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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Trae Agent is an LLM-based agent for general purpose software engineering tasks.
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Today
+2 stars today
This week
+19 stars this week
This month
+64 stars this month
Momentum
0.0
growth rate 0.16%/day
# Trae Agent
[](https://arxiv.org/abs/2507.23370)
[](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT)
[](https://github.com/bytedance/trae-agent/actions/workflows/pre-commit.yml)
[](https://github.com/bytedance/trae-agent/actions/workflows/unit-test.yml)
[](https://discord.gg/VwaQ4ZBHvC)
**Trae Agent** is an LLM-based agent for general purpose software engineering tasks. It provides a powerful CLI interface that can understand natural language instructions and execute complex software engineering workflows using various tools and LLM providers.
For technical details please refer to [our technical report](https://arxiv.org/abs/2507.23370).
**Project Status:** The project is still being actively developed. Please refer to [docs/roadmap.md](docs/roadmap.md) and [CONTRIBUTING](CONTRIBUTING.md) if you are willing to help us improve Trae Agent.
**Difference with Other CLI Agents:** Trae Agent offers a transparent, modular architecture that researchers and developers can easily modify, extend, and analyze, making it an ideal platform for **studying AI agent architectures, conducting ablation studies, and developing novel agent capabilities**. This **_research-friendly design_** enables the academic and open-source communities to contribute to and build upon the foundational agent framework, fostering innovation in the rapidly evolving field of AI agents.
## ✨ Features
- 🌊 **Lakeview**: Provides short and concise summarisation for agent steps
- 🤖 **Multi-LLM Support**: Works with OpenAI, Anthropic, Doubao, Azure, OpenRouter, Ollama and Google Gemini APIs
- 🛠️ **Rich Tool Ecosystem**: File editing, bash execution, sequential thinking, and more
- 🎯 **Interactive Mode**: Conversational interface for iterative development
- 📊 **Trajectory Recording**: Detailed logging of all agent actions for debugging and analysis
- ⚙️ **Flexible Configuration**: YAML-based configuration with environment variable support
- 🚀 **Easy Installation**: Simple pip-based installation
## 🚀 Installation
### Requirements
- UV (https://docs.astral.sh/uv/)
- API key for your chosen provider (OpenAI, Anthropic, Google Gemini, OpenRouter, etc.)
### Setup
```bash
git clone https://github.com/bytedance/trae-agent.git
cd trae-agent
uv sync --all-extras
source .venv/bin/activate
```
## ⚙️ Configuration
### YAML Configuration (Recommended)
1. Copy the example configuration file:
```bash
cp trae_config.yaml.example trae_config.yaml
```
2. Edit `trae_config.yaml` with your API credentials and preferences:
```yaml
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
```
**Note:** The `trae_config.yaml` file is ignored by git to protect your API keys.
### Using Base URL
In some cases, we need to use a custom URL for the api. Just add the `base_url` field after `provider`, take the following config as an example:
```
openai:
api_key: your_openroutExcerpt of 10,196 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:198649ea28d2c444, topic:llm