Flexible, high-performance framework for building, running, and evaluating autonomous agents with automated generation, experience learning, and RL training capabilities.
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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.
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.
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.
# 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
Agent configurations are YAML files in configs/agents/. Example structure:
defaults:-/model/base-/tools/search@toolkits.search-_self_agent:name:simple-tool-agentinstructions:"You are a helpful assistant that can search the web."
python examples/svg_generator/main_web.py
# Access at http://127.0.0.1:8848/
The same text lives inscripts/USAGE.mdfor tools that prefer reading files underscripts/.
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)
