LibreChat

LibreChat puts a single chat interface in front of many model providers, among them OpenAI, Azure, Anthropic, AWS Bedrock, Google, Vertex AI, Ollama, Mistral, Groq, Cohere, OpenRouter and DeepSeek. Endpoints and presets can be switched mid-conversation, and messages can be edited, resubmitted, forked or branched instead of abandoned.

Beyond chat, several subsystems make it usable as a working environment.

• Agents: no-code assistants with MCP servers, tools, file search and code execution, shareable with specific users and groups.
• Subagents: focused work is delegated to isolated child runs with their own context windows.
• Code Interpreter: sandboxed execution in Python, Node, Go, C, Java, PHP, Rust and Fortran, with file upload and download.
• Web search: search providers, content scrapers and result rerankers combine to pull context into a conversation.
• Code artifacts: React, HTML and Mermaid content renders inline and exports as SVG or PNG.
• Speech and audio: speech-to-text and text-to-speech through OpenAI, Azure and ElevenLabs.

Recent work has gone into durability. Responses reconnect and resume when a connection drops, the same chat syncs across tabs and devices, agent runs can be interrupted and steered, and human-in-the-loop pauses wait for input or tool approval before carrying on.

Deployment templates exist for several hosting providers, the interface is translated into more than thirty languages, and security defaults include HTTP headers, per-user code interpreter tokens, SAML identity binding and SSRF protection on web tool traffic.