官方说明2 个来源昨天
AutoPR
AI-generated pull requests agent that fixes issues
在 GitHub 查看 ↗直链 · 无中转页
官方说明7e82-489e-905e-6ad79005adcb" /> AutoPR <video src="user-images.githubusercontent.com AutoPR autonomously wrote pull requests in response to issues.
- 来源明细
- 收录自 e2b-dev/awesome-ai-agents 榜单（我们从中收集的条目之一） · 条目类型：开源项目
- 收录与活跃
- 收录于 2026-10-16 · 最近见到 2026-10-16 · 共见到 3 次 · 被 2 个来源列出
- 评分构成
- 综合分 203 · 2 个来源 · repo
常见问题（答案都来自我们的记录）
怎么安装？
我们【没有】从该仓库取到安装命令（我们的 install 覆盖率只有约 4%）。请看它的 README 或 releases 页。
它适合谁 / 用来做什么？
我们还没有为它记录标签。
谁维护它、还在更新吗？
我们收录于 2026-10-16；最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记
🌳 AutoPR 🌳
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
AutoPR autonomously wrote pull requests in response to issues.
Built with Guardrails.
What is this?
A vision of user experience I had in March of 2023, back when OpenAI had just launched its first "ChatGPT API".
As far as I am aware, AutoPR was the first bot to autonomously generate pull requests in response to issues.
Like most demos back in the day, it worked about 20% of the time.
What inspired the initial weekend coding sprint was Guardrails,
who were prompting LLMs to generate structured data with JSON Schemas, and reasking it when it did not adhere.
This was a time before grammar-powered structured data generation.
Enjoy this brief glimpse into the past. 🜂
💪 How did it work?
Triggered by adding a label containing AutoPR to an issue, AutoPR would:
1. Plan a fix
2. Write the code
3. Push a branch
4. Open a pull request
💎 Examples
Well-written issues often lead to better results.
- Create a dice rolling bot
- Create a 'Tech Jargon Generator'
- Create a user-friendly weather app
- Write three programming interview challenges
- Replace GPT2FastTokenizer with tiktoken
🤞 Limitations
This GitHub Action was **in development**, and in **alpha release**.
It still:
- Incorrectly referenced code in other files
- Duplicated lines
- Called functions that don't exist
- Only worked on GitHub (see #46)
🔨 Usage
Please see USAGE.md for more information.
📝 Contributing
Please see CONTRIBUTING.md for more information.
Built with Guardrails.
What is this?
A vision of user experience I had in March of 2023, back when OpenAI had just launched its first "ChatGPT API".
As far as I am aware, AutoPR was the first bot to autonomously generate pull requests in response to issues.
Like most demos back in the day, it worked about 20% of the time.
What inspired the initial weekend coding sprint was Guardrails,
who were prompting LLMs to generate structured data with JSON Schemas, and reasking it when it did not adhere.
This was a time before grammar-powered structured data generation.
Enjoy this brief glimpse into the past. 🜂
💪 How did it work?
Triggered by adding a label containing AutoPR to an issue, AutoPR would:
1. Plan a fix
2. Write the code
3. Push a branch
4. Open a pull request
💎 Examples
Well-written issues often lead to better results.
- Create a dice rolling bot
- Create a 'Tech Jargon Generator'
- Create a user-friendly weather app
- Write three programming interview challenges
- Replace GPT2FastTokenizer with tiktoken
🤞 Limitations
This GitHub Action was **in development**, and in **alpha release**.
It still:
- Incorrectly referenced code in other files
- Duplicated lines
- Called functions that don't exist
- Only worked on GitHub (see #46)
🔨 Usage
Please see USAGE.md for more information.
📝 Contributing
Please see CONTRIBUTING.md for more information.
- 来源
- awesome · https://github.com/irgolic/AutoPR
- 收录于
- 昨天