-loading proxy and type stub * fixed tests and updated new pieces * fix agui typevar * fix merge errors * fix merge conflicts * fiux merge * Remove unused links --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
0521f5bed8
·
2026-02-10 23:04:32 +00:00
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Agent Examples
This folder contains examples demonstrating how to create and use agents with different chat clients from the Agent Framework. Each sub-folder focuses on a specific provider and client type, showing various capabilities like function tools, code interpreter, thread management, structured outputs, image processing, web search, Model Context Protocol (MCP) integration, and more.
Examples by Provider
Azure AI Foundry Examples
| Folder | Description |
|---|---|
azure_ai_agent/ |
Create agents using Azure AI Agent Service (based on azure-ai-agents V1 package) including function tools, code interpreter, MCP integration, thread management, and more. |
azure_ai/ |
Create agents using Azure AI Agent Service (based on azure-ai-projects V2 package) including function tools, code interpreter, MCP integration, thread management, and more. |
Microsoft Copilot Studio Examples
| Folder | Description |
|---|---|
copilotstudio/ |
Create agents using Microsoft Copilot Studio with streaming and non-streaming responses, authentication handling, and explicit configuration options |
Azure OpenAI Examples
| Folder | Description |
|---|---|
azure_openai/ |
Create agents using Azure OpenAI APIs with multiple client types (Assistants, Chat, and Responses clients) supporting function tools, code interpreter, thread management, and more |
OpenAI Examples
| Folder | Description |
|---|---|
openai/ |
Create agents using OpenAI APIs with comprehensive examples including Assistants, Chat, and Responses clients featuring function tools, code interpreter, file search, web search, MCP integration, image analysis/generation, structured outputs, reasoning, and thread management |
Anthropic Examples
| Folder | Description |
|---|---|
anthropic/ |
Create agents using Anthropic models through OpenAI Chat Client configuration, demonstrating tool calling capabilities |
Custom Implementation Examples
| Folder | Description |
|---|---|
custom/ |
Create custom agents and chat clients by extending the base framework classes, showing complete control over agent behavior and backend integration |