Files
agent-framework/python/packages/lab
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westey 8b191de936 Merge and move scripts (#4308)
* .NET: Add Microsoft Fabric sample #3674 (#4230)

Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>

* Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)

* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference

Add embedding client implementations to existing provider packages:

- OllamaEmbeddingClient: Text embeddings via Ollama's embed API
- BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock
- AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI
  Inference, supporting Content | str input with separate model IDs for
  text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image
  (AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints

Additional changes:
- Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT
- Add otel_provider_name passthrough to all embedding clients
- Register integration pytest marker in all packages
- Add lazy-loading namespace exports for Ollama and Bedrock embeddings
- Add image embedding sample using Cohere-embed-v3-english
- Add azure-ai-inference dependency to azure-ai package

Part of #1188

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

* Fix mypy duplicate name and ruff lint issues

- Rename second 'vector' variable to 'img_vector' in image embedding loop
- Combine nested with statements in tests
- Remove unused result assignments in tests

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

* updates from feedback

* Fix CI failures in embedding usage handling

- Fix Azure AI embedding mypy issues by normalizing vectors to list[float],
  safely accumulating optional usage token fields, and filtering None entries
  before constructing GeneratedEmbeddings
- Avoid Bandit false positive by initializing usage details as an empty dict
- Update OpenAI embedding tests to assert canonical usage keys
  (input_token_count/total_token_count)

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

---------

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

* [Purview] Mark responses as responses and fix epoch bug for python long overflow (#4225)

* .NET: Support InvokeMcpTool for declarative workflows (#4204)

* Initial implementation of InvokeMcpTool in declarative workflow

* Cleaned up sample implementation

* Updated sample comments.

* Added missing executor routing attribute

* Fix PR comments.

* Updated based on PR comments.

* Updated based on PR comments.

* Removed unnecessary using statement.

* Update Python package versions to rc2 (#4258)

- Bump core and azure-ai to 1.0.0rc2
- Bump preview packages to 1.0.0b260225
- Update dependencies to >=1.0.0rc2
- Add CHANGELOG entries for changes since rc1
- Update uv.lock

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

* .NET: Fixing issue where OpenTelemetry span is never exported in .NET in-process workflow execution (#4196)

* 1. Add reproduction test for issue #4155: workflow.run Activity never stopped in streaming OffThread path

The WorkflowRunActivity_IsStopped_Streaming_OffThread test demonstrates that
the workflow.run OpenTelemetry Activity created in StreamingRunEventStream.RunLoopAsync
is started but never stopped when using the OffThread/Default streaming execution.
The background run loop keeps running after event consumption completes, so the
using Activity? declaration never disposes until explicit StopAsync() is called.

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

2. Fix workflow.run Activity never stopped in streaming OffThread execution (#4155)

The workflow.run OpenTelemetry Activity in StreamingRunEventStream.RunLoopAsync
was scoped to the method lifetime via 'using'. Since the run loop only exits on
cancellation, the Activity was never stopped/exported until explicit disposal.

Fix: Remove 'using' and explicitly dispose the Activity when the workflow reaches
Idle status (all supersteps complete). A safety-net disposal in the finally block
handles cancellation and error paths.

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

* Add root-level workflow.session activity spanning run loop lifetime\n\nImplements two-level telemetry hierarchy per PR feedback from lokitoth:\n- workflow.session: spans the entire run loop / stream lifetime\n- workflow_invoke: per input-to-halt cycle, nested within the session\n\nThis ensures the session activity stays open across multiple turns,\nwhile individual run activities are created and disposed per cycle.\n\nAlso fixes linkedSource CancellationTokenSource disposal leak in\nStreamingRunEventStream (added using declaration)."

* Address Copilot review: fix Activity/CTS disposal, rename activity, add error tag\n\n1. LockstepRunEventStream: Remove 'using' from Activity in async iterator\n   and manually dispose in finally block (fixes #4155 pattern). Also dispose\n   linkedSource CTS in finally to prevent leak.\n2. Tags.cs: Add ErrorMessage (\"error.message\") tag for runtime errors,\n   distinct from BuildErrorMessage (\"build.error.message\").\n3. ActivityNames: Rename WorkflowRun from \"workflow_invoke\" to \"workflow.run\"\n   for cross-language consistency.\n4. WorkflowTelemetryContext: Fix XML doc to say \"outer/parent span\" instead\n   of \"root-level span\".\n5. ObservabilityTests: Assert WorkflowSession absence when DisableWorkflowRun\n   is true.\n6. WorkflowRunActivityStopTests: Fix streaming test race by disposing\n   StreamingRun before asserting activities are stopped.\n7. StreamingRunEventStream/LockstepRunEventStream: Use Tags.ErrorMessage\n   instead of Tags.BuildErrorMessage for runtime error events."

* Review fixes: revert workflow_invoke rename, use 'using' for linkedSource, move SessionStarted earlier\n\n- Revert ActivityNames.WorkflowRun back to \"workflow_invoke\" (OTEL semantic convention contract)\n- Use 'using' declaration for linkedSource CTS in LockstepRunEventStream (no timing sensitivity)\n- Move SessionStarted event before WaitForInputAsync in StreamingRunEventStream to match Lockstep behavior"

* Improve naming and comments in WorkflowRunActivityStopTests"

* Prevent session Activity.Current leak in lockstep mode, add nesting test

Save and restore Activity.Current in LockstepRunEventStream.Start() so the
session activity doesn't leak into caller code via AsyncLocal. Re-establish
Activity.Current = sessionActivity before creating the run activity in
TakeEventStreamAsync to preserve parent-child nesting.

Add test verifying app activities after RunAsync are not parented under the
session, and that the workflow_invoke activity nests under the session."

* Fix stale XML doc: WorkflowRun -> WorkflowInvoke in ObservabilityTests

---------

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

* Python / .NET Samples - Restructure and Improve Samples (Feature Branc… (#4092)

* Python: .NET Samples - Restructure and Improve Samples (Feature Branch) (#4091)

* Moved by agent (#4094)

* Fix readme links

* .NET Samples - Create `04-hosting` learning path step (#4098)

* Agent move

* Agent reorderd

* Remove A2A section from README 

Removed A2A section from the Getting Started README.

* Agent fixed links

* Fix broken sample links in durable-agents README (#4101)

* Initial plan

* Fix broken internal links in documentation

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Revert template link changes; keep only durable-agents README fix

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `03-workflows` learning path step (#4102)

* Fix solution project path

* Python: Fix broken markdown links to repo resources (outside /docs) (#4105)

* Initial plan

* Fix broken markdown links to repo resources

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update README to rename .NET Workflows Samples section

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* .NET Samples - Create `02-agents` learning path step (#4107)

* .NET: Fix broken relative link in GroupChatToolApproval README (#4108)

* Initial plan

* Fix broken link in GroupChatToolApproval README

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Update labeler configuration for workflow samples

* .NET - Reorder Agents samples to start from Step01 instead of Step04 (#4110)

* Fix solution

* Resolve new sample paths

* Move new AgentSkills and AgentWithMemory_Step04 samples

* Fix link

* Fix readme path

* fix: update stale dotnet/samples/Durable path reference in AGENTS.md

Co-authored-by: crickman <66376200+crickman@users.noreply.github.com>

* Moved new sample

* Update solution

* Resolve merge (new sample)

* Sync to new sample - FoundryAgents_Step21_BingCustomSearch

* Updated README

* .NET Samples - Configuration Naming Update (#4149)

* .NET: Restore AzureFunctions index parity with ConsoleApps under DurableAgents samples (#4221)

* Clean-up `05_host_your_agent`

* Config setting consistency

* Refine samples

* AGENTS.md

* Move new samples

* Re-order samples

* Move new project and fixup solution

* Fixup model config

* Fix up new UT project

---------

Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>

* Python: Fix Bedrock embedding test stub missing meta attribute (#4287)

* Fix Bedrock embedding test stub missing meta attribute

* Increase test coverage so gate passes

* Python: (ag-ui): fix approval payloads being re-processed on subsequent conversation turns (#4232)

* Fix ag-ui tool call issue

* Safe json fix

* Python: Update workflow orchestration samples to use AzureOpenAIResponsesClient (#4285)

* Update workflow orchestration samples to use AzureOpenAIResponsesClient

* Fix broken link

* Move scripts to scripts folder

---------

Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>
Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Rishabh Chawla <rishabhchawla1995@gmail.com>
Co-authored-by: Peter Ibekwe <109177538+peibekwe@users.noreply.github.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>
Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
8b191de936 · 2026-02-26 10:49:07 +00:00
History
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2026-02-26 10:49:07 +00:00

Agent Framework Lab

This is the experimental package for Microsoft Agent Framework, agent-framework-lab, which contains various lab modules built on top of the core framework. Lab modules are not part of the core framework and may experience breaking changes or be deprecated in the future.

What are Lab Modules?

Lab modules are extensions to the core Agent Framework that fall into one of the following categories:

  1. Incubation of new features that may get incorporated by the core framework.
  2. Research prototypes built on the core framework.
  3. Benchmarks and experimentation tools.

Lab Modules

  • gaia: Evaluate your agents using the GAIA benchmark for general assistant tasks
  • tau2: Evaluate your agents using the TAU2 benchmark for customer support tasks
  • lightning: RL training for agents using Agent Lightning

Repository Structure

agent-framework-lab/
├── pyproject.toml          # Single package configuration for agent-framework-lab
├── README.md               # This file
├── LICENSE                 # License file
├── namespace/              # Centralized namespace package files
│   └── agent_framework/
│       └── lab/
│           ├── gaia/       # Re-exports from agent_framework_lab_gaia
│           ├── lightning/  # Re-exports from agent_framework_lab_lightning
│           └── tau2/       # Re-exports from agent_framework_lab_tau2
├── gaia/                   # GAIA module implementation
│   └── agent_framework_lab_gaia/
├── lightning/              # Lightning module implementation
│   └── agent_framework_lab_lightning/
└── tau2/                   # TAU2 module implementation
    └── agent_framework_lab_tau2/

This structure maintains a single PyPI package agent-framework-lab while supporting modular imports through the namespace package mechanism.

Installation

To install each lab module, use the extras syntax with pip:

pip install "agent-framework-lab[gaia]"
pip install "agent-framework-lab[tau2]"
pip install "agent-framework-lab[lightning]"

Usage

Import and use lab modules from the agent_framework.lab namespace. For example, to use the GAIA module:

# Using GAIA module
from agent_framework.lab.gaia import GAIA

Should I consume Lab Modules?

If you are looking for stable and production-ready features, you should not use lab modules. Stick to the core framework.

If you are looking for experimentation, research, or want to benchmark different approaches -- most importantly, if you don't mind breaking changes and potential deprecations -- then lab modules are for you.

Contributing to Lab Modules

Microsoft-maintained modules

For Microsoft-maintained modules in this repository, please follow standard contribution guidelines and submit pull requests directly to this repository.

Community modules

If you want to contribute a community-maintained lab module:

  1. Create a new repository on GitHub for your module
  2. Tag your repository with agent-framework-lab for discoverability
  3. Submit a PR to add a link to your repository in the Lab Modules section above
  4. Use the PR title format: [New Lab Module] Your Module Name

We will review your submission based on the guidelines below.

Guidelines

  1. Purpose: Community modules should fit into one of the three categories of lab modules (incubation, research, benchmarks)
  2. Namespace: Community modules should avoid the agent_framework.lab namespace (reserved for modules maintained in this repository)
  3. Dependencies: Minimize external dependencies, always include agent-framework as a base dependency
  4. Documentation: Include comprehensive README with installation instructions and usage examples
  5. Tests: Write comprehensive tests with good coverage
  6. Type hints: Always include type hints and a py.typed file
  7. Versioning: Use semantic versioning, start with 0.1.0 for initial releases