SETA: Scaling Environments for Terminal Agents

Designing resilient toolkits and scalable RL environments for CAMEL terminal agents

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Getting Started 🎯

Installation

# Clone the repository
git clone https://github.com/camel-ai/seta.git
cd seta
bash setup.sh

Run task by task

#=========================================
# Run single developer agent / workforce
#=========================================
cd evaluation/terminal_bench_run/
bash run_agent.sh \
        -a <attempt,0..n> \
        -n <total_attempts> \
        -e <conda env name> \
        -w <use_workforce>  # can have a try, focus on single chat agent now.

Log folder explaination

└── play-zork
    └── play-zork.1-of-1.test_run       # trial name
        ├── CAMEL_WORKDIR               # not used at the moment
        ├── agent-logs                  # not used at the moment
        ├── commands.txt                # not used at the moment
        ├── chatagent.log               # ❗️❗️ full history of running agent including test results
        ├── eigent_logs.json            # ⚠️ exists only when running workforce
        ├── panes                       # not used at the moment
        └── sessions                    # session logs
            ├── agent.cast              # not used at the moment
            ├── agent.log               # not used at the moment
            ├── session_logs            # ❗️❗️session logs for terminal toolkit
            │   ├── blocking_commands.log                   # ❗️❗️all block mode commands + output
            │   ├── session_run_zork_1_correct_path.log     # ❗️❗️non-block mode single session command + output
            │   ├── session_zork-1.log                      # ❗️❗️same as above session_{id}.log
            │   └── session_zork_start.log                  # ❗️❗️same as above session_{id}.log
            ├── tests.cast              # not used at the moment    
            ├── tests.log               # ❗️❗️test log
            └── tests.log.strip         # ❗️❗️test log with ansi control characters removed

Run terminal bench official evaluation

cd evaluation/terminal_bench_eval/

# terminal bench 1.0
bash run_eval.sh

# terminal bench 2.0
bash run_tb2.sh

## The agent class is implemented in tbench_camel_agent.py 

❗️Note: Results of evaluation

- final results will be in `evaluation/terminal_bench_eval/run/{run_id}/results.json`

- task specific terminal session logs will be in `evaluation/terminal_bench_eval/logs/camel_logs/{task_id}/`

Train terminal agent

Everything is under training folder

Please refer to Training Setup for detailed instructions.

Note: new TerminalToolkit design document Terminal Toolkit Design

Citation

@misc{seta,
  author    = {Qijia Shen and Jay Rainton and Aznaur Aliev and Ahmed Awelkair and Boyuan Ma and Zhiqi (Julie) Huang and Yuzhen Mao and Wendong Fan and Philip Torr and Bernard Ghanem and Changran Hu and Urmish Thakker and Guohao Li},
  title     = {{SETA: Scaling Environments for Terminal Agents}},
  year      = {2026},
  month     = jan,
  url       = {https://github.com/camel-ai/seta},
  note      = {Blog: \url{https://eigent-ai.notion.site/SETA-Scaling-Environments-for-Terminal-Agents-2d2511c70ba280a9b7c0fe3e7f1b6ab8}}
}