bytedance/trae-agent

git clone https://github.com/bytedance/trae-agent.git
cd trae-agent
uv sync --all-extras
source .venv/bin/activate

agents:
  trae_agent:
    enable_lakeview: true
    model: trae_agent_model  # the model configuration name for Trae Agent
    max_steps: 200  # max number of agent steps
    tools:  # tools used with Trae Agent
      - bash
      - str_replace_based_edit_tool
      - sequentialthinking
      - task_done

model_providers:  # model providers configuration
  anthropic:
    api_key: your_anthropic_api_key
    provider: anthropic
  openai:
    api_key: your_openai_api_key
    provider: openai

models:
  trae_agent_model:
    model_provider: anthropic
    model: claude-sonnet-4-20250514
    max_tokens: 4096
    temperature: 0.5

openai:
    api_key: your_openrouter_api_key
    provider: openai
    base_url: https://openrouter.ai/api/v1

export OPENAI_API_KEY="your-openai-api-key"
export OPENAI_BASE_URL="your-openai-base-url"
export ANTHROPIC_API_KEY="your-anthropic-api-key"
export ANTHROPIC_BASE_URL="your-anthropic-base-url"
export GOOGLE_API_KEY="your-google-api-key"
export GOOGLE_BASE_URL="your-google-base-url"
export OPENROUTER_API_KEY="your-openrouter-api-key"
export OPENROUTER_BASE_URL="https://openrouter.ai/api/v1"
export DOUBAO_API_KEY="your-doubao-api-key"
export DOUBAO_BASE_URL="https://ark.cn-beijing.volces.com/api/v3/"

mcp_servers:
  playwright:
    command: npx
    args:
      - "@playwright/[email protected]"

# Simple task execution
trae-cli run "Create a hello world Python script"

# Check configuration
trae-cli show-config

# Interactive mode
trae-cli interactive

# OpenAI
trae-cli run "Fix the bug in main.py" --provider openai --model gpt-4o

# Anthropic
trae-cli run "Add unit tests" --provider anthropic --model claude-sonnet-4-20250514

# Google Gemini
trae-cli run "Optimize this algorithm" --provider google --model gemini-2.5-flash

# OpenRouter (access to multiple providers)
trae-cli run "Review this code" --provider openrouter --model "anthropic/claude-3-5-sonnet"
trae-cli run "Generate documentation" --provider openrouter --model "openai/gpt-4o"

# Doubao
trae-cli run "Refactor the database module" --provider doubao --model doubao-seed-1.6

# Ollama (local models)
trae-cli run "Comment this code" --provider ollama --model qwen3

# Custom working directory
trae-cli run "Add tests for utils module" --working-dir /path/to/project

# Save execution trajectory
trae-cli run "Debug authentication" --trajectory-file debug_session.json

# Force patch generation
trae-cli run "Update API endpoints" --must-patch

# Interactive mode with custom settings
trae-cli interactive --provider openai --model gpt-4o --max-steps 30

# Specify a Docker image to run the task in a new container
trae-cli run "Add tests for utils module" --docker-image python:3.11

# Specify a Docker image to run the task in a new container and mount the directory
trae-cli run "write a script to print helloworld" --docker-image python:3.12 --working-dir test_workdir/

# Attach to an existing Docker container by ID (`--working-dir` is invalid with `--docker-container-id`)
trae-cli run "Update API endpoints" --docker-container-id 91998a56056c

# Specify an absolute path to a Dockerfile to build an environment
trae-cli run "Debug authentication" --dockerfile-path test_workspace/Dockerfile

# Specify a path to a local Docker image file (tar archive) to load
trae-cli run "Fix the bug in main.py" --docker-image-file test_workspace/trae_agent_custom.tar

# Remove the Docker container after finishing the task (keep default)
trae-cli run "Add tests for utils module" --docker-image python:3.11 --docker-keep false

# Auto-generated trajectory file
trae-cli run "Debug the authentication module"
# Saves to: trajectories/trajectory_YYYYMMDD_HHMMSS.json

# Custom trajectory file
trae-cli run "Optimize database queries" --trajectory-file optimization_debug.json

PYTHONPATH=. trae-cli run "your task"

# Verify API keys
echo $OPENAI_API_KEY
trae-cli show-config

uv run trae-cli run "your task"

chmod +x /path/to/your/project

@article{traeresearchteam2025traeagent,
      title={Trae Agent: An LLM-based Agent for Software Engineering with Test-time Scaling},
      author={Trae Research Team and Pengfei Gao and Zhao Tian and Xiangxin Meng and Xinchen Wang and Ruida Hu and Yuanan Xiao and Yizhou Liu and Zhao Zhang and Junjie Chen and Cuiyun Gao and Yun Lin and Yingfei Xiong and Chao Peng and Xia Liu},
      year={2025},
      eprint={2507.23370},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2507.23370},
}