curl -fsSL https://raw.githubusercontent.com/Shangri-la-0428/oasyce-sdk/main/scripts/bootstrap.sh | bash

pip install oasyce-sdk
oasyce start

oasyce join

python3 -m pip uninstall -y oasyce oasyce-sdk
python3 -m pip install --user -U oasyce-sdk

python3 -m pip install --user -U "git+https://github.com/Shangri-la-0428/oasyce-sdk.git"
oasyce start

oasyce join

oasyce share
oasyce join ~/Desktop/oasyce-connection.json
oasyce status

~/.thronglets/bin/thronglets-managed

thronglets setup

export THRONGLETS_DATA_DIR=/path/to/thronglets-data

pip install oasyce-sdk

import requests
from oasyce_sdk import OasyceClient
from oasyce_sdk.crypto import Wallet, NativeSigner

# 首次设备 / first device
wallet = Wallet.create()
print(f"地址: {wallet.address}")
print(f"助记词(保存好): {wallet.mnemonic}")

# 之后的运行、MCP、LangChain、runtime 集成优先复用本机 binding:
# wallet = Wallet.auto()  # OASYCE_MNEMONIC > ~/.oasyce/wallet.json

# 领测试币（免费，每次 20 OAS）/ get free testnet tokens
resp = requests.get(f"http://47.93.32.88:8080/faucet?address={wallet.address}")
print(resp.json())  # {"status": "ok", "amount": "20 OAS", ...}

# 连接链 / connect
client = OasyceClient("http://47.93.32.88:1317")
signer = NativeSigner(wallet, client, chain_id="oasyce-testnet-1")

# 查余额 / check balance
bal = client.get_balance(wallet.address)
print(f"余额: {bal.amount_oas} OAS")

# 注册数据资产 / register a data asset
result = signer.register_asset(
    name="My Analysis Report",
    content_hash="sha256-of-your-data",
    tags=["analysis", "finance"],
    description="Q4 financial analysis",
)
print(f"TX: {result.tx_hash}, 成功: {result.success}")

# 注册 AI 能力 / register an AI capability
signer.register_capability(
    name="Translation Service",
    endpoint="https://my-api.com/translate",
    price_uoas=500_000,  # 0.5 OAS per call
    tags=["nlp", "translation"],
)

# 买数据资产股份 / buy shares of a data asset
signer.buy_shares("DATA_0000000000000001", amount_uoas=1_000_000)

# 查看信誉 / check reputation
rep = client.get_reputation(wallet.address)
print(f"信誉分: {rep.score}")

# 正常路径：
# 1) 第一台设备第一次写链时，自动成为 root principal，并生成本地 delegate policy
# 2) 之后第二台设备通过 Thronglets share/join 或本地 policy bootstrap 接入
# 3) SDK 会在第一次写链时自动 enroll，并开始用 MsgExec 代理执行

# 高级回退（一般不需要）:
signer.set_delegate_policy(
    token="shared-secret",
    allowed_msgs=["/oasyce.datarights.v1.MsgBuyShares"],
    per_tx_uoas=1_000_000,
    window_uoas=10_000_000,
)

client = OasyceClient("http://47.93.32.88:1317")

# 资产 / Assets
client.get_data_asset("DATA_...")           # 单个资产详情
client.list_data_assets()                   # 所有资产列表
client.get_shareholders("DATA_...")         # 股东列表
client.get_access_level("DATA_...", addr)   # 访问权限等级

# 能力 / Capabilities
client.list_capabilities()                  # 所有能力
client.list_capabilities(tag="llm")         # 按标签筛选
client.get_capability("CAP_...")            # 单个能力详情

# 信誉 / Reputation
client.get_reputation(addr)                 # 信誉分

# 委托 / Delegate
client.get_delegate_policy(principal)       # 查看委托政策
client.get_delegates(principal)             # 列出所有代理
client.get_delegate_spend(principal)        # 查看花费窗口
client.get_principal(delegate)              # 反查：代理→委托人

# 工作 / Work
client.get_task("TASK_...")                 # 任务详情

# 通用 / General
client.get_balance(addr)                    # 余额
client.get_latest_block()                   # 最新区块
client.health()                             # 节点健康检查

pip install oasyce-sdk            # 基础 SDK + Data Agent
pip install oasyce-sdk[mcp]       # + MCP Server（Claude / Cursor / Windsurf）
pip install oasyce-sdk[langchain] # + LangChain Tools
pip install oasyce-sdk[all]       # 全部 / everything

from oasyce_sdk.agent.runtime import AgentRuntime

agent = AgentRuntime()

# 读集体经验 + 情绪状态 / read collective experience + emotional state
perception = agent.perceive("分析金融数据")
# perception.capabilities → 集体能力统计
# perception.kernel       → 情绪内核 (vitality, tension, warmth, guard)

# 写回结果 / write outcome back
agent.act("分析了 Q4 营收", "succeeded", "金融分析", capability="data-analysis")
# → Thronglets 记录痕迹 → Psyche 接收 trust_up

thronglets bootstrap    # 自动检测本机 AI 工具并写入适配层配置

oasyce start                       # 默认前门：接好本地栈并启动 agent
oasyce status                      # 统一查看本机 stack 状态
oasyce-agent status                # 仅查看 data-agent 运行状态 + 已注册资产数
oasyce-agent stop                  # 停止
oasyce-agent scan ~/Documents      # 手动扫描（分类 + 隐私报告）
oasyce-agent privacy ~/secret.csv  # 单文件 PII 检查
oasyce-agent stats                 # 资产统计

{
  "mcpServers": {
    "oasyce": {
      "command": "oasyce-mcp",
      "env": {
        "OASYCE_NODE": "http://47.93.32.88:1317",
        "OASYCE_FAUCET": "http://47.93.32.88:8080"
      }
    }
  }
}

from oasyce_sdk.langchain_tools import oasyce_tools  # 18 个工具（8 读 + 10 写）
from langchain.agents import create_react_agent

agent = create_react_agent(llm, oasyce_tools)
agent.invoke({"input": "注册一个 AI 翻译服务，0.5 OAS/次"})

from oasyce_sdk import OasyceClient
from oasyce_sdk.errors import NotFoundError, TimeoutError, OasyceError

client = OasyceClient()

try:
    cap = client.get_capability("cap-xyz")
except NotFoundError:
    print("能力不存在")
except TimeoutError:
    print("节点响应慢")
except OasyceError as e:
    print(f"出错了: {e}")

OasyceError
  +-- NotFoundError      # 链上未找到资源 (404 / gRPC NOT_FOUND)
  +-- ChainError         # 应用层链错误
  +-- HTTPError          # 非预期 HTTP 状态码
  +-- ConnectionError    # 无法连接节点
  +-- TimeoutError       # 请求超时
  +-- ValidationError    # 请求发出前的输入校验错误