Merge branch 'main' into feature-foundry-agents

This commit is contained in:
Chris
2025-11-12 08:53:51 -08:00
committed by GitHub
Unverified
17 changed files with 677 additions and 374 deletions
@@ -6,16 +6,64 @@
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<!--
Disable central package management for this project.
This project requires explicit package references with versions specified inline rather than
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
be created from this project, and the Docker build process only has access to this folder
and cannot access parent folders where Directory.Packages.props resides.
-->
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
</PropertyGroup>
<!--
Remove analyzer PackageReference items inherited from Directory.Packages.props.
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
and the PackageReference items are always inherited through MSBuild imports regardless of the
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
-->
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
<PackageReference Remove="xunit.analyzers" />
<PackageReference Remove="Moq.Analyzers" />
<PackageReference Remove="Roslynator.Analyzers" />
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.OpenAI\Microsoft.Agents.AI.OpenAI.csproj" />
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.4" />
<PackageReference Include="Azure.AI.OpenAI" Version="2.5.0-beta.1" />
<PackageReference Include="Azure.Identity" Version="1.17.0" />
<PackageReference Include="Microsoft.Agents.AI.OpenAI" Version="1.0.0-preview.251110.2" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="9.10.2-preview.1.25552.1" />
</ItemGroup>
<!-- Add analyzers with compatible versions -->
<ItemGroup>
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="9.0.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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@@ -0,0 +1,20 @@
# Build the application
FROM mcr.microsoft.com/dotnet/sdk:9.0-alpine AS build
WORKDIR /src
# Copy files from the current directory on the host to the working directory in the container
COPY . .
RUN dotnet restore
RUN dotnet build -c Release --no-restore
RUN dotnet publish -c Release --no-build -o /app
# Run the application
FROM mcr.microsoft.com/dotnet/aspnet:9.0-alpine AS final
WORKDIR /app
# Copy everything needed to run the app from the "build" stage.
COPY --from=build /app .
EXPOSE 8088
ENTRYPOINT ["dotnet", "AgentWithTextSearchRag.dll"]
@@ -4,6 +4,7 @@
// capabilities to an AI agent. The provider runs a search against an external knowledge base
// before each model invocation and injects the results into the model context.
using Azure.AI.AgentServer.AgentFramework.Extensions;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
@@ -23,7 +24,7 @@ TextSearchProviderOptions textSearchOptions = new()
AIAgent agent = new AzureOpenAIClient(
new Uri(endpoint),
new AzureCliCredential())
new DefaultAzureCredential())
.GetChatClient(deploymentName)
.CreateAIAgent(new ChatClientAgentOptions
{
@@ -31,16 +32,7 @@ AIAgent agent = new AzureOpenAIClient(
AIContextProviderFactory = ctx => new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)
});
AgentThread thread = agent.GetNewThread();
Console.WriteLine(">> Asking about returns\n");
Console.WriteLine(await agent.RunAsync("Hi! I need help understanding the return policy.", thread));
Console.WriteLine("\n>> Asking about shipping\n");
Console.WriteLine(await agent.RunAsync("How long does standard shipping usually take?", thread));
Console.WriteLine("\n>> Asking about product care\n");
Console.WriteLine(await agent.RunAsync("What is the best way to maintain the TrailRunner tent fabric?", thread));
await agent.RunAIAgentAsync();
static Task<IEnumerable<TextSearchProvider.TextSearchResult>> MockSearchAsync(string query, CancellationToken cancellationToken)
{
@@ -0,0 +1,29 @@
name: AgentWithTextSearchRag
displayName: "Text Search RAG Agent"
description: >
An AI agent that uses TextSearchProvider for retrieval augmented generation (RAG) capabilities.
The agent runs searches against an external knowledge base before each model invocation and
injects the results into the model context. It can answer questions about Contoso Outdoors
policies and products, including return policies, refunds, shipping options, and product care
instructions such as tent maintenance.
metadata:
authors:
- Microsoft Agent Framework Team
tags:
- example
- Agent Framework
template:
kind: hosted
name: AgentWithTextSearchRag
protocols:
- protocol: responses
version: v1
environment_variables:
- name: AZURE_OPENAI_ENDPOINT
value: ${AZURE_OPENAI_ENDPOINT}
- name: AZURE_OPENAI_DEPLOYMENT_NAME
value: gpt-4o-mini
resources:
- name: "gpt-4o-mini"
kind: model
id: gpt-4o-mini
@@ -0,0 +1,30 @@
@host = http://localhost:8088
@endpoint = {{host}}/responses
### Health Check
GET {{host}}/readiness
### Simple string input
POST {{endpoint}}
Content-Type: application/json
{
"input": "Hi! I need help understanding the return policy."
}
### Explicit input
POST {{endpoint}}
Content-Type: application/json
{
"input": [
{
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "How long does standard shipping usually take?"
}
]
}
]
}
@@ -6,18 +6,64 @@
<Nullable>enable</Nullable>
<ImplicitUsings>enable</ImplicitUsings>
<!--
Disable central package management for this project.
This project requires explicit package references with versions specified inline rather than
inheriting them from Directory.Packages.props. This is necessary because a Docker image will
be created from this project, and the Docker build process only has access to this folder
and cannot access parent folders where Directory.Packages.props resides.
-->
<ManagePackageVersionsCentrally>false</ManagePackageVersionsCentrally>
</PropertyGroup>
<!--
Remove analyzer PackageReference items inherited from Directory.Packages.props.
Note: ManagePackageVersionsCentrally only controls PackageVersion items, not PackageReference items.
Directory.Packages.props contains both PackageVersion and PackageReference entries for analyzers,
and the PackageReference items are always inherited through MSBuild imports regardless of the
ManagePackageVersionsCentrally setting. We must explicitly remove them before adding our own versions.
-->
<ItemGroup>
<PackageReference Include="Azure.AI.OpenAI" />
<PackageReference Include="Azure.Identity" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
<PackageReference Remove="Microsoft.CodeAnalysis.NetAnalyzers" />
<PackageReference Remove="Microsoft.VisualStudio.Threading.Analyzers" />
<PackageReference Remove="xunit.analyzers" />
<PackageReference Remove="Moq.Analyzers" />
<PackageReference Remove="Roslynator.Analyzers" />
<PackageReference Remove="Roslynator.CodeAnalysis.Analyzers" />
<PackageReference Remove="Roslynator.Formatting.Analyzers" />
</ItemGroup>
<ItemGroup>
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI.AzureAI.Persistent\Microsoft.Agents.AI.AzureAI.Persistent.csproj" />
<ProjectReference Include="..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
<PackageReference Include="Azure.AI.AgentServer.AgentFramework" Version="1.0.0-beta.4" />
<PackageReference Include="Azure.AI.OpenAI" Version="2.5.0-beta.1" />
<PackageReference Include="Azure.Identity" Version="1.17.0" />
<PackageReference Include="Microsoft.Agents.AI.Workflows" Version="1.0.0-preview.251110.2" />
<PackageReference Include="Microsoft.Extensions.AI.OpenAI" Version="9.10.2-preview.1.25552.1" />
</ItemGroup>
<!-- Add analyzers with compatible versions -->
<ItemGroup>
<PackageReference Include="Microsoft.CodeAnalysis.NetAnalyzers" Version="9.0.0">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Microsoft.VisualStudio.Threading.Analyzers" Version="17.14.15">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.Analyzers" Version="4.12.9">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
<PackageReference Include="Roslynator.CodeAnalysis.Analyzers" Version="4.12.9">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
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<PackageReference Include="Roslynator.Formatting.Analyzers" Version="4.12.9">
<PrivateAssets>all</PrivateAssets>
<IncludeAssets>runtime; build; native; contentfiles; analyzers; buildtransitive</IncludeAssets>
</PackageReference>
</ItemGroup>
</Project>
@@ -0,0 +1,20 @@
# Build the application
FROM mcr.microsoft.com/dotnet/sdk:9.0-alpine AS build
WORKDIR /src
# Copy files from the current directory on the host to the working directory in the container
COPY . .
RUN dotnet restore
RUN dotnet build -c Release --no-restore
RUN dotnet publish -c Release --no-build -o /app
# Run the application
FROM mcr.microsoft.com/dotnet/aspnet:9.0-alpine AS final
WORKDIR /app
# Copy everything needed to run the app from the "build" stage.
COPY --from=build /app .
EXPOSE 8088
ENTRYPOINT ["dotnet", "AgentsInWorkflows.dll"]
@@ -4,6 +4,7 @@
// Three translation agents are connected sequentially to create a translation chain:
// English → French → Spanish → English, showing how agents can be composed as workflow executors.
using Azure.AI.AgentServer.AgentFramework.Extensions;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
@@ -14,7 +15,7 @@ using Microsoft.Extensions.AI;
var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
IChatClient chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
IChatClient chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
.GetChatClient(deploymentName)
.AsIChatClient();
@@ -23,26 +24,14 @@ AIAgent frenchAgent = GetTranslationAgent("French", chatClient);
AIAgent spanishAgent = GetTranslationAgent("Spanish", chatClient);
AIAgent englishAgent = GetTranslationAgent("English", chatClient);
// Build the workflow by adding executors and connecting them
Workflow workflow = new WorkflowBuilder(frenchAgent)
// Build the workflow and turn it into an agent
AIAgent agent = new WorkflowBuilder(frenchAgent)
.AddEdge(frenchAgent, spanishAgent)
.AddEdge(spanishAgent, englishAgent)
.Build();
.Build()
.AsAgent();
// Execute the workflow
await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!"));
// Must send the turn token to trigger the agents.
// The agents are wrapped as executors. When they receive messages,
// they will cache the messages and only start processing when they receive a TurnToken.
await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
await foreach (WorkflowEvent evt in run.WatchStreamAsync())
{
if (evt is AgentRunUpdateEvent executorComplete)
{
Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
}
}
await agent.RunAIAgentAsync();
static ChatClientAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
new(chatClient, $"You are a translation assistant that translates the provided text to {targetLanguage}.");
@@ -0,0 +1,28 @@
name: AgentsInWorkflows
displayName: "Translation Chain Workflow Agent"
description: >
A workflow agent that performs sequential translation through multiple languages.
The agent translates text from English to French, then to Spanish, and finally back
to English, leveraging AI-powered translation capabilities in a pipeline workflow.
metadata:
authors:
- Agent Framework Team
tags:
- example
- Microsoft Agent Framework Team
- workflows
template:
kind: hosted
name: AgentsInWorkflows
protocols:
- protocol: responses
version: v1
environment_variables:
- name: AZURE_OPENAI_ENDPOINT
value: ${AZURE_OPENAI_ENDPOINT}
- name: AZURE_OPENAI_DEPLOYMENT_NAME
value: gpt-4o-mini
resources:
- name: "gpt-4o-mini"
kind: model
id: gpt-4o-mini
@@ -0,0 +1,30 @@
@host = http://localhost:8088
@endpoint = {{host}}/responses
### Health Check
GET {{host}}/readiness
### Simple string input
POST {{endpoint}}
Content-Type: application/json
{
"input": "Hello, how are you today?"
}
### Explicit input
POST {{endpoint}}
Content-Type: application/json
{
"input": [
{
"type": "message",
"role": "user",
"content": [
{
"type": "input_text",
"text": "Hello, how are you today?"
}
]
}
]
}
@@ -330,11 +330,19 @@ class AnthropicClient(BaseChatClient):
if content.has_top_level_media_type("image"):
a_content.append({
"type": "image",
"source": {"data": content.uri, "media_type": content.media_type},
"source": {
"data": content.get_data_bytes_as_str(),
"media_type": content.media_type,
"type": "base64",
},
})
else:
logger.debug(f"Ignoring unsupported data content media type: {content.media_type} for now")
case "uri":
if content.has_top_level_media_type("image"):
a_content.append({"type": "image", "source": {"type": "url", "url": content.uri}})
else:
logger.debug(f"Ignoring unsupported data content media type: {content.media_type} for now")
case "function_call":
a_content.append({
"type": "tool_use",
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@@ -1,5 +1,6 @@
# Copyright (c) Microsoft. All rights reserved.
import os
from pathlib import Path
from typing import Annotated
from unittest.mock import MagicMock, patch
@@ -9,6 +10,7 @@ from agent_framework import (
ChatMessage,
ChatOptions,
ChatResponseUpdate,
DataContent,
FinishReason,
FunctionCallContent,
FunctionResultContent,
@@ -775,3 +777,31 @@ async def test_anthropic_client_integration_ordering() -> None:
assert response is not None
assert response.messages[0].text is not None
@pytest.mark.flaky
@skip_if_anthropic_integration_tests_disabled
async def test_anthropic_client_integration_images() -> None:
"""Integration test with images."""
client = AnthropicClient()
# get a image from the assets folder
image_path = Path(__file__).parent / "assets" / "sample_image.jpg"
with open(image_path, "rb") as img_file: # noqa [ASYNC230]
image_bytes = img_file.read()
messages = [
ChatMessage(
role=Role.USER,
contents=[
TextContent(text="Describe this image"),
DataContent(media_type="image/jpeg", data=image_bytes),
],
),
]
response = await client.get_response(messages=messages)
assert response is not None
assert response.messages[0].text is not None
assert "house" in response.messages[0].text.lower()
+26 -3
View File
@@ -897,6 +897,9 @@ class TextReasoningContent(BaseContent):
return self
TDataContent = TypeVar("TDataContent", bound="DataContent")
class DataContent(BaseContent):
"""Represents binary data content with an associated media type (also known as a MIME type).
@@ -1079,8 +1082,8 @@ class DataContent(BaseContent):
except Exception:
return "png" # Fallback if decoding fails
@classmethod
def create_data_uri_from_base64(cls, image_base64: str) -> tuple[str, str]:
@staticmethod
def create_data_uri_from_base64(image_base64: str) -> tuple[str, str]:
"""Create a data URI and media type from base64 image data.
Args:
@@ -1089,11 +1092,31 @@ class DataContent(BaseContent):
Returns:
Tuple of (data_uri, media_type)
"""
format_type = cls.detect_image_format_from_base64(image_base64)
format_type = DataContent.detect_image_format_from_base64(image_base64)
uri = f"data:image/{format_type};base64,{image_base64}"
media_type = f"image/{format_type}"
return uri, media_type
def get_data_bytes_as_str(self) -> str:
"""Extracts and returns the base64-encoded data from the data URI.
Returns:
The binary data as str.
"""
match = URI_PATTERN.match(self.uri)
if not match:
raise ValueError(f"Invalid data URI format: {self.uri}")
return match.group("base64_data")
def get_data_bytes(self) -> bytes:
"""Extracts and returns the binary data from the data URI.
Returns:
The binary data as bytes.
"""
base64_data = self.get_data_bytes_as_str()
return base64.b64decode(base64_data)
class UriContent(BaseContent):
"""Represents a URI content.
+1 -1
View File
@@ -56,7 +56,7 @@ math = [
[dependency-groups]
dev = [
"uv>=0.8.2,<0.9.0",
"uv",
"pre-commit >= 3.7",
"ruff>=0.11.8",
"pytest>=8.4.1",
+1 -1
View File
@@ -39,7 +39,7 @@ dependencies = [
[dependency-groups]
dev = [
"uv>=0.8.2,<0.10.0",
"uv>=0.9,<1.0.0",
"flit>=3.12.0",
"pre-commit >= 3.7",
"ruff>=0.11.8",
+339 -329
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