name: youtu_agent description: Flexible, high-performance framework for building, running, and evaluating autonomous agents with automated generation, experience learning, and RL training capabilities. source_type: github auth_required: true repository_url: "https://github.com/TencentCloudADP/youtu-agent" reference_url: "https://arxiv.org/abs/2512.24615"
youtu_agent
Flexible, high-performance framework for building, running, and evaluating autonomous agents with automated generation, experience learning, and RL training capabilities.
Code repository
https://github.com/TencentCloudADP/youtu-agent
Use this as the implementation source: clone the repo and follow its README for install, dependencies, and how to run code or experiments. The generated client prints JSON with a suggested git clone command.
Paper (arXiv — explanation)
https://arxiv.org/abs/2512.24615
This is the paper reference. The client can optionally fetch live Atom metadata (title, abstract) for agents; it does not run training or upstream research code by itself.
What “running” this client does
The *_client.py script prints JSON that combines a GitHub repository (clone URL + suggested git clone) with optional paper context from arXiv (live Atom metadata when reference_url is arXiv). Run the real code by cloning the repo and following its README — the skill is your agent-facing entrypoint, not a substitute for the repo’s install steps.
To call a REST API instead, set BASE_URL in scripts/youtu_agent_client.py or wrap the upstream CLI with subprocess after clone.
How to run the method (from the source)
Extracted for operators and agents. Confirm against the upstream repository or paper before relying on it in production.
Prerequisites
- Python 3.12 or higher
- uv package manager (recommended) or pip
- API keys for LLM providers (DeepSeek, OpenAI, etc.)
- Optional: API keys for tools (Serper for web search, Jina for web reading)
Installation
Clone and set up the repository:
git clone https://github.com/TencentCloudADP/youtu-agent.git
cd youtu-agent
uv sync # or, `make sync`
source ./.venv/bin/activate
cp .env.example .env
Alternatively, use Docker:
# Refer to docker/README.md for Docker-based setup with interactive frontend
How to run
Interactive CLI Chat
# Basic agent (no internet search)
python scripts/cli_chat.py --config simple/base
# Agent with web search capabilities
python scripts/cli_chat.py --config simple/base_search
Generate Agent Automatically
# Interactively clarify requirements and auto-generate a config
python scripts/gen_simple_agent.py
# Run the generated config
python scripts/cli_chat.py --config generated/xxx
Run Examples
# SVG generator (requires SERPER_API_KEY and JINA_API_KEY)
python examples/svg_generator/main.py
# SVG generator with web UI
python examples/svg_generator/main_web.py
Run Evaluations
# Prepare WebWalkerQA dataset
python scripts/data/process_web_walker_qa.py
# Run evaluation
python scripts/run_eval.py --config_name ww --exp_id <your_exp_id> --dataset WebWalkerQA_15 --concurrency 5
Configuration
Environment Variables
Edit .env file with required API keys:
# LLM Configuration (OpenAI API format compatible)
UTU_LLM_TYPE=chat.completions
UTU_LLM_MODEL=deepseek-chat
UTU_LLM_BASE_URL=https://api.deepseek.com/v1
UTU_LLM_API_KEY=replace-to-your-api-key
# Optional: Judge LLM (for evaluation)
JUDGE_LLM_TYPE=chat.completions
JUDGE_LLM_MODEL=deepseek-chat
JUDGE_LLM_BASE_URL=https://api.deepseek.com/v1
JUDGE_LLM_API_KEY=replace-to-your-api-key
# Tool APIs (optional, for web search)
SERPER_API_KEY=your-serper-api-key
JINA_API_KEY=your-jina-api-key
Alternative: Tencent Cloud DeepSeek
UTU_LLM_TYPE=chat.completions
UTU_LLM_MODEL=deepseek-v3
UTU_LLM_BASE_URL=https://api.lkeap.cloud.tencent.com/v1
UTU_LLM_API_KEY=replace-with-your-api-key
Agent Configuration Files
Agent configurations are YAML files in configs/agents/. Example structure:
defaults:
- /model/base
- /tools/search@toolkits.search
- _self_
agent:
name: simple-tool-agent
instructions: "You are a helpful assistant that can search the web."
Web UI Frontend
Download and install the frontend package:
curl -LO https://github.com/Tencent/Youtu-agent/releases/download/frontend%2Fv0.2.0/utu_agent_ui-0.2.0-py3-none-any.whl
uv pip install utu_agent_ui-0.2.0-py3-none-any.whl
Then run web-enabled examples:
python examples/svg_generator/main_web.py
# Access at http://127.0.0.1:8848/
The same text lives in scripts/USAGE.md for tools that prefer reading files under scripts/.
Parameters
--api-key (str) [required] API key for authentication --config (str) [required] Path or name of the agent configuration file (YAML). Examples: 'simple/base_search', 'simple/base', 'ww' --exp-id (str) [optional, default=None] Experiment identifier for evaluation runs --dataset (str) [optional, default=None] Dataset name for evaluation. Examples: 'WebWalkerQA_15', 'GAIA' --concurrency (int) [optional, default=5] Number of concurrent evaluation tasks --config-name (str) [optional, default=None] Configuration name for evaluation (e.g., 'ww' for WebWalkerQA)
Usage
python3 scripts/youtu_agent_client.py --config simple/base_search
Example Output
{"response": "agent_output", "trajectory": [...]}