快速开始¶
5 分钟内运行你的第一个 SAGE Pipeline
前置要求¶
- Python 3.9+
- conda 或 virtualenv (推荐)
- Git
1. 安装 SAGE¶
使用快速安装脚本(推荐)¶
# 克隆仓库
git clone https://github.com/intellistream/SAGE.git
cd SAGE
# 切换到开发分支
git checkout main-dev
# 快速安装(包含依赖、submodules、hooks)
./quickstart.sh --dev --yes
手动安装¶
# 创建虚拟环境
conda create -n sage python=3.11
conda activate sage
# 安装 SAGE
pip install -e packages/sage-common
pip install -e packages/sage-platform
pip install -e packages/sage-kernel
pip install -e packages/sage-libs
pip install -e packages/sage-middleware
pip install -e packages/sage-studio
pip install -e packages/sage-tools
2. 验证安装¶
3. 第一个 Pipeline¶
创建文件 hello_sage.py:
from sage.kernel.api import LocalEnvironment
from sage.libs.io import FileSource, TerminalSink
from sage.kernel.api.function import MapFunction
# 创建简单的处理函数
class UpperCaseMap(MapFunction):
def map(self, record):
record.data = record.data.upper()
return record
# 构建 Pipeline
env = LocalEnvironment("hello_sage")
(
env.from_source(FileSource, {"file_path": "input.txt"})
.map(UpperCaseMap)
.sink(TerminalSink)
)
# 执行
env.submit()
创建测试数据 input.txt:
运行:
输出:
4. 构建 RAG Pipeline¶
from sage.kernel.api import LocalEnvironment
from sage.libs.io import FileSource, TerminalSink
from sage.middleware.operators.rag import ChromaRetriever, QAPromptor, OpenAIGenerator
env = LocalEnvironment("rag_pipeline")
(
env.from_source(FileSource, {"file_path": "questions.txt"})
.map(ChromaRetriever, {"collection": "my_docs", "top_k": 3})
.map(QAPromptor, {"template": "Context: {context}\n\nQ: {query}\nA:"})
.map(OpenAIGenerator, {"model": "gpt-3.5-turbo", "api_key": "your-api-key"})
.sink(TerminalSink)
)
env.submit()
5. 使用 Web UI¶
启动 SAGE Studio(可视化界面):
访问 http://localhost:8000 即可使用图形界面构建 Pipeline。
6. 探索示例¶
SAGE 提供了丰富的示例:
# 查看所有示例
ls examples/tutorials/
# 运行 Agent 示例
python examples/tutorials/agents/basic_agent.py
# 运行 RAG 示例
python examples/tutorials/rag/simple_rag.py
📚 下一步¶
🆘 获取帮助¶
⚡ 快速参考¶
常用命令¶
# 启动服务
sage studio start
sage llm start
# 开发工具
sage-dev test # 运行测试
sage-dev format # 格式化代码
sage-dev check # 代码检查
# Pipeline 构建
sage pipeline create # 创建新 pipeline
sage pipeline list # 列出所有 pipelines
常用导入¶
# 核心 API
from sage.kernel.api import LocalEnvironment
from sage.libs.io import FileSource, TerminalSink
# Agents
from sage.libs.agentic.agents.bots import AnswerBot, QuestionBot
# RAG
from sage.middleware.operators.rag import ChromaRetriever, OpenAIGenerator
# 配置
from sage.common.config import load_config
开始构建你的 AI Agent 应用吧! 🚀