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For many applications of LLM agents, the environment is real (internet, database, REPL, etc). However, we can also define agents to interact in simulated environments like text-based games. This is an example of how to create a simple agent-environment interaction loop with [Gymnasium](https://github.com/Farama-Foundation/Gymnasium) (formerly [OpenAI Gym](https://github.com/openai/gym)). |
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| .. | ||
| _static | ||
| ecosystem | ||
| getting_started | ||
| modules | ||
| reference | ||
| tracing | ||
| use_cases | ||
| conf.py | ||
| deployments.md | ||
| ecosystem.rst | ||
| gallery.rst | ||
| glossary.md | ||
| index.rst | ||
| make.bat | ||
| Makefile | ||
| model_laboratory.ipynb | ||
| reference.rst | ||
| requirements.txt | ||
| tracing.md | ||
| youtube.md | ||