Directories
¶
| Path | Synopsis |
|---|---|
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01-get-started
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01_hello_agent
command
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02_add_tools
command
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03_multi_turn
command
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04_memory
command
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05_first_workflow
command
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02-agents
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a2a/as_function_tools
command
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a2a/polling_for_task_completion
command
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a2a/protocol_selection
command
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a2a/stream_reconnection
command
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agents/message-injection
command
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agents/step01_running
command
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agents/step05_structured_output
command
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agents/step08_observability
command
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agents/step09_dependency_injection
command
This sample shows how to use dependency injection to register an Agent and use it from a hosted service with a user input chat loop.
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This sample shows how to use dependency injection to register an Agent and use it from a hosted service with a user input chat loop. |
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agents/step10_as_mcp_tool
command
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agents/step11_using_images
command
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agents/step12_as_function_tool
command
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agents/step13_middleware
command
This sample shows how to write custom agent middleware.
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This sample shows how to write custom agent middleware. |
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agents/step19_loop_reinvocation
command
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agents/step22_foundry_memory
command
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agents/step24_filememory
command
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agui/step02_backend_tools/client
command
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agui/step02_backend_tools/server
command
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agui/step04_human_in_loop/client
command
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agui/step04_human_in_loop/server
command
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harness/step01_loop
command
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harness/step03_agentmode
command
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harness/step04_composite_harness
command
This sample uses the reusable harness setup with a normal Foundry agent.
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This sample uses the reusable harness setup with a normal Foundry agent. |
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mcp/agent_mcp_server
command
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mcp/local_stdio_mcp
command
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memory/step01_chat_history_memory
command
This sample recalls chat messages from earlier sessions for the same user.
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This sample recalls chat messages from earlier sessions for the same user. |
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memory/step05_bounded_chat_history
command
This sample archives older chat messages and recalls them from a vector store.
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This sample archives older chat messages and recalls them from a vector store. |
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providers/a2a
command
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providers/anthrophic
command
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providers/anthrophic/thinking
command
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providers/azure/ai_project
command
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providers/azure/ai_search
command
This sample stores generated embeddings in Azure AI Search and runs scoped vector and hybrid queries.
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This sample stores generated embeddings in Azure AI Search and runs scoped vector and hybrid queries. |
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providers/azure/cosmosdb
command
This sample stores generated embeddings in a temporary Cosmos DB container.
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This sample stores generated embeddings in a temporary Cosmos DB container. |
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providers/azure/foundry_model
command
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providers/azure/openai_responses
command
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providers/azure/openai_responses_background
command
This sample demonstrates long-running agent operations using the OpenAI Responses API "background" option.
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This sample demonstrates long-running agent operations using the OpenAI Responses API "background" option. |
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providers/foundry/step01_basic
command
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providers/foundry/step10_images
command
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providers/foundry/step13_plugins
command
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providers/gemini
command
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providers/gemini/thinking
command
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providers/github-copilot
command
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providers/openai/chat_completion
command
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providers/openai/responses
command
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providers/openai/step01_running
command
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providers/openai/step06_code_interpreter_file_download
command
This sample shows how to download files generated by Code Interpreter using the OpenAI Containers API.
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This sample shows how to download files generated by Code Interpreter using the OpenAI Containers API. |
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rag/step01_basic_text_rag
command
This sample retrieves text from an in-memory vector store before each agent invocation and keeps retrieved context out of retained conversation history.
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This sample retrieves text from an in-memory vector store before each agent invocation and keeps retrieved context out of retained conversation history. |
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rag/step02_custom_vector_store_rag
command
This sample uses a custom Qdrant schema to retrieve Agent Framework documentation, including recent conversation context in each search.
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This sample uses a custom Qdrant schema to retrieve Agent Framework documentation, including recent conversation context in each search. |
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rag/step04_foundry_service_rag
command
This sample uploads a knowledge base and creates a Foundry vector store and prompt agent version that uses server-side file search.
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This sample uploads a knowledge base and creates a Foundry vector store and prompt agent version that uses server-side file search. |
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rag/step05_neo4j_graph_rag
command
This sample retrieves graph-enriched text from a Neo4j full-text index.
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This sample retrieves graph-enriched text from a Neo4j full-text index. |
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skills/step01_file_based_skills
command
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skills/step03_mixed_skills
command
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03-workflows
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01-start-here/01_streaming
command
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01-start-here/05_subworkflow
command
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agents/custom_agent_executors
command
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agents/group_chat_tool_approval
command
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agents/workflow_as_an_agent
command
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cancellation
command
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checkpoint/checkpoint_and_resume
command
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checkpoint/filesystem_checkpoint
command
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concurrent/concurrent
command
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concurrent/map_reduce
command
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conditional-edges/02_switch_case
command
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loop
command
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message-workflow
command
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observability/executor_io
command
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shared-states
command
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05-end-to-end
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a2a_client_server/a2a_client
command
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a2a_client_server/a2a_server
command
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demos
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chat_cli
command
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internal
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