Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.
Enables AI agents to connect to and chat with multiple LLM models (OpenAI, OpenRouter, custom endpoints) with conversation history management and model switching capabilities.
Aggregates dozens of pre-built connectors into one OpenAI-compatible endpoint for AI clients, with a web UI for installing, configuring, monitoring, and managing them.
Enables running AI agents via OpenAI-compatible APIs with custom system prompts, models, and queries. Supports persistent memory, preset agents, and multi-step workflows like pipelines and swarms.
Enables interaction with OpenAI-compatible APIs (like Ollama) through MCP tools. Provides access to chat completions, model listings, and embeddings generation from local or remote OpenAI-style endpoints.
