ajet/copilot/conda-install-agentjet-swarm-server/SKILL.md
Install AgentJet swarm server using Conda. Handles Python 3.10 environment creation, dependency installation with the verl training backbone, flash-attn compilation, and optional PyPI mirror for China users.
npx skillsauth add modelscope/agentjet conda-install-agentjet-swarm-serverInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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when the user only need to run agentjet client, and do not have to run models locally (e.g. user in their laptop), ONLY install AgentJet basic requirements is enough (pip install -e .). see
install-agentjet-clientskill
Check Python version requirement (3.10) and conda availability.
Verify user has conda installed:
conda --version
Clone the AgentJet repository from GitHub and navigate into the project directory:
git clone https://github.com/modelscope/AgentJet.git
cd AgentJet
Create a new conda environment with Python 3.10:
conda create -n ajet-verl python=3.10
conda activate ajet-verl
Install AgentJet with the verl training backbone:
pip install -e .[verl]
Use Aliyun PyPI mirror for faster downloads:
pip install -i https://mirrors.aliyun.com/pypi/simple/ -e .[verl]
Before installing flash-attn, test the connection to GitHub:
curl -I --connect-timeout 10 https://github.com 2>/dev/null | head -n 1
If the connection test fails or times out:
!!! danger "IMPORTANT: GitHub Connection Issue Detected" ⚠️ WARNING: You cannot connect to GitHub stably!
flash-attn requires downloading pre-compiled wheels from GitHub. Without a stable GitHub connection, pip will attempt to build flash-attn from source, which can take **30 minutes to several hours**.
**Recommended actions:**
1. Set up a stable connection to GitHub (VPN, proxy, etc.)
2. Use a mirror that hosts flash-attn pre-compiled wheels
3. If you must proceed, set `MAX_JOBS` to limit CPU usage during build:
```bash
export MAX_JOBS=4 # Adjust based on your CPU cores
```
**Do you want to proceed anyway?** (This may take a very long time)
flash-attn must be installed after other dependencies:
pip install --verbose flash-attn --no-deps --no-build-isolation --no-cache
pip install -i https://mirrors.aliyun.com/pypi/simple/ --verbose flash-attn --no-deps --no-build-isolation --no-cache
!!! warning "flash-attn Installation"
- flash-attn must be installed after other dependencies.
- Ensure a healthy connection to GitHub to install pre-compiled wheels.
- If you find your machine spend a long time installing flash-attn, ensure a healthy connection to GitHub.
- To build faster, export MAX_JOBS=${N_CPU}.
Verify the installation:
python -c "import ajet; print(ajet.__version__)"
data-ai
How `max_env_worker` caps the "Running Episodes" gauge, and how `AgentJetJob` relates to the YAML config.
tools
Convert skills in non-standard formats to the standard Agent Skills `SKILL.md` format. Validates YAML frontmatter (name, description, license, compatibility, metadata, allowed-tools), directory structure (SKILL.md, scripts/, references/, assets/), and best practices. Use when the user asks to normalize, validate, or fix a skill.
devops
Download per-step time-series metric data (reward, entropy, response length, etc.) from a SwanLab cloud run URL as a pandas.DataFrame. Use when the user provides a SwanLab URL and wants to fetch or analyze training curves.
development
Your task is to investigate the chat template of given model, go to its tokenizer config and check whether the following behavior exists: > > Remove history <think> block from the input when apply chat template when converting messages. > This behavior will make RL training slower, if this behavior exists, please change the chat template to forbid such behavior. You must not do this in-place, instead, please create another model. E.g., "/mnt/data_cpfs/xielipeng.xlp/models/Qwen3-8B" -> "/mnt