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Eduard van Valkenburg
977c3adfb2
* python: replace pre-commit with prek, add PEP 723 script deps, clean up dev dependencies - Replace pre-commit with prek (Rust-native, faster pre-commit alternative) - Move supported hooks to repo: builtin for zero-clone speed - Add new builtin hooks: trailing-whitespace, check-merge-conflict, detect-private-key, check-added-large-files - Update all hook versions to latest (pre-commit-hooks v6, pyupgrade v3.21.2, bandit 1.9.3, uv-pre-commit 0.10.0) - Add PEP 723 inline script metadata to 34 samples with external deps - Remove autogen-agentchat/autogen-ext from dev deps (now declared per-sample) - Remove unused dev deps: pytest-env, tomli-w - Add agent-framework-core>=1.0.0b260130 lower bound to all 21 packages - Update CI workflow to use j178/prek-action - Update docs: DEV_SETUP.md, AGENTS.md, CODING_STANDARD.md, SAMPLE_GUIDELINES.md * updated lock * python: fix prek config paths for local execution and CI workflow Remove global 'files: ^python/' filter and strip python/ prefix from all path patterns in .pre-commit-config.yaml so prek finds files when run from the python/ directory. Update CI workflow to use --cd python instead of --config path. Include trailing whitespace fixes and dev dependency cleanup. * python: move helper scripts to scripts/ folder and exclude from checks * python: exclude AGENTS.md from prek markdown code lint * python: exclude AGENTS.md and azure_ai_search sample from markdown lint * fix m365 sample * python: ignore CPY rule for samples with PEP 723 headers * fix in dev_setup * python: replace aiofiles with regular open in samples * python: suppress reportUnusedImport in markdown code block checker * python: use samples pyright config for markdown code block checker Write a temp pyrightconfig.json matching pyrightconfig.samples.json rules (typeCheckingMode=off, only reportMissingImports and reportAttributeAccessIssue). Filter output to only fail on these rules since syntax-level errors (top-level await, undefined vars) are expected in README documentation snippets. * python: use markdown-code-lint with fixed globs instead of prek file list The prek-markdown-code-lint task received all changed files including non-README markdown and files with pre-existing broken imports. Replace with the standard markdown-code-lint task which uses the correct glob patterns (README.md, packages/**/README.md, samples/**/*.md). * python: exclude READMEs with pre-existing broken imports from markdown lint * python: fix broken README code snippets instead of excluding them - ag-ui: replace TextContent (removed) with content.type == 'text' - durabletask: fix import path to durabletask.worker.TaskHubGrpcWorker - orchestrations: use constructor params instead of .participants() method - observability: mark deprecated code blocks as plain text, filter reportMissingImports to agent_framework modules only - remove README excludes from markdown-code-lint task * add revision to gaia download * feat(python): parallelize checks across packages Run (package × task) cross-product in parallel using ThreadPoolExecutor and subprocesses. Key changes: - Add scripts/task_runner.py with shared parallel execution engine - Update run_tasks_in_packages_if_exists.py to accept multiple tasks - Update run_tasks_in_changed_packages.py with --files flag and parallel support - Add check-packages poe task (fmt+lint+pyright+mypy in parallel) - Add prek-markdown-code-lint and prek-samples-check with change detection - Split CI code quality workflow into parallel prek and mypy jobs - Update DEV_SETUP.md to document new parallel behavior Core package changes still trigger checks on all packages. * feat(ci): split code quality into 4 parallel jobs Split the single prek job into parallel jobs: - pre-commit-hooks: lightweight hooks (SKIP=poe-check) - package-checks: fmt/lint/pyright/mypy via check-packages - samples-markdown: samples-lint, samples-syntax, markdown-code-lint - mypy: change-detected mypy checks All 4 jobs run concurrently (×2 Python versions = 8 runners). * feat(ci): use only Python 3.10 for code quality checks * refactor(python): add future annotations and remove quoted types Add `from __future__ import annotations` to 93 package files that used quoted string annotations, then run pyupgrade --py310-plus to remove the now-unnecessary quotes. Fixes https://github.com/microsoft/agent-framework/issues/3578
977c3adfb2
·
2026-02-09 17:51:01 +00:00
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Python Samples
This directory contains samples demonstrating the capabilities of Microsoft Agent Framework for Python.
Agents
A2A (Agent-to-Agent)
| File | Description |
|---|---|
getting_started/agents/a2a/agent_with_a2a.py |
Agent2Agent (A2A) Protocol Integration Sample |
Anthropic
| File | Description |
|---|---|
getting_started/agents/anthropic/anthropic_basic.py |
Agent with Anthropic Client |
getting_started/agents/anthropic/anthropic_advanced.py |
Advanced sample with thinking and hosted tools. |
Azure AI (based on azure-ai-agents V1 package)
Azure AI (based on azure-ai-projects V2 package)
Azure OpenAI
Copilot Studio
| File | Description |
|---|---|
getting_started/agents/copilotstudio/copilotstudio_basic.py |
Copilot Studio Agent Basic Example |
getting_started/agents/copilotstudio/copilotstudio_with_explicit_settings.py |
Copilot Studio Agent with Explicit Settings Example |
Custom
| File | Description |
|---|---|
getting_started/agents/custom/custom_agent.py |
Custom Agent Implementation Example |
getting_started/chat_client/custom_chat_client.py |
Custom Chat Client Implementation Example |
Ollama
The recommended way to use Ollama is via the native OllamaChatClient from the agent-framework-ollama package.
| File | Description |
|---|---|
getting_started/agents/ollama/ollama_agent_basic.py |
Basic Ollama Agent with native Ollama Chat Client |
getting_started/agents/ollama/ollama_agent_reasoning.py |
Ollama Agent with reasoning capabilities |
getting_started/agents/ollama/ollama_chat_client.py |
Direct usage of Ollama Chat Client |
getting_started/agents/ollama/ollama_chat_multimodal.py |
Ollama Chat Client with multimodal (image) input |
getting_started/agents/ollama/ollama_with_openai_chat_client.py |
Alternative: Ollama via OpenAI Chat Client |
OpenAI
Chat Client
| File | Description |
|---|---|
getting_started/chat_client/azure_ai_chat_client.py |
Azure AI Chat Client Direct Usage Example |
getting_started/chat_client/azure_assistants_client.py |
Azure OpenAI Assistants Client Direct Usage Example |
getting_started/chat_client/azure_chat_client.py |
Azure Chat Client Direct Usage Example |
getting_started/chat_client/azure_responses_client.py |
Azure OpenAI Responses Client Direct Usage Example |
getting_started/chat_client/chat_response_cancellation.py |
Chat Response Cancellation Example |
getting_started/chat_client/openai_assistants_client.py |
OpenAI Assistants Client Direct Usage Example |
getting_started/chat_client/openai_chat_client.py |
OpenAI Chat Client Direct Usage Example |
getting_started/chat_client/openai_responses_client.py |
OpenAI Responses Client Direct Usage Example |
Context Providers
Mem0
| File | Description |
|---|---|
getting_started/context_providers/mem0/mem0_basic.py |
Basic Mem0 integration example |
getting_started/context_providers/mem0/mem0_oss.py |
Mem0 OSS (Open Source) integration example |
getting_started/context_providers/mem0/mem0_threads.py |
Mem0 with thread management example |
Redis
| File | Description |
|---|---|
getting_started/context_providers/redis/redis_basics.py |
Basic Redis provider example |
getting_started/context_providers/redis/redis_conversation.py |
Redis conversation context management example |
getting_started/context_providers/redis/redis_threads.py |
Redis with thread management example |
Other
| File | Description |
|---|---|
getting_started/context_providers/simple_context_provider.py |
Simple context provider implementation example |
getting_started/context_providers/aggregate_context_provider.py |
Shows how to combine multiple context providers using an AggregateContextProvider |
Declarative
| File | Description |
|---|---|
getting_started/declarative/azure_openai_responses_agent.py |
Basic agent using Azure OpenAI with structured responses |
getting_started/declarative/get_weather_agent.py |
Agent with custom function tools using declarative bindings |
getting_started/declarative/inline_yaml.py |
Agent created from inline YAML string |
getting_started/declarative/mcp_tool_yaml.py |
MCP tool configuration with API key and Azure Foundry connection auth |
getting_started/declarative/microsoft_learn_agent.py |
Agent with MCP server integration for Microsoft Learn documentation |
getting_started/declarative/openai_responses_agent.py |
Basic agent using OpenAI directly |
DevUI
| File | Description |
|---|---|
getting_started/devui/fanout_workflow/workflow.py |
Complex fan-out/fan-in workflow example |
getting_started/devui/foundry_agent/agent.py |
Azure AI Foundry agent example |
getting_started/devui/in_memory_mode.py |
In-memory mode example for DevUI |
getting_started/devui/spam_workflow/workflow.py |
Spam detection workflow example |
getting_started/devui/weather_agent_azure/agent.py |
Weather agent using Azure OpenAI example |
getting_started/devui/workflow_agents/workflow.py |
Workflow with multiple agents example |
Evaluation
| File | Description |
|---|---|
getting_started/evaluation/red_teaming/red_team_agent_sample.py |
Red team agent evaluation sample for Azure AI Foundry |
getting_started/evaluation/self_reflection/self_reflection.py |
LLM self-reflection with AI Foundry graders example |
demos/workflow_evaluation/run_evaluation.py |
Multi-agent workflow evaluation demo with travel planning agents evaluated using Azure AI Foundry evaluators |
MCP (Model Context Protocol)
| File | Description |
|---|---|
getting_started/mcp/agent_as_mcp_server.py |
Agent as MCP Server Example |
getting_started/mcp/mcp_api_key_auth.py |
MCP Authentication Example |
Middleware
Multimodal Input
| File | Description |
|---|---|
getting_started/multimodal_input/azure_chat_multimodal.py |
Azure OpenAI Chat with multimodal (image) input example |
getting_started/multimodal_input/azure_responses_multimodal.py |
Azure OpenAI Responses with multimodal (image) input example |
getting_started/multimodal_input/openai_chat_multimodal.py |
OpenAI Chat with multimodal (image) input example |
Azure Functions
| Sample | Description |
|---|---|
getting_started/azure_functions/01_single_agent/ |
Host a single agent in Azure Functions with Durable Extension HTTP endpoints and per-session state. |
getting_started/azure_functions/02_multi_agent/ |
Register multiple agents in one function app with dedicated run routes and a health check endpoint. |
getting_started/azure_functions/03_reliable_streaming/ |
Implement reliable streaming for durable agents using Redis Streams with cursor-based resumption. |
getting_started/azure_functions/04_single_agent_orchestration_chaining/ |
Chain sequential agent executions inside a durable orchestration while preserving the shared thread context. |
getting_started/azure_functions/05_multi_agent_orchestration_concurrency/ |
Run two agents concurrently within a durable orchestration and combine their domain-specific outputs. |
getting_started/azure_functions/06_multi_agent_orchestration_conditionals/ |
Route orchestration logic based on structured agent responses for spam detection and reply drafting. |
getting_started/azure_functions/07_single_agent_orchestration_hitl/ |
Implement a human-in-the-loop approval loop that iterates on agent output inside a durable orchestration. |
getting_started/azure_functions/08_mcp_server/ |
Configure agents as both HTTP endpoints and MCP tools for flexible integration patterns. |
Durable Task
These samples demonstrate durable agent hosting using the Durable Task Scheduler with a worker-client architecture pattern, enabling distributed agent execution with persistent conversation state.
| Sample | Description |
|---|---|
getting_started/durabletask/01_single_agent/ |
Host a single conversational agent with worker-client architecture and agent state management. |
getting_started/durabletask/02_multi_agent/ |
Host multiple domain-specific agents and route requests based on question topic. |
getting_started/durabletask/03_single_agent_streaming/ |
Implement reliable streaming using Redis Streams with cursor-based resumption for durable agents. |
getting_started/durabletask/04_single_agent_orchestration_chaining/ |
Chain multiple agent invocations using durable orchestration while preserving conversation context. |
getting_started/durabletask/05_multi_agent_orchestration_concurrency/ |
Run multiple agents concurrently within an orchestration and aggregate their responses. |
getting_started/durabletask/06_multi_agent_orchestration_conditionals/ |
Implement conditional branching with spam detection using structured outputs and activity functions. |
getting_started/durabletask/07_single_agent_orchestration_hitl/ |
Human-in-the-loop pattern with external event handling, timeouts, and iterative refinement. |
Observability
| File | Description |
|---|---|
getting_started/observability/advanced_manual_setup_console_output.py |
Advanced manual observability setup with console output |
getting_started/observability/advanced_zero_code.py |
Zero-code observability setup example |
getting_started/observability/agent_observability.py |
Agent observability example |
getting_started/observability/agent_with_foundry_tracing.py |
Any chat client setup with Azure Foundry Observability |
getting_started/observability/azure_ai_agent_observability.py |
Azure AI agent observability example |
getting_started/observability/configure_otel_providers_with_env_var.py |
Setup observability using environment variables |
getting_started/observability/configure_otel_providers_with_parameters.py |
Setup observability using parameters |
getting_started/observability/workflow_observability.py |
Workflow observability example |
Threads
| File | Description |
|---|---|
getting_started/threads/custom_chat_message_store_thread.py |
Implementation of custom chat message store state |
getting_started/threads/redis_chat_message_store_thread.py |
Basic example of using Redis chat message store |
getting_started/threads/suspend_resume_thread.py |
Demonstrates how to suspend and resume a service-managed thread |
Tools
Note: Many tool samples set approval_mode="never_require" to keep the examples concise. For production scenarios,
keep approval_mode="always_require" unless you are confident in the tool behavior and approval flow. See
getting_started/tools/function_tool_with_approval.py and
getting_started/tools/function_tool_with_approval_and_threads.py, plus the workflow approval samples in
getting_started/workflows/tool-approval/, for end-to-end approval handling.
| File | Description |
|---|---|
getting_started/tools/function_tool_declaration_only.py |
Function declarations without implementations for testing agent reasoning |
getting_started/tools/function_tool_from_dict_with_dependency_injection.py |
Creating local tools from dictionary definitions using dependency injection |
getting_started/tools/function_tool_recover_from_failures.py |
Graceful error handling when tools raise exceptions |
getting_started/tools/function_tool_with_approval.py |
User approval workflows for function calls without threads |
getting_started/tools/function_tool_with_approval_and_threads.py |
Tool approval workflows using threads for conversation history management |
getting_started/tools/function_tool_with_max_exceptions.py |
Limiting tool failure exceptions using max_invocation_exceptions |
getting_started/tools/function_tool_with_max_invocations.py |
Limiting total tool invocations using max_invocations |
getting_started/tools/tool_in_class.py |
Using the tool decorator with class methods for stateful tools |
Workflows
View the list of Workflows samples here.
Sample Guidelines
For information on creating new samples, see SAMPLE_GUIDELINES.md.