- Delete all launchSettings.json files (port 8088 now comes from ASPNETCORE_URLS in .env)
- Add DotNetEnv to Hosted-Invocations-EchoAgent so it loads .env like the responses samples
- Create .env.example for EchoAgent with ASPNETCORE_URLS and ASPNETCORE_ENVIRONMENT
- Add AGENT_NAME to ChatClientAgent and FoundryAgent .env.example (required by those samples)
- Add AZURE_BEARER_TOKEN=DefaultAzureCredential to all .env.example files
- Update DevTemporaryTokenCredential in all 6 samples to treat the sentinel value
as unavailable, allowing ChainedTokenCredential to fall through to DefaultAzureCredential
- Update EchoAgent README with Configuration section
Align dotnet hosted agent samples with the Python side (PR #5281) by
reorganizing the directory structure:
- Remove HostedAgentsV1 entirely (old API pattern)
- Split HostedAgentsV2 into invocations/ and responses/ based on protocol
- Move Using-Samples accordingly (SimpleAgent to responses, SimpleInvocationsAgent to invocations)
- Update slnx with new project paths and add previously missing invocations projects
- Update README cd paths from HostedAgentsV2 to invocations or responses
- Rename .env.local to .env.example to match Python naming convention
- Fix format violations in newly included invocations projects
Add Hosted-Invocations-EchoAgent: a minimal echo agent hosted via the
Invocations protocol (POST /invocations) using AddInvocationsServer and
MapInvocationsServer, bridged to an Agent Framework AIAgent through a
custom InvocationHandler.
Add SimpleInvocationsAgent: a console REPL client that wraps HttpClient
calls to the /invocations endpoint in a custom InvocationsAIAgent,
demonstrating programmatic consumption of the Invocations protocol.
Both samples default to port 8088 for consistency with other hosted
agent samples.
Demonstrates two MCP integration layers in a single hosted agent:
- Client-side MCP: McpClient connects to Microsoft Learn, agent handles
tool invocations locally (docs_search, code_sample_search, docs_fetch)
- Server-side MCP: HostedMcpServerTool delegates tool discovery and
invocation to the LLM provider (Responses API), no local connection
Includes DevTemporaryTokenCredential for Docker local debugging,
Dockerfile.contributor for ProjectReference builds, and the openai/v1
route mapping for AIProjectClient compatibility in Development mode.
Previously, unhandled exceptions from agent execution would bubble up
to the SDK orchestrator, which emits a generic 'An internal server
error occurred.' message — hiding the actual cause (e.g., 401 auth
failures, model not found, etc.).
Now AgentFrameworkResponseHandler catches non-cancellation exceptions
and emits a proper response.failed event containing the real error
message, making it visible to clients and in logs.
OperationCanceledException still propagates for proper cancellation
handling by the SDK.
Also bumps package version to 0.9.0-hosted.260403.2.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- InputConverter: stop propagating request.Model to ChatOptions.ModelId
Hosted agents use their own model; client-provided model values like
'hosted-agent' were being passed through and causing server errors.
- Add FoundryResponsesRepl sample: interactive CLI client that connects
to a Foundry Responses endpoint using ResponsesClient.AsAIAgent()
- Bump package version to 0.9.0-hosted.260403.1
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Move source and test files from the standalone Hosting.AzureAIResponses project
into the Foundry package under a Hosting/ subfolder. This consolidates the
Foundry-specific hosting adapter into the main Foundry package.
- Source: Microsoft.Agents.AI.Foundry.Hosting namespace
- Tests: merged into Foundry.UnitTests/Hosting/
- Conditionally compiled for .NETCoreApp TFMs only (net8.0+)
- Deleted standalone Hosting.AzureAIResponses project and test project
- Updated sample and solution references
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Implement Microsoft.Agents.AI.Hosting.AzureAIResponses to host agent-framework
AIAgents and workflows within Azure Foundry as hosted agents via the
Azure.AI.AgentServer.Responses SDK.
- AgentFrameworkResponseHandler: bridges ResponseHandler to AIAgent execution
- InputConverter: converts Responses API inputs/history to MEAI ChatMessage
- OutputConverter: converts agent response updates to SSE event stream
- ServiceCollectionExtensions: DI registration helpers
- 336 unit tests across net8.0/net9.0/net10.0 (112 per TFM)
- ResponseStreamValidator: SSE protocol validation tool for samples
- FoundryResponsesHosting sample app
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Demonstrates two MCP integration layers in a single hosted agent:
- Client-side MCP: McpClient connects to Microsoft Learn, agent handles
tool invocations locally (docs_search, code_sample_search, docs_fetch)
- Server-side MCP: HostedMcpServerTool delegates tool discovery and
invocation to the LLM provider (Responses API), no local connection
Includes DevTemporaryTokenCredential for Docker local debugging,
Dockerfile.contributor for ProjectReference builds, and the openai/v1
route mapping for AIProjectClient compatibility in Development mode.
* support reflection for discovery of resources and scripts in class-based skills
* fix format issues
* refactor samples to use reflection
* Validate resource member signatures during discovery
Add discovery-time validation in AgentClassSkill.DiscoverResources() to
fail fast when [AgentSkillResource] is applied to members with incompatible
signatures:
- Reject indexer properties (getter has parameters)
- Reject methods with parameters other than IServiceProvider or
CancellationToken
Throws InvalidOperationException with actionable error messages instead of
allowing silent runtime failures when ReadAsync invokes the AIFunction with
no named arguments.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* prevent duplicates
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Concurrent Workflow Sample
* Switch to using Azure AI Projects APIs
* Remove agent streaming outputs by changing emitEvents to false on TurnToken
* Disable forwarding input from agent host executors
* Make output format more legible
* refactor: Update Concurrent sample to use message delivery event callback
Roger Barreto
alliscodeandCopilot
Jacob AlberandGitHub