github-featured/microsoft--agent-framework

Files

T

Evan Mattson 435201b71b Python: Fix A2A input handling in orchestrations (#7761 )

* fix(a2a): reject empty invocations explicitly

Key decisions:
- Keep A2A continuation authority explicit; durable session task state only enriches diagnostics.
- Raise AgentInvalidRequestException with participant and available task context instead of inventing input.
- Leave AgentExecutor and Group Chat production contracts unchanged.

Files changed:
- packages/a2a/agent_framework_a2a/_agent.py
- packages/a2a/tests/test_a2a_agent.py
- packages/a2a/tests/test_a2a_group_chat.py

Notes for next iteration:
- No blockers. INPUT_REQUIRED pause/resume remains a separate task.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* fix(a2a): pause group chat for remote input

Key decisions:
- Translate A2A INPUT_REQUIRED task content into the existing Content user-input-request contract.
- Use the remote task ID as stable request correlation for streamed and finalized responses.
- Reuse AgentExecutor request handling so caller input resumes the same task without a workflow-specific A2A path.

Files changed:
- packages/a2a/agent_framework_a2a/_agent.py
- packages/a2a/tests/test_a2a_agent.py
- packages/a2a/tests/test_a2a_group_chat.py

Notes for next iteration:
- Checkpoint restoration of pending A2A input is now unblocked.
- The local issue file could not be moved because repository issue files are restricted by content exclusion policy.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* fix(a2a): restore pending input from checkpoints

Key decisions:
- Keep normalized INPUT_REQUIRED content durable by excluding transport-only protobuf raw representations.
- Restore through the existing AgentExecutor checkpoint and request-response path without a new schema or continuation API.
- Cover file-backed restoration in streaming and non-streaming Group Chat runs, including unrelated-response rejection and exact task resumption.

Files changed:
- packages/a2a/agent_framework_a2a/_agent.py
- packages/a2a/tests/test_a2a_group_chat.py

Notes for next iteration:
- The local issue file could not be moved because repository issue files are restricted by content exclusion policy.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* test(handoff): lock textless target context

Key decisions:
- Exercise the built Handoff workflow in streaming and non-streaming modes instead of bypassing routing, sessions, or termination.
- Keep the slice test-only because current production already carries the initial task to a textless handoff target without synthetic user input.
- Revisit the source to verify its handoff function call retains a matching result and user-turn termination sees only caller messages.

Files changed:
- packages/orchestrations/tests/test_handoff.py

Notes for next iteration:
- No production defect was reproduced.
- The local issue file could not be moved because repository issue files are restricted by content exclusion policy.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* test(handoff): use resolved IDs in event assertions

* fix(workflows): preserve A2A input request semantics

* fix(workflows): preserve input request correlation

* fix(a2a): deduplicate message-less input requests

* fix(workflows): preserve specialized input requests

* test(openai): use current web search model

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

2026-08-19 23:55:01 +00:00

agent_framework_openai

Python: Add response/request customization hooks to OpenAIChatCompletionClient (#7028 )

2026-08-07 02:51:06 +00:00

tests

Python: Fix A2A input handling in orchestrations (#7761 )

2026-08-19 23:55:01 +00:00

AGENTS.md

Python: Add response/request customization hooks to OpenAIChatCompletionClient (#7028 )

2026-08-07 02:51:06 +00:00

LICENSE

Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818 )

2026-03-25 09:56:29 +00:00

pyproject.toml

Python: Bump Python package versions for 1.14.0 release (#7661 )

2026-08-14 11:06:35 +09:00

README.md

Python: [BREAKING] update to v1.0.0 (#5062 )

2026-04-02 15:26:30 +00:00

README.md

agent-framework-openai

OpenAI integration for Microsoft Agent Framework.

This package provides:

OpenAIChatClient for the OpenAI Responses API
OpenAIChatCompletionClient for the Chat Completions API
OpenAIEmbeddingClient for embeddings

Installation

pip install agent-framework-openai

Which chat client should I use?

Use OpenAIChatClient for new work unless you specifically need the Chat Completions API.

OpenAIChatClient uses the Responses API and is the preferred general-purpose chat client.
OpenAIChatCompletionClient uses the Chat Completions API and is mainly for compatibility with existing Chat Completions-based integrations.

The previous deprecated Responses alias has been removed. Use OpenAIChatClient directly.

Environment variables

OpenAI

These variables are used when the client is configured for OpenAI:

Variable	Purpose
`OPENAI_API_KEY`	OpenAI API key
`OPENAI_ORG_ID`	OpenAI organization ID
`OPENAI_BASE_URL`	Custom OpenAI-compatible base URL
`OPENAI_MODEL`	Generic fallback model
`OPENAI_CHAT_MODEL`	Preferred model for `OpenAIChatClient`
`OPENAI_CHAT_COMPLETION_MODEL`	Preferred model for `OpenAIChatCompletionClient`
`OPENAI_EMBEDDING_MODEL`	Preferred model for `OpenAIEmbeddingClient`

Model lookup order:

OpenAIChatClient: OPENAI_CHAT_MODEL -> OPENAI_MODEL
OpenAIChatCompletionClient: OPENAI_CHAT_COMPLETION_MODEL -> OPENAI_MODEL
OpenAIEmbeddingClient: OPENAI_EMBEDDING_MODEL -> OPENAI_MODEL

These model variables are only consulted when you do not pass model= directly. In other words, OpenAIChatClient(model="...") ignores OPENAI_CHAT_MODEL, and OpenAIChatCompletionClient(model="...") ignores OPENAI_CHAT_COMPLETION_MODEL.

Azure OpenAI

These variables are used when the client is configured for Azure OpenAI:

Variable	Purpose
`AZURE_OPENAI_ENDPOINT`	Azure OpenAI resource endpoint
`AZURE_OPENAI_BASE_URL`	Full Azure OpenAI base URL (`.../openai/v1`)
`AZURE_OPENAI_API_KEY`	Azure OpenAI API key
`AZURE_OPENAI_API_VERSION`	Azure OpenAI API version
`AZURE_OPENAI_MODEL`	Generic fallback deployment
`AZURE_OPENAI_CHAT_MODEL`	Preferred deployment for `OpenAIChatClient`
`AZURE_OPENAI_CHAT_COMPLETION_MODEL`	Preferred deployment for `OpenAIChatCompletionClient`
`AZURE_OPENAI_EMBEDDING_MODEL`	Preferred deployment for `OpenAIEmbeddingClient`

Deployment lookup order:

OpenAIChatClient: AZURE_OPENAI_CHAT_MODEL -> AZURE_OPENAI_MODEL
OpenAIChatCompletionClient: AZURE_OPENAI_CHAT_COMPLETION_MODEL -> AZURE_OPENAI_MODEL
OpenAIEmbeddingClient: AZURE_OPENAI_EMBEDDING_MODEL -> AZURE_OPENAI_MODEL

For Azure routing, the same rule applies: the client-specific deployment variable is checked first, then the generic AZURE_OPENAI_MODEL fallback. Passing model= overrides both environment variables.

When both OpenAI and Azure environment variables are present, the generic clients prefer OpenAI when OPENAI_API_KEY is configured. To use Azure explicitly, pass azure_endpoint or credential.

OpenAI example

from agent_framework.openai import OpenAIChatClient

client = OpenAIChatClient(model="gpt-4.1")

Azure OpenAI example

from azure.identity.aio import AzureCliCredential

from agent_framework.openai import OpenAIChatClient

client = OpenAIChatClient(
    model="my-responses-deployment",
    azure_endpoint="https://my-resource.openai.azure.com",
    credential=AzureCliCredential(),
)

ChatClient vs ChatCompletionClient

Use OpenAIChatClient when you want the Responses API as your default chat surface.

Use OpenAIChatCompletionClient when you specifically need the Chat Completions API:

from agent_framework.openai import OpenAIChatCompletionClient

client = OpenAIChatCompletionClient(model="gpt-4o-mini")