5.2 KiB
5.2 KiB
Pocket Flow: A 100-line minimalist LLM framework
- Expressive: Support (Multi-)Agents, Workflow, RAG, etc.—everything you’d expect from larger frameworks.
- Lightweight: Only the core graph abstraction in 100 lines. No dependencies or vendor lock-ins.
- Principled: Designed for clear modularity and separation of concerns.
- To install,
pip install pocketflowor just copy the source code (only 100 lines). - To learn more, check out the documentation. For an in-depth design dive, read the essay.
Why Pocket Flow?
For a new development paradigmn: Build LLM Apps by Chatting with LLM agents, Not Coding!
- 🧑 Human describe LLM App requirements in a design doc.
- 🤖 The agent (like Cursor AI) implements App your code automatically.
👈 How to set up Pocket Flow for LLM agents?
- For quick questions: Use the GPT assistant (note: it uses older models not ideal for coding).
- For one-time LLM task: Create a ChatGPT or Claude project; upload the docs to project knowledge.
- For LLM App development: Use Cursor AI.
- If you want to start a new project, check out the project template.
- If you already have a project, copy .cursorrules to your project root as Cursor Rules.
👈 How does Pocket Flow compare to other frameworks? Pocket Flow is purpose-built for LLM Agents:
- 🫠 LangChain-like frameworks overwhelm Cursor AI with complex abstractions, deprecated functions and irritating dependency issues.
- 😐 Without a framework, code is ad hoc—suitable only for immediate tasks, not modular or maintainable.
- 🥰 With Pocket Flow: (1) Minimal and expressive—easy for Cursor AI to pick up. (2) Nodes and Flows keep everything modular. (3) A Shared Store decouples your data structure from compute logic.
In short, the 100 lines ensures LLM Agents follows solid coding practices without sacrificing flexibility.
What can Pocket Flow build?
Below are examples LLM Apps and tutorials
| Formal App Name | Informal One-Liner | Difficulty | Learning Objectives |
|---|---|---|---|
| Youtube Summarizer | Explain YouTube Videos to you like you're 5 | ★☆☆ Beginner | Map Reduce |
| YC Adice Retriever | AI Paul Graham, in case you don't get in | ★☆☆ Beginner | RAG |
- Do you want to create your own Python project? Start with this template
How does Pocket Flow work?
The 100 lines capture what we believe to be the core abstraction of LLM frameworks:
- Computation: A graph that breaks down tasks into nodes, with branching, looping, and nesting.
- Communication: A shared store that all nodes can read and write to.
From there, it’s easy to implement popular design patterns like (Multi-)Agents, Workflow, RAG, etc.
