Files
agent-framework/python/samples/getting_started/agents/openai/README.md
T
Dmytro Struk 361c47f30f Python: [Feature Branch] Merge from main to Azure AI branch (#2111)
* Do not build DevUI assets during .NET project build (#2010)

* .NET: Add unit tests for declarative executor SetMultipleVariables (#2016)

* Add unit tests for create conversation executor

* Update indentation and comment typo.

* Added unit tests for declarative executor SetMultipleVariablesExecutor

* Updated comments and syntactic sugar

* Python: DevUI: Use metadata.entity_id instead of model field (#1984)

* DevUI: Use metadata.entity_id for agent/workflow name instead of model field

* OpenAI Responses: add explicit request validation

* Review feedback

* .NET: DevUI - Do not automatically add/map OpenAI services/endpoints (#2014)

* Don't add OpenAIResponses as part of Dev UI

You should be able to add and remove Dev UI without impacting your other production endpoints.

* Remove `AddDevUI()` and do not map OpenAI endpoints from `MapDevUI()`

* Fix comment wording

* Revise documentation

---------

Co-authored-by: Daniel Roth <daroth@microsoft.com>

* Python: DevUI: Add OpenAI Responses API proxy support  + HIL for Workflows (#1737)

* DevUI: Add OpenAI Responses API proxy support with enhanced UI features

This commit adds support for proxying requests to OpenAI's Responses API,
allowing DevUI to route conversations to OpenAI models when configured to enable testing.

Backend changes:
- Add OpenAI proxy executor with conversation routing logic
- Enhance event mapper to support OpenAI Responses API format
- Extend server endpoints to handle OpenAI proxy mode
- Update models with OpenAI-specific response types
- Remove emojis from logging and CLI output for cleaner text

Frontend changes:
- Add settings modal with OpenAI proxy configuration UI
- Enhance agent and workflow views with improved state management
- Add new UI components (separator, switch) for settings
- Update debug panel with better event filtering
- Improve message renderers for OpenAI content types
- Update types and API client for OpenAI integration

* update ui, settings modal and workflow input form, add register cleanup hooks.

* add workflow HIL support, user mode, other fixes

* feat(devui): add human-in-the-loop (HIL) support with dynamic response schemas

Implement  HIL workflow support allowing workflows to pause for user input
with dynamically generated JSON schemas based on response handler type hints.

Key Features:
- Automatic response schema extraction from @response_handler decorators
- Dynamic form generation in UI based on Pydantic/dataclass response types
- Checkpoint-based conversation storage for HIL requests/responses
- Resume workflow execution after user provides HIL response

Backend Changes:
- Add extract_response_type_from_executor() to introspect response handlers
- Enrich RequestInfoEvent with response_schema via _enrich_request_info_event_with_response_schema()
- Map RequestInfoEvent to response.input.requested OpenAI event format
- Store HIL responses in conversation history and restore checkpoints

Frontend Changes:
- Add HILInputModal component with SchemaFormRenderer for dynamic forms
- Support Pydantic BaseModel and dataclass response types
- Render enum fields as dropdowns, strings as text/textarea, numbers, booleans, arrays, objects
- Display original request context alongside response form

Testing:
- Add  tests for checkpoint storage (test_checkpoints.py)
- Add schema generation tests for all input types (test_schema_generation.py)
- Validate end-to-end HIL flow with spam workflow sample

This enables workflows to seamlessly pause execution and request structured user input
with type-safe, validated forms generated automatically from response type annotations.

* improve HIL support, improve workflow execution view

* ui updates

* ui updates

* improve HIL for workflows, add auth and view modes

* update workflow

* security improvements , ui fixes

* fix mypy error

* update loading spinner in ui

---------

Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com>

* .NET: Remove launchSettings.json from .gitignore in dotnet/samples (#2006)

* Remove launchSettings.json from .gitignore in dotnet/samples

* Update dotnet/samples/GettingStarted/DevUI/DevUI_Step01_BasicUsage/Properties/launchSettings.json

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update dotnet/samples/AGUIClientServer/AGUIServer/Properties/launchSettings.json

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* DevUI: Serialize workflow input as string to maintain conformance with OpenAI Responses format (#2021)

Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>

* Add Microsoft Agent Framework logo to assets (#2007)

* Updated package versions (#2027)

* DevUI: Prevent line breaks within words in the agent view (#2024)

Co-authored-by: Victor Dibia <chuvidi2003@gmail.com>

* .NET [AG-UI]: Adds support for shared state. (#1996)

* Product changes

* Tests

* Dojo project

* Cleanups

* Python: Fix underlying tool choice bug and all for return to previous Handoff subagent (#2037)

* Fix tool_choice override bug and add enable_return_to_previous support

* Add unit test for handoff checkpointing

* Handle tools when we have them

* added missing chatAgent params (#2044)

* .NET: fix ChatCompletions Tools serialization (#2043)

* fix serialization in chat completions on tools

* nit

* .NET: assign AgentCard's URL to mapped-endpoint if not defined explicitly (#2047)

* fix serialization in chat completions on tools

* nit

* write e2e test for agent card resolve + adjust behavior

* nit

* Version 1.0.0-preview.251110.1 (#2048)

* .NET: Remove moved OpenAPI sample and point to SK one. (#1997)

* Remove moved OpenAPI sample and point to SK one.

* Update dotnet/samples/GettingStarted/Agents/README.md

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Bump AWSSDK.Extensions.Bedrock.MEAI from 4.0.4.2 to 4.0.4.6 (#2031)

---
updated-dependencies:
- dependency-name: AWSSDK.Extensions.Bedrock.MEAI
  dependency-version: 4.0.4.6
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* .NET: Separate all memory and rag samples into their own folders (#2000)

* Separate all memory and rag samples into their own folders

* Fix broken link.

* Python: .Net: Dotnet devui compatibility fixes (#2026)

* DevUI: Add OpenAI Responses API proxy support with enhanced UI features

This commit adds support for proxying requests to OpenAI's Responses API,
allowing DevUI to route conversations to OpenAI models when configured to enable testing.

Backend changes:
- Add OpenAI proxy executor with conversation routing logic
- Enhance event mapper to support OpenAI Responses API format
- Extend server endpoints to handle OpenAI proxy mode
- Update models with OpenAI-specific response types
- Remove emojis from logging and CLI output for cleaner text

Frontend changes:
- Add settings modal with OpenAI proxy configuration UI
- Enhance agent and workflow views with improved state management
- Add new UI components (separator, switch) for settings
- Update debug panel with better event filtering
- Improve message renderers for OpenAI content types
- Update types and API client for OpenAI integration

* update ui, settings modal and workflow input form, add register cleanup hooks.

* add workflow HIL support, user mode, other fixes

* feat(devui): add human-in-the-loop (HIL) support with dynamic response schemas

Implement  HIL workflow support allowing workflows to pause for user input
with dynamically generated JSON schemas based on response handler type hints.

Key Features:
- Automatic response schema extraction from @response_handler decorators
- Dynamic form generation in UI based on Pydantic/dataclass response types
- Checkpoint-based conversation storage for HIL requests/responses
- Resume workflow execution after user provides HIL response

Backend Changes:
- Add extract_response_type_from_executor() to introspect response handlers
- Enrich RequestInfoEvent with response_schema via _enrich_request_info_event_with_response_schema()
- Map RequestInfoEvent to response.input.requested OpenAI event format
- Store HIL responses in conversation history and restore checkpoints

Frontend Changes:
- Add HILInputModal component with SchemaFormRenderer for dynamic forms
- Support Pydantic BaseModel and dataclass response types
- Render enum fields as dropdowns, strings as text/textarea, numbers, booleans, arrays, objects
- Display original request context alongside response form

Testing:
- Add  tests for checkpoint storage (test_checkpoints.py)
- Add schema generation tests for all input types (test_schema_generation.py)
- Validate end-to-end HIL flow with spam workflow sample

This enables workflows to seamlessly pause execution and request structured user input
with type-safe, validated forms generated automatically from response type annotations.

* improve HIL support, improve workflow execution view

* ui updates

* ui updates

* improve HIL for workflows, add auth and view modes

* update workflow

* security improvements , ui fixes

* fix mypy error

* update loading spinner in ui

* DevUI: Serialize workflow input as string to maintain conformance with OpenAI Responses format

* Phase 1: Add /meta endpoint and fix workflow event naming for .NET DevUI compatibility

* additional fixes for .NET DevUI workflow visualization item ID tracking

**Problem:**
.NET DevUI was generating different item IDs for ExecutorInvokedEvent and
ExecutorCompletedEvent, causing only the first executor to highlight in the
workflow graph. Long executor names and error messages also broke UI layout.

**Changes:**
- Add ExecutorActionItemResource to match Python DevUI implementation
- Track item IDs per executor using dictionary in AgentRunResponseUpdateExtensions
- Reuse same item ID across invoked/completed/failed events for proper pairing
- Add truncateText() utility to workflow-utils.ts
- Truncate executor names to 35 chars in execution timeline
- Truncate error messages to 150 chars in workflow graph nodes

** Details:**
- ExecutorActionItemResource registered with JSON source generation context
- Dictionary cleaned up after executor completion/failure to prevent memory leaks
- Frontend item tracking by unique item.id supports multiple executor runs
- All changes follow existing codebase patterns and conventions

Tested with review-workflow showing correct executor highlighting and state
transitions for sequential and concurrent executors.

* format fixes, remove cors tests

* remove unecessary attributes

---------

Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com>
Co-authored-by: Reuben Bond <reuben.bond@gmail.com>

* DevUI: support having both an agent and a workflow with the same id in discovery (#2023)

* Python: Fix Model ID attribute not showing up in `invoke_agent` span (#2061)

* Best effort to surface the model id to invoke agent span

* Fix tests

* Fix tests

* Version 1.0.0-preview.251107.2 (#2065)

* Version 1.0.0-preview.251110.2 (#2067)

* Update README.md to change Grafana links to Azure portal links for dashboard access (#1983)

* .NET - Enable build & test on branch `feature-foundry-agents` (#2068)

* Tests good, mkay

* Update .github/workflows/dotnet-build-and-test.yml

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Enable feature build pipelines

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>

* Python: Add concrete AGUIChatClient (#2072)

* Add concrete AGUIChatClient

* Update logging docstrings and conventions

* PR feedback

* Updates to support client-side tool calls

* .NET: Move catalog samples to the HostedAgents folder (#2090)

* move catalog samples to the HostedAgents folder

* move the catalog samples' projects to the HostedAgents folder

* Bump OpenTelemetry.Instrumentation.Runtime from 1.12.0 to 1.13.0 (#1856)

---
updated-dependencies:
- dependency-name: OpenTelemetry.Instrumentation.Runtime
  dependency-version: 1.13.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* .NET: Bump Microsoft.SemanticKernel.Agents.Abstractions from 1.66.0 to 1.67.0 (#1962)

* Bump Microsoft.SemanticKernel.Agents.Abstractions from 1.66.0 to 1.67.0

---
updated-dependencies:
- dependency-name: Microsoft.SemanticKernel.Agents.Abstractions
  dependency-version: 1.67.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>

* .NET: Bump all Microsoft.SemanticKernel packages from 1.66.* to 1.67.* (#1969)

* Initial plan

* Update all Microsoft.SemanticKernel packages to 1.67.*

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Remove unrelated changes to package-lock.json and yarn.lock

Co-authored-by: markwallace-microsoft <127216156+markwallace-microsoft@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
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Co-authored-by: markwallace-microsoft <127216156+markwallace-microsoft@users.noreply.github.com>

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Co-authored-by: markwallace-microsoft <127216156+markwallace-microsoft@users.noreply.github.com>

* .NET: fix: WorkflowAsAgent Sample (#1787)

* fix: WorkflowAsAgent Sample

* Also makes ChatForwardingExecutor public

* feat: Expand ChatForwardingExecutor handled types

Make ChatForwardingExecutor match the input types of ChatProtocolExecutor.

* fix: Update for the new AgentRunResponseUpdate merge logic

AIAgent always sends out List<ChatMessage> now.

* Updated (#2076)

* Bump vite in /python/samples/demos/chatkit-integration/frontend (#1918)

Bumps [vite](https://github.com/vitejs/vite/tree/HEAD/packages/vite) from 7.1.9 to 7.1.12.
- [Release notes](https://github.com/vitejs/vite/releases)
- [Changelog](https://github.com/vitejs/vite/blob/v7.1.12/packages/vite/CHANGELOG.md)
- [Commits](https://github.com/vitejs/vite/commits/v7.1.12/packages/vite)

---
updated-dependencies:
- dependency-name: vite
  dependency-version: 7.1.12
  dependency-type: direct:development
...

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* Bump Roslynator.Analyzers from 4.14.0 to 4.14.1 (#1857)

---
updated-dependencies:
- dependency-name: Roslynator.Analyzers
  dependency-version: 4.14.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Bump MishaKav/pytest-coverage-comment from 1.1.57 to 1.1.59 (#2034)

Bumps [MishaKav/pytest-coverage-comment](https://github.com/mishakav/pytest-coverage-comment) from 1.1.57 to 1.1.59.
- [Release notes](https://github.com/mishakav/pytest-coverage-comment/releases)
- [Changelog](https://github.com/MishaKav/pytest-coverage-comment/blob/main/CHANGELOG.md)
- [Commits](https://github.com/mishakav/pytest-coverage-comment/compare/v1.1.57...v1.1.59)

---
updated-dependencies:
- dependency-name: MishaKav/pytest-coverage-comment
  dependency-version: 1.1.59
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Python: Handle agent user input request in AgentExecutor (#2022)

* Handle agent user input request in AgentExecutor

* fix test

* Address comments

* Fix tests

* Fix tests

* Address comments

* Address comments

* Python: OpenAI Responses Image Generation Stream Support, Sample and Unit Tests (#1853)

* support for image gen streaming

* small fixes

* fixes

* added comment

* Python: Fix MCP Tool Parameter Descriptions Not Propagated to LLMs (#1978)

* mcp tool description fix

* small fix

* .NET: Allow extending agent run options via additional properties (#1872)

* Allow extending agent run options via additional properties

This mirrors the M.E.AI model in ChatOptions.AdditionalProperties which is very useful when building functionality pipelines.

Fixes https://github.com/microsoft/agent-framework/issues/1815

* Expand XML documentation

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* Add AdditionalProperties tests to AgentRunOptions

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* Python: Use the last entry in the task history to avoid empty responses (#2101)

* Use the last entry in the task history to avoid empty responses

* History only contains Messages

* Updated package versions (#2104)

---------

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2025-11-11 23:12:09 -08:00

7.7 KiB

OpenAI Agent Framework Examples

This folder contains examples demonstrating different ways to create and use agents with the OpenAI Assistants client from the agent_framework.openai package.

Examples

File Description
openai_assistants_basic.py The simplest way to create an agent using ChatAgent with OpenAIAssistantsClient. Shows both streaming and non-streaming responses with automatic assistant creation and cleanup.
openai_assistants_with_code_interpreter.py Shows how to use the HostedCodeInterpreterTool with OpenAI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks.
openai_assistants_with_existing_assistant.py Shows how to work with a pre-existing assistant by providing the assistant ID to the OpenAI Assistants client. Demonstrates proper cleanup of manually created assistants.
openai_assistants_with_explicit_settings.py Shows how to initialize an agent with a specific assistants client, configuring settings explicitly including API key and model ID.
openai_assistants_with_file_search.py Demonstrates how to use file search capabilities with OpenAI agents, allowing the agent to search through uploaded files to answer questions.
openai_assistants_with_function_tools.py Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries).
openai_assistants_with_thread.py Demonstrates thread management with OpenAI agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions.
openai_chat_client_basic.py The simplest way to create an agent using ChatAgent with OpenAIChatClient. Shows both streaming and non-streaming responses for chat-based interactions with OpenAI models.
openai_chat_client_with_explicit_settings.py Shows how to initialize an agent with a specific chat client, configuring settings explicitly including API key and model ID.
openai_chat_client_with_function_tools.py Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries).
openai_chat_client_with_local_mcp.py Shows how to integrate OpenAI agents with local Model Context Protocol (MCP) servers for enhanced functionality and tool integration.
openai_chat_client_with_thread.py Demonstrates thread management with OpenAI agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions.
openai_chat_client_with_web_search.py Shows how to use web search capabilities with OpenAI agents to retrieve and use information from the internet in responses.
openai_responses_client_basic.py The simplest way to create an agent using ChatAgent with OpenAIResponsesClient. Shows both streaming and non-streaming responses for structured response generation with OpenAI models.
openai_responses_client_image_analysis.py Demonstrates how to use vision capabilities with agents to analyze images.
openai_responses_client_image_generation.py Demonstrates how to use image generation capabilities with OpenAI agents to create images based on text descriptions. Requires PIL (Pillow) for image display.
openai_responses_client_reasoning.py Demonstrates how to use reasoning capabilities with OpenAI agents, showing how the agent can provide detailed reasoning for its responses.
openai_responses_client_streaming_image_generation.py Demonstrates streaming image generation with partial images for real-time image creation feedback and improved user experience.
openai_responses_client_with_code_interpreter.py Shows how to use the HostedCodeInterpreterTool with OpenAI agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks.
openai_responses_client_with_explicit_settings.py Shows how to initialize an agent with a specific responses client, configuring settings explicitly including API key and model ID.
openai_responses_client_with_file_search.py Demonstrates how to use file search capabilities with OpenAI agents, allowing the agent to search through uploaded files to answer questions.
openai_responses_client_with_function_tools.py Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and run-level tools (provided with specific queries).
openai_responses_client_with_hosted_mcp.py Shows how to integrate OpenAI agents with hosted Model Context Protocol (MCP) servers, including approval workflows and tool management for remote MCP services.
openai_responses_client_with_local_mcp.py Shows how to integrate OpenAI agents with local Model Context Protocol (MCP) servers for enhanced functionality and tool integration.
openai_responses_client_with_structured_output.py Demonstrates how to use structured outputs with OpenAI agents to get structured data responses in predefined formats.
openai_responses_client_with_thread.py Demonstrates thread management with OpenAI agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions.
openai_responses_client_with_web_search.py Shows how to use web search capabilities with OpenAI agents to retrieve and use information from the internet in responses.

Environment Variables

Make sure to set the following environment variables before running the examples:

  • OPENAI_API_KEY: Your OpenAI API key
  • OPENAI_CHAT_MODEL_ID: The OpenAI model to use (e.g., gpt-4o, gpt-4o-mini, gpt-3.5-turbo)
  • OPENAI_RESPONSES_MODEL_ID: The OpenAI model to use (e.g., gpt-4o, gpt-4o-mini, gpt-3.5-turbo)
  • For image processing examples, use a vision-capable model like gpt-4o or gpt-4o-mini

Optionally, you can set:

  • OPENAI_ORG_ID: Your OpenAI organization ID (if applicable)
  • OPENAI_API_BASE_URL: Your OpenAI base URL (if using a different base URL)

Optional Dependencies

Some examples require additional dependencies:

  • Image Generation Example: The openai_responses_client_image_generation.py example requires PIL (Pillow) for image display. Install with:
    # Using uv
    uv add pillow
    
    # Or using pip
    pip install pillow