Search Results for "switch"

...Users can categorize, import, edit, enable, disable, cache, and synchronize Markdown instruction templates. Provider tools store multiple API configurations, test connections, retrieve models, and switch between official and third-party services. Session management can search, group, inspect, synchronize, and permanently delete local Codex histories. The application also displays authentication and configuration files while creating backups before important changes. Packages are offered for macOS, Windows, and Linux through a Tauri-based desktop application.

...It runs locally on Windows, macOS, and Linux, keeping your conversations and data stored on your own device. Chatbox acts as a unified interface for popular LLMs like ChatGPT, Claude, Gemini, and local models via Ollama, making it easy to switch providers without changing tools. Built with an ergonomic UI, it’s optimized for long sessions, prompt experimentation, and everyday productivity. The app supports rich formatting, streaming responses, and advanced prompting to help you get clearer, more useful outputs. For individuals and teams alike, Chatbox serves as a powerful desktop copilot that blends simplicity with flexibility.

...It runs on the user's own computer and can work with real files, signed-in applications, browsers, computers, and connected phones. Claude Code and Codex are supported harnesses, and users can switch models or harnesses during a task without losing workspace context. Tasks can be planned, executed in parallel, and reviewed by different agent and model combinations. Persistent memory, reusable skills, scheduled automation, MCP integrations, and planned plugins let the system adapt over time. The client includes Electron desktop and Expo-based mobile applications in a shared pnpm monorepo. ...

...It streams Markdown, tool calls, reasoning status, token usage, context consumption, and throughput directly in the terminal. Users can resume, fork, compact, search, rewind, and switch models while preserving session history through DSH services. File references, image attachments, slash commands, questionnaires, and keyboard-driven input are built into the interface. Long conversations use event-driven rendering, virtualization, and bounded caches to control terminal and memory costs. The plugin also supports themes, MCP, skills, subagents, agent presets, and VS Code terminal workflows.

...It lets a named teammate enter an existing Codex or Claude Code conversation without switching tools or recreating its context. The host explicitly chooses which native sessions to share, while Tailscale provides the private device network. Teammates can follow live transcripts, switch sessions, show presence, and submit prompts with their identity attached. Viewer and participant roles, revocation, shared access rules, and an append-only audit trail help preserve owner control. The public alpha currently targets macOS and existing Tailscale networks, with no public relay or arbitrary remote shell access.

...In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. It supports multiple model providers through a dedicated configuration resource, allowing teams to switch providers or run mixed environments while keeping the agent spec stable. A major focus is tool integration via MCP: agents can connect to MCP servers for tool access, and kagent includes an MCP server with tools for common Kubernetes and platform engineering systems.

Askimo is an open-source, privacy-first AI desktop application designed to help users work with multiple AI models from a single, consistent interface. It supports popular AI providers such as OpenAI, Anthropic (Claude), Gemini, Ollama, LocalAI, Docker AI, LM Studio, and X AI, allowing users to switch models easily without vendor lock-in. A core feature of Askimo is Retrieval-Augmented Generation (RAG). Users can connect the app to local files, documents, and project folders so the AI can answer questions using their own knowledge base. All indexing, search, and history storage happen locally, ensuring sensitive data stays on the user’s machine. ...