autogen/TRANSPARENCY_FAQS.md
What operational factors and settings allow for effective and responsible use of AutoGen? -	Code execution: AutoGen recommends using docker containers so that code execution can happen in a safer manner. Users can use function call instead of free-form code to execute pre-defined functions only. That helps increase the reliability and safety. Users can customize the code execution environment to tailor to their requirements. -	Human involvement: AutoGen prioritizes human involvement in multi agent conversation. The overseers can step in to give feedback to agents and steer them in the correct direction. By default, users get chance to confirm before code is executed. -	Agent modularity: Modularity allows agents to have different levels of information access. Additional agents can assume roles that help keep other agents in check. For example, one can easily add a dedicated agent to play the role of safeguard. -	LLMs: Users can choose the LLM that is optimized for responsible use. The default LLM is GPT-4 which inherits the existing RAI mechanisms and filters from the LLM provider. Caching is enabled by default to increase reliability and control cost. We encourage developers to review [OpenAI’s Usage policies](https://openai.com/policies/usage-policies) and [Azure OpenAI’s Code of Conduct](https://learn.microsoft.com/en-us/legal/cognitive-services/openai/code-of-conduct) when using GPT-4. -	Multi-agent setup: When using auto replies, the users can limit the number of auto replies, termination conditions etc. in the settings to increase reliability. 