lupantech/AgentFlow 源码下载_部署教程

项目概述

AgentFlow: In-the-Flow Agentic System Optimization

项目地址

https://github.com/lupantech/AgentFlow

项目页面预览

lupantech/AgentFlow preview

关键指标

Stars：1489
主要语言：Python
License：MIT License
最近更新：2025-12-17T08:08:03Z
默认分支：main

本站高速下载（国内可用）

源码压缩包下载：点击下载（本站镜像）
SHA256：f5618fa9318381169464329957d23f4971a6da9a7e6d445e003baa65e77dccf6

安装部署要点（README 精选）

⚙️ Setup

Installation

bash setup.sh
source .venv/bin/activate
# (Optional) Install `parallel` for running benchmark experiments in parallel:
sudo apt-get update
sudo apt-get install parallel

Setup Environment Variables

Copy the .env.template file from agentflow/.env.template and rename it to .env, then place it in the agentflow/ folder. Update the following variables with your own API keys:
– OPENAI_API_KEY (for judging reasponse)
– GOOGLE_API_KEY (for Google Search tool)
– DASHSCOPE_API_KEY (for calling Qwen-2.5-7B-Instruct as engine for agents and tools)
– TOGETHER_API_KEY (alternative for calling Qwen-2.5-7B-Instruct as engine for agents and tools – recommended for international users)
– More ways: serve Qwen2.5-7B-instruct model with vLLM (details refer to serve_vllm_local.md).

Please check API Key Setup Guide for detailed instructions on how to obtain these keys.

cp agentflow/.env.template agentflow/.env
# Then edit agentflow/.env with your API keys

常用命令（从 README 提取）

bash setup.sh
source .venv/bin/activate
# (Optional) Install `parallel` for running benchmark experiments in parallel:
sudo apt-get update
sudo apt-get install parallel

cp agentflow/.env.template agentflow/.env
# Then edit agentflow/.env with your API keys

# train data
python data/get_train_data.py
# validation data
python data/aime24_data.py