Integration with Microsoft Foundry Local for local model inference. Uses foundry_local_sdk (SDK 2.3.1+, below 3.0) on Python 3.11-3.14. Clients share FoundryLocalManager.instance and use its built-in web service with the existing OpenAI transport. Model lifecycle operations live on catalog model objects. The adapter defaults to the public catalog and /v1. Use catalog_type="local" or foundry_local_sdk.catalog.CatalogType.LOCAL for SDK-registered BYOM models: both lookup and HTTP inference use the local catalog and /catalogs/local/v1. Catalogs never fall back to each other; per-request model overrides remain in…
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Integration with Google's Gemini Developer API and Enterprise (Vertex AI) via the google-genai SDK. The shared _sdk_client.create_genai_client resolves authentication, backend mode, and service URL for chat and embeddings. GeminiEmbeddingClient supports only gemini-embedding-2 and gemini-embedding-2-preview, requiring per-call task instructions for text strings. Multimodal Google SDK Content or media Part inputs receive no task prefix, even with mixed text-and-media parts. Text-only SDK content is rejected so callers cannot bypass the task requirement. Enterprise accepts one content per request; the client splits batches…
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Integration with GitHub Copilot extensions. _build_session_kwargs forwards options to the SDK verbatim except for a few keys that get an explicit default: on_permission_request (deny-all) and enable_file_hooks (False, so a session behaves the same way in every working directory). Callers opt in through default_options or per-run options. Keep such defaults to options the working directory controls: options that only shape prompt context (for example enable_host_git_operations) are deliberately left alone. When the agent applies the enable_file_hooks default and the working directory actually…
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Conversion and native card-generation helpers for hosting Agent Framework agents and workflows through an application-owned A2A server. - a2a_to_run(message, *, stream=False) converts an A2A Message to AgentRunArgs; pass input_modes for optional advertised-mode validation. - a2a_from_run(result) converts an Agent Framework response, message, or streaming update to A2A Part values; pass output_modes for optional advertised-mode validation. - await AgentA2AAdapter(target, ...).get_card() creates a native AgentCard from an agent or AgentState, target metadata, and explicit A2A discovery policy. The adapter also re-exposes a2a_to_run(...) and…
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Side-effect-free adapters and conversion helpers for hosting Agent Framework agents and workflows through the native MCP SDK. - AgentMCPTool(target, ...) generates one native MCP Tool from an agent, converts and executes calls, and optionally persists sessions through an existing AgentState. - WorkflowMCPTool(target, ...) derives one native MCP Tool from a workflow's single start-executor input type and converts completed workflow outputs. - mcp_to_run(arguments, *, argument_name="task", chat_option_arguments=()) converts MCP tool arguments to AgentRunArgs and copies only explicitly selected arguments into chat options.…
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Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives. This package contains experimental sub-packages: Lab packages are experimental and may change frequently. They are not included in the standard agent-framework[all] installation. Lab is a standalone uv project, excluded from the root python workspace so its experimental dependencies do not constrain released provider packages. It resolves released Core and provider distributions by default. Run dependency and validation commands from python/packages/lab. Lab code must use APIs available in published…
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Integration with Mem0 for agent memory management. - application_id / agent_id / user_id are the storage scope stamped on written memories. - search_application_id / search_agent_id / search_user_id are the retrieval scope. - Retrieval scope never defaults to the storage scope. With no search_* value set, before_run retrieves nothing and logs a warning. This prevents memories written under a shared agent_id from being retrieved for every user of that agent. Mem0 telemetry is disabled by default. Set MEM0_TELEMETRY=true to enable.
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Monty-backed CodeAct integrations for the Microsoft Agent Framework. [!NOTE] Beta package. Included in agent-framework[all] and available through the lazy-loading namespace agent_framework.monty. - MontyCodeActProvider — ContextProvider that injects a run-scoped execute_code tool plus dynamic CodeAct instructions. Mirrors the HyperlightCodeActProvider API for the parts that apply to a non-sandboxed Python interpreter. - MontyExecuteCodeTool — FunctionTool that wraps the Monty interpreter. Use directly for mixed-tool agents or manual static wiring. Mirrors HyperlightExecuteCodeTool. MontyCodeActProvider and MontyExecuteCodeTool both accept: - tools — host tool callables…
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Integration with TypeSafe AI System One models, including Jev. - TypeSafeChatClient - Adds function invocation, middleware, and telemetry to the TypeSafe transport. - RawTypeSafeChatClient - Provider transport that can emit constrained function calls but does not execute them; it has no function-invocation, middleware, or telemetry layers. - TypeSafeChatOptions - Uses response_format for the required TypeSafe Questions mapping. - Calls always return structured SystemOneResponse data. This provider does not generate free-form chat text. - Every call requires response_format to contain at…
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This file documents the structure and conventions of the Python samples so that agents (AI or human) can maintain them without rediscovering decisions. Durable Task and Azure Functions samples are maintained in the Durable Agent Framework extension. 1. Progressive complexity: Sections 01→05 build from "hello world" to production. Within 01-get-started, files are numbered 01–07 and each step adds exactly one concept. 3. Workflows preserved: 03-workflows/ keeps the upstream folder names and file names intact. Do not rename or restructure workflow…
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Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded project_endpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
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Use this skill when building, modifying, reviewing, evaluating, integrating, or hosting .NET (C#) applications with Microsoft Agent Framework. Use it for Agent Framework agents, harness agents, workflows, orchestrations, declarative definitions, tools, sessions, middleware, evaluation, observability, integrations, or hosting, even when the user has not yet chosen the correct framework pattern.
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Keeps the Language Server Protocol specification and the vscode-languageserver-node TypeScript implementation aligned. Use when adding, changing, reviewing, or auditing LSP requests, notifications, capabilities, registration options, wire types, proposed or final status, since tags, meta-model data, or related documentation across microsoft/language-server-protocol and microsoft/vscode-languageserver-node.
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Read this file at the start of every session. It contains the essential commands, conventions, and architecture knowledge needed to work on this repository. Do not create git commits automatically. The maintainer reviews all changes first and handles commits manually. Make changes locally, run fmt/clippy/tests to verify, and report back. Treat reliability work as a sequence of small contracts, not a broad cleanup or rewrite. A fast demo, a green suite, and a review with no findings do not establish…
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Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md or AGENTS.md?
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
What is a skill?
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Can I search my own team's files too?
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
MicrosoftAGENTS.md