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Eduard van Valkenburg
0cd40f8354
* [BREAKING] Refactor middleware layering and raw clients Reorder chat client layers so function invocation wraps chat middleware, and chat middleware stays outside telemetry while still running for each inner model call. Add middleware pipeline caching, refresh docs and samples, and split Anthropic into raw and public clients to match the standard layering model. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten typing ignores in ancillary modules Add targeted typing ignores in workflow visualization and lab modules so pyright stays clean alongside the middleware refactor work. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix categorize_middleware to unpack tuple/Sequence and use relative MRO assertions - Broaden isinstance check in categorize_middleware from list to Sequence so tuples and other Sequence types are properly unpacked instead of being appended as a single item. - Replace fragile hardcoded MRO index assertions in anthropic test with relative ordering via mro.index(). - Add regression tests for categorize_middleware with tuple, list, and None inputs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix middleware string decomposition, add middleware param to FunctionInvocationLayer, and add tests (#4710) - Guard categorize_middleware Sequence check against str/bytes to prevent character-by-character decomposition of accidentally passed strings - Add explicit middleware parameter to FunctionInvocationLayer.get_response and merge it into client_kwargs before categorization, fixing the inconsistency where only OpenAIChatClient supported this parameter - Add assertions that RawAnthropicClient does not inherit convenience layers - Add chat middleware cache test with non-empty base middleware - Add tests for single unwrapped middleware item and string input Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Apply pre-commit auto-fixes * Address review feedback for #4710: review comment fixes --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com>
0cd40f8354
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2026-03-20 00:43:37 +00:00
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Provider Samples Overview
This directory groups provider-specific samples for Agent Framework.
| Folder | What you will find |
|---|---|
anthropic/ |
Anthropic Claude samples using both AnthropicClient and ClaudeAgent, including tools, MCP, sessions, and Foundry Anthropic integration. |
amazon/ |
AWS Bedrock samples using BedrockChatClient, including tool-enabled agent usage. |
azure_ai/ |
Azure AI Foundry V2 (azure-ai-projects) samples with AzureAIClient, from basic setup to advanced patterns like search, memory, A2A, MCP, and provider methods. |
azure_ai_agent/ |
Azure AI Foundry V1 (azure-ai-agents) samples with AzureAIAgentsProvider, including provider methods and common hosted tool integrations. |
azure_openai/ |
Azure OpenAI samples for Assistants, Chat, and Responses clients, with examples for sessions, tools, MCP, file search, and code interpreter. |
copilotstudio/ |
Microsoft Copilot Studio agent samples, including required environment/app registration setup and explicit authentication patterns. |
custom/ |
Framework extensibility samples for building custom BaseAgent and BaseChatClient implementations, including layer-composition guidance. |
foundry_local/ |
Foundry Local samples using FoundryLocalClient for local model inference with streaming, non-streaming, and tool-calling patterns. |
github_copilot/ |
GitHubCopilotAgent samples showing basic usage, session handling, permission-scoped shell/file/url access, and MCP integration. |
ollama/ |
Local Ollama samples using OllamaChatClient (recommended) plus OpenAI-compatible Ollama setup, including reasoning and multimodal examples. |
openai/ |
OpenAI provider samples for Assistants, Chat, and Responses clients, including tools, structured output, sessions, MCP, web search, and multimodal tasks. |
Each folder has its own README with setup requirements and file-by-file details.