Intelligent LLM orchestrator that automatically routes tasks to the most appropriate AI model (Gemini, Qwen, Ollama, LM Studio) based on task characteristics, enabling distributed processing and parallel execution across local and network services.
Routes AI tasks to appropriate local LLM models (quick, coder, MoE, thinking) with automatic model selection, multi-backend support (Ollama, llama.cpp, Gemini), and parallel processing capabilities.
Multi-agent research server that runs multiple LLM providers in parallel with web search capabilities, synthesizing their responses into comprehensive answers for complex queries.
A goal-agnostic parallel orchestration framework that enables sophisticated multi-agent coordination for tasks like code generation, UI development, and research through specification-driven architecture. It utilizes wave-based generation and intelligent context management to execute complex, iterative agentic loops.
Orchestrates multiple AI models (Gemini, OpenAI, Claude, local models) within a single conversation context, enabling collaborative workflows like multi-model code reviews, consensus building, and CLI-to-CLI bridging for specialized tasks.
