autogen/TRANSPARENCY_FAQS.md
	What is/are AutoGen’s intended use(s)? Please note that AutoGen is an open-source library under active development and intended for  use for research purposes. It should not be used in any downstream applications without additional detailed evaluation of robustness, safety issues and assessment of any potential harm or bias in the proposed application.  AutoGen is a generic infrastructure that can be used in multiple scenarios. The system’s intended uses include:  -	Building LLM workflows that solve more complex tasks: Users can create agents that interleave reasoning and tool use capabilities of the latest LLMs such as GPT-4. To solve complex tasks, multiple agents can converse to work together (e.g., by partitioning a complex problem into simpler steps or by providing different viewpoints or perspectives). -	Application-specific agent topologies: Users can create application specific agent topologies and patterns for agents to interact. The exact topology may depend on the domain’s complexity and semantic capabilities of the LLM available. -	Code generation and execution: Users can implement agents that can assume the roles of writing code and other agents that can execute code. Agents can do this with varying levels of human involvement. Users can add more agents and program the conversations to enforce constraints on code and output. -	Question answering: Users can create agents that can help answer questions using retrieval augmented generation. -	End user and multi-agent chat and debate: Users can build chat applications where they converse with multiple agents at the same time.  While AutoGen automates LLM workflows, decisions about how to use specific LLM outputs should always have a human in the loop. For example, you should not use AutoGen to automatically post LLM generated content to social media. 