gptme Agent工作流 是 AI Skill Hub 本期精选AI工具之一。已获得 4.3k 颗 GitHub Star,综合评分 8.2 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。
gptme Agent工作流 是一款基于 Python 开发的开源工具,专注于 AI代理、工作流自动化、终端工具 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
gptme Agent工作流 是一款基于 Python 开发的开源工具,专注于 AI代理、工作流自动化、终端工具 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install gptme
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install gptme
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/gptme/gptme
cd gptme
pip install -e .
# 验证安装
python -c "import gptme; print('安装成功')"
# 命令行使用
gptme --help
# 基本用法
gptme input_file -o output_file
# Python 代码中调用
import gptme
# 示例
result = gptme.process("input")
print(result)
# gptme 配置文件示例(config.yml) app: name: "gptme" debug: false log_level: "INFO" # 运行时指定配置文件 gptme --config config.yml # 或通过环境变量配置 export GPTME_API_KEY="your-key" export GPTME_OUTPUT_DIR="./output"
<p align="center"> <img src="https://gptme.org/media/logo.png" width=150 /> </p>
<p align="center"> <i>/ʤiː piː tiː miː/</i> <br> <sub><a href="https://gptme.org/docs/misc/acronyms.html">what does it stand for?</a></sub> </p>
<p align="center"> <a href="https://gptme.org/docs/getting-started.html">Getting Started</a> • <a href="https://gptme.org/downloads/">Downloads</a> • <a href="https://gptme.org/">Website</a> • <a href="https://gptme.org/docs/">Documentation</a> </p>
<p align="center"> <a href="https://github.com/gptme/gptme/actions/workflows/build.yml"> <img src="https://github.com/gptme/gptme/actions/workflows/build.yml/badge.svg" alt="Build Status" /> </a> <a href="https://github.com/gptme/gptme/actions/workflows/docs.yml"> <img src="https://github.com/gptme/gptme/actions/workflows/docs.yml/badge.svg" alt="Docs Build Status" /> </a> <a href="https://codecov.io/gh/gptme/gptme"> <img src="https://codecov.io/gh/gptme/gptme/graph/badge.svg?token=DYAYJ8EF41" alt="Codecov" /> </a> <br> <a href="https://pypi.org/project/gptme/"> <img src="https://img.shields.io/pypi/v/gptme" alt="PyPI version" /> </a> <a href="https://pepy.tech/project/gptme"> <img src="https://img.shields.io/pepy/dt/gptme" alt="PyPI - Downloads all-time" /> </a> <a href="https://pypistats.org/packages/gptme"> <img src="https://img.shields.io/pypi/dd/gptme?color=success" alt="PyPI - Downloads per day" /> </a> <br> <a href="https://discord.gg/NMaCmmkxWv"> <img src="https://img.shields.io/discord/1271539422017618012?logo=discord&style=social" alt="Discord" /> </a> <a href="https://x.com/gptmeorg"> <img src="https://img.shields.io/twitter/follow/gptmeorg?style=social" alt="X.com" /> </a> <br> <a href="https://gptme.org/docs/projects.html"> <img src="https://img.shields.io/badge/powered%20by-gptme%20%F0%9F%A4%96-5151f5?style=flat" alt="Powered by gptme" /> </a> </p>
<p align="center"> 📜 A personal AI agent that runs <i>anywhere a terminal runs</i> — your laptop, ssh sessions, tmux, headless servers, CI pipelines.<br/> Provider-agnostic, local-first, and unconstrained: ships with shell, Python, web, vision, and everything else an agent needs.<br/> A great coding agent, but general-purpose enough to assist in all kinds of knowledge-work. </p>
<p align="center"> Free and open-source. Works with Anthropic, OpenAI, Google, xAI, DeepSeek, OpenRouter, or fully local via <code>llama.cpp</code> — your data, your models, your terminal.<br/> A capable <a href="https://gptme.org/docs/alternatives.html">alternative</a> to Claude Code, Codex, Cursor, and Warp — one of the first agent CLIs (Spring 2023), still in very active development. </p>
llama.cpp.GPTME_TOOL_SOUNDS=true.- Python 3.10 or newer - Credentials for at least one LLM provider: - OpenRouter can be configured interactively with /account setup openrouter inside gptme, using browser OAuth onboarding. - You can also set API keys manually for Anthropic (ANTHROPIC_API_KEY), OpenAI (OPENAI_API_KEY), OpenRouter (OPENROUTER_API_KEY), and other providers. - Local models via llama.cpp need no key — see [providers docs][docs-providers].
pipx install gptme
For full setup instructions, see the [Getting Started guide][docs-getting-started].
```sh
Prerequisites: Python 3.10+
Installation: ```bash pip install gptme
gptme
You'll be greeted with a prompt. Type your request and gptme will respond, using tools as needed.
```sh
$ gptme --help
Usage: gptme [OPTIONS] [PROMPTS]...
gptme is a chat-CLI for LLMs, empowering them with tools to run shell
commands, execute code, read and manipulate files, and more.
If PROMPTS are provided, a new conversation will be started with it. PROMPTS
can be chained with the '-' separator.
The interface provides user commands that can be used to interact with the
system.
Available commands:
/undo Undo the last action
/log Show the conversation log
/edit Edit the conversation in your editor
/rename Rename the conversation
/fork Create a copy of the conversation
/summarize Summarize the conversation
/replay Replay tool operations
/export Export conversation as HTML
/model Show or switch the current model
/models List available models
/tokens Show token usage and costs
/context Show context token breakdown
/tools Show available tools
/commit Ask assistant to git commit
/compact Compact the conversation
/impersonate Impersonate the assistant
/restart Restart gptme process
/setup Setup gptme
/help Show this help message
/exit Exit the program
See docs for all commands: https://gptme.org/docs/commands.html
Keyboard shortcuts:
Ctrl+X Ctrl+E Edit prompt in your editor
Ctrl+J Insert a new line without executing the prompt
Options:
--name TEXT Name of conversation. Defaults to generating a random
name.
-m, --model TEXT Model to use, e.g. openai/gpt-5, anthropic/claude-
sonnet-4-20250514. If only provider given then a
default is used.
-w, --workspace TEXT Path to workspace directory. Pass '@log' to create a
workspace in the log directory.
--agent-path TEXT Path to agent workspace directory.
-r, --resume Load most recent conversation.
-y, --no-confirm Skip all confirmation prompts.
-n, --non-interactive Non-interactive mode. Implies --no-confirm.
--output-format [text|json]
Output format for non-interactive mode. 'json'
emits one JSON object per line on stdout.
--system TEXT System prompt. Options: 'full', 'short', or something
custom.
-t, --tools TEXT Tools to allow as comma-separated list. Available:
append, browser, chats, choice, computer, gh,
ipython, morph, patch, rag, read, save, screenshot,
shell, subagent, tmux, vision.
--tool-format TEXT Tool format to use. Options: markdown, xml, tool
--no-stream Don't stream responses
--show-hidden Show hidden system messages.
-v, --verbose Show verbose output.
--version Show version and configuration information
--help Show this message and exit.
Pair `--non-interactive with --output-format json` when stdout needs to be machine-readable, for example in CI or a supervising process. Use `--resume` to continue an existing automated conversation or pick up queued follow-up prompts without passing a new prompt.
gptme is general-purpose but excels at:
[!NOTE] The screencasts below are from 2023. gptme has evolved a lot since then! For up-to-date examples and screenshots, see the [Documentation][docs-examples]. We're working on automated demo generation: #1554.
| Fibonacci | Snake with curses | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
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<details> <summary>Steps</summary> <ol> <li> Create a new dir 'gptme-test-fib' and git init <li> Write a fib function to fib.py, commit <li> Create a public repo and push to GitHub </ol> </details> </td> <td width="50%"> <details> <summary>Steps</summary> <ol> <li> Create a snake game with curses to snake.py <li> Running fails, ask gptme to fix a bug <li> Game runs <li> Ask gptme to add color <li> Minor struggles <li> Finished game with green snake and red apple pie! </ol> </details> </td> </tr> <tr> <th>Mandelbrot with curses</th> <th>Answer question from URL</th> </tr> <tr> <td width="50%"> <details> <summary>Steps</summary> <ol> <li> Render mandelbrot with curses to mandelbrot_curses.py <li> Program runs <li> Add color </ol> </details> </td> <td width="25%"> <details> <summary>Steps</summary> <ol> <li> Ask who the CEO of Superuser Labs is, passing website URL <li> gptme browses the website, and answers correctly </ol> </details> </td> </tr> <tr> <th>Terminal UI</th> <th>Web UI</th> </tr> <tr> <td width="50%"> <details> <summary>Features</summary> <ul> <li> Powerful terminal interface <li> Convenient CLI commands <li> Diff & Syntax highlighting <li> Tab completion <li> Command history </ul> </details> </td> <td width="50%"> <details> <summary>Features</summary> <ul> <li> Chat with gptme from your browser <li> Access to all tools and features <li> Modern, responsive interface <li> Self-hostable <li> Available at <a href="https://chat.gptme.org">chat.gptme.org</a> </ul> </details> </td> </tr> </table> You can find more [Demos][docs-demos] and [Examples][docs-examples] in the [documentation][docs]. With optional extraspipx install 'gptme[browser]' # Playwright for web browsing pipx install 'gptme[all]' # Everything Get configuration suggestionsgptme 'suggest improvements to my vimrc' ⚙️ ConfigurationCreate ```toml [user] name = "User" about = "I am a curious human programmer." response_preference = "Don't explain basic concepts" [prompt] config.yamlname: "MyAgent" role: "Code reviewer" schedule: "hourly" bash python agent.py ```
See Bob for an example autonomous agent that has been running continuously since late 2024. How do I configure gptme?Configuration via environment variables: ```bash API keysexport ANTHROPIC_API_KEY=your-key 🔌 Extensibility: Plugins, Skills & Lessonsgptme has a layered extensibility system that lets you tailor it to your workflow: [Plugins][docs-plugins] — extend gptme with custom tools, hooks, and commands via Python packages: ```toml 🔗 Integrations: MCP & ACP[MCP (Model Context Protocol)][docs-mcp] — use any MCP server as a tool source:
gptme can discover and dynamically load MCP servers, giving the agent access to databases, APIs, file systems, and any other MCP-compatible tool. See the [MCP docs][docs-mcp] for server configuration. [ACP (Agent Client Protocol)][docs-acp] — use gptme as a coding agent directly from your editor:
This makes gptme available as a drop-in coding agent in Zed and JetBrains IDEs. Your editor sends requests, gptme executes with its full toolset (shell, browser, files, etc.) and streams results back. How does the MCP integration work?gptme has built-in MCP support:
Example MCP servers supported: - [gptme-codegraph] — structural code graph analysis with tree-sitter (9 tools) - GitHub MCP - Puppeteer MCP - SQLite MCP - Custom MCP servers What is the plugin system?gptme has a full plugin system:
Example plugins: - Twitter/X bot - Discord bot - Email tools - Consortium (multi-agent) How does gptme compare to other AI coding assistants?
❓ FAQ
🇨🇳 中文文档镜像
AI 翻译
2026-05-25
英文原文章节由系统翻译为中文摘要,便于快速理解。完整原文见上方 "📑 README 深度解析"。
📌 简介
gptme 是一个强大的 AI 终端助手,旨在通过自然语言交互提升开发效率。它不仅是一个聊天界面,更是一个能够理解并操作本地环境的智能代理,帮助开发者在命令行中更高效地完成任务。 ⚡ 功能介绍
gptme 具备卓越的自动化能力:支持通过 shell 和 python 工具在本地执行代码;能够利用 patch 工具对文件进行增量读写与修改;集成 Playwright 实现网页搜索与浏览;并具��� Vision 能力,能够理解并处理图像信息。 📋 环境依赖
运行 gptme 需要 Python 3.10 或更高版本。此外,您需要配置至少一个 LLM 提供商的凭据,支持通过 OpenRouter 进行交互式 OAuth 配置,或手动设置 Anthropic 等平台的 API keys。 🛠 安装步骤(Docker/pip/源码)
推荐使用 pipx 进行安装(需 Python 3.10+),执行 `pipx install gptme` 即可快速部署。如果需要增强功能,可以使用 `pipx install 'gptme[browser]'` 安装浏览器支持,或使用 `pipx install 'gptme[all]'` 获取完整功能集。 🚀 使用教程
安装完成后,直接在终端输入 `gptme` 即可启动。您可以像聊天一样输入自然语言请求,gptme 会根据需求自动调用相应的工具来执行任务。它适用于代码开发、Shell 命令辅助、数据分析以及通过交互式学习探索新技术的多种场景。 ⚙️ 配置说明(含 MCP / env)
用户可以通过创建 `~/.config/gptme/config.toml` 文件来自定义个人信息、回复偏好及 Prompt 模板。此外,可以通过设置环境变量(如 `export ANTHROPIC_API_KEY=your-key`)来管理 API 密钥。您还可以利用 gptme 的建议功能来优化配置文件。 🔌 API 说明
gptme 通过环境变量管理各类 LLM 的 API keys,确保安全且灵活地调用 Anthropic 等模型服务。开发者可以根据需求配置不同的 API 访问权限,以驱动其核心的智能代理功能。 🔄 工作流/模块
gptme 拥有强大的分层扩展系统。通过 Plugins,您可以利用 Python 包扩展自定义工具和命令;通过内置的 MCP (Model Context Protocol) 支持,gptme 可以动态发现并加载 MCP 服务器,从而将数据库、API 和文件系统等外部工具无缝集成到工作流中。 ❓ FAQ 摘要
本章节包含了关于 gptme 使用过程中常见问题的解答,涵盖了从安装、配置到功能使用的疑难点,帮助开发者快速解决在使用过程中遇到的各类技术问题。
🎯 aiskill88 AI 点评
A 级
2026-05-21
设计思路新颖,将AI代理与本地工具有机结合。代码质量高,社区活跃,是构建智能工作流的优秀框架。 📚 实用指南(长尾问题)
适合谁
最佳实践
常见错误
部署方案
⚡ 核心功能
👥 适合谁
⭐ 最佳实践
⚠️ 常见错误
👥 适合人群
🎯 使用场景
⚖️ 优点与不足
✅ 优点
⚠️ 不足
⚠️ 使用须知
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。 建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。 📄 License 说明
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。 🔗 相关工具推荐
📚 相关教程推荐 📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合
技能寻求者 MCP · Agent · 工作流 natively-cluely-ai-assistant — Claude Skill 中文使用文档 免费开源的AI面试助手,实时转录,隐蔽模式,局部RAG,BYOK。无订阅,防止数据泄露。 开源AI工具:RAG知识库系统 基于Vue.js前端的RAG知识库系统,提供高效的知识检索和生成功能,助力AI应用开发 DeepCode Agent工作流 MCP · Agent · 工作流 total-agent-memory MCP工具 为Claude Code和Codex CLI提供持久化记忆功能的开源MCP工具。自动提取知识图谱,支持多轮对话上下文保留,适合需要长期记忆和 MassGen多智能体系统 MCP · Agent · 工作流 ❓ 常见问题 FAQ
主要支持Anthropic Claude系列模型,可扩展配置其他模型
💡 AI Skill Hub 点评
经综合评估,gptme Agent工作流 在AI工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。 🌐 原始信息
🔗 原始来源
🐙 GitHub 仓库 https://github.com/gptme/gptme
🌐 官方网站 https://gptme.org/docs/
收录时间:2026-05-14 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。 |