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MicrosoftReads credentialsAGENTS.mdmicrosoft/agent-framework/python/packages/mistral/AGENTS.md
Integration with Mistral AI for chat completions and embedding generation.
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MicrosoftAGENTS.mdmicrosoft/agent-framework/python/packages/monty/AGENTS.md
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…
MicrosoftReads credentialsAGENTS.mdmicrosoft/agent-framework/python/packages/nvidia/AGENTS.md
Integration with NVIDIA NIM for embedding generation. - NVIDIA NIM exposes an OpenAI-compatible endpoint, so this package builds on RawOpenAIEmbeddingClient from agent-framework-openai rather than reimplementing the wire format. This mirrors agent-framework-foundry-local, which builds on the OpenAI Chat Completions client for the same reason. - The default endpoint is https://integrate.api.nvidia.com/v1. base_url overrides it, which is the hook for a self-hosted NIM container. - Model availability is per-account. An unentitled model returns 404 ... Not found for account, and a retired model…
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MicrosoftAGENTS.mdmicrosoft/agent-framework/python/packages/ollama/AGENTS.md
Integration with Ollama for local LLM inference.
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MicrosoftReads credentialsAGENTS.mdmicrosoft/agent-framework/python/packages/openai/AGENTS.md
OpenAI integration package for Agent Framework. Contains OpenAI Responses API and Chat Completions API clients. All clients follow the Raw + Full-Featured pattern (e.g., RawOpenAIChatClient + OpenAIChatClient). For Responses API continuation with service-side storage, a prior hosted function_approval_request is server-issued and must not be replayed inline, while the new hosted function_approval_response is serialized as mcp_approval_response so the user's approved or rejected decision reaches the service. Local FunctionTool approval controls are resolved in-process and must not be serialized as MCP items.…
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MicrosoftAGENTS.mdmicrosoft/agent-framework/python/packages/purview/AGENTS.md
Integration with Microsoft Purview for data governance and policy enforcement.
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MicrosoftReads credentialsAGENTS.mdmicrosoft/agent-framework/python/packages/redis/AGENTS.md
Redis-based storage for agent threads and context. - RedisHistoryProvider - Persistent chat history provider using scoped Redis keys. Scoped mode requires an application ID and non-empty session ID, and can additionally isolate tenants and agents. Use explicit legacy mode only while deliberately migrating historical keys; scoped mode never accesses them automatically. It can construct an owned client from a URL or credential provider, or borrow a standalone async Redis client configured with decode_responses=True; borrowed clients remain caller-owned. - RedisContextProvider -…
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MicrosoftAGENTS.mdmicrosoft/agent-framework/python/packages/typesafe/AGENTS.md
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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MicrosoftAGENTS.mdmicrosoft/agent-framework/python/samples/AGENTS.md
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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MicrosoftAGENTS.mdmicrosoft/presidio/AGENTS.md
Presidio is a Python SDK for detecting (presidio-analyzer) and anonymizing (presidio-anonymizer) PII in text and images, plus CLI, structured-data, and image-redaction components. It is a widely used library: users depend on current detection behavior, and configuration files written years ago must keep working. Correctness and backward compatibility outrank cleverness. The review-side versions of these rules — which the Copilot PR review agent also enforces — live in .github/copilot-instructions.md and .github/instructions/*.instructions.md. Follow them at authoring time; the pre-PR check below verifies…
MicrosoftAGENTS.mdmicrosoft/winget-pkgs/AGENTS.md
Follow .github/copilot-instructions.md for repository-specific development guidance. Before filing a GitHub issue in this repository: Before opening a pull request:
MicrosoftAGENTS.mdmicrosoft/fluentui-system-icons/AGENTS.md
No summary in the file. Open it to read it.
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An open format for instructions to coding agents, read by Codex, Cursor and others. Think of it as a README written for agents.
At the repository root, with more specific files in subdirectories. Agents read the one closest to the file they're editing.
Setup and test commands, code style, and the rules a new contributor would need to know.
Claude Code reads CLAUDE.md. A one-line CLAUDE.md that points at AGENTS.md covers both.
