Alex Goodall

What an agent can do with the MASA-Safe-RL corpus

sacktock/MASA-Safe-RL: MASA-Safe-RL: A safe reinforcement library for providing a common interface for different constraints and environments

• Look up how MASA-Safe-RL implements benchmark, constrained-reinforcement-learning, constraint-satisfaction-problem, with answers cited to file and line.
• Reuse a worked example: the commit “drop tensorflow probability dependencies with native jax implementation” (6 files · Python).
• Answer from MASA-Safe-RL's real Python source instead of memory (AI, prompts and agents).

• How does MASA-Safe-RL implement benchmark?
• What does masa do in MASA-Safe-RL?

Search the GitHub repository sacktock/MASA-Safe-RL with XERJ (https://hub.xerj.org/corpus/sacktock--masa-safe-rl).
Run these in a shell, in order, and check each result before the next:
1. xerj --help  (success: it prints usage). If xerj is missing: curl -fsSL https://xerj.org/get | sh
2. git clone https://github.com/sacktock/MASA-Safe-RL MASA-Safe-RL && git -C MASA-Safe-RL checkout c8e93cf8b099a259aef5e3c7b56ff5f4abd4d963
3. Start a local node and leave it running: xerj --insecure --data-dir ./xerj-data
4. xerj autoindex ./MASA-Safe-RL --url http://127.0.0.1:9200 --prefix masa-safe-rl --progress plain
5. xerj autoindex map --url http://127.0.0.1:9200
Then answer my question from the indexed files and cite the ax_path of every hit. Query syntax: https://xerj.org/llms.txt
Licence: Apache-2.0. Keep the copyright notice and credit the authors.

corpus sacktock--masa-safe-rl · AI, prompts and agents
Related corpora: cognita, ann-benchmarks, jamilhammoudeh/vbar, SaiSampathKedari/Deep-Reinforcement-Learning
AI search and retrieval with XERJ · Case study: reference coding for agents