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GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | This tutorial shows how to use AutoGen.Net agent as model in AG Studio |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Step 1. Create Dotnet empty web app and install AutoGen and AutoGen.WebAPI package ```bash dotnet new web dotnet add package AutoGen dotnet add package AutoGen.WebAPI ``` |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Step 2. Replace the Program.cs with following code ```bash using AutoGen.Core; using AutoGen.Service; var builder = WebApplication.CreateBuilder(args); var app = builder.Build(); var helloWorldAgent = new HelloWorldAgent(); app.UseAgentAsOpenAIChatCompletionEndpoint(helloWorldAgent); app.Run(); class HelloWorldAge... |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Step 3: Start the web app Run the following command to start web api ```bash dotnet RUN ``` The web api will listen at `http://localhost:5264/v1/chat/completion  |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Step 4: In another terminal, start autogen-studio ```bash autogenstudio ui ``` |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Step 5: Navigate to AutoGen Studio UI and add hello world agent as openai Model ### Step 5.1: Go to model tab  ### Step 5.2: Select "OpenAI model" card   |
GitHub | autogen | autogen/dotnet/website/tutorial/Use-AutoGen.Net-agent-as-model-in-AG-Studio.md | autogen | Final Step: Use the hello world agent in workflow   ] |
GitHub | autogen | autogen/dotnet/website/tutorial/Chat-with-an-agent.md | autogen | Step 3: Create an @AutoGen.OpenAI.OpenAIChatAgent > [!NOTE] > The @AutoGen.OpenAI.Extension.OpenAIAgentExtension.RegisterMessageConnector* method registers an @AutoGen.OpenAI.OpenAIChatRequestMessageConnector middleware which converts OpenAI message types to AutoGen message types. This step is necessary when you want ... |
GitHub | autogen | autogen/dotnet/website/tutorial/Chat-with-an-agent.md | autogen | Step 4: Generate Response To generate response, you can use one of the overloaded method of @AutoGen.Core.AgentExtension.SendAsync* method. The following code shows how to generate response with text message: [!code-csharp[Generate Response](../../samples/AutoGen.BasicSamples/GettingStart/Chat_With_Agent.cs?name=Chat_... |
GitHub | autogen | autogen/dotnet/website/tutorial/Chat-with-an-agent.md | autogen | Further Reading - [Chat with google gemini](../articles/AutoGen.Gemini/Chat-with-google-gemini.md) - [Chat with vertex gemini](../articles/AutoGen.Gemini/Chat-with-vertex-gemini.md) - [Chat with Ollama](../articles/AutoGen.Ollama/Chat-with-llama.md) - [Chat with Semantic Kernel Agent](../articles/AutoGen.SemanticKernel... |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | This tutorial shows how to perform image chat with an agent using the @AutoGen.OpenAI.OpenAIChatAgent as an example. > [!NOTE] > To chat image with an agent, the model behind the agent needs to support image input. Here is a partial list of models that support image input: > - gpt-4o > - gemini-1.5 > - llava > - claud... |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Step 1: Install AutoGen First, install the AutoGen package using the following command: ```bash dotnet add package AutoGen ``` |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Step 2: Add Using Statements [!code-csharp[Using Statements](../../samples/AutoGen.BasicSamples/GettingStart/Image_Chat_With_Agent.cs?name=Using)] |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Step 3: Create an @AutoGen.OpenAI.OpenAIChatAgent [!code-csharp[Create an OpenAIChatAgent](../../samples/AutoGen.BasicSamples/GettingStart/Image_Chat_With_Agent.cs?name=Create_Agent)] |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Step 4: Prepare Image Message In AutoGen, you can create an image message using either @AutoGen.Core.ImageMessage or @AutoGen.Core.MultiModalMessage. The @AutoGen.Core.ImageMessage takes a single image as input, whereas the @AutoGen.Core.MultiModalMessage allows you to pass multiple modalities like text or image. Her... |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Step 5: Generate Response To generate response, you can use one of the overloaded methods of @AutoGen.Core.AgentExtension.SendAsync* method. The following code shows how to generate response with an image message: [!code-csharp[Generate Response](../../samples/AutoGen.BasicSamples/GettingStart/Image_Chat_With_Agent.c... |
GitHub | autogen | autogen/dotnet/website/tutorial/Image-chat-with-agent.md | autogen | Further Reading - [Image chat with gemini](../articles/AutoGen.Gemini/Image-chat-with-gemini.md) - [Image chat with llava](../articles/AutoGen.Ollama/Chat-with-llava.md) |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | This tutorial shows how to use tools in an agent. |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | What is tool Tools are pre-defined functions in user's project that agent can invoke. Agent can use tools to perform actions like search web, perform calculations, etc. With tools, it can greatly extend the capabilities of an agent. > [!NOTE] > To use tools with agent, the backend LLM model used by the agent needs to ... |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Key Concepts - @AutoGen.Core.FunctionContract: The contract of a function that agent can invoke. It contains the function name, description, parameters schema, and return type. - @AutoGen.Core.ToolCallMessage: A message type that represents a tool call request in AutoGen.Net. - @AutoGen.Core.ToolCallResultMessage: A me... |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Install AutoGen and AutoGen.SourceGenerator First, install the AutoGen and AutoGen.SourceGenerator package using the following command: ```bash dotnet add package AutoGen dotnet add package AutoGen.SourceGenerator ``` Also, you might need to enable structural xml document support by setting `GenerateDocumentationFile... |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Add Using Statements [!code-csharp[Using Statements](../../samples/AutoGen.BasicSamples/GettingStart/Use_Tools_With_Agent.cs?name=Using)] |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Create agent Create an @AutoGen.OpenAI.OpenAIChatAgent with `GPT-3.5-turbo` as the backend LLM model. [!code-csharp[Create an agent with tools](../../samples/AutoGen.BasicSamples/GettingStart/Use_Tools_With_Agent.cs?name=Create_Agent)] |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Define `Tool` class and create tools Create a `public partial` class to host the tools you want to use in AutoGen agents. The method has to be a `public` instance method and its return type must be `Task<string>`. After the methods is defined, mark them with @AutoGen.Core.FunctionAttribute attribute. In the following ... |
GitHub | autogen | autogen/dotnet/website/tutorial/Create-agent-with-tools.md | autogen | Tool call without auto-invoke In this case, when receiving a @AutoGen.Core.ToolCallMessage, the agent will not automatically invoke the tool. Instead, the agent will return the original message back to the user. The user can then decide whether to invoke the tool or not.  - [Function call with gemini](../articles/AutoGen.Gemini/Function-call-with-gemini.md) - [Function call with local model](../articles/Function-call-with-ollama-and-litellm.md) - [Use kernel plugin in other agents](../article... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-simple-chat.md | autogen | The following example shows how to create an @AutoGen.OpenAI.OpenAIChatAgent and chat with it. Firsly, import the required namespaces: [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/OpenAICodeSnippet.cs?name=using_statement)] Then, create an @AutoGen.OpenAI.OpenAIChatAgent and chat with it: [!code-csh... |
GitHub | autogen | autogen/dotnet/website/articles/Create-a-user-proxy-agent.md | autogen | ## UserProxyAgent [`UserProxyAgent`](../api/AutoGen.UserProxyAgent.yml) is a special type of agent that can be used to proxy user input to another agent or group of agents. It supports the following human input modes: - `ALWAYS`: Always ask user for input. - `NEVER`: Never ask user for input. In this mode, the agent w... |
GitHub | autogen | autogen/dotnet/website/articles/AutoGen-OpenAI-Overview.md | autogen | ## AutoGen.OpenAI Overview AutoGen.OpenAI provides the following agents over openai models: - @AutoGen.OpenAI.OpenAIChatAgent: A slim wrapper agent over `OpenAIClient`. This agent only support `IMessage<ChatRequestMessage>` message type. To support more message types like @AutoGen.Core.TextMessage, register the agent ... |
GitHub | autogen | autogen/dotnet/website/articles/Group-chat.md | autogen | @AutoGen.Core.GroupChat invokes agents in a dynamic way. On one hand, It relies on its admin agent to intellegently determines the next speaker based on conversation context, and on the other hand, it also allows you to control the conversation flow by using a @AutoGen.Core.Graph. This makes it a more dynamic yet contr... |
GitHub | autogen | autogen/dotnet/website/articles/Group-chat.md | autogen | Use @AutoGen.Core.GroupChat to implement a code interpreter chat flow The following example shows how to create a dynamic group chat with @AutoGen.Core.GroupChat. In this example, we will create a dynamic group chat with 4 agents: `admin`, `coder`, `reviewer` and `runner`. Each agent has its own role in the group chat:... |
GitHub | autogen | autogen/dotnet/website/articles/function-comparison-page-between-python-AutoGen-and-autogen.net.md | autogen | ### Function comparison between Python AutoGen and AutoGen\.Net #### Agentic pattern | Feature | AutoGen | AutoGen\.Net | | :---------------- | :------ | :---- | | Code interpreter | run python code in local/docker/notebook executor | run csharp code in dotnet interactive executor | | Single agent chat pattern | ✔️ ... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-use-function-call.md | autogen | The following example shows how to create a `GetWeatherAsync` function and pass it to @AutoGen.OpenAI.OpenAIChatAgent. Firstly, you need to install the following packages: ```xml <ItemGroup> <PackageReference Include="AutoGen.OpenAI" Version="AUTOGEN_VERSION" /> <PackageReference Include="AutoGen.SourceGenerat... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | ## Use function call in AutoGen agent Typically, there are three ways to pass a function definition to an agent to enable function call: - Pass function definitions when creating an agent. This only works if the agent supports pass function call from its constructor. - Passing function definitions in @AutoGen.Core.Gen... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | Pass function definitions when creating an agent In some agents like @AutoGen.AssistantAgent or @AutoGen.OpenAI.GPTAgent, you can pass function definitions when creating the agent Suppose the `TypeSafeFunctionCall` is defined in the following code snippet: [!code-csharp[TypeSafeFunctionCall](../../samples/AutoGen.Basi... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | Passing function definitions in @AutoGen.Core.GenerateReplyOptions when invoking an agent You can also pass function definitions in @AutoGen.Core.GenerateReplyOptions when invoking an agent. This is useful when you want to override the function definitions passed to the agent when creating it. [!code-csharp[assistant ... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | Register an agent with @AutoGen.Core.FunctionCallMiddleware to process and invoke function calls You can also register an agent with @AutoGen.Core.FunctionCallMiddleware to process and invoke function calls. This is useful when you want to process and invoke function calls in a more flexible way. [!code-csharp[assista... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | Invoke function call inside an agent To invoke a function instead of returning the function call object, you can pass its function call wrapper to the agent via `functionMap`. You can then pass the `WeatherReportWrapper` to the agent via `functionMap`: [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/Fun... |
GitHub | autogen | autogen/dotnet/website/articles/Use-function-call.md | autogen | Invoke function call by another agent You can also use another agent to invoke the function call from one agent. This is a useful pattern in two-agent chat, where one agent is used as a function proxy to invoke the function call from another agent. Once the function call is invoked, the result can be returned to the or... |
GitHub | autogen | autogen/dotnet/website/articles/Create-your-own-agent.md | autogen | ## Coming soon |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-connect-to-third-party-api.md | autogen | The following example shows how to connect to third-party OpenAI API using @AutoGen.OpenAI.OpenAIChatAgent. [](https://github.com/microsoft/autogen/blob/main/dotnet/samples/AutoGen.OpenAI.Sample/Connect_To_Ollama.cs) |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-connect-to-third-party-api.md | autogen | Overview A lot of LLM applications/platforms support spinning up a chat server that is compatible with OpenAI API, such as LM Studio, Ollama, Mistral etc. This means that you can connect to these servers using the @AutoGen.OpenAI.OpenAIChatAgent. > [!NOTE] > Some platforms might not support all the features of OpenAI ... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-connect-to-third-party-api.md | autogen | Prerequisites - Install the following packages: ```bash dotnet add package AutoGen.OpenAI --version AUTOGEN_VERSION ``` - Spin up a chat server that is compatible with OpenAI API. The following example uses Ollama as the chat server, and llama3 as the llm model. ```bash ollama serve ``` |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-connect-to-third-party-api.md | autogen | Steps - Import the required namespaces: [!code-csharp[](../../samples/AutoGen.OpenAI.Sample/Connect_To_Ollama.cs?name=using_statement)] - Create a `CustomHttpClientHandler` class. The `CustomHttpClientHandler` class is used to customize the HttpClientHandler. In this example, we override the `SendAsync` method to red... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-connect-to-third-party-api.md | autogen | Sample Output The following is the sample output of the code snippet above:  |
GitHub | autogen | autogen/dotnet/website/articles/Middleware-overview.md | autogen | `Middleware` is a key feature in AutoGen.Net that enables you to customize the behavior of @AutoGen.Core.IAgent.GenerateReplyAsync*. It's similar to the middleware concept in ASP.Net and is widely used in AutoGen.Net for various scenarios, such as function call support, converting message of different types, print mess... |
GitHub | autogen | autogen/dotnet/website/articles/Middleware-overview.md | autogen | Use middleware in an agent To use middleware in an existing agent, you can either create a @AutoGen.Core.MiddlewareAgent on top of the original agent or register middleware functions to the original agent. ### Create @AutoGen.Core.MiddlewareAgent on top of the original agent [!code-csharp[](../../samples/AutoGen.Basic... |
GitHub | autogen | autogen/dotnet/website/articles/Middleware-overview.md | autogen | Short-circuit the next agent The example below shows how to short-circuit the inner agent [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/MiddlewareAgentCodeSnippet.cs?name=short_circuit_middleware_agent)] > [!Note] > When multiple middleware functions are registered, the order of middleware functions ... |
GitHub | autogen | autogen/dotnet/website/articles/Middleware-overview.md | autogen | Streaming middleware You can also modify the behavior of @AutoGen.Core.IStreamingAgent.GenerateStreamingReplyAsync* by registering streaming middleware to it. One example is @AutoGen.OpenAI.OpenAIChatRequestMessageConnector which converts `StreamingChatCompletionsUpdate` to one of `AutoGen.Core.TextMessageUpdate` or `A... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-middleware.md | autogen | # Coming soon |
GitHub | autogen | autogen/dotnet/website/articles/Create-an-agent.md | autogen | ## AssistantAgent [`AssistantAgent`](../api/AutoGen.AssistantAgent.yml) is a built-in agent in `AutoGen` that acts as an AI assistant. It uses LLM to generate response to user input. It also supports function call if the underlying LLM model supports it (e.g. `gpt-3.5-turbo-0613`). |
GitHub | autogen | autogen/dotnet/website/articles/Create-an-agent.md | autogen | Create an `AssistantAgent` using OpenAI model. [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/CreateAnAgent.cs?name=code_snippet_1)] |
GitHub | autogen | autogen/dotnet/website/articles/Create-an-agent.md | autogen | Create an `AssistantAgent` using Azure OpenAI model. [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/CreateAnAgent.cs?name=code_snippet_2)] |
GitHub | autogen | autogen/dotnet/website/articles/Group-chat-overview.md | autogen | @AutoGen.Core.IGroupChat is a fundamental feature in AutoGen. It provides a way to organize multiple agents under the same context and work together to resolve a given task. In AutoGen, there are two types of group chat: - @AutoGen.Core.RoundRobinGroupChat : This group chat runs agents in a round-robin sequence. The c... |
GitHub | autogen | autogen/dotnet/website/articles/Print-message-middleware.md | autogen | @AutoGen.Core.PrintMessageMiddleware is a built-in @AutoGen.Core.IMiddleware that pretty print @AutoGen.Core.IMessage to console. > [!NOTE] > @AutoGen.Core.PrintMessageMiddleware support the following @AutoGen.Core.IMessage types: > - @AutoGen.Core.TextMessage > - @AutoGen.Core.MultiModalMessage > - @AutoGen.Core.Tool... |
GitHub | autogen | autogen/dotnet/website/articles/Print-message-middleware.md | autogen | Use @AutoGen.Core.PrintMessageMiddleware in an agent You can use @AutoGen.Core.PrintMessageMiddlewareExtension.RegisterPrintMessage* to register the @AutoGen.Core.PrintMessageMiddleware to an agent. [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/PrintMessageMiddlewareCodeSnippet.cs?name=PrintMessageMid... |
GitHub | autogen | autogen/dotnet/website/articles/Print-message-middleware.md | autogen | Streaming message support @AutoGen.Core.PrintMessageMiddleware also supports streaming message types like @AutoGen.Core.TextMessageUpdate and @AutoGen.Core.ToolCallMessageUpdate. If you register @AutoGen.Core.PrintMessageMiddleware to a @AutoGen.Core.IStreamingAgent, it will format the streaming message and print it t... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | This example shows how to use function call with local LLM models where [Ollama](https://ollama.com/) as local model provider and [LiteLLM](https://docs.litellm.ai/docs/) proxy server which provides an openai-api compatible interface. [](https://gith... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | Install Ollama and pull `dolphincoder:latest` model First, install Ollama by following the instructions on the [Ollama website](https://ollama.com/). After installing Ollama, pull the `dolphincoder:latest` model by running the following command: ```bash ollama pull dolphincoder:latest ``` |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | Install LiteLLM and start the proxy server You can install LiteLLM by following the instructions on the [LiteLLM website](https://docs.litellm.ai/docs/). ```bash pip install 'litellm[proxy]' ``` Then, start the proxy server by running the following command: ```bash litellm --model ollama_chat/dolphincoder --port 400... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | Install AutoGen and AutoGen.SourceGenerator In your project, install the AutoGen and AutoGen.SourceGenerator package using the following command: ```bash dotnet add package AutoGen dotnet add package AutoGen.SourceGenerator ``` The `AutoGen.SourceGenerator` package is used to automatically generate type-safe `Functio... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | Define `WeatherReport` function and create @AutoGen.Core.FunctionCallMiddleware Create a `public partial` class to host the methods you want to use in AutoGen agents. The method has to be a `public` instance method and its return type must be `Task<string>`. After the methods are defined, mark them with `AutoGen.Core.... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-with-ollama-and-litellm.md | autogen | Create @AutoGen.OpenAI.OpenAIChatAgent with `GetWeatherReport` tool and chat with it Because LiteLLM proxy server is openai-api compatible, we can use @AutoGen.OpenAI.OpenAIChatAgent to connect to it as a third-party openai-api provider. The agent is also registered with a @AutoGen.Core.FunctionCallMiddleware which co... |
GitHub | autogen | autogen/dotnet/website/articles/Roundrobin-chat.md | autogen | @AutoGen.Core.RoundRobinGroupChat is a group chat that invokes agents in a round-robin order. It's useful when you want to call multiple agents in a fixed sequence. For example, asking search agent to retrieve related information followed by a summarization agent to summarize the information. Beside, it also used by @A... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-use-json-mode.md | autogen | The following example shows how to enable JSON mode in @AutoGen.OpenAI.OpenAIChatAgent. [](https://github.com/microsoft/autogen/blob/main/dotnet/samples/AutoGen.OpenAI.Sample/Use_Json_Mode.cs) |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-use-json-mode.md | autogen | What is JSON mode? JSON mode is a new feature in OpenAI which allows you to instruct model to always respond with a valid JSON object. This is useful when you want to constrain the model output to JSON format only. > [!NOTE] > Currently, JOSN mode is only supported by `gpt-4-turbo-preview` and `gpt-3.5-turbo-0125`. Fo... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-use-json-mode.md | autogen | How to enable JSON mode in OpenAIChatAgent. To enable JSON mode for @AutoGen.OpenAI.OpenAIChatAgent, set `responseFormat` to `ChatCompletionsResponseFormat.JsonObject` when creating the agent. Note that when enabling JSON mode, you also need to instruct the agent to output JSON format in its system message. [!code-cs... |
GitHub | autogen | autogen/dotnet/website/articles/Create-your-own-middleware.md | autogen | ## Coming soon |
GitHub | autogen | autogen/dotnet/website/articles/Create-type-safe-function-call.md | autogen | ## Create type-safe function call using AutoGen.SourceGenerator `AutoGen` provides a source generator to easness the trouble of manually craft function definition and function call wrapper from a function. To use this feature, simply add the `AutoGen.SourceGenerator` package to your project and decorate your function ... |
GitHub | autogen | autogen/dotnet/website/articles/getting-start.md | autogen | ### Get start with AutoGen for dotnet [](https://github.com/microsoft/autogen/actions/workflows/dotnet-build.yml) [](https://badge.fury.io/nu/AutoGen.Core) Firstly, ... |
GitHub | autogen | autogen/dotnet/website/articles/MistralChatAgent-use-function-call.md | autogen | ## Use tool in MistralChatAgent The following example shows how to enable tool support in @AutoGen.Mistral.MistralClientAgent by creating a `GetWeatherAsync` function and passing it to the agent. Firstly, you need to install the following packages: ```bash dotnet add package AutoGen.Mistral dotnet add package AutoGen... |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | `AutoGen` provides a built-in feature to run code snippet from agent response. Currently the following languages are supported: - dotnet More languages will be supported in the future. |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | What is a code snippet? A code snippet in agent response is a code block with a language identifier. For example: [!code-csharp[](../../samples/AutoGen.BasicSamples/CodeSnippet/RunCodeSnippetCodeSnippet.cs?name=code_snippet_1_3)] |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | Why running code snippet is useful? The ability of running code snippet can greatly extend the ability of an agent. Because it enables agent to resolve tasks by writing code and run it, which is much more powerful than just returning a text response. For example, in data analysis scenario, agent can resolve tasks like... |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | Use dotnet interactive kernel to execute code snippet? The built-in feature of running dotnet code snippet is provided by [dotnet-interactive](https://github.com/dotnet/interactive). To run dotnet code snippet, you need to install the following package to your project, which provides the intergraion with dotnet-interac... |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | Run python code snippet To run python code, firstly you need to have python installed on your machine, then you need to set up ipykernel and jupyter in your environment. ```bash pip install ipykernel pip install jupyter ``` After `ipykernel` and `jupyter` are installed, you can confirm the ipykernel is installed corr... |
GitHub | autogen | autogen/dotnet/website/articles/Run-dotnet-code.md | autogen | Further reading You can refer to the following examples for running code snippet in agentic workflow: - Dynamic_GroupChat_Coding_Task: [](https://github.com/microsoft/autogen/blob/main/dotnet/samples/AutoGen.BasicSample/Example04_Dynamic_GroupChat_Co... |
GitHub | autogen | autogen/dotnet/website/articles/Two-agent-chat.md | autogen | In `AutoGen`, you can start a conversation between two agents using @AutoGen.Core.AgentExtension.InitiateChatAsync* or one of @AutoGen.Core.AgentExtension.SendAsync* APIs. When conversation starts, the sender agent will firstly send a message to receiver agent, then receiver agent will generate a reply and send it back... |
GitHub | autogen | autogen/dotnet/website/articles/Two-agent-chat.md | autogen | A basic example The following example shows how to start a conversation between the teacher agent and student agent, where the student agent starts the conversation by asking teacher to create math questions. > [!TIP] > You can use @AutoGen.Core.PrintMessageMiddlewareExtension.RegisterPrintMessage* to pretty print th... |
GitHub | autogen | autogen/dotnet/website/articles/Use-graph-in-group-chat.md | autogen | Sometimes, you may want to add more control on how the next agent is selected in a @AutoGen.Core.GroupChat based on the task you want to resolve. For example, in the previous [code writing example](./Group-chat.md), the original code interpreter workflow can be improved by the following diagram because it's not necessa... |
GitHub | autogen | autogen/dotnet/website/articles/Consume-LLM-server-from-LM-Studio.md | autogen | ## Consume LLM server from LM Studio You can use @AutoGen.LMStudio.LMStudioAgent from `AutoGen.LMStudio` package to consume openai-like API from LMStudio local server. ### What's LM Studio [LM Studio](https://lmstudio.ai/) is an app that allows you to deploy and inference hundreds of thousands of open-source language ... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | `Agent` is one of the most fundamental concepts in AutoGen.Net. In AutoGen.Net, you construct a single agent to process a specific task, and you extend an agent using [Middlewares](./Middleware-overview.md), and you construct a multi-agent workflow using [GroupChat](./Group-chat-overview.md). > [!NOTE] > Every agent i... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | Create an agent - Create an @AutoGen.AssistantAgent: [Create an assistant agent](./Create-an-agent.md) - Create an @AutoGen.OpenAI.OpenAIChatAgent: [Create an OpenAI chat agent](./OpenAIChatAgent-simple-chat.md) - Create a @AutoGen.SemanticKernel.SemanticKernelAgent: [Create a semantic kernel agent](./AutoGen.SemanticK... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | Chat with an agent To chat with an agent, typically you can invoke @AutoGen.Core.IAgent.GenerateReplyAsync*. On top of that, you can also use one of the extension methods like @AutoGen.Core.AgentExtension.SendAsync* as shortcuts. > [!NOTE] > AutoGen provides a list of built-in message types like @AutoGen.Core.TextMess... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | Streaming chat If an agent implements @AutoGen.Core.IStreamingAgent, you can use @AutoGen.Core.IStreamingAgent.GenerateStreamingReplyAsync* to chat with the agent in a streaming way. You would need to process the streaming updates on your side though. - Send a @AutoGen.Core.TextMessage to an agent via @AutoGen.Core.IS... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | Register middleware to an agent @AutoGen.Core.IMiddleware and @AutoGen.Core.IStreamingMiddleware are used to extend the behavior of @AutoGen.Core.IAgent.GenerateReplyAsync* and @AutoGen.Core.IStreamingAgent.GenerateStreamingReplyAsync*. You can register middleware to an agent to customize the behavior of the agent on t... |
GitHub | autogen | autogen/dotnet/website/articles/Agent-overview.md | autogen | Group chat You can construct a multi-agent workflow using @AutoGen.Core.IGroupChat. In AutoGen.Net, there are two type of group chat: @AutoGen.Core.SequentialGroupChat: Orchestrates the agents in the group chat in a fix, sequential order. @AutoGen.Core.GroupChat: Provide more dynamic yet controllable way to orchestrate... |
GitHub | autogen | autogen/dotnet/website/articles/AutoGen-Mistral-Overview.md | autogen | ## AutoGen.Mistral overview AutoGen.Mistral provides the following agent(s) to connect to [Mistral.AI](https://mistral.ai/) platform. - @AutoGen.Mistral.MistralClientAgent: A slim wrapper agent over @AutoGen.Mistral.MistralClient. ### Get started with AutoGen.Mistral To get started with AutoGen.Mistral, follow the [... |
GitHub | autogen | autogen/dotnet/website/articles/Built-in-messages.md | autogen | ## An overview of built-in @AutoGen.Core.IMessage types Start from 0.0.9, AutoGen introduces the @AutoGen.Core.IMessage and @AutoGen.Core.IMessage`1 types to provide a unified message interface for different agents. The @AutoGen.Core.IMessage is a non-generic interface that represents a message. The @AutoGen.Core.IMes... |
GitHub | autogen | autogen/dotnet/website/articles/Installation.md | autogen | ### Current version: [](https://badge.fury.io/nu/AutoGen.Core) AutoGen.Net provides the following packages, you can choose to install one or more of them based on your needs: - `AutoGen`: The one-in-all package. This package has dependencies over `AutoGen.Co... |
GitHub | autogen | autogen/dotnet/website/articles/Function-call-overview.md | autogen | ## Overview of function call In some LLM models, you can provide a list of function definitions to the model. The function definition is usually essentially an OpenAPI schema object which describes the function, its parameters and return value. And these function definitions tells the model what "functions" are availa... |
GitHub | autogen | autogen/dotnet/website/articles/OpenAIChatAgent-support-more-messages.md | autogen | By default, @AutoGen.OpenAI.OpenAIChatAgent only supports the @AutoGen.Core.IMessage<T> type where `T` is original request or response message from `Azure.AI.OpenAI`. To support more AutoGen built-in message types like @AutoGen.Core.TextMessage, @AutoGen.Core.ImageMessage, @AutoGen.Core.MultiModalMessage and so on, you... |
GitHub | autogen | autogen/dotnet/website/articles/MistralChatAgent-count-token-usage.md | autogen | The following example shows how to create a `MistralAITokenCounterMiddleware` @AutoGen.Core.IMiddleware and count the token usage when chatting with @AutoGen.Mistral.MistralClientAgent. ### Overview To collect the token usage for the entire chat session, one easy solution is simply collect all the responses from agent... |
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