菜单
Query the ASI:One LLM — the AI model by the ASI Alliance (Fetch.ai + SingularityNET + Ocean Protocol). OpenAI-compatible API. Supports asi1 (default) and asi1-mini models. Requires ASI_ONE_API_KEY env var. Use when asked to "use ASI", "query ASI:One", or "use the Fetch.ai LLM".
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Give any AI agent persistent, graph-native memory via Agentverse Memory — a managed MCP service with 35 JSON-RPC tools covering 4 memory types (episodic, semantic/graph, procedural, working) plus shared multi-agent memory spaces. Zero LLM at write time (<5ms writes, $0 ingest). Graph memory on every tier — including free. Hybrid retrieval (TF-IDF + dense, RRF-fused). Requires AM_API_KEY env var. Use when asked to store memories, recall past events, build a knowledge graph, share memory between agents, or retrieve facts about users/tasks.
Send messages to any agent on Fetch.ai's Agentverse and receive responses. Handles text, images, and structured data. Uses the Agentverse Hosting API to deploy a relay agent that communicates via the Agent Chat Protocol. Requires AGENTVERSE_API_KEY env var. Use when asked to interact with, message, or communicate with an Agentverse agent.
Generate images using AI agents on Fetch.ai's Agentverse. Sends a text prompt to an image generation agent and returns the generated image URL. Handles agent discovery, relay deployment, and response parsing automatically. Requires AGENTVERSE_API_KEY env var. Use when asked to generate, create, or make an image via Agentverse.
Manage hosted agents on Fetch.ai's Agentverse: list, start, stop, view logs, and delete agents. Provides operational control over your deployed agents. Requires AGENTVERSE_API_KEY env var. Use when asked to list agents, check agent status, view logs, start/stop agents, or clean up.
Search Fetch.ai's Agentverse for agents by keyword, capability, or protocol. Returns agent names, addresses, descriptions, and supported protocols. Use when asked to find, discover, or list available agents on Agentverse. Requires AGENTVERSE_API_KEY env var.
Deploy Python code as a hosted agent on Fetch.ai's Agentverse. Creates a new agent, uploads code, and optionally starts it. Handles the tricky code upload format automatically. Requires AGENTVERSE_API_KEY env var. Use when asked to deploy, host, or publish an agent on Agentverse.
| name | asi1-chat |
| description | Query the ASI:One LLM — the AI model by the ASI Alliance (Fetch.ai + SingularityNET + Ocean Protocol). OpenAI-compatible API. Supports asi1 (default) and asi1-mini models. Requires ASI_ONE_API_KEY env var. Use when asked to "use ASI", "query ASI:One", or "use the Fetch.ai LLM". |
| license | Apache-2.0 |
| compatibility | Python 3.8+, network access, ASI_ONE_API_KEY env var |
| metadata | {"version":"1.1.0","author":"Fetch.ai","last-updated":"2026-04-21"} |
| allowed-tools | Read Bash(python3 *) Bash(curl *) Bash(pip install requests) |
Query the ASI:One large language model — built by the Artificial Superintelligence (ASI) Alliance. OpenAI-compatible API with asi1 (default, recommended) and asi1-mini (faster, lighter) models.
ASI_ONE_API_KEY environment variable set
requestspython3 scripts/asi1_chat.py --prompt "Explain the ASI Alliance in 3 sentences"
python3 scripts/asi1_chat.py \
--prompt "What are the benefits of decentralized AI?" \
--system "You are a blockchain and AI expert. Be concise." \
--model asi1
python3 scripts/asi1_chat.py --prompt "Write a haiku about AI agents" --stream
{
"status": "success",
"model": "asi1",
"response": "The ASI Alliance is a collaboration between Fetch.ai, SingularityNET, and Ocean Protocol...",
"usage": {
"prompt_tokens": 12,
"completion_tokens": 87,
"total_tokens": 99
}
}
https://api.asi1.ai/v1/chat/completionsasi1 (default, recommended), asi1-mini (faster, lighter)Authorization: Bearer {ASI_ONE_API_KEY}from openai import OpenAI
client = OpenAI(
api_key=os.environ["ASI_ONE_API_KEY"],
base_url="https://api.asi1.ai/v1"
)
response = client.chat.completions.create(
model="asi1",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
--max-tokens or use --stream for real-time output. Use asi1-mini if you need lower latency.--stream for real-time output on long responsesASI:One is the AI model from the ASI Alliance — a merger of:
The ASI token (formerly FET) is the native token of the ecosystem.