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The agent framework is still going through API churn as it heads to GA (see microsoft/agent-framework#2542).
Rather than delaying v1 of Devlooped.Extensions.AI (and Grok support), declouple the two and ship from independent repos. The MS.E.AI API is far more stable at this point.
Console.WriteLine($"Agent: {agent.Name} by {metadata.ProviderName}");
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}
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```
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You can of course use any config format supported by .NET configuration, such as
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TOML which is arguably more human-friendly for hand-editing:
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```toml
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[ai.clients.openai]
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modelid = "gpt-4.1"
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[ai.clients.grok]
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endpoint = "https://api.x.ai/v1"
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modelid = "grok-4-fast-non-reasoning"
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[ai.agents.orders]
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description = "Manage orders using catalogs for food or any other item."
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instructions = """
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You are an AI agent responsible for processing orders for food or other items.
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Your primary goals are to identify user intent, extract or request provider information, manage order data using tools and friendly responses to guide users through the ordering process.
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"""
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# ai.clients.openai, can omit the ai.clients prefix
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client = "openai"
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[ai.agents.orders.options]
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modelid = "gpt-4o-mini"
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```
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This can be used by leveraging [Tomlyn.Extensions.Configuration](https://www.nuget.org/packages/Tomlyn.Extensions.Configuration).
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> [!NOTE]
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> This package will automatically dedent and trim start and end newlines from
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> multi-line instructions and descriptions when applying the configuration,
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> avoiding unnecessary tokens being used for indentation while allowing flexible
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> formatting in the config file.
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You can also leverage the format pioneered by [VS Code Chat Modes](https://code.visualstudio.com/docs/copilot/customization/custom-chat-modes),
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(por "custom agents") by using markdown format plus YAML front-matter for better readability:
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```yaml
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---
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id: ai.agents.notes
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description: Provides free-form memory
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client: grok
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model: grok-4-fast
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---
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You organize and keep notes for the user.
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# Some header
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More content
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```
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Visual Studio Code will ignore the additional attributes used by this project. In particular, the `model`
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property is a shorthand for setting the `options.modelid`, but in our implementation, the latter takes
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precedence over the former, which allows you to rely on `model` to drive the VSCode testing, and the
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longer form for run-time with the Agents Framework:
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```yaml
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---
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id: ai.agents.notes
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description: Provides free-form memory
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model: Grok Code Fast 1 (copilot)
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client: grok
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options:
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modelid: grok-code-fast-1
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---
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// Instructions
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```
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Use the provided `AddAgentMarkdown` extension method to load instructions from files as follows:
The `id` field in the front-matter is required and specifies the configuration section name, and
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all other fields are added as if they were specified under it in the configuration.
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### Extensible AI Contexts
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The Microsoft [agent framework](https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview) allows extending
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agents with dynamic context via [AIContextProvider](https://learn.microsoft.com/en-us/dotnet/api/microsoft.agents.ai.aicontextprovider)
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and `AIContext`. This package supports dynamic extension of a configured agent in the following ways (in order of priority):
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1. A keyed service `AIContextProviderFactory` with the same name as the agent will be set up just as if you had
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set it manually as the [ChatClientAgentOptions.AIContextProviderFactory](https://learn.microsoft.com/en-us/dotnet/api/microsoft.agents.ai.chatclientagentoptions.aicontextproviderfactory)
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in code.
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2. Aggregate of AI contexts from:
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a. Keyed service `AIContextProvider` with the same name as the agent.
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b. Keyed service `AIContext` with the same name as the agent.
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c. Other services pulled in via `use` setting for an agent registered as either `AIContextProvider` or `AIContext`
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with a matching key.
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The first option assumes you want full control of the context, so it does not allow futher composition.
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The second alternative allows more declarative scenarios involving reusable and cross-cutting
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context definitions.
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For example, let's say you want to provide consistent tone for all your agents. It would be tedious, repetitive and harder
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to maintain if you had to set that in each agent's instructions. Instead, you can define a reusable context named `tone` such as:
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```toml
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[ai.context.tone]
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instructions = """\
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Default to using spanish language, using argentinean "voseo" in your responses \
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(unless the user explicitly talks in a different language). \
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This means using "vos" instead of "tú" and conjugating verbs accordingly. \
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Don't use the expression "pa'" instead of "para". Don't mention the word "voseo".
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"""
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```
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Then, you can reference that context in any agent using the `use` setting:
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```toml
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[ai.agents.support]
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description = "An AI agent that helps with customer support."
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instructions = "..."
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client = "grok"
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use = ["tone"]
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[ai.agents.sales]
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description = "An AI agent that helps with sales inquiries."
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instructions = "..."
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client = "openai"
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use = ["tone"]
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```
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Configured contexts can provide all three components of an `AIContext`: instructions, messages and tools, such as:
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```toml
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[ai.context.timezone]
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instructions = "Always assume the user's timezone is America/Argentina/Buenos_Aires unless specified otherwise."
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messages = [
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{ system = "You are aware of the current date and time in America/Argentina/Buenos_Aires." }
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]
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tools = ["get_date"]
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```
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If multiple contexts are specified in `use`, they are applied in order, concatenating their instructions, messages and tools.
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In addition to configured sections, the `use` property can also reference exported contexts as either `AIContext`
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(for static context) or `AIContextProvider` (for dynamic context) registered in DI with a matching name.
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### Extensible Tools
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The `tools` section allows specifying tool names registered in the DI container, such as:
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