Unicorn-Forest/cogterm

AI Summary: Update the Windows Terminal repository's README and documentation to include details about the new AI features introduced in version 7.3. This involves adding sections or subsections to the README and creating new AI integration guides within the `doc/` directory.

AI Summary: Create integration tests for the Windows Terminal AI features. This involves creating a new directory, `src/cascadia/LocalTests_TerminalAI/`, and a C++ source file, `AIIntegrationTests.cpp`, within it to house the tests. The tests will likely interact with the Terminal's AI capabilities.

AI Summary: Create unit tests for the Artificial Intelligence (AI) components of the Windows Terminal, specifically focusing on the AIEngine and AIConnection. This involves creating new directories and source files within the project's source code and implementing the tests themselves.

AI Summary: This task involves adding AI-related commands to the Windows Terminal's command palette. This includes modifying the XAML file (`CommandPalette.xaml`) to define the UI elements for the new commands and updating the C++ code (`CommandPalette.cpp`) to handle the logic for creating new AI chat and agent tabs within the terminal.

AI Summary: The task involves adding a visual indicator (AI icon) to the Windows Terminal's tab header UI. This requires modifying the XAML and C++ code of the `TabHeaderControl` to display the icon conditionally. The provided code snippet shows the XAML modification to add the icon and set its initial visibility to collapsed; the C++ code will need to handle when to make the icon visible.

AI Summary: The task involves creating a new settings UI page within the Windows Terminal application for configuring AI-related features. This includes creating XAML and C++ code for a page with toggle switches for enabling AI chat and function calling, text boxes for the AI provider, API key, and default model.

AI Summary: The task involves creating a JavaScript runtime within the Windows Terminal project to enable execution of JavaScript scripts for extending the terminal's functionality. This includes creating header and source files, implementing a class to manage the JavaScript context (potentially using V8 or Chakra), parsing scripts to identify available functions, and providing methods to execute functions asynchronously with parameters.

AI Summary: The task involves creating two C++ files, `CliiConnection.h` and `CliiConnection.cpp`, implementing a `CliiConnection` class that inherits from `BaseTerminalConnection`. This class will handle CLI integration within the Windows Terminal, including initialization, starting the connection, writing input, resizing, closing, and potentially interacting with a JavaScript runtime for command execution. The implementation will involve interacting with existing Windows Terminal components and potentially external CLI tools.

AI Summary: This task involves integrating a Large Language Model (LLM) function-calling engine and an agent system into the Windows Terminal. This includes creating a function calling engine to execute functions from various scripting languages (Bash, JavaScript, Python), an agent system to manage agent definitions and interactions, and integrating these components with the Terminal's tab system to allow for agent-based interactions within terminal tabs.

AI Summary: The task involves integrating AI agent support into the Windows Terminal's tab functionality. This requires modifying the `Tab.cpp` and `Tab.h` files to add an agent interface and handle agent responses, specifically for tabs using the `AIAgent` connection type. The provided code snippet shows a basic implementation of initializing the agent, loading it, and handling received responses by writing them to the terminal.

AI Summary: The task involves creating an AI agent system for the Windows Terminal, including the implementation of an AIAgent class to handle agent loading, definition, and execution using an AI engine and function-calling engine. This requires creating header and source files and implementing methods for loading agent definitions from a specified path and asynchronously processing user input with available tools.

AI Summary: The task involves creating a C++ class, `FunctionCallingEngine`, to manage the execution of functions from various scripting languages (Bash, JavaScript, Python) within the Windows Terminal AI. This includes loading function definitions from a directory, asynchronously executing functions based on name and arguments, and providing a method to retrieve available functions.

AI Summary: This task involves integrating an Argc parser into the Windows Terminal to enable AI-powered command suggestions and autocompletion. This includes creating the Argc parser, integrating it with the command palette and enhancing the suggestions control to incorporate AI-generated completions, and finally adding the autocompletion functionality to the terminal's core control.

AI Summary: The task involves integrating several AI-powered command-line tools (aichat, argc, llm-functions, clii) into the Windows Terminal. This includes creating an AI integration framework, extending the terminal connection system, adding AI settings and UI elements, implementing AI-powered features like chat, command parsing, function calling, and JavaScript-based CLI tool creation, and ensuring compatibility, security, and performance.

AI Summary: This task involves integrating AI capabilities into the Windows Terminal. It requires creating new components for an AI engine and connection, modifying existing terminal connection interfaces, and adding AI-specific settings to the settings model. The implementation includes defining interfaces for AI engine interaction (initialization, command processing, chat, function execution), handling AI connections, and serializing AI settings for configuration.

AI Summary: The task involves integrating AI chat functionality into the Windows Terminal. This includes creating classes for AI chat connection and engine, handling AI-specific settings in profiles, and managing AI tabs within the terminal application. The implementation will require handling asynchronous operations, API requests (likely to OpenAI or a similar service), and managing conversation history.

AI Summary: This task involves adding AI capabilities to the Windows Terminal, including unit and integration tests, and updating documentation. This requires creating new files for AI-related code (engine, chat, function calling), modifying the build system (CMake and project files), adding AI configuration options to the settings.json schema, and expanding the documentation to include AI features and integration guides. Dependencies for AI functionality (like OpenAI API interaction) need to be added using vcpkg.

AI Summary: This task involves integrating an AI chat functionality into the Windows Terminal. It requires creating a settings UI for AI parameters (provider, API key, model), adding visual indicators to tabs using AI, and implementing AI-specific commands in the command palette. This includes modifying existing XAML and C++ code for the settings page, tab header control, and command palette.

AI Summary: The task involves integrating a command-line interface (CLI) into the Windows Terminal by creating a JavaScript runtime to execute CLI scripts and a connection class to handle CLI commands. This includes parsing scripts to identify available functions, executing functions asynchronously, and managing the connection between the terminal and the CLI.